diff options
| author |  Reinier van der Leer <pwuts@agpt.co>
| 2024-01-29 17:23:47 +0100 |
|---|---|---|
| committer | Reinier van der Leer <pwuts@agpt.co>
| 2024-01-29 17:23:47 +0100 |
| commit | 7ffc374bb58376317f249c929e5846e57b0da543 (patch) | |
| tree | 49c4f6ced963ce22da38a6e1c308def0ec8ef180 | |
| parent | fix: Fix missing categories in data_types.py (diff) | |
| parent | fix(agent/json_utils): Make `extract_dict_from_response` more robust (diff) | |
| download | Auto-GPT-bringing-in-the-benchmark.tar.gz Auto-GPT-bringing-in-the-benchmark.tar.bz2 Auto-GPT-bringing-in-the-benchmark.zip | |
Merge branch 'master' into bringing-in-the-benchmarkbringing-in-the-benchmark
269 files changed, 14632 insertions, 16589 deletions
@@ -9,3 +9,4 @@ exclude = .venv/*, reports/*, dist/*, + data/*, diff --git a/.github/workflows/autogpt-ci.yml b/.github/workflows/autogpt-ci.yml index 375a433a8..2ce756a7a 100644 --- a/.github/workflows/autogpt-ci.yml +++ b/.github/workflows/autogpt-ci.yml @@ -4,16 +4,13 @@ on: push: branches: [ master, development, ci-test* ] paths: + - '.github/workflows/autogpt-ci.yml' - 'autogpts/autogpt/**' - '!autogpts/autogpt/tests/vcr_cassettes' pull_request: branches: [ master, development, release-* ] paths: - - 'autogpts/autogpt/**' - - '!autogpts/autogpt/tests/vcr_cassettes' - pull_request_target: - branches: [ master, development, release-*, ci-test* ] - paths: + - '.github/workflows/autogpt-ci.yml' - 'autogpts/autogpt/**' - '!autogpts/autogpt/tests/vcr_cassettes' @@ -27,9 +24,6 @@ defaults: jobs: lint: - # eliminate duplicate runs - if: github.event_name == 'push' || (github.event.pull_request.head.repo.fork == (github.event_name == 'pull_request_target')) - runs-on: ubuntu-latest env: min-python-version: "3.10" @@ -39,8 +33,6 @@ jobs: uses: actions/checkout@v3 with: fetch-depth: 0 - ref: ${{ github.event.pull_request.head.ref }} - repository: ${{ github.event.pull_request.head.repo.full_name }} - name: Set up Python ${{ env.min-python-version }} uses: actions/setup-python@v4 @@ -73,40 +65,38 @@ jobs: run: poetry run isort . --check if: success() || failure() - - name: Check mypy formatting - run: poetry run mypy - if: success() || failure() + # - name: Check mypy formatting + # run: poetry run mypy + # if: success() || failure() - - name: Check for unused imports and pass statements - run: | - cmd="autoflake --remove-all-unused-imports --recursive --ignore-init-module-imports --ignore-pass-after-docstring autogpt tests" - poetry run $cmd --check || (echo "You have unused imports or pass statements, please run '${cmd} --in-place'" && exit 1) + # - name: Check for unused imports and pass statements + # run: | + # cmd="autoflake --remove-all-unused-imports --recursive --ignore-init-module-imports --ignore-pass-after-docstring autogpt tests" + # poetry run $cmd --check || (echo "You have unused imports or pass statements, please run '${cmd} --in-place'" && exit 1) test: - # eliminate duplicate runs - if: github.event_name == 'push' || (github.event.pull_request.head.repo.fork == (github.event_name == 'pull_request_target')) - permissions: - # Gives the action the necessary permissions for publishing new - # comments in pull requests. - pull-requests: write - # Gives the action the necessary permissions for pushing data to the - # python-coverage-comment-action branch, and for editing existing - # comments (to avoid publishing multiple comments in the same PR) - contents: write + contents: read runs-on: ubuntu-latest timeout-minutes: 30 strategy: matrix: python-version: ["3.10"] + services: + minio: + image: minio/minio:edge-cicd + ports: + - 9000:9000 + options: > + --health-interval=10s --health-timeout=5s --health-retries=3 + --health-cmd="curl -f http://localhost:9000/minio/health/live" + steps: - name: Checkout repository uses: actions/checkout@v3 with: fetch-depth: 0 - ref: ${{ github.event.pull_request.head.ref }} - repository: ${{ github.event.pull_request.head.repo.full_name }} submodules: true - name: Configure git user Auto-GPT-Bot @@ -116,9 +106,13 @@ jobs: - name: Checkout cassettes if: ${{ startsWith(github.event_name, 'pull_request') }} + env: + PR_BASE: ${{ github.event.pull_request.base.ref }} + PR_BRANCH: ${{ github.event.pull_request.head.ref }} + PR_AUTHOR: ${{ github.event.pull_request.user.login }} run: | - cassette_branch="${{ github.event.pull_request.user.login }}-${{ github.event.pull_request.head.ref }}" - cassette_base_branch="${{ github.event.pull_request.base.ref }}" + cassette_branch="${PR_AUTHOR}-${PR_BRANCH}" + cassette_base_branch="${PR_BASE}" cd tests/vcr_cassettes if ! git ls-remote --exit-code --heads origin $cassette_base_branch ; then @@ -169,11 +163,11 @@ jobs: tests/unit tests/integration env: CI: true - PROXY: ${{ github.event_name == 'pull_request_target' && secrets.PROXY || '' }} - AGENT_MODE: ${{ github.event_name == 'pull_request_target' && secrets.AGENT_MODE || '' }} - AGENT_TYPE: ${{ github.event_name == 'pull_request_target' && secrets.AGENT_TYPE || '' }} - OPENAI_API_KEY: ${{ github.event_name != 'pull_request_target' && secrets.OPENAI_API_KEY || '' }} PLAIN_OUTPUT: True + OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} + S3_ENDPOINT_URL: http://localhost:9000 + AWS_ACCESS_KEY_ID: minioadmin + AWS_SECRET_ACCESS_KEY: minioadmin - name: Upload coverage reports to Codecov uses: codecov/codecov-action@v3 @@ -198,11 +192,14 @@ jobs: - id: push_cassettes name: Push updated cassettes # For pull requests, push updated cassettes even when tests fail - if: github.event_name == 'push' || success() || failure() + if: github.event_name == 'push' || (! github.event.pull_request.head.repo.fork && (success() || failure())) + env: + PR_BRANCH: ${{ github.event.pull_request.head.ref }} + PR_AUTHOR: ${{ github.event.pull_request.user.login }} run: | if [ "${{ startsWith(github.event_name, 'pull_request') }}" = "true" ]; then is_pull_request=true - cassette_branch="${{ github.event.pull_request.user.login }}-${{ github.event.pull_request.head.ref }}" + cassette_branch="${PR_AUTHOR}-${PR_BRANCH}" else cassette_branch="${{ github.ref_name }}" fi @@ -234,20 +231,15 @@ jobs: - name: Apply "behaviour change" label and comment on PR if: ${{ startsWith(github.event_name, 'pull_request') }} run: | - PR_NUMBER=${{ github.event.pull_request.number }} - TOKEN=${{ secrets.PAT_REVIEW }} - REPO=${{ github.repository }} + PR_NUMBER="${{ github.event.pull_request.number }}" + TOKEN="${{ secrets.PAT_REVIEW }}" + REPO="${{ github.repository }}" if [[ "${{ steps.push_cassettes.outputs.updated }}" == "true" ]]; then echo "Adding label and comment..." - curl -X POST \ - -H "Authorization: Bearer $TOKEN" \ - -H "Accept: application/vnd.github.v3+json" \ - https://api.github.com/repos/$REPO/issues/$PR_NUMBER/labels \ - -d '{"labels":["behaviour change"]}' - echo $TOKEN | gh auth login --with-token - gh api repos/$REPO/issues/$PR_NUMBER/comments -X POST -F body="You changed AutoGPT's behaviour. The cassettes have been updated and will be merged to the submodule when this Pull Request gets merged." + gh issue edit $PR_NUMBER --add-label "behaviour change" + gh issue comment $PR_NUMBER --body "You changed AutoGPT's behaviour. The cassettes have been updated and will be merged to the submodule when this Pull Request gets merged." fi - name: Upload logs to artifact diff --git a/.github/workflows/autogpt-docker-ci.yml b/.github/workflows/autogpt-docker-ci.yml index a6f336a75..dc555c381 100644 --- a/.github/workflows/autogpt-docker-ci.yml +++ b/.github/workflows/autogpt-docker-ci.yml @@ -4,11 +4,13 @@ on: push: branches: [ master, development ] paths: + - '.github/workflows/autogpt-docker-ci.yml' - 'autogpts/autogpt/**' - '!autogpts/autogpt/tests/vcr_cassettes' pull_request: branches: [ master, development, release-* ] paths: + - '.github/workflows/autogpt-docker-ci.yml' - 'autogpts/autogpt/**' - '!autogpts/autogpt/tests/vcr_cassettes' @@ -22,6 +24,8 @@ defaults: env: IMAGE_NAME: auto-gpt + DEPLOY_IMAGE_NAME: ${{ secrets.DOCKER_USER }}/auto-gpt + DEV_IMAGE_TAG: latest-dev jobs: build: @@ -85,12 +89,27 @@ jobs: test: runs-on: ubuntu-latest timeout-minutes: 10 + + services: + minio: + image: minio/minio:edge-cicd + options: > + --name=minio + --health-interval=10s --health-timeout=5s --health-retries=3 + --health-cmd="curl -f http://localhost:9000/minio/health/live" + steps: - name: Check out repository uses: actions/checkout@v3 with: submodules: true + - name: Log in to Docker hub + uses: docker/login-action@v2 + with: + username: ${{ secrets.DOCKER_USER }} + password: ${{ secrets.DOCKER_PASSWORD }} + - name: Set up Docker Buildx uses: docker/setup-buildx-action@v2 @@ -100,7 +119,9 @@ jobs: with: context: autogpts/autogpt build-args: BUILD_TYPE=dev # include pytest - tags: ${{ env.IMAGE_NAME }} + tags: > + ${{ env.IMAGE_NAME }}, + ${{ env.DEPLOY_IMAGE_NAME }}:${{ env.DEV_IMAGE_TAG }} load: true # save to docker images # cache layers in GitHub Actions cache to speed up builds cache-from: type=gha,scope=autogpt-docker-dev @@ -112,24 +133,30 @@ jobs: CI: true PLAIN_OUTPUT: True OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} + S3_ENDPOINT_URL: http://minio:9000 + AWS_ACCESS_KEY_ID: minioadmin + AWS_SECRET_ACCESS_KEY: minioadmin run: | set +e - test_output=$( - docker run --env CI --env OPENAI_API_KEY \ - --entrypoint poetry ${{ env.IMAGE_NAME }} run \ - pytest -v --cov=autogpt --cov-branch --cov-report term-missing \ - --numprocesses=4 --durations=10 \ - tests/unit tests/integration 2>&1 - ) - test_failure=$? + docker run --env CI --env OPENAI_API_KEY \ + --network container:minio \ + --env S3_ENDPOINT_URL --env AWS_ACCESS_KEY_ID --env AWS_SECRET_ACCESS_KEY \ + --entrypoint poetry ${{ env.IMAGE_NAME }} run \ + pytest -v --cov=autogpt --cov-branch --cov-report term-missing \ + --numprocesses=4 --durations=10 \ + tests/unit tests/integration 2>&1 | tee test_output.txt - echo "$test_output" + test_failure=${PIPESTATUS[0]} cat << $EOF >> $GITHUB_STEP_SUMMARY # Tests $([ $test_failure = 0 ] && echo '✅' || echo '❌') \`\`\` - $test_output + $(cat test_output.txt) \`\`\` $EOF exit $test_failure + + - if: github.event_name == 'push' && github.ref_name == 'master' + name: Push image to Docker Hub + run: docker push ${{ env.DEPLOY_IMAGE_NAME }}:${{ env.DEV_IMAGE_TAG }} diff --git a/.github/workflows/autogpt-docker-release.yml b/.github/workflows/autogpt-docker-release.yml index df2f0e9f2..4213c78b5 100644 --- a/.github/workflows/autogpt-docker-release.yml +++ b/.github/workflows/autogpt-docker-release.yml @@ -20,6 +20,7 @@ env: jobs: build: + if: startsWith(github.ref, 'refs/tags/autogpt-') runs-on: ubuntu-latest steps: - name: Checkout repository @@ -37,7 +38,9 @@ jobs: # slashes are not allowed in image tags, but can appear in git branch or tag names - id: sanitize_tag name: Sanitize image tag - run: echo tag=${raw_tag//\//-} >> $GITHUB_OUTPUT + run: | + tag=${raw_tag//\//-} + echo tag=${tag#autogpt-} >> $GITHUB_OUTPUT env: raw_tag: ${{ github.ref_name }} diff --git a/.github/workflows/autogpts-ci.yml b/.github/workflows/autogpts-ci.yml index 4f89fb7c9..0385470ac 100644 --- a/.github/workflows/autogpts-ci.yml +++ b/.github/workflows/autogpts-ci.yml @@ -1,4 +1,4 @@ -name: Valid AutoGPTs +name: AutoGPTs smoke test CI on: workflow_dispatch: @@ -6,8 +6,24 @@ on: - cron: '0 8 * * *' push: branches: [ master, development, ci-test* ] + paths: + - '.github/workflows/autogpts-ci.yml' + - 'autogpts/**' + - 'benchmark/**' + - 'run' + - 'cli.py' + - 'setup.py' + - '!**/*.md' pull_request: branches: [ master, development, release-* ] + paths: + - '.github/workflows/autogpts-ci.yml' + - 'autogpts/**' + - 'benchmark/**' + - 'run' + - 'cli.py' + - 'setup.py' + - '!**/*.md' jobs: run-tests: @@ -17,13 +33,13 @@ jobs: agent-name: [ autogpt, forge ] fail-fast: false timeout-minutes: 20 + env: + min-python-version: '3.10' steps: - name: Checkout repository uses: actions/checkout@v3 with: fetch-depth: 0 - ref: ${{ github.event.pull_request.head.ref }} - repository: ${{ github.event.pull_request.head.repo.full_name }} submodules: true - name: Set up Python ${{ env.min-python-version }} diff --git a/.github/workflows/benchmark-ci.yml b/.github/workflows/benchmark-ci.yml index fd8020d24..5f95dd025 100644 --- a/.github/workflows/benchmark-ci.yml +++ b/.github/workflows/benchmark-ci.yml @@ -14,19 +14,18 @@ on: - '!benchmark/reports/**' - .github/workflows/benchmark-ci.yml +env: + min-python-version: '3.10' + jobs: lint: runs-on: ubuntu-latest - env: - min-python-version: '3.10' steps: - name: Checkout repository uses: actions/checkout@v3 with: fetch-depth: 0 - ref: ${{ github.event.pull_request.head.ref }} - repository: ${{ github.event.pull_request.head.repo.full_name }} - name: Set up Python ${{ env.min-python-version }} uses: actions/setup-python@v2 @@ -82,8 +81,6 @@ jobs: uses: actions/checkout@v3 with: fetch-depth: 0 - ref: ${{ github.event.pull_request.head.ref }} - repository: ${{ github.event.pull_request.head.repo.full_name }} submodules: true - name: Set up Python ${{ env.min-python-version }} diff --git a/.github/workflows/benchmarks.yml b/.github/workflows/benchmarks.yml deleted file mode 100644 index af2383a63..000000000 --- a/.github/workflows/benchmarks.yml +++ /dev/null @@ -1,73 +0,0 @@ -name: Benchmarks (legacy) - -on: - schedule: - - cron: '0 8 * * *' - workflow_dispatch: - -jobs: - Benchmark: - name: ${{ matrix.config.task-name }} - runs-on: ubuntu-latest - timeout-minutes: 30 - strategy: - fail-fast: false - matrix: - config: - - python-version: "3.10" - task: "tests/challenges" - task-name: "Mandatory Tasks" - - python-version: "3.10" - task: "--beat-challenges -ra tests/challenges" - task-name: "Challenging Tasks" - - steps: - - name: Checkout repository - uses: actions/checkout@v3 - with: - ref: master - - - name: Set up Python ${{ matrix.config.python-version }} - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.config.python-version }} - - - id: get_date - name: Get date - run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT - - - name: Set up Python dependency cache - uses: actions/cache@v3 - with: - path: ~/.cache/pypoetry - key: ${{ runner.os }}-poetry-${{ hashFiles('autogpts/autogpt/pyproject.toml') }}-${{ steps.get_date.outputs.date }} - - - name: Install Python dependencies - run: | - curl -sSL https://install.python-poetry.org | python3 - - poetry install - - - name: Run pytest with coverage - run: | - rm -rf tests/vcr_cassettes - pytest -n auto --record-mode=all ${{ matrix.config.task }} - env: - CI: true - PROXY: ${{ secrets.PROXY }} - AGENT_MODE: ${{ secrets.AGENT_MODE }} - AGENT_TYPE: ${{ secrets.AGENT_TYPE }} - PLAIN_OUTPUT: True - - - name: Upload logs as artifact - if: always() - uses: actions/upload-artifact@v3 - with: - name: test-logs-${{ matrix.config.task-name }} - path: logs/ - - - name: Upload cassettes as artifact - if: always() - uses: actions/upload-artifact@v3 - with: - name: cassettes-${{ matrix.config.task-name }} - path: tests/vcr_cassettes/ diff --git a/.github/workflows/close-stale-issues.yml b/.github/workflows/close-stale-issues.yml index 615e3ef64..f8d66dcea 100644 --- a/.github/workflows/close-stale-issues.yml +++ b/.github/workflows/close-stale-issues.yml @@ -13,7 +13,7 @@ jobs: steps: - uses: actions/stale@v8 with: - operations-per-run: 5000 + # operations-per-run: 5000 stale-issue-message: > This issue has automatically been marked as _stale_ because it has not had any activity in the last 50 days. You can _unstale_ it by commenting or @@ -28,7 +28,7 @@ jobs: days-before-stale: 50 days-before-close: 10 # Do not touch meta issues: - exempt-issue-labels: meta + exempt-issue-labels: meta,fridge,project management # Do not affect pull requests: days-before-pr-stale: -1 days-before-pr-close: -1 diff --git a/.github/workflows/hackathon.yml b/.github/workflows/hackathon.yml index 6d80f644c..3becee799 100644 --- a/.github/workflows/hackathon.yml +++ b/.github/workflows/hackathon.yml @@ -2,16 +2,33 @@ name: Hackathon on: workflow_dispatch: - branches: [hackathon] inputs: agents: description: "Agents to run (comma-separated)" required: false - default: "ZEROAGPT_03" # Default agents if none are specified + default: "autogpt" # Default agents if none are specified jobs: matrix-setup: runs-on: ubuntu-latest + # Service containers to run with `matrix-setup` + services: + # Label used to access the service container + postgres: + # Docker Hub image + image: postgres + # Provide the password for postgres + env: + POSTGRES_PASSWORD: postgres + # Set health checks to wait until postgres has started + options: >- + --health-cmd pg_isready + --health-interval 10s + --health-timeout 5s + --health-retries 5 + ports: + # Maps tcp port 5432 on service container to the host + - 5432:5432 outputs: matrix: ${{ steps.set-matrix.outputs.matrix }} env-name: ${{ steps.set-matrix.outputs.env-name }} @@ -20,7 +37,7 @@ jobs: run: | if [ "${{ github.event_name }}" == "schedule" ]; then echo "::set-output name=env-name::production" - echo "::set-output name=matrix::[ 'ZEROAGPT_03', 'evo-ninja', 'gpt-engineer']" + echo "::set-output name=matrix::[ 'irrelevant']" elif [ "${{ github.event_name }}" == "workflow_dispatch" ]; then IFS=',' read -ra matrix_array <<< "${{ github.event.inputs.agents }}" matrix_string="[ \"$(echo "${matrix_array[@]}" | sed 's/ /", "/g')\" ]" @@ -28,7 +45,7 @@ jobs: echo "::set-output name=matrix::$matrix_string" else echo "::set-output name=env-name::testing" - echo "::set-output name=matrix::[ 'mini-agi' ]" + echo "::set-output name=matrix::[ 'irrelevant' ]" fi tests: @@ -39,6 +56,23 @@ jobs: min-python-version: "3.10" name: "${{ matrix.agent-name }}" runs-on: ubuntu-latest + services: + # Label used to access the service container + postgres: + # Docker Hub image + image: postgres + # Provide the password for postgres + env: + POSTGRES_PASSWORD: postgres + # Set health checks to wait until postgres has started + options: >- + --health-cmd pg_isready + --health-interval 10s + --health-timeout 5s + --health-retries 5 + ports: + # Maps tcp port 5432 on service container to the host + - 5432:5432 timeout-minutes: 50 strategy: fail-fast: false @@ -49,12 +83,14 @@ jobs: run: | echo "Matrix Setup Environment Name: ${{ needs.matrix-setup.outputs.env-name }}" + - name: Check Docker Container + id: check + run: docker ps + - name: Checkout repository uses: actions/checkout@v3 with: fetch-depth: 0 - ref: ${{ github.event.pull_request.head.ref }} - repository: ${{ github.event.pull_request.head.repo.full_name }} submodules: true - name: Set up Python ${{ env.min-python-version }} @@ -70,16 +106,28 @@ jobs: run: | curl -sSL https://install.python-poetry.org | python - + - name: Install Node.js + uses: actions/setup-node@v1 + with: + node-version: v18.15 + - name: Run benchmark run: | link=$(jq -r '.["github_repo_url"]' arena/$AGENT_NAME.json) branch=$(jq -r '.["branch_to_benchmark"]' arena/$AGENT_NAME.json) git clone "$link" -b "$branch" "$AGENT_NAME" cd $AGENT_NAME + cp ./autogpts/$AGENT_NAME/.env.example ./autogpts/$AGENT_NAME/.env || echo "file not found" ./run agent start $AGENT_NAME - cd benchmark + cd ../benchmark poetry install - poetry run agbenchmark + poetry run agbenchmark --no-dep env: OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} + SERP_API_KEY: ${{ secrets.SERP_API_KEY }} + SERPAPI_API_KEY: ${{ secrets.SERP_API_KEY }} + WEAVIATE_API_KEY: ${{ secrets.WEAVIATE_API_KEY }} + WEAVIATE_URL: ${{ secrets.WEAVIATE_URL }} + GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }} + GOOGLE_CUSTOM_SEARCH_ENGINE_ID: ${{ secrets.GOOGLE_CUSTOM_SEARCH_ENGINE_ID }} AGENT_NAME: ${{ matrix.agent-name }} diff --git a/.gitignore b/.gitignore index dcfbc4df7..c4f86e958 100644 --- a/.gitignore +++ b/.gitignore @@ -172,4 +172,8 @@ pri* # ignore ig* .github_access_token -arena/TestAgent.json
\ No newline at end of file +arena/TestAgent.json + +# evo.ninja +autogpts/evo.ninja/* +!autogpts/evo.ninja/setup diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 994dde3f2..acea33066 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -2,36 +2,33 @@ If you are reading this, you are probably looking for our **[contribution guide]**, which is part of our [knowledge base]. +You can find our immediate priorities and their progress on our public [kanban board]. + [contribution guide]: https://github.com/Significant-Gravitas/Nexus/wiki/Contributing [knowledge base]: https://github.com/Significant-Gravitas/Nexus/wiki +[kanban board]: https://github.com/orgs/Significant-Gravitas/projects/1 ## In short 1. Avoid duplicate work, issues, PRs etc. -2. Also consider contributing something other than code; see the [contribution guide] - for options. -3. Create a draft PR before starting work on non-small changes. Also post your proposal - in the [dev channel]. -4. Clearly explain your changes when submitting a PR. -5. Don't submit stuff that's broken. -6. Avoid making unnecessary changes, especially if they're purely based on your personal - preferences. Doing so is the maintainers' job. +2. We encourage you to collaborate with fellow community members on some of our bigger + [todo's][kanban board]! + * We highly recommend to post your idea and discuss it in the [dev channel]. +4. Create a draft PR when starting work on bigger changes. +3. Please also consider contributing something other than code; see the + [contribution guide] for options. +5. Clearly explain your changes when submitting a PR. +6. Don't submit stuff that's broken. +7. Avoid making unnecessary changes, especially if they're purely based on your personal + preferences. Doing so is the maintainers' job. ;-) [dev channel]: https://discord.com/channels/1092243196446249134/1095817829405704305 -## Why instructions like these are necessary -We would like to say "We value all contributions". After all, we are an open-source -project, so we should welcome any input that people are willing to give, right? - -Well, the reality is that some contributions are SUPER-valuable, while others create -more trouble than they are worth and actually _create_ work for the core team. So to -ensure maximum chances of a smooth ride, please stick to the guidelines. - If you wish to involve with the project (beyond just contributing PRs), please read the wiki [catalyzing](https://github.com/Significant-Gravitas/Nexus/wiki/Catalyzing) page. In fact, why not just look through the whole wiki (it's only a few pages) and hop on our Discord. See you there! :-) -❤️ & 🔆 -The team @ AutoGPT +❤️ & 🔆 +The team @ AutoGPT https://discord.gg/autogpt @@ -1,76 +1,106 @@ -# 🌟 AutoGPT: the heart of the open-source agent ecosystem +# AutoGPT: build & use AI agents -[](https://discord.gg/autogpt) [](https://github.com/Significant-Gravitas/AutoGPT/stargazers) [](https://twitter.com/Auto_GPT) [](https://opensource.org/licenses/MIT) +[](https://discord.gg/autogpt)   +[](https://twitter.com/Auto_GPT)   +[](https://opensource.org/licenses/MIT) -**AutoGPT** is your go-to toolkit for supercharging agents. With its modular and extensible framework, you're empowered to focus on: +**AutoGPT** is the vision of the power of AI accessible to everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters: - 🏗️ **Building** - Lay the foundation for something amazing. - 🧪 **Testing** - Fine-tune your agent to perfection. -- 👀 **Viewing** - See your progress come to life. +- 🤝 **Delegating** - Let AI work for you, and have your ideas come to life. -Be part of the revolution! **AutoGPT** stays at the forefront of AI innovation, featuring the codebase for the reigning champion in the Open-Source ecosystem. +Be part of the revolution! **AutoGPT** is here to stay, at the forefront of AI innovation. ---- +**📖 [Documentation](https://docs.agpt.co)** + |  +**🚀 [Contributing](CONTRIBUTING.md)** + |  +**🛠️ [Build your own Agent - Quickstart](QUICKSTART.md)** -<p align="center"> - <a href="https://lablab.ai/event/autogpt-arena-hacks"> - <img src="https://lablab.ai/_next/image?url=https%3A%2F%2Fstorage.googleapis.com%2Flablab-static-eu%2Fimages%2Fevents%2Fcll6p5cxj0000356zslac05gg%2Fcll6p5cxj0000356zslac05gg_imageLink_562z1jzj.jpg&w=1080&q=75" alt="AutoGPT Arena Hacks Hackathon" /> - </a> -</p> -<p align="center"> - <strong>We're hosting a Hackathon!</strong> - <br> - Click the banner above for details and registration! -</p> +## 🥇 Current Best Agent: evo.ninja +[Current Best Agent]: #-current-best-agent-evoninja ---- +The AutoGPT Arena Hackathon saw [**evo.ninja**](https://github.com/polywrap/evo.ninja) earn the top spot on our Arena Leaderboard, proving itself as the best open-source generalist agent. Try it now at https://evo.ninja! -## 🥇 Current Best Agent: AutoGPT +📈 To challenge evo.ninja, AutoGPT, and others, submit your benchmark run to the [Leaderboard](#-leaderboard), and maybe your agent will be up here next! -Among our currently benchmarked agents, AutoGPT scores the best. This will change after the hackathon - the top-performing generalist agent will earn the esteemed position as the primary AutoGPT 🎊 +## 🧱 Building blocks -📈 To enter, submit your benchmark run through the UI. +### 🏗️ Forge -## 🌟 Quickstart +**Forge your own agent!** – Forge is a ready-to-go template for your agent application. All the boilerplate code is already handled, letting you channel all your creativity into the things that set *your* agent apart. All tutorials are located [here](https://medium.com/@aiedge/autogpt-forge-e3de53cc58ec). Components from the [`forge.sdk`](/autogpts/forge/forge/sdk) can also be used individually to speed up development and reduce boilerplate in your agent project. -- **To build your own agent** and to be eligible for the hackathon, follow the quickstart guide [here](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpts/forge/tutorials/001_getting_started.md). This will guide you through the process of creating your own agent and using the benchmark and user interface. +🚀 [**Getting Started with Forge**](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpts/forge/tutorials/001_getting_started.md) – +This guide will walk you through the process of creating your own agent and using the benchmark and user interface. -- **To activate the best agent** follow the guide [here](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpts/autogpt/README.md). +📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/forge) about Forge -Want to build your own groundbreaking agent using AutoGPT? 🛠️ There are three major components to focus on: +### 🎯 Benchmark -### 🏗️ the Forge +**Measure your agent's performance!** The `agbenchmark` can be used with any agent that supports the agent protocol, and the integration with the project's [CLI] makes it even easier to use with AutoGPT and forge-based agents. The benchmark offers a stringent testing environment. Our framework allows for autonomous, objective performance evaluations, ensuring your agents are primed for real-world action. -**Forge your future!** The `forge` is your innovation lab. All the boilerplate code is already handled, letting you channel all your creativity into building a revolutionary agent. It's more than a starting point, it's a launchpad for your ideas. All tutorials are located [here](https://medium.com/@aiedge/autogpt-forge-e3de53cc58ec). +<!-- TODO: insert visual demonstrating the benchmark --> -📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/forge) +📦 [`agbenchmark`](https://pypi.org/project/agbenchmark/) on Pypi + |  +📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/blob/master/benchmark) about the Benchmark -### 🎯 the Benchmark +#### 🏆 [Leaderboard][leaderboard] +[leaderboard]: https://leaderboard.agpt.co -**Test to impress!** The `benchmark` offers a stringent testing environment. Our framework allows for autonomous, objective performance evaluations, ensuring your agents are primed for real-world action. +Submit your benchmark run through the UI and claim your place on the AutoGPT Arena Leaderboard! The best scoring general agent earns the title of **[Current Best Agent]**, and will be adopted into our repo so people can easily run it through the [CLI]. -📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/blob/master/benchmark) +[][leaderboard] -### 🎮 the UI +### 💻 UI -**Take Control!** The `frontend` is your personal command center. It gives you a user-friendly interface to control and monitor your agents, making it easier to bring your ideas to life. +**Makes agents easy to use!** The `frontend` gives you a user-friendly interface to control and monitor your agents. It connects to agents through the [agent protocol](#-agent-protocol), ensuring compatibility with many agents from both inside and outside of our ecosystem. -📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/frontend) +<!-- TODO: instert screenshot of front end --> ---- +The frontend works out-of-the-box with all agents in the repo. Just use the [CLI] to run your agent of choice! -### 🔄 Agent Protocol +📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/tree/master/frontend) about the Frontend + +### ⌨️ CLI + +[CLI]: #-cli -🔌 **Standardize to Maximize!** To maintain a uniform standard and ensure seamless compatibility, AutoGPT employs the [agent protocol](https://agentprotocol.ai/) from the AI Engineer Foundation. This standardizes the communication pathways from your agent to the frontend and benchmark. +To make it as easy as possible to use all of the tools offered by the repository, a CLI is included at the root of the repo: -### 🤔 Questions? Problems? Suggestions? +```shell +$ ./run +Usage: cli.py [OPTIONS] COMMAND [ARGS]... -#### Get help - [Discord 💬](https://discord.gg/autogpt) +Options: + --help Show this message and exit. + +Commands: + agent Commands to create, start and stop agents + arena Commands to enter the arena + benchmark Commands to start the benchmark and list tests and categories + setup Installs dependencies needed for your system. +``` + +Just clone the repo, install dependencies with `./run setup`, and you should be good to go! + +## 🤔 Questions? Problems? Suggestions? + +### Get help - [Discord 💬](https://discord.gg/autogpt) [](https://discord.gg/autogpt) To report a bug or request a feature, create a [GitHub Issue](https://github.com/Significant-Gravitas/AutoGPT/issues/new/choose). Please ensure someone else hasn’t created an issue for the same topic. +## 🤝 Sister projects + +### 🔄 Agent Protocol + +To maintain a uniform standard and ensure seamless compatibility with many current and future applications, AutoGPT employs the [agent protocol](https://agentprotocol.ai/) standard by the AI Engineer Foundation. This standardizes the communication pathways from your agent to the frontend and benchmark. + +--- + <p align="center"> <a href="https://star-history.com/#Significant-Gravitas/AutoGPT&Date"> <img src="https://api.star-history.com/svg?repos=Significant-Gravitas/AutoGPT&type=Date" alt="Star History Chart"> diff --git a/ai_settings.yaml b/ai_settings.yaml deleted file mode 100644 index 6f5fe4aa2..000000000 --- a/ai_settings.yaml +++ /dev/null @@ -1,7 +0,0 @@ -ai_goals: -- Give a report of recent activities of linkedin competitors -- The report should be brief, contains only important messages -- If applicable, provide numbers and links -- Give conclusion and suggestions to CEO -ai_name: CEO Office -ai_role: an AI designed to study the competitors of Linkedin company diff --git a/arena/Susan.json b/arena/Susan.json new file mode 100644 index 000000000..4689ef84e --- /dev/null +++ b/arena/Susan.json @@ -0,0 +1,6 @@ +{ + "github_repo_url": "https://github.com/CodeZeno/Susan", + "timestamp": "2023-11-03T11:29:28.704822", + "commit_hash_to_benchmark": "82fecfae1b4fb5d64050eefa77d8f028292aa8f3", + "branch_to_benchmark": "master" +}
\ No newline at end of file diff --git a/arena/autogpt.json b/arena/autogpt.json index 59e129caa..2de49117f 100644 --- a/arena/autogpt.json +++ b/arena/autogpt.json @@ -1,6 +1,6 @@ { - "github_repo_url": "https://github.com/significant-gravitas/AutoGPT", - "timestamp": "2023-11-08T16:19:12.986257", - "commit_hash_to_benchmark": "6c84035c7e0586e2c16c9cc8b1f2540588b6a7ba", + "github_repo_url": "https://github.com/Significant-Gravitas/AutoGPT", + "timestamp": "2023-11-15T07:22:09.723393", + "commit_hash_to_benchmark": "fa357dd13928baa4d1e30054bc75edc5d68b08f1", "branch_to_benchmark": "master" -}
\ No newline at end of file +} diff --git a/arena/songyalei.json b/arena/songyalei.json new file mode 100644 index 000000000..2c3b7dcc3 --- /dev/null +++ b/arena/songyalei.json @@ -0,0 +1,6 @@ +{ + "github_repo_url": "https://github.com/songyalei/AutoGPT", + "timestamp": "2023-11-16T07:11:39.746384", + "commit_hash_to_benchmark": "fa357dd13928baa4d1e30054bc75edc5d68b08f1", + "branch_to_benchmark": "master" +}
\ No newline at end of file diff --git a/autogpts/autogpt/.env.template b/autogpts/autogpt/.env.template index 0ab9a4e55..9ec564a5d 100644 --- a/autogpts/autogpt/.env.template +++ b/autogpts/autogpt/.env.template @@ -1,5 +1,3 @@ -# For further descriptions of these settings see docs/configuration/options.md or go to docs.agpt.co - ################################################################################ ### AutoGPT - GENERAL SETTINGS ################################################################################ @@ -10,9 +8,32 @@ OPENAI_API_KEY=your-openai-api-key ## EXECUTE_LOCAL_COMMANDS - Allow local command execution (Default: False) # EXECUTE_LOCAL_COMMANDS=False -## RESTRICT_TO_WORKSPACE - Restrict file operations to workspace ./auto_gpt_workspace (Default: True) +### Workspace ### + +## RESTRICT_TO_WORKSPACE - Restrict file operations to workspace ./data/agents/<agent_id>/workspace (Default: True) # RESTRICT_TO_WORKSPACE=True +## DISABLED_COMMAND_CATEGORIES - The list of categories of commands that are disabled (Default: None) +# DISABLED_COMMAND_CATEGORIES= + +## WORKSPACE_BACKEND - Choose a storage backend for workspace contents +## Options: local, gcs, s3 +# WORKSPACE_BACKEND=local + +## WORKSPACE_STORAGE_BUCKET - GCS/S3 Bucket to store workspace contents in +# WORKSPACE_STORAGE_BUCKET=autogpt + +## GCS Credentials +# see https://cloud.google.com/storage/docs/authentication#libauth + +## AWS/S3 Credentials +# see https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html + +## S3_ENDPOINT_URL - If you're using non-AWS S3, set your endpoint here. +# S3_ENDPOINT_URL= + +### Miscellaneous ### + ## USER_AGENT - Define the user-agent used by the requests library to browse website (string) # USER_AGENT="Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36" @@ -25,26 +46,12 @@ OPENAI_API_KEY=your-openai-api-key ## PROMPT_SETTINGS_FILE - Specifies which Prompt Settings file to use, relative to the AutoGPT root directory. (defaults to prompt_settings.yaml) # PROMPT_SETTINGS_FILE=prompt_settings.yaml -## OPENAI_API_BASE_URL - Custom url for the OpenAI API, useful for connecting to custom backends. No effect if USE_AZURE is true, leave blank to keep the default url -# the following is an example: -# OPENAI_API_BASE_URL=http://localhost:443/v1 - -## OPENAI_FUNCTIONS - Enables OpenAI functions: https://platform.openai.com/docs/guides/gpt/function-calling -## WARNING: this feature is only supported by OpenAI's newest models. Until these models become the default on 27 June, add a '-0613' suffix to the model of your choosing. -# OPENAI_FUNCTIONS=False - ## AUTHORISE COMMAND KEY - Key to authorise commands # AUTHORISE_COMMAND_KEY=y ## EXIT_KEY - Key to exit AutoGPT # EXIT_KEY=n -## PLAIN_OUTPUT - Plain output, which disables the spinner (Default: False) -# PLAIN_OUTPUT=False - -## DISABLED_COMMAND_CATEGORIES - The list of categories of commands that are disabled (Default: None) -# DISABLED_COMMAND_CATEGORIES= - ################################################################################ ### LLM PROVIDER ################################################################################ @@ -52,15 +59,28 @@ OPENAI_API_KEY=your-openai-api-key ## TEMPERATURE - Sets temperature in OpenAI (Default: 0) # TEMPERATURE=0 +## OPENAI_API_BASE_URL - Custom url for the OpenAI API, useful for connecting to custom backends. No effect if USE_AZURE is true, leave blank to keep the default url +# the following is an example: +# OPENAI_API_BASE_URL=http://localhost:443/v1 + +# OPENAI_API_TYPE= +# OPENAI_API_VERSION= + +## OPENAI_FUNCTIONS - Enables OpenAI functions: https://platform.openai.com/docs/guides/gpt/function-calling +## Note: this feature is only supported by OpenAI's newer models. +# OPENAI_FUNCTIONS=False + ## OPENAI_ORGANIZATION - Your OpenAI Organization key (Default: None) # OPENAI_ORGANIZATION= ## USE_AZURE - Use Azure OpenAI or not (Default: False) # USE_AZURE=False -## AZURE_CONFIG_FILE - The path to the azure.yaml file, relative to the AutoGPT root directory. (Default: azure.yaml) +## AZURE_CONFIG_FILE - The path to the azure.yaml file, relative to the folder containing this file. (Default: azure.yaml) # AZURE_CONFIG_FILE=azure.yaml +# AZURE_OPENAI_AD_TOKEN= +# AZURE_OPENAI_ENDPOINT= ################################################################################ ### LLM MODELS @@ -91,32 +111,6 @@ OPENAI_API_KEY=your-openai-api-key # SHELL_ALLOWLIST= ################################################################################ -### MEMORY -################################################################################ - -### General - -## MEMORY_BACKEND - Memory backend type -# MEMORY_BACKEND=json_file - -## MEMORY_INDEX - Value used in the Memory backend for scoping, naming, or indexing (Default: auto-gpt) -# MEMORY_INDEX=auto-gpt - -### Redis - -## REDIS_HOST - Redis host (Default: localhost, use "redis" for docker-compose) -# REDIS_HOST=localhost - -## REDIS_PORT - Redis port (Default: 6379) -# REDIS_PORT=6379 - -## REDIS_PASSWORD - Redis password (Default: "") -# REDIS_PASSWORD= - -## WIPE_REDIS_ON_START - Wipes data / index on start (Default: True) -# WIPE_REDIS_ON_START=True - -################################################################################ ### IMAGE GENERATION PROVIDER ################################################################################ @@ -191,13 +185,12 @@ OPENAI_API_KEY=your-openai-api-key ################################################################################ ## TEXT_TO_SPEECH_PROVIDER - Which Text to Speech provider to use (Default: gtts) +## Options: gtts, streamelements, elevenlabs, macos # TEXT_TO_SPEECH_PROVIDER=gtts -### Only if TEXT_TO_SPEECH_PROVIDER=streamelements ## STREAMELEMENTS_VOICE - Voice to use for StreamElements (Default: Brian) # STREAMELEMENTS_VOICE=Brian -### Only if TEXT_TO_SPEECH_PROVIDER=elevenlabs ## ELEVENLABS_API_KEY - Eleven Labs API key (Default: None) # ELEVENLABS_API_KEY= @@ -210,3 +203,31 @@ OPENAI_API_KEY=your-openai-api-key ## CHAT_MESSAGES_ENABLED - Enable chat messages (Default: False) # CHAT_MESSAGES_ENABLED=False + +################################################################################ +### LOGGING +################################################################################ + +## LOG_LEVEL - Set the minimum level to filter log output by. Setting this to DEBUG implies LOG_FORMAT=debug, unless LOG_FORMAT is set explicitly. +## Options: DEBUG, INFO, WARNING, ERROR, CRITICAL +# LOG_LEVEL=INFO + +## LOG_FORMAT - The format in which to log messages to the console (and log files). +## Options: simple, debug, structured_google_cloud +# LOG_FORMAT=simple + +## LOG_FILE_FORMAT - Normally follows the LOG_FORMAT setting, but can be set separately. +## Note: Log file output is disabled if LOG_FORMAT=structured_google_cloud. +# LOG_FILE_FORMAT=simple + +## PLAIN_OUTPUT - Disables animated typing and the spinner in the console output. (Default: False) +# PLAIN_OUTPUT=False + + +################################################################################ +### Agent Protocol Server Settings +################################################################################ +## AP_SERVER_PORT - Specifies what port the agent protocol server will listen on. (Default: 8000) +# AP_SERVER_PORT=8000 +# # AP_SERVER_DB_URL - Specifies what connection url the agent protocol database will connect to (Default: Internal SQLite) +# AP_SERVER_DB_URL=sqlite:///data/ap_server.db diff --git a/autogpts/autogpt/.flake8 b/autogpts/autogpt/.flake8 new file mode 100644 index 000000000..b9aa1bc73 --- /dev/null +++ b/autogpts/autogpt/.flake8 @@ -0,0 +1,11 @@ +[flake8] +max-line-length = 88 +extend-exclude = + .*_cache/, + .venv, + data/, + logs/, + tests/unit/data/, +extend-ignore = + # No whitespace before ':' conflicts with Black style for slices + E203, diff --git a/autogpts/autogpt/.gitignore b/autogpts/autogpt/.gitignore index 30555099c..aaff758a0 100644 --- a/autogpts/autogpt/.gitignore +++ b/autogpts/autogpt/.gitignore @@ -1,7 +1,6 @@ ## Original ignores autogpt/keys.py autogpt/*.json -auto_gpt_workspace/* *.mpeg .env azure.yaml diff --git a/autogpts/autogpt/.isort.cfg b/autogpts/autogpt/.isort.cfg deleted file mode 100644 index 17eab482f..000000000 --- a/autogpts/autogpt/.isort.cfg +++ /dev/null @@ -1,10 +0,0 @@ -[settings] -profile = black -multi_line_output = 3 -include_trailing_comma = true -force_grid_wrap = 0 -use_parentheses = true -ensure_newline_before_comments = true -line_length = 88 -sections = FUTURE,STDLIB,THIRDPARTY,FIRSTPARTY,LOCALFOLDER -skip = .tox,__pycache__,*.pyc,venv*/*,reports,venv,env,node_modules,.env,.venv,dist diff --git a/autogpts/autogpt/.pre-commit-config.yaml b/autogpts/autogpt/.pre-commit-config.yaml index cb7180d4c..d2a061a4d 100644 --- a/autogpts/autogpt/.pre-commit-config.yaml +++ b/autogpts/autogpt/.pre-commit-config.yaml @@ -22,21 +22,21 @@ repos: - id: black language_version: python3.10 - - repo: https://github.com/pre-commit/mirrors-mypy - rev: 'v1.3.0' - hooks: - - id: mypy + # - repo: https://github.com/pre-commit/mirrors-mypy + # rev: 'v1.3.0' + # hooks: + # - id: mypy - repo: local hooks: - - id: autoflake - name: autoflake - entry: autoflake --in-place --remove-all-unused-imports --recursive --ignore-init-module-imports --ignore-pass-after-docstring autogpt tests - language: python - types: [ python ] + # - id: autoflake + # name: autoflake + # entry: autoflake --in-place --remove-all-unused-imports --recursive --ignore-init-module-imports --ignore-pass-after-docstring autogpt tests + # language: python + # types: [ python ] - id: pytest-check name: pytest-check - entry: pytest --cov=autogpt tests/unit + entry: bash -c 'cd autogpts/autogpt && poetry run pytest --cov=autogpt tests/unit' language: system pass_filenames: false always_run: true diff --git a/autogpts/autogpt/BULLETIN.md b/autogpts/autogpt/BULLETIN.md index b75ed33ba..0140e7122 100644 --- a/autogpts/autogpt/BULLETIN.md +++ b/autogpts/autogpt/BULLETIN.md @@ -1,21 +1,13 @@ # QUICK LINKS 🔗 # -------------- 🌎 *Official Website*: https://agpt.co. -📖 *User Guide*: https://docs.agpt.co. +📖 *User Guide*: https://docs.agpt.co/autogpt. 👩 *Contributors Wiki*: https://github.com/Significant-Gravitas/Nexus/wiki/Contributing. -# v0.4.7 RELEASE HIGHLIGHTS! 🚀 -# ----------------------------- -This release introduces initial REST API support, powered by e2b's agent -protocol SDK (https://github.com/e2b-dev/agent-protocol#sdk). - -It also includes improvements to prompt generation and support -for our new benchmarking tool, Auto-GPT-Benchmarks -(https://github.com/Significant-Gravitas/Auto-GPT-Benchmarks). - -We've also moved our documentation to Material Theme, at https://docs.agpt.co. - -As usual, we've squashed a few bugs and made some under-the-hood improvements. +# v0.5.0 RELEASE HIGHLIGHTS! 🚀🚀 +# ------------------------------- +Cloud-readiness, a new UI, support for the newest Agent Protocol version, and much more: +*v0.5.0 is our biggest release yet!* Take a look at the Release Notes on Github for the full changelog: https://github.com/Significant-Gravitas/AutoGPT/releases. diff --git a/autogpts/autogpt/Dockerfile b/autogpts/autogpt/Dockerfile index 7121c6914..b7af437a8 100644 --- a/autogpts/autogpt/Dockerfile +++ b/autogpts/autogpt/Dockerfile @@ -6,7 +6,7 @@ FROM python:3.10-slim AS autogpt-base # Install browsers RUN apt-get update && apt-get install -y \ - chromium-driver firefox-esr ca-certificates gcc \ + chromium-driver ca-certificates gcc \ && apt-get clean && rm -rf /var/lib/apt/lists/* # Install utilities @@ -19,6 +19,7 @@ ENV PIP_NO_CACHE_DIR=yes \ PYTHONUNBUFFERED=1 \ PYTHONDONTWRITEBYTECODE=1 \ POETRY_HOME="/opt/poetry" \ + POETRY_VIRTUALENVS_PATH="/venv" \ POETRY_VIRTUALENVS_IN_PROJECT=0 \ POETRY_NO_INTERACTION=1 @@ -31,17 +32,19 @@ WORKDIR /app COPY pyproject.toml poetry.lock ./ # Set the entrypoint -ENTRYPOINT ["poetry", "run", "autogpt", "--install-plugin-deps"] +ENTRYPOINT ["poetry", "run", "autogpt"] CMD [] # dev build -> include everything FROM autogpt-base as autogpt-dev -RUN poetry install --no-root +RUN poetry install --no-cache --no-root \ + && rm -rf $(poetry env info --path)/src ONBUILD COPY . ./ # release build -> include bare minimum FROM autogpt-base as autogpt-release -RUN poetry install --no-root --without dev +RUN poetry install --no-cache --no-root --without dev \ + && rm -rf $(poetry env info --path)/src ONBUILD COPY autogpt/ ./autogpt ONBUILD COPY scripts/ ./scripts ONBUILD COPY plugins/ ./plugins diff --git a/autogpts/autogpt/README.md b/autogpts/autogpt/README.md index 3d8ad7118..86e0aa69f 100644 --- a/autogpts/autogpt/README.md +++ b/autogpts/autogpt/README.md @@ -1,14 +1,10 @@ # AutoGPT: An Autonomous GPT-4 Experiment -[](https://discord.gg/autogpt) -[](https://github.com/Significant-Gravitas/AutoGPT/stargazers) -[](https://twitter.com/SigGravitas) +[📖 **Documentation**][docs] + |  +[🚀 **Contributing**](../../CONTRIBUTING.md) -## 💡 Get help - [Q&A](https://github.com/Significant-Gravitas/AutoGPT/discussions/categories/q-a) or [Discord 💬](https://discord.gg/autogpt) - -<hr/> - -AutoGPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, AutoGPT pushes the boundaries of what is possible with AI. +AutoGPT is an experimental open-source application showcasing the capabilities of modern Large Language Models. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, AutoGPT pushes the boundaries of what is possible with AI. <h2 align="center"> Demo April 16th 2023 </h2> @@ -18,94 +14,140 @@ Demo made by <a href=https://twitter.com/BlakeWerlinger>Blake Werlinger</a> ## 🚀 Features +- 🔌 Agent Protocol ([docs](https://agentprotocol.ai)) +- 💻 Easy to use UI - 🌐 Internet access for searches and information gathering -- 💾 Long-term and short-term memory management -- 🧠 GPT-4 instances for text generation +- 🧠 Powered by a mix of GPT-4 and GPT-3.5 Turbo - 🔗 Access to popular websites and platforms -- 🗃️ File storage and summarization with GPT-3.5 +- 🗃️ File generation and editing capabilities - 🔌 Extensibility with Plugins +<!-- - 💾 Long-term and short-term memory management --> -## Quickstart - -0. Check out the [wiki](https://github.com/Significant-Gravitas/Nexus/wiki) +## Setting up AutoGPT 1. Get an OpenAI [API Key](https://platform.openai.com/account/api-keys) -2. Download the [latest release](https://github.com/Significant-Gravitas/AutoGPT/releases/latest) -3. Follow the [installation instructions][docs/setup] -4. Configure any additional features you want, or install some [plugins][docs/plugins] -5. [Run][docs/usage] the app - -Please see the [documentation][docs] for full setup instructions and configuration options. - -[docs]: https://docs.agpt.co/ - -## 📖 Documentation - -- [⚙️ Setup][docs/setup] -- [💻 Usage][docs/usage] -- [🔌 Plugins][docs/plugins] -- Configuration - - [🔍 Web Search](https://docs.agpt.co/configuration/search/) - - [🧠 Memory](https://docs.agpt.co/configuration/memory/) - - [🗣️ Voice (TTS)](https://docs.agpt.co/configuration/voice/) - - [🖼️ Image Generation](https://docs.agpt.co/configuration/imagegen/) - -[docs/setup]: https://docs.agpt.co/setup/ -[docs/usage]: https://docs.agpt.co/usage/ -[docs/plugins]: https://docs.agpt.co/plugins/ - -## 🏗️ Setting up for development -1. Make sure `poetry` is installed: `python3 -m pip install poetry` -2. Install all dependencies: `poetry install` - - -<h2 align="center"> 💖 Help Fund AutoGPT's Development 💖</h2> -<p align="center"> -If you can spare a coffee, you can help to cover the costs of developing AutoGPT and help to push the boundaries of fully autonomous AI! -Your support is greatly appreciated. Development of this free, open-source project is made possible by all the <a href="https://github.com/Significant-Gravitas/AutoGPT/graphs/contributors">contributors</a> and <a href="https://github.com/sponsors/Torantulino">sponsors</a>. 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</p> +2. Copy `.env.template` to `.env` and set `OPENAI_API_KEY` +3. Make sure you have Poetry [installed](https://python-poetry.org/docs/#installation) + +For more ways to run AutoGPT, more detailed instructions, and more configuration options, +see the [setup guide][docs/setup]. + +## Running AutoGPT +The CLI should be self-documenting: +```shell +$ ./autogpt.sh --help +Usage: python -m autogpt [OPTIONS] COMMAND [ARGS]... + +Options: + --help Show this message and exit. + +Commands: + run Sets up and runs an agent, based on the task specified by the... + serve Starts an Agent Protocol compliant AutoGPT server, which creates... +``` +When run without a sub-command, it will default to `run` for legacy reasons. + +<details> +<summary> +<code>$ ./autogpt.sh run --help</code> +</summary> + +The `run` sub-command starts AutoGPT with the legacy CLI interface: + +```shell +$ ./autogpt.sh run --help +Usage: python -m autogpt run [OPTIONS] + + Sets up and runs an agent, based on the task specified by the user, or + resumes an existing agent. + +Options: + -c, --continuous Enable Continuous Mode + -y, --skip-reprompt Skips the re-prompting messages at the + beginning of the script + -C, --ai-settings FILE Specifies which ai_settings.yaml file to + use, relative to the AutoGPT root directory. + Will also automatically skip the re-prompt. + -P, --prompt-settings FILE Specifies which prompt_settings.yaml file to + use. + -l, --continuous-limit INTEGER Defines the number of times to run in + continuous mode + --speak Enable Speak Mode + --debug Enable Debug Mode + --gpt3only Enable GPT3.5 Only Mode + --gpt4only Enable GPT4 Only Mode + -m, --use-memory TEXT Defines which Memory backend to use + -b, --browser-name TEXT Specifies which web-browser to use when + using selenium to scrape the web. + --allow-downloads Dangerous: Allows AutoGPT to download files + natively. + --skip-news Specifies whether to suppress the output of + latest news on startup. + --install-plugin-deps Installs external dependencies for 3rd party + plugins. + --ai-name TEXT AI name override + --ai-role TEXT AI role override + --constraint TEXT Add or override AI constraints to include in + the prompt; may be used multiple times to + pass multiple constraints + --resource TEXT Add or override AI resources to include in + the prompt; may be used multiple times to + pass multiple resources + --best-practice TEXT Add or override AI best practices to include + in the prompt; may be used multiple times to + pass multiple best practices + --override-directives If specified, --constraint, --resource and + --best-practice will override the AI's + directives instead of being appended to them + --help Show this message and exit. +``` +</details> + + +<details> +<summary> +<code>$ ./autogpt.sh serve --help</code> +</summary> + +The `serve` sub-command starts AutoGPT wrapped in an Agent Protocol server: + +```shell +$ ./autogpt.sh serve --help +Usage: python -m autogpt serve [OPTIONS] + + Starts an Agent Protocol compliant AutoGPT server, which creates a custom + agent for every task. + +Options: + -P, --prompt-settings FILE Specifies which prompt_settings.yaml file to + use. + --debug Enable Debug Mode + --gpt3only Enable GPT3.5 Only Mode + --gpt4only Enable GPT4 Only Mode + -m, --use-memory TEXT Defines which Memory backend to use + -b, --browser-name TEXT Specifies which web-browser to use when using + selenium to scrape the web. + --allow-downloads Dangerous: Allows AutoGPT to download files + natively. + --install-plugin-deps Installs external dependencies for 3rd party + plugins. + --help Show this message and exit. +``` +</details> + +With `serve`, the application exposes an Agent Protocol compliant API and serves a frontend, +by default on `http://localhost:8000`. + +For more comprehensive instructions, see the [user guide][docs/usage]. + +[docs]: https://docs.agpt.co/autogpt +[docs/setup]: https://docs.agpt.co/autogpt/setup +[docs/usage]: https://docs.agpt.co/autogpt/usage +[docs/plugins]: https://docs.agpt.co/autogpt/plugins + +## 📚 Resources +* 📔 AutoGPT [team wiki](https://github.com/Significant-Gravitas/Nexus/wiki) +* 🧮 AutoGPT [project kanban](https://github.com/orgs/Significant-Gravitas/projects/1) +* 🌃 AutoGPT [roadmap](https://github.com/orgs/Significant-Gravitas/projects/2) ## ⚠️ Limitations @@ -127,13 +169,9 @@ As an autonomous experiment, AutoGPT may generate content or take actions that a By using AutoGPT, you agree to indemnify, defend, and hold harmless the developers, contributors, and any affiliated parties from and against any and all claims, damages, losses, liabilities, costs, and expenses (including reasonable attorneys' fees) arising from your use of this software or your violation of these terms. -## 🐦 Connect with Us on Twitter - -Stay up-to-date with the latest news, updates, and insights about AutoGPT by following our Twitter accounts. Engage with the developer and the AI's own account for interesting discussions, project updates, and more. - -- **Developer**: Follow [@siggravitas](https://twitter.com/siggravitas) for insights into the development process, project updates, and related topics from the creator of Entrepreneur-GPT. +--- -We look forward to connecting with you and hearing your thoughts, ideas, and experiences with AutoGPT. Join us on Twitter and let's explore the future of AI together! +In Q2 of 2023, AutoGPT became the fastest growing open-source project in history. Now that the dust has settled, we're committed to continued sustainable development and growth of the project. <p align="center"> <a href="https://star-history.com/#Significant-Gravitas/AutoGPT&Date"> diff --git a/autogpts/autogpt/agbenchmark_config/analyze_reports.py b/autogpts/autogpt/agbenchmark_config/analyze_reports.py index f02cbe616..2a8f95443 100644 --- a/autogpts/autogpt/agbenchmark_config/analyze_reports.py +++ b/autogpts/autogpt/agbenchmark_config/analyze_reports.py @@ -98,7 +98,7 @@ for report_file in sorted(report_files): test_metrics = test_data["metrics"] result_indicator = "❔" - if not "attempted" in test_metrics: + if "attempted" not in test_metrics: return elif test_metrics["attempted"]: if test_name not in test_names: @@ -116,7 +116,7 @@ for report_file in sorted(report_files): for test_name, suite in test_tree.items(): try: process_test(test_name, suite) - except KeyError as e: + except KeyError: print(f"{test_name}.metrics: {suite['metrics']}") raise diff --git a/autogpts/autogpt/agbenchmark_config/benchmarks.py b/autogpts/autogpt/agbenchmark_config/benchmarks.py index 467486588..c7e75406e 100644 --- a/autogpts/autogpt/agbenchmark_config/benchmarks.py +++ b/autogpts/autogpt/agbenchmark_config/benchmarks.py @@ -1,4 +1,5 @@ import asyncio +import logging import sys from pathlib import Path @@ -19,20 +20,16 @@ def run_specific_agent(task: str, continuous_mode: bool = False) -> None: def bootstrap_agent(task: str, continuous_mode: bool) -> Agent: config = ConfigBuilder.build_config_from_env() - config.debug_mode = False + config.logging.level = logging.DEBUG + config.logging.log_dir = LOG_DIR + config.logging.plain_console_output = True + configure_logging(**config.logging.dict()) + config.continuous_mode = continuous_mode config.continuous_limit = 20 - config.temperature = 0 config.noninteractive_mode = True - config.plain_output = True config.memory_backend = "no_memory" - configure_logging( - debug_mode=config.debug_mode, - plain_output=config.plain_output, - log_dir=LOG_DIR, - ) - command_registry = CommandRegistry.with_command_modules(COMMAND_CATEGORIES, config) ai_profile = AIProfile( diff --git a/autogpts/autogpt/run.bat b/autogpts/autogpt/autogpt.bat index 22462f007..12b89f212 100644 --- a/autogpts/autogpt/run.bat +++ b/autogpts/autogpt/autogpt.bat @@ -2,7 +2,7 @@ setlocal enabledelayedexpansion :FindPythonCommand -for %%A in (python python3) do ( +for %%A in (python3 python) do ( where /Q %%A if !errorlevel! EQU 0 ( set "PYTHON_CMD=%%A" @@ -18,10 +18,10 @@ exit /B 1 %PYTHON_CMD% scripts/check_requirements.py if errorlevel 1 ( echo - %PYTHON_CMD% -m poetry install --without dev + poetry install --without dev echo echo Finished installing packages! Starting AutoGPT... echo ) -%PYTHON_CMD% -m autogpt %* +poetry run autogpt %* pause diff --git a/autogpts/autogpt/run.sh b/autogpts/autogpt/autogpt.sh index 9246a433f..57e1f4192 100755 --- a/autogpts/autogpt/run.sh +++ b/autogpts/autogpt/autogpt.sh @@ -1,12 +1,12 @@ #!/usr/bin/env bash function find_python_command() { - if command -v python &> /dev/null - then - echo "python" - elif command -v python3 &> /dev/null + if command -v python3 &> /dev/null then echo "python3" + elif command -v python &> /dev/null + then + echo "python" else echo "Python not found. Please install Python." exit 1 @@ -16,16 +16,14 @@ function find_python_command() { PYTHON_CMD=$(find_python_command) if $PYTHON_CMD -c "import sys; sys.exit(sys.version_info < (3, 10))"; then - $PYTHON_CMD scripts/check_requirements.py - if [ $? -eq 1 ] - then + if ! $PYTHON_CMD scripts/check_requirements.py; then echo - $PYTHON_CMD -m poetry install --without dev + poetry install --without dev echo echo "Finished installing packages! Starting AutoGPT..." echo fi - $PYTHON_CMD -m autogpt "$@" + poetry run autogpt "$@" else echo "Python 3.10 or higher is required to run Auto GPT." fi diff --git a/autogpts/autogpt/autogpt/agent_factory/configurators.py b/autogpts/autogpt/autogpt/agent_factory/configurators.py index 3af417748..a8e9cbab6 100644 --- a/autogpts/autogpt/autogpt/agent_factory/configurators.py +++ b/autogpts/autogpt/autogpt/agent_factory/configurators.py @@ -6,7 +6,6 @@ from autogpt.commands import COMMAND_CATEGORIES from autogpt.config import AIDirectives, AIProfile, Config from autogpt.core.resource.model_providers import ChatModelProvider from autogpt.logs.config import configure_chat_plugins -from autogpt.logs.helpers import print_attribute from autogpt.models.command_registry import CommandRegistry from autogpt.plugins import scan_plugins @@ -61,7 +60,7 @@ def _configure_agent( "Either (state) or (task, ai_profile, directives) must be specified" ) - app_config.plugins = scan_plugins(app_config, app_config.debug_mode) + app_config.plugins = scan_plugins(app_config) configure_chat_plugins(app_config) # Create a CommandRegistry instance and scan default folder @@ -79,8 +78,6 @@ def _configure_agent( # TODO: configure memory - print_attribute("Configured Browser", app_config.selenium_web_browser) - return Agent( settings=agent_state, llm_provider=llm_provider, diff --git a/autogpts/autogpt/autogpt/agent_factory/profile_generator.py b/autogpts/autogpt/autogpt/agent_factory/profile_generator.py index 34362e20c..8d9ff399e 100644 --- a/autogpts/autogpt/autogpt/agent_factory/profile_generator.py +++ b/autogpts/autogpt/autogpt/agent_factory/profile_generator.py @@ -1,3 +1,4 @@ +import json import logging from autogpt.config import AIDirectives, AIProfile, Config @@ -9,7 +10,7 @@ from autogpt.core.prompting import ( ) from autogpt.core.prompting.utils import json_loads from autogpt.core.resource.model_providers.schema import ( - AssistantChatMessageDict, + AssistantChatMessage, ChatMessage, ChatModelProvider, CompletionModelFunction, @@ -23,14 +24,61 @@ class AgentProfileGeneratorConfiguration(SystemConfiguration): model_classification: LanguageModelClassification = UserConfigurable( default=LanguageModelClassification.SMART_MODEL ) + _example_call: object = [ + { + "type": "function", + "function": { + "name": "create_agent", + "arguments": { + "name": "CMOGPT", + "description": ( + "a professional digital marketer AI that assists Solopreneurs " + "in growing their businesses by providing " + "world-class expertise in solving marketing problems " + "for SaaS, content products, agencies, and more." + ), + "directives": { + "best_practices": [ + ( + "Engage in effective problem-solving, prioritization, " + "planning, and supporting execution to address your " + "marketing needs as your virtual " + "Chief Marketing Officer." + ), + ( + "Provide specific, actionable, and concise advice to " + "help you make informed decisions without the use of " + "platitudes or overly wordy explanations." + ), + ( + "Identify and prioritize quick wins and cost-effective " + "campaigns that maximize results with minimal time and " + "budget investment." + ), + ( + "Proactively take the lead in guiding you and offering " + "suggestions when faced with unclear information or " + "uncertainty to ensure your marketing strategy remains " + "on track." + ), + ], + "constraints": [ + "Do not suggest illegal or unethical plans or strategies.", + "Take reasonable budgetary limits into account.", + ], + }, + }, + }, + } + ] system_prompt: str = UserConfigurable( default=( "Your job is to respond to a user-defined task, given in triple quotes, by " "invoking the `create_agent` function to generate an autonomous agent to " "complete the task. " "You should supply a role-based name for the agent (_GPT), " - "an informative description for what the agent does, and " - "1 to 5 directives in each of the categories Best Practices and Constraints, " + "an informative description for what the agent does, and 1 to 5 directives " + "in each of the categories Best Practices and Constraints, " "that are optimally aligned with the successful completion " "of its assigned task.\n" "\n" @@ -38,38 +86,8 @@ class AgentProfileGeneratorConfiguration(SystemConfiguration): '"""Help me with marketing my business"""\n\n' "Example Call:\n" "```\n" - "[" # tool_calls - '{"type": "function", "function": {' - '"name": "create_agent",' - ' "arguments": {' - '"name": "CMOGPT",' - ' "description": "a professional digital marketer AI that assists Solopreneurs in' - " growing their businesses by providing world-class expertise in solving" - ' marketing problems for SaaS, content products, agencies, and more.",' - ' "directives": {' - ' "best_practices": [' - '"Engage in effective problem-solving, prioritization, planning, and' - " supporting execution to address your marketing needs as your virtual Chief" - ' Marketing Officer.",' - ' "Provide specific, actionable, and concise advice to help you make' - " informed decisions without the use of platitudes or overly wordy" - ' explanations.",' - ' "Identify and prioritize quick wins and cost-effective campaigns that' - ' maximize results with minimal time and budget investment.",' - ' "Proactively take the lead in guiding you and offering suggestions when' - " faced with unclear information or uncertainty to ensure your marketing" - ' strategy remains on track."' - "]," # best_practices - ' "constraints": [' - '"Do not suggest illegal or unethical plans or strategies.",' - ' "Take reasonable budgetary limits into account."' - "]" # constraints - "}" # directives - "}" # arguments - "}" # function - "}" # tool call - "]\n" # tool_calls - "```" + f"{json.dumps(_example_call, indent=4)}" + "\n```" ) ) user_prompt_template: str = UserConfigurable(default='"""{user_objective}"""') @@ -85,7 +103,10 @@ class AgentProfileGeneratorConfiguration(SystemConfiguration): ), "description": JSONSchema( type=JSONSchema.Type.STRING, - description="An informative one sentence description of what the AI agent does", + description=( + "An informative one sentence description " + "of what the AI agent does" + ), required=True, ), "directives": JSONSchema( @@ -99,8 +120,9 @@ class AgentProfileGeneratorConfiguration(SystemConfiguration): type=JSONSchema.Type.STRING, ), description=( - "One to five highly effective best practices that are" - " optimally aligned with the completion of the given task." + "One to five highly effective best practices " + "that are optimally aligned with the completion " + "of the given task" ), required=True, ), @@ -112,8 +134,9 @@ class AgentProfileGeneratorConfiguration(SystemConfiguration): type=JSONSchema.Type.STRING, ), description=( - "One to five highly effective constraints that are" - " optimally aligned with the completion of the given task." + "One to five reasonable and efficacious constraints " + "that are optimally aligned with the completion " + "of the given task" ), required=True, ), @@ -163,7 +186,7 @@ class AgentProfileGenerator(PromptStrategy): def parse_response_content( self, - response_content: AssistantChatMessageDict, + response_content: AssistantChatMessage, ) -> tuple[AIProfile, AIDirectives]: """Parse the actual text response from the objective model. @@ -175,16 +198,21 @@ class AgentProfileGenerator(PromptStrategy): """ try: - arguments = json_loads( - response_content["tool_calls"][0]["function"]["arguments"] + if not response_content.tool_calls: + raise ValueError( + f"LLM did not call {self._create_agent_function.name} function; " + "agent profile creation failed" + ) + arguments: object = json_loads( + response_content.tool_calls[0].function.arguments ) ai_profile = AIProfile( ai_name=arguments.get("name"), ai_role=arguments.get("description"), ) ai_directives = AIDirectives( - best_practices=arguments["directives"].get("best_practices"), - constraints=arguments["directives"].get("constraints"), + best_practices=arguments.get("directives", {}).get("best_practices"), + constraints=arguments.get("directives", {}).get("constraints"), resources=[], ) except KeyError: diff --git a/autogpts/autogpt/autogpt/agent_manager/agent_manager.py b/autogpts/autogpt/autogpt/agent_manager/agent_manager.py index dc3bc6461..0b4731bc6 100644 --- a/autogpts/autogpt/autogpt/agent_manager/agent_manager.py +++ b/autogpts/autogpt/autogpt/agent_manager/agent_manager.py @@ -29,6 +29,7 @@ class AgentManager: ] def get_agent_dir(self, agent_id: str, must_exist: bool = False) -> Path: + assert len(agent_id) > 0 agent_dir = self.agents_dir / agent_id if must_exist and not agent_dir.exists(): raise FileNotFoundError(f"No agent with ID '{agent_id}'") diff --git a/autogpts/autogpt/autogpt/agents/agent.py b/autogpts/autogpt/autogpt/agents/agent.py index 13275a4e8..8847ae7f2 100644 --- a/autogpts/autogpt/autogpt/agents/agent.py +++ b/autogpts/autogpt/autogpt/agents/agent.py @@ -15,9 +15,9 @@ from pydantic import Field from autogpt.core.configuration import Configurable from autogpt.core.prompting import ChatPrompt from autogpt.core.resource.model_providers import ( + AssistantChatMessage, ChatMessage, ChatModelProvider, - ChatModelResponse, ) from autogpt.llm.api_manager import ApiManager from autogpt.logs.log_cycle import ( @@ -26,6 +26,7 @@ from autogpt.logs.log_cycle import ( USER_INPUT_FILE_NAME, LogCycleHandler, ) +from autogpt.logs.utils import fmt_kwargs from autogpt.models.action_history import ( Action, ActionErrorResult, @@ -44,7 +45,12 @@ from .prompt_strategies.one_shot import ( OneShotAgentPromptConfiguration, OneShotAgentPromptStrategy, ) -from .utils.exceptions import AgentException, CommandExecutionError, UnknownCommandError +from .utils.exceptions import ( + AgentException, + AgentTerminated, + CommandExecutionError, + UnknownCommandError, +) logger = logging.getLogger(__name__) @@ -76,6 +82,8 @@ class Agent( description=__doc__, ) + prompt_strategy: OneShotAgentPromptStrategy + def __init__( self, settings: AgentSettings, @@ -164,20 +172,18 @@ class Agent( return prompt def parse_and_process_response( - self, llm_response: ChatModelResponse, *args, **kwargs + self, llm_response: AssistantChatMessage, *args, **kwargs ) -> Agent.ThoughtProcessOutput: for plugin in self.config.plugins: if not plugin.can_handle_post_planning(): continue - llm_response.response["content"] = plugin.post_planning( - llm_response.response.get("content", "") - ) + llm_response.content = plugin.post_planning(llm_response.content or "") ( command_name, arguments, assistant_reply_dict, - ) = self.prompt_strategy.parse_response_content(llm_response.response) + ) = self.prompt_strategy.parse_response_content(llm_response) self.log_cycle_handler.log_cycle( self.ai_profile.ai_name, @@ -232,7 +238,7 @@ class Agent( ) # Intercept ContextItem if one is returned by the command - if type(return_value) == tuple and isinstance( + if type(return_value) is tuple and isinstance( return_value[1], ContextItem ): context_item = return_value[1] @@ -243,8 +249,13 @@ class Agent( self.context.add(context_item) result = ActionSuccessResult(outputs=return_value) + except AgentTerminated: + raise except AgentException as e: result = ActionErrorResult.from_exception(e) + logger.warning( + f"{command_name}({fmt_kwargs(command_args)}) raised an error: {e}" + ) result_tlength = self.llm_provider.count_tokens(str(result), self.llm.name) if result_tlength > self.send_token_limit // 3: diff --git a/autogpts/autogpt/autogpt/agents/base.py b/autogpts/autogpt/autogpt/agents/base.py index 1dd9ac493..846427ae7 100644 --- a/autogpts/autogpt/autogpt/agents/base.py +++ b/autogpts/autogpt/autogpt/agents/base.py @@ -12,6 +12,7 @@ if TYPE_CHECKING: from autogpt.config import Config from autogpt.core.prompting.base import PromptStrategy from autogpt.core.resource.model_providers.schema import ( + AssistantChatMessage, ChatModelInfo, ChatModelProvider, ChatModelResponse, @@ -124,7 +125,7 @@ class BaseAgentConfiguration(SystemConfiguration): class BaseAgentSettings(SystemSettings): - agent_id: Optional[str] = None + agent_id: str = "" agent_data_dir: Optional[Path] = None ai_profile: AIProfile = Field(default_factory=lambda: AIProfile(ai_name="AutoGPT")) @@ -230,10 +231,7 @@ class BaseAgent(Configurable[BaseAgentSettings], ABC): return self.config.send_token_limit or self.llm.max_tokens * 3 // 4 async def propose_action(self) -> ThoughtProcessOutput: - """Runs the agent for one cycle. - - Params: - instruction: The instruction to put at the end of the prompt. + """Proposes the next action to execute, based on the task and current state. Returns: The command name and arguments, if any, and the agent's thoughts. @@ -250,7 +248,7 @@ class BaseAgent(Configurable[BaseAgentSettings], ABC): prompt = self.on_before_think(prompt, scratchpad=self._prompt_scratchpad) logger.debug(f"Executing prompt:\n{dump_prompt(prompt)}") - raw_response = await self.llm_provider.create_chat_completion( + response = await self.llm_provider.create_chat_completion( prompt.messages, functions=get_openai_command_specs( self.command_registry.list_available_commands(self) @@ -259,11 +257,16 @@ class BaseAgent(Configurable[BaseAgentSettings], ABC): if self.config.use_functions_api else [], model_name=self.llm.name, + completion_parser=lambda r: self.parse_and_process_response( + r, + prompt, + scratchpad=self._prompt_scratchpad, + ), ) self.config.cycle_count += 1 return self.on_response( - llm_response=raw_response, + llm_response=response, prompt=prompt, scratchpad=self._prompt_scratchpad, ) @@ -283,7 +286,7 @@ class BaseAgent(Configurable[BaseAgentSettings], ABC): user_input: The user's input, if any. Returns: - The results of the command. + ActionResult: An object representing the result(s) of the command. """ ... @@ -294,13 +297,13 @@ class BaseAgent(Configurable[BaseAgentSettings], ABC): extra_messages: Optional[list[ChatMessage]] = None, **extras, ) -> ChatPrompt: - """Constructs and returns a prompt with the following structure: - 1. System prompt - 2. Message history of the agent, truncated & prepended with running summary as needed - 3. `cycle_instruction` + """Constructs a prompt using `self.prompt_strategy`. Params: - cycle_instruction: The final instruction for a thinking cycle + scratchpad: An object for plugins to write additional prompt elements to. + (E.g. commands, constraints, best practices) + extra_commands: Additional commands that the agent has access to. + extra_messages: Additional messages to include in the prompt. """ if not extra_commands: extra_commands = [] @@ -349,7 +352,9 @@ class BaseAgent(Configurable[BaseAgentSettings], ABC): output to the prompt. Params: - instruction: The instruction for the current cycle, also used in constructing the prompt + prompt: The prompt that is about to be executed. + scratchpad: An object for plugins to write additional prompt elements to. + (E.g. commands, constraints, best practices) Returns: The prompt to execute @@ -386,30 +391,26 @@ class BaseAgent(Configurable[BaseAgentSettings], ABC): ) -> ThoughtProcessOutput: """Called upon receiving a response from the chat model. - Adds the last/newest message in the prompt and the response to `history`, - and calls `self.parse_and_process_response()` to do the rest. + Calls `self.parse_and_process_response()`. Params: - llm_response: The raw response from the chat model - prompt: The prompt that was executed - instruction: The instruction for the current cycle, also used in constructing the prompt + llm_response: The raw response from the chat model. + prompt: The prompt that was executed. + scratchpad: An object containing additional prompt elements from plugins. + (E.g. commands, constraints, best practices) Returns: The parsed command name and command args, if any, and the agent thoughts. """ - return self.parse_and_process_response( - llm_response, - prompt, - scratchpad=scratchpad, - ) + return llm_response.parsed_result # TODO: update memory/context @abstractmethod def parse_and_process_response( self, - llm_response: ChatModelResponse, + llm_response: AssistantChatMessage, prompt: ChatPrompt, scratchpad: PromptScratchpad, ) -> ThoughtProcessOutput: @@ -419,9 +420,10 @@ class BaseAgent(Configurable[BaseAgentSettings], ABC): since the implementation depends on the role of the derivative Agent. Params: - llm_response: The raw response from the chat model - prompt: The prompt that was executed - instruction: The instruction for the current cycle, also used in constructing the prompt + llm_response: The raw response from the chat model. + prompt: The prompt that was executed. + scratchpad: An object containing additional prompt elements from plugins. + (E.g. commands, constraints, best practices) Returns: The parsed command name and command args, if any, and the agent thoughts. diff --git a/autogpts/autogpt/autogpt/agents/features/context.py b/autogpts/autogpt/autogpt/agents/features/context.py index 3e92c867c..748635ddc 100644 --- a/autogpts/autogpt/autogpt/agents/features/context.py +++ b/autogpts/autogpt/autogpt/agents/features/context.py @@ -61,10 +61,10 @@ class ContextMixin: 0, ChatMessage.system( "## Context\n" - + self.context.format_numbered() - + "\n\nWhen a context item is no longer needed and you are not done yet," - " you can hide the item by specifying its number in the list above" - " to `hide_context_item`.", + f"{self.context.format_numbered()}\n\n" + "When a context item is no longer needed and you are not done yet, " + "you can hide the item by specifying its number in the list above " + "to `hide_context_item`.", ), ) diff --git a/autogpts/autogpt/autogpt/agents/features/file_workspace.py b/autogpts/autogpt/autogpt/agents/features/file_workspace.py index ecdd28747..22ab8119d 100644 --- a/autogpts/autogpt/autogpt/agents/features/file_workspace.py +++ b/autogpts/autogpt/autogpt/agents/features/file_workspace.py @@ -5,11 +5,15 @@ from typing import TYPE_CHECKING if TYPE_CHECKING: from pathlib import Path - from ..base import BaseAgent + from ..base import BaseAgent, Config -from autogpt.file_workspace import FileWorkspace +from autogpt.file_workspace import ( + FileWorkspace, + FileWorkspaceBackendName, + get_workspace, +) -from ..base import AgentFileManager, BaseAgentConfiguration +from ..base import AgentFileManager, BaseAgentSettings class FileWorkspaceMixin: @@ -22,32 +26,36 @@ class FileWorkspaceMixin: # Initialize other bases first, because we need the config from BaseAgent super(FileWorkspaceMixin, self).__init__(**kwargs) - config: BaseAgentConfiguration = getattr(self, "config") - if not isinstance(config, BaseAgentConfiguration): - raise ValueError( - "Cannot initialize Workspace for Agent without compatible .config" - ) file_manager: AgentFileManager = getattr(self, "file_manager") if not file_manager: return - self.workspace = _setup_workspace(file_manager, config) + self._setup_workspace() def attach_fs(self, agent_dir: Path): res = super(FileWorkspaceMixin, self).attach_fs(agent_dir) - self.workspace = _setup_workspace(self.file_manager, self.config) + self._setup_workspace() return res + def _setup_workspace(self) -> None: + settings: BaseAgentSettings = getattr(self, "state") + assert settings.agent_id, "Cannot attach workspace to anonymous agent" + app_config: Config = getattr(self, "legacy_config") + file_manager: AgentFileManager = getattr(self, "file_manager") -def _setup_workspace(file_manager: AgentFileManager, config: BaseAgentConfiguration): - workspace = FileWorkspace( - file_manager.root / "workspace", - restrict_to_root=not config.allow_fs_access, - ) - workspace.initialize() - return workspace + ws_backend = app_config.workspace_backend + local = ws_backend == FileWorkspaceBackendName.LOCAL + workspace = get_workspace( + backend=ws_backend, + id=settings.agent_id if not local else "", + root_path=file_manager.root / "workspace" if local else None, + ) + if local and settings.config.allow_fs_access: + workspace._restrict_to_root = False # type: ignore + workspace.initialize() + self.workspace = workspace def get_agent_workspace(agent: BaseAgent) -> FileWorkspace | None: diff --git a/autogpts/autogpt/autogpt/agents/planning_agent.py b/autogpts/autogpt/autogpt/agents/planning_agent.py deleted file mode 100644 index c59faf76e..000000000 --- a/autogpts/autogpt/autogpt/agents/planning_agent.py +++ /dev/null @@ -1,340 +0,0 @@ -from __future__ import annotations - -import logging -import re -from datetime import datetime -from typing import TYPE_CHECKING, Literal, Optional - -if TYPE_CHECKING: - from autogpt.config import Config - from autogpt.llm.base import ChatModelResponse, ChatSequence - from autogpt.memory.vector import VectorMemory - from autogpt.models.command_registry import CommandRegistry - -from autogpt.agents.utils.exceptions import AgentException, InvalidAgentResponseError -from autogpt.json_utils.utilities import extract_dict_from_response, validate_dict -from autogpt.llm.base import Message -from autogpt.llm.utils import count_string_tokens -from autogpt.logs.log_cycle import ( - CURRENT_CONTEXT_FILE_NAME, - NEXT_ACTION_FILE_NAME, - USER_INPUT_FILE_NAME, - LogCycleHandler, -) -from autogpt.models.action_history import ( - ActionErrorResult, - ActionInterruptedByHuman, - ActionResult, - ActionSuccessResult, -) -from autogpt.models.context_item import ContextItem - -from .agent import execute_command, extract_command -from .base import BaseAgent -from .features.context import ContextMixin -from .features.file_workspace import FileWorkspaceMixin - -logger = logging.getLogger(__name__) - - -class PlanningAgent(ContextMixin, FileWorkspaceMixin, BaseAgent): - """Agent class for interacting with AutoGPT.""" - - ThoughtProcessID = Literal["plan", "action", "evaluate"] - - def __init__( - self, - command_registry: CommandRegistry, - memory: VectorMemory, - triggering_prompt: str, - config: Config, - cycle_budget: Optional[int] = None, - ): - super().__init__( - command_registry=command_registry, - config=config, - default_cycle_instruction=triggering_prompt, - cycle_budget=cycle_budget, - ) - - self.memory = memory - """VectorMemoryProvider used to manage the agent's context (TODO)""" - - self.created_at = datetime.now().strftime("%Y%m%d_%H%M%S") - """Timestamp the agent was created; only used for structured debug logging.""" - - self.log_cycle_handler = LogCycleHandler() - """LogCycleHandler for structured debug logging.""" - - self.plan: list[str] = [] - """List of steps that the Agent plans to take""" - - def construct_base_prompt( - self, thought_process_id: ThoughtProcessID, **kwargs - ) -> ChatSequence: - prepend_messages = kwargs["prepend_messages"] = kwargs.get( - "prepend_messages", [] - ) - - # Add the current plan to the prompt, if any - if self.plan: - plan_section = [ - "## Plan", - "To complete your task, you have composed the following plan:", - ] - plan_section += [f"{i}. {s}" for i, s in enumerate(self.plan, 1)] - - # Add the actions so far to the prompt - if self.event_history: - plan_section += [ - "\n### Progress", - "So far, you have executed the following actions based on the plan:", - ] - for i, cycle in enumerate(self.event_history, 1): - if not (cycle.action and cycle.result): - logger.warn(f"Incomplete action in history: {cycle}") - continue - - plan_section.append( - f"{i}. You executed the command `{cycle.action.format_call()}`, " - f"which gave the result `{cycle.result}`." - ) - - prepend_messages.append(Message("system", "\n".join(plan_section))) - - if self.context: - context_section = [ - "## Context", - "Below is information that may be relevant to your task. These take up " - "part of your working memory, which is limited, so when a context item is " - "no longer relevant for your plan, use the `close_context_item` command to " - "free up some memory." - "\n", - self.context.format_numbered(), - ] - prepend_messages.append(Message("system", "\n".join(context_section))) - - match thought_process_id: - case "plan": - # TODO: add planning instructions; details about what to pay attention to when planning - pass - case "action": - # TODO: need to insert the functions here again? - pass - case "evaluate": - # TODO: insert latest action (with reasoning) + result + evaluation instructions - pass - case _: - raise NotImplementedError( - f"Unknown thought process '{thought_process_id}'" - ) - - return super().construct_base_prompt( - thought_process_id=thought_process_id, **kwargs - ) - - def response_format_instruction(self, thought_process_id: ThoughtProcessID) -> str: - match thought_process_id: - case "plan": - # TODO: add planning instructions; details about what to pay attention to when planning - response_format = f"""```ts - interface Response {{ - thoughts: {{ - // Thoughts - text: string; - // A short logical explanation about how the action is part of the earlier composed plan - reasoning: string; - // Constructive self-criticism - criticism: string; - }}; - // A plan to achieve the goals with the available resources and/or commands. - plan: Array<{{ - // An actionable subtask - subtask: string; - // Criterium to determine whether the subtask has been completed - completed_if: string; - }}>; - }} - ```""" - pass - case "action": - # TODO: need to insert the functions here again? - response_format = """```ts - interface Response { - thoughts: { - // Thoughts - text: string; - // A short logical explanation about how the action is part of the earlier composed plan - reasoning: string; - // Constructive self-criticism - criticism: string; - }; - // The action to take, from the earlier specified list of commands - command: { - name: string; - args: Record<string, any>; - }; - } - ```""" - pass - case "evaluate": - # TODO: insert latest action (with reasoning) + result + evaluation instructions - response_format = f"""```ts - interface Response {{ - thoughts: {{ - // Thoughts - text: string; - reasoning: string; - // Constructive self-criticism - criticism: string; - }}; - result_evaluation: {{ - // A short logical explanation of why the given partial result does or does not complete the corresponding subtask - reasoning: string; - // Whether the current subtask has been completed - completed: boolean; - // An estimate of the progress (0.0 - 1.0) that has been made on the subtask with the actions that have been taken so far - progress: float; - }}; - }} - ```""" - pass - case _: - raise NotImplementedError( - f"Unknown thought process '{thought_process_id}'" - ) - - response_format = re.sub( - r"\n\s+", - "\n", - response_format, - ) - - return ( - f"Respond strictly with JSON. The JSON should be compatible with " - "the TypeScript type `Response` from the following:\n" - f"{response_format}\n" - ) - - def on_before_think(self, *args, **kwargs) -> ChatSequence: - prompt = super().on_before_think(*args, **kwargs) - - self.log_cycle_handler.log_count_within_cycle = 0 - self.log_cycle_handler.log_cycle( - self.ai_profile.ai_name, - self.created_at, - self.cycle_count, - self.event_history.episodes, - "event_history.json", - ) - self.log_cycle_handler.log_cycle( - self.ai_profile.ai_name, - self.created_at, - self.cycle_count, - prompt.raw(), - CURRENT_CONTEXT_FILE_NAME, - ) - return prompt - - def execute( - self, - command_name: str, - command_args: dict[str, str] = {}, - user_input: str = "", - ) -> ActionResult: - result: ActionResult - - if command_name == "human_feedback": - result = ActionInterruptedByHuman(feedback=user_input) - self.log_cycle_handler.log_cycle( - self.ai_profile.ai_name, - self.created_at, - self.cycle_count, - user_input, - USER_INPUT_FILE_NAME, - ) - - else: - for plugin in self.config.plugins: - if not plugin.can_handle_pre_command(): - continue - command_name, arguments = plugin.pre_command(command_name, command_args) - - try: - return_value = execute_command( - command_name=command_name, - arguments=command_args, - agent=self, - ) - - # Intercept ContextItem if one is returned by the command - if type(return_value) == tuple and isinstance( - return_value[1], ContextItem - ): - self.context.add(return_value[1]) - return_value = return_value[0] - - result = ActionSuccessResult(outputs=return_value) - except AgentException as e: - result = ActionErrorResult.from_exception(e) - - result_tlength = count_string_tokens(str(result), self.llm.name) - memory_tlength = count_string_tokens( - str(self.event_history.fmt_paragraph()), self.llm.name - ) - if result_tlength + memory_tlength > self.send_token_limit: - result = ActionErrorResult( - reason=f"Command {command_name} returned too much output. " - "Do not execute this command again with the same arguments." - ) - - for plugin in self.config.plugins: - if not plugin.can_handle_post_command(): - continue - if result.status == "success": - result.outputs = plugin.post_command(command_name, result.outputs) - elif result.status == "error": - result.reason = plugin.post_command(command_name, result.reason) - - return result - - def parse_and_process_response( - self, - llm_response: ChatModelResponse, - thought_process_id: ThoughtProcessID, - *args, - **kwargs, - ) -> PlanningAgent.ThoughtProcessOutput: - if not llm_response.content: - raise InvalidAgentResponseError("Assistant response has no text content") - - response_content = llm_response.content - - for plugin in self.config.plugins: - if not plugin.can_handle_post_planning(): - continue - response_content = plugin.post_planning(response_content) - - assistant_reply_dict = extract_dict_from_response(response_content) - - _, errors = validate_dict(assistant_reply_dict, self.config) - if errors: - raise InvalidAgentResponseError( - "Validation of response failed:\n " - + ";\n ".join([str(e) for e in errors]) - ) - - # Get command name and arguments - command_name, arguments = extract_command( - assistant_reply_dict, llm_response, self.config - ) - response = command_name, arguments, assistant_reply_dict - - self.log_cycle_handler.log_cycle( - self.ai_profile.ai_name, - self.created_at, - self.cycle_count, - assistant_reply_dict, - NEXT_ACTION_FILE_NAME, - ) - return response diff --git a/autogpts/autogpt/autogpt/agents/prompt_strategies/one_shot.py b/autogpts/autogpt/autogpt/agents/prompt_strategies/one_shot.py index 5873c604c..e8c726c18 100644 --- a/autogpts/autogpt/autogpt/agents/prompt_strategies/one_shot.py +++ b/autogpts/autogpt/autogpt/agents/prompt_strategies/one_shot.py @@ -7,7 +7,6 @@ from logging import Logger from typing import TYPE_CHECKING, Callable, Optional import distro -from pydantic import Field if TYPE_CHECKING: from autogpt.agents.agent import Agent @@ -22,7 +21,7 @@ from autogpt.core.prompting import ( PromptStrategy, ) from autogpt.core.resource.model_providers.schema import ( - AssistantChatMessageDict, + AssistantChatMessage, ChatMessage, CompletionModelFunction, ) @@ -85,7 +84,10 @@ class OneShotAgentPromptConfiguration(SystemConfiguration): required=True, ), "plan": JSONSchema( - description="Short markdown-style bullet list that conveys the long-term plan", + description=( + "Short markdown-style bullet list that conveys the " + "long-term plan" + ), type=JSONSchema.Type.STRING, required=True, ), @@ -165,11 +167,9 @@ class OneShotAgentPromptStrategy(PromptStrategy): ) -> ChatPrompt: """Constructs and returns a prompt with the following structure: 1. System prompt - 2. Message history of the agent, truncated & prepended with running summary as needed + 2. Message history of the agent, truncated & prepended with running summary + as needed 3. `cycle_instruction` - - Params: - cycle_instruction: The final instruction for a thinking cycle """ if not extra_messages: extra_messages = [] @@ -264,7 +264,7 @@ class OneShotAgentPromptStrategy(PromptStrategy): steps: list[str] = [] tokens: int = 0 - start: int = len(episode_history) + # start: int = len(episode_history) for i, c in reversed(list(enumerate(episode_history))): step = f"### Step {i+1}: Executed `{c.action.format_call()}`\n" @@ -291,11 +291,10 @@ class OneShotAgentPromptStrategy(PromptStrategy): tokens += step_tokens steps.insert(0, step) - start = i - - # TODO: summarize remaining + # start = i - part = slice(0, start) + # # TODO: summarize remaining + # part = slice(0, start) return "\n\n".join(steps) @@ -315,10 +314,16 @@ class OneShotAgentPromptStrategy(PromptStrategy): response_schema.to_typescript_object_interface("Response"), ) + instruction = ( + "Respond with pure JSON containing your thoughts, " "and invoke a tool." + if use_functions_api + else "Respond with pure JSON." + ) + return ( - f"Respond strictly with a JSON object{' containing your thoughts, and a tool_call specifying the next command to use' if use_functions_api else ''}. " - "The JSON object should be compatible with the TypeScript type `Response` from the following:\n" - f"{response_format}" + f"{instruction} " + "The JSON object should be compatible with the TypeScript type `Response` " + f"from the following:\n{response_format}" ) def _generate_intro_prompt(self, ai_profile: AIProfile) -> list[str]: @@ -376,17 +381,29 @@ class OneShotAgentPromptStrategy(PromptStrategy): try: return format_numbered_list([cmd.fmt_line() for cmd in commands]) except AttributeError: - self.logger.warn(f"Formatting commands failed. {commands}") + self.logger.warning(f"Formatting commands failed. {commands}") raise def parse_response_content( self, - response: AssistantChatMessageDict, + response: AssistantChatMessage, ) -> Agent.ThoughtProcessOutput: - if "content" not in response: + if not response.content: raise InvalidAgentResponseError("Assistant response has no text content") - assistant_reply_dict = extract_dict_from_response(response["content"]) + self.logger.debug( + "LLM response content:" + + ( + f"\n{response.content}" + if "\n" in response.content + else f" '{response.content}'" + ) + ) + assistant_reply_dict = extract_dict_from_response(response.content) + self.logger.debug( + "Validating object extracted from LLM response:\n" + f"{json.dumps(assistant_reply_dict, indent=4)}" + ) _, errors = self.response_schema.validate_object( object=assistant_reply_dict, @@ -412,14 +429,14 @@ class OneShotAgentPromptStrategy(PromptStrategy): def extract_command( assistant_reply_json: dict, - assistant_reply: AssistantChatMessageDict, + assistant_reply: AssistantChatMessage, use_openai_functions_api: bool, ) -> tuple[str, dict[str, str]]: """Parse the response and return the command name and arguments Args: assistant_reply_json (dict): The response object from the AI - assistant_reply (ChatModelResponse): The model response from the AI + assistant_reply (AssistantChatMessage): The model response from the AI config (Config): The config object Returns: @@ -431,13 +448,11 @@ def extract_command( Exception: If any other error occurs """ if use_openai_functions_api: - if not assistant_reply.get("tool_calls"): + if not assistant_reply.tool_calls: raise InvalidAgentResponseError("No 'tool_calls' in assistant reply") assistant_reply_json["command"] = { - "name": assistant_reply["tool_calls"][0]["function"]["name"], - "args": json.loads( - assistant_reply["tool_calls"][0]["function"]["arguments"] - ), + "name": assistant_reply.tool_calls[0].function.name, + "args": json.loads(assistant_reply.tool_calls[0].function.arguments), } try: if not isinstance(assistant_reply_json, dict): diff --git a/autogpts/autogpt/autogpt/agents/utils/prompt_scratchpad.py b/autogpts/autogpt/autogpt/agents/utils/prompt_scratchpad.py index 07b324254..224493338 100644 --- a/autogpts/autogpt/autogpt/agents/utils/prompt_scratchpad.py +++ b/autogpts/autogpt/autogpt/agents/utils/prompt_scratchpad.py @@ -52,7 +52,7 @@ class PromptScratchpad(BaseModel): """ for p, s in params.items(): invalid = False - if type(s) == str and s not in JSONSchema.Type._value2member_map_: + if type(s) is str and s not in JSONSchema.Type._value2member_map_: invalid = True logger.warning( f"Cannot add command '{name}':" @@ -72,7 +72,7 @@ class PromptScratchpad(BaseModel): description=description, parameters={ name: JSONSchema(type=JSONSchema.Type._value2member_map_[spec]) - if type(spec) == str + if type(spec) is str else JSONSchema.from_dict(spec) for name, spec in params.items() }, diff --git a/autogpts/autogpt/autogpt/app/agent_protocol_server.py b/autogpts/autogpt/autogpt/app/agent_protocol_server.py index d59b79628..12e54582b 100644 --- a/autogpts/autogpt/autogpt/app/agent_protocol_server.py +++ b/autogpts/autogpt/autogpt/app/agent_protocol_server.py @@ -12,8 +12,7 @@ from fastapi.staticfiles import StaticFiles from forge.sdk.db import AgentDB from forge.sdk.errors import NotFoundError from forge.sdk.middlewares import AgentMiddleware -from forge.sdk.routes.agent_protocol import base_router -from forge.sdk.schema import ( +from forge.sdk.model import ( Artifact, Step, StepRequestBody, @@ -23,6 +22,7 @@ from forge.sdk.schema import ( TaskRequestBody, TaskStepsListResponse, ) +from forge.sdk.routes.agent_protocol import base_router from hypercorn.asyncio import serve as hypercorn_serve from hypercorn.config import Config as HypercornConfig @@ -33,13 +33,22 @@ from autogpt.commands.system import finish from autogpt.commands.user_interaction import ask_user from autogpt.config import Config from autogpt.core.resource.model_providers import ChatModelProvider -from autogpt.file_workspace import FileWorkspace +from autogpt.core.resource.model_providers.openai import OpenAIProvider +from autogpt.core.resource.model_providers.schema import ModelProviderBudget +from autogpt.file_workspace import ( + FileWorkspace, + FileWorkspaceBackendName, + get_workspace, +) +from autogpt.logs.utils import fmt_kwargs from autogpt.models.action_history import ActionErrorResult, ActionSuccessResult logger = logging.getLogger(__name__) class AgentProtocolServer: + _task_budgets: dict[str, ModelProviderBudget] + def __init__( self, app_config: Config, @@ -50,6 +59,7 @@ class AgentProtocolServer: self.db = database self.llm_provider = llm_provider self.agent_manager = AgentManager(app_data_dir=app_config.app_data_dir) + self._task_budgets = {} async def start(self, port: int = 8000, router: APIRouter = base_router): """Start the agent server.""" @@ -58,18 +68,14 @@ class AgentProtocolServer: config.bind = [f"localhost:{port}"] app = FastAPI( title="AutoGPT Server", - description="Forked from AutoGPT Forge; Modified version of The Agent Protocol.", + description="Forked from AutoGPT Forge; " + "Modified version of The Agent Protocol.", version="v0.4", ) # Add CORS middleware origins = [ - "http://localhost:5000", - "http://127.0.0.1:5000", - "http://localhost:8000", - "http://127.0.0.1:8000", - "http://localhost:8080", - "http://127.0.0.1:8080", + "*", # Add any other origins you want to whitelist ] @@ -98,7 +104,8 @@ class AgentProtocolServer: else: logger.warning( - f"Frontend not found. {frontend_path} does not exist. The frontend will not be available." + f"Frontend not found. {frontend_path} does not exist. " + "The frontend will not be available." ) # Used to access the methods on this class from API route handlers @@ -114,20 +121,23 @@ class AgentProtocolServer: """ Create a task for the agent. """ - logger.debug(f"Creating agent for task: '{task_request.input}'") - task_agent = await generate_agent_for_task( - task=task_request.input, - app_config=self.app_config, - llm_provider=self.llm_provider, - ) task = await self.db.create_task( input=task_request.input, additional_input=task_request.additional_input, ) + logger.debug(f"Creating agent for task: '{task.input}'") + task_agent = await generate_agent_for_task( + task=task.input, + app_config=self.app_config, + llm_provider=self._get_task_llm_provider(task), + ) + + # Assign an ID and a folder to the Agent and persist it agent_id = task_agent.state.agent_id = task_agent_id(task.task_id) logger.debug(f"New agent ID: {agent_id}") task_agent.attach_fs(self.app_config.app_data_dir / "agents" / agent_id) task_agent.state.save_to_json_file(task_agent.file_manager.state_file_path) + return task async def list_tasks(self, page: int = 1, pageSize: int = 10) -> TaskListResponse: @@ -139,7 +149,7 @@ class AgentProtocolServer: response = TaskListResponse(tasks=tasks, pagination=pagination) return response - async def get_task(self, task_id: int) -> Task: + async def get_task(self, task_id: str) -> Task: """ Get a task by ID. """ @@ -163,15 +173,11 @@ class AgentProtocolServer: logger.debug(f"Creating a step for task with ID: {task_id}...") # Restore Agent instance + task = await self.get_task(task_id) agent = configure_agent_with_state( state=self.agent_manager.retrieve_state(task_agent_id(task_id)), app_config=self.app_config, - llm_provider=self.llm_provider, - ) - agent.workspace.on_write_file = lambda path: self.db.create_artifact( - task_id=task_id, - file_name=path.parts[-1], - relative_path=str(path), + llm_provider=self._get_task_llm_provider(task), ) # According to the Agent Protocol spec, the first execute_step request contains @@ -209,10 +215,14 @@ class AgentProtocolServer: input=step_request, is_last=execute_command == finish.__name__ and execute_approved, ) + agent.llm_provider = self._get_task_llm_provider(task, step.step_id) # Execute previously proposed action if execute_command: assert execute_command_args is not None + agent.workspace.on_write_file = lambda path: self._on_agent_write_file( + task=task, step=step, relative_path=path + ) if step.is_last and execute_command == finish.__name__: assert execute_command_args @@ -221,6 +231,10 @@ class AgentProtocolServer: step_id=step.step_id, output=execute_command_args["reason"], ) + logger.info( + f"Total LLM cost for task {task_id}: " + f"${round(agent.llm_provider.get_incurred_cost(), 2)}" + ) return step if execute_command == ask_user.__name__: # HACK @@ -263,17 +277,17 @@ class AgentProtocolServer: # Format step output output = ( ( - f"Command `{execute_command}({fmt_kwargs(execute_command_args)})` returned:" + f"`{execute_command}({fmt_kwargs(execute_command_args)})` returned:" + ("\n\n" if "\n" in str(execute_result) else " ") + f"{execute_result}\n\n" ) - if execute_command_args and execute_command != "ask_user" + if execute_command_args and execute_command != ask_user.__name__ else "" ) output += f"{raw_output['thoughts']['speak']}\n\n" output += ( f"Next Command: {next_command}({fmt_kwargs(next_command_args)})" - if next_command != "ask_user" + if next_command != ask_user.__name__ else next_command_args["question"] ) @@ -307,9 +321,37 @@ class AgentProtocolServer: additional_output=additional_output, ) + logger.debug( + f"Running total LLM cost for task {task_id}: " + f"${round(agent.llm_provider.get_incurred_cost(), 3)}" + ) agent.state.save_to_json_file(agent.file_manager.state_file_path) return step + async def _on_agent_write_file( + self, task: Task, step: Step, relative_path: pathlib.Path + ) -> None: + """ + Creates an Artifact for the written file, or updates the Artifact if it exists. + """ + if relative_path.is_absolute(): + raise ValueError(f"File path '{relative_path}' is not relative") + for a in task.artifacts or []: + if a.relative_path == str(relative_path): + logger.debug(f"Updating Artifact after writing to existing file: {a}") + if not a.agent_created: + await self.db.update_artifact(a.artifact_id, agent_created=True) + break + else: + logger.debug(f"Creating Artifact for new file '{relative_path}'") + await self.db.create_artifact( + task_id=step.task_id, + step_id=step.step_id, + file_name=relative_path.parts[-1], + agent_created=True, + relative_path=str(relative_path), + ) + async def get_step(self, task_id: str, step_id: str) -> Step: """ Get a step by ID. @@ -332,7 +374,6 @@ class AgentProtocolServer: """ Create an artifact for the task. """ - data = None file_name = file.filename or str(uuid4()) data = b"" while contents := file.file.read(1024 * 1024): @@ -343,7 +384,7 @@ class AgentProtocolServer: else: file_path = os.path.join(relative_path, file_name) - workspace = get_task_agent_file_workspace(task_id, self.agent_manager) + workspace = self._get_task_agent_file_workspace(task_id, self.agent_manager) await workspace.write_file(file_path, data) artifact = await self.db.create_artifact( @@ -354,9 +395,9 @@ class AgentProtocolServer: ) return artifact - async def get_artifact(self, task_id: str, artifact_id: str) -> Artifact: + async def get_artifact(self, task_id: str, artifact_id: str) -> StreamingResponse: """ - Get an artifact by ID. + Download a task artifact by ID. """ try: artifact = await self.db.get_artifact(artifact_id) @@ -364,39 +405,77 @@ class AgentProtocolServer: file_path = os.path.join(artifact.relative_path, artifact.file_name) else: file_path = artifact.relative_path - workspace = get_task_agent_file_workspace(task_id, self.agent_manager) + workspace = self._get_task_agent_file_workspace(task_id, self.agent_manager) retrieved_artifact = workspace.read_file(file_path, binary=True) - except NotFoundError as e: + except NotFoundError: raise - except FileNotFoundError as e: + except FileNotFoundError: raise return StreamingResponse( BytesIO(retrieved_artifact), media_type="application/octet-stream", headers={ - "Content-Disposition": f"attachment; filename={artifact.file_name}" + "Content-Disposition": f'attachment; filename="{artifact.file_name}"' }, ) + def _get_task_agent_file_workspace( + self, + task_id: str | int, + agent_manager: AgentManager, + ) -> FileWorkspace: + use_local_ws = ( + self.app_config.workspace_backend == FileWorkspaceBackendName.LOCAL + ) + agent_id = task_agent_id(task_id) + workspace = get_workspace( + backend=self.app_config.workspace_backend, + id=agent_id if not use_local_ws else "", + root_path=agent_manager.get_agent_dir( + agent_id=agent_id, + must_exist=True, + ) + / "workspace" + if use_local_ws + else None, + ) + workspace.initialize() + return workspace -def task_agent_id(task_id: str | int) -> str: - return f"AutoGPT-{task_id}" + def _get_task_llm_provider( + self, task: Task, step_id: str = "" + ) -> ChatModelProvider: + """ + Configures the LLM provider with headers to link outgoing requests to the task. + """ + task_llm_budget = self._task_budgets.get( + task.task_id, self.llm_provider.default_settings.budget.copy(deep=True) + ) + task_llm_provider_config = self.llm_provider._configuration.copy(deep=True) + _extra_request_headers = task_llm_provider_config.extra_request_headers + _extra_request_headers["AP-TaskID"] = task.task_id + if step_id: + _extra_request_headers["AP-StepID"] = step_id + if task.additional_input and (user_id := task.additional_input.get("user_id")): + _extra_request_headers["AutoGPT-UserID"] = user_id + + task_llm_provider = None + if isinstance(self.llm_provider, OpenAIProvider): + settings = self.llm_provider._settings.copy() + settings.budget = task_llm_budget + settings.configuration = task_llm_provider_config # type: ignore + task_llm_provider = OpenAIProvider( + settings=settings, + logger=logger.getChild(f"Task-{task.task_id}_OpenAIProvider"), + ) -def get_task_agent_file_workspace( - task_id: str | int, - agent_manager: AgentManager, -) -> FileWorkspace: - return FileWorkspace( - root=agent_manager.get_agent_dir( - agent_id=task_agent_id(task_id), - must_exist=True, - ) - / "workspace", - restrict_to_root=True, - ) + if task_llm_provider and task_llm_provider._budget: + self._task_budgets[task.task_id] = task_llm_provider._budget + + return task_llm_provider or self.llm_provider -def fmt_kwargs(kwargs: dict) -> str: - return ", ".join(f"{n}={repr(v)}" for n, v in kwargs.items()) +def task_agent_id(task_id: str | int) -> str: + return f"AutoGPT-{task_id}" diff --git a/autogpts/autogpt/autogpt/app/cli.py b/autogpts/autogpt/autogpt/app/cli.py index 4f97b60ac..ccfa9a8ae 100644 --- a/autogpts/autogpt/autogpt/app/cli.py +++ b/autogpts/autogpt/autogpt/app/cli.py @@ -1,9 +1,12 @@ """Main script for the autogpt package.""" +from logging import _nameToLevel as logLevelMap from pathlib import Path from typing import Optional import click +from autogpt.logs.config import LogFormatName + @click.group(invoke_without_command=True) @click.pass_context @@ -16,44 +19,15 @@ def cli(ctx: click.Context): @cli.command() @click.option("-c", "--continuous", is_flag=True, help="Enable Continuous Mode") @click.option( - "--skip-reprompt", - "-y", - is_flag=True, - help="Skips the re-prompting messages at the beginning of the script", -) -@click.option( - "--ai-settings", - "-C", - type=click.Path(exists=True, dir_okay=False, path_type=Path), - help=( - "Specifies which ai_settings.yaml file to use, relative to the AutoGPT" - " root directory. Will also automatically skip the re-prompt." - ), -) -@click.option( - "--prompt-settings", - "-P", - type=click.Path(exists=True, dir_okay=False, path_type=Path), - help="Specifies which prompt_settings.yaml file to use.", -) -@click.option( "-l", "--continuous-limit", type=int, help="Defines the number of times to run in continuous mode", ) @click.option("--speak", is_flag=True, help="Enable Speak Mode") -@click.option("--debug", is_flag=True, help="Enable Debug Mode") @click.option("--gpt3only", is_flag=True, help="Enable GPT3.5 Only Mode") @click.option("--gpt4only", is_flag=True, help="Enable GPT4 Only Mode") @click.option( - "--use-memory", - "-m", - "memory_type", - type=str, - help="Defines which Memory backend to use", -) -@click.option( "-b", "--browser-name", help="Specifies which web-browser to use when using selenium to scrape the web.", @@ -64,16 +38,11 @@ def cli(ctx: click.Context): help="Dangerous: Allows AutoGPT to download files natively.", ) @click.option( - "--skip-news", - is_flag=True, - help="Specifies whether to suppress the output of latest news on startup.", -) -@click.option( # TODO: this is a hidden option for now, necessary for integration testing. - # We should make this public once we're ready to roll out agent specific workspaces. + # We should make this public once we're ready to roll out agent specific workspaces. "--workspace-directory", "-w", - type=click.Path(), + type=click.Path(file_okay=False), hidden=True, ) @click.option( @@ -82,6 +51,26 @@ def cli(ctx: click.Context): help="Installs external dependencies for 3rd party plugins.", ) @click.option( + "--skip-news", + is_flag=True, + help="Specifies whether to suppress the output of latest news on startup.", +) +@click.option( + "--skip-reprompt", + "-y", + is_flag=True, + help="Skips the re-prompting messages at the beginning of the script", +) +@click.option( + "--ai-settings", + "-C", + type=click.Path(exists=True, dir_okay=False, path_type=Path), + help=( + "Specifies which ai_settings.yaml file to use, relative to the AutoGPT" + " root directory. Will also automatically skip the re-prompt." + ), +) +@click.option( "--ai-name", type=str, help="AI name override", @@ -92,6 +81,12 @@ def cli(ctx: click.Context): help="AI role override", ) @click.option( + "--prompt-settings", + "-P", + type=click.Path(exists=True, dir_okay=False, path_type=Path), + help="Specifies which prompt_settings.yaml file to use.", +) +@click.option( "--constraint", type=str, multiple=True, @@ -126,28 +121,51 @@ def cli(ctx: click.Context): " the AI's directives instead of being appended to them" ), ) +@click.option( + "--debug", is_flag=True, help="Implies --log-level=DEBUG --log-format=debug" +) +@click.option("--log-level", type=click.Choice([*logLevelMap.keys()])) +@click.option( + "--log-format", + help=( + "Choose a log format; defaults to 'simple'." + " Also implies --log-file-format, unless it is specified explicitly." + " Using the 'structured_google_cloud' format disables log file output." + ), + type=click.Choice([i.value for i in LogFormatName]), +) +@click.option( + "--log-file-format", + help=( + "Override the format used for the log file output." + " Defaults to the application's global --log-format." + ), + type=click.Choice([i.value for i in LogFormatName]), +) def run( continuous: bool, - continuous_limit: int, - ai_settings: Optional[Path], - prompt_settings: Optional[Path], - skip_reprompt: bool, + continuous_limit: Optional[int], speak: bool, - debug: bool, gpt3only: bool, gpt4only: bool, - memory_type: str, - browser_name: str, + browser_name: Optional[str], allow_downloads: bool, - skip_news: bool, - workspace_directory: str, + workspace_directory: Optional[Path], install_plugin_deps: bool, + skip_news: bool, + skip_reprompt: bool, + ai_settings: Optional[Path], ai_name: Optional[str], ai_role: Optional[str], + prompt_settings: Optional[Path], resource: tuple[str], constraint: tuple[str], best_practice: tuple[str], override_directives: bool, + debug: bool, + log_level: Optional[str], + log_format: Optional[str], + log_file_format: Optional[str], ) -> None: """ Sets up and runs an agent, based on the task specified by the user, or resumes an @@ -164,9 +182,11 @@ def run( skip_reprompt=skip_reprompt, speak=speak, debug=debug, + log_level=log_level, + log_format=log_format, + log_file_format=log_file_format, gpt3only=gpt3only, gpt4only=gpt4only, - memory_type=memory_type, browser_name=browser_name, allow_downloads=allow_downloads, skip_news=skip_news, @@ -188,17 +208,9 @@ def run( type=click.Path(exists=True, dir_okay=False, path_type=Path), help="Specifies which prompt_settings.yaml file to use.", ) -@click.option("--debug", is_flag=True, help="Enable Debug Mode") @click.option("--gpt3only", is_flag=True, help="Enable GPT3.5 Only Mode") @click.option("--gpt4only", is_flag=True, help="Enable GPT4 Only Mode") @click.option( - "--use-memory", - "-m", - "memory_type", - type=str, - help="Defines which Memory backend to use", -) -@click.option( "-b", "--browser-name", help="Specifies which web-browser to use when using selenium to scrape the web.", @@ -213,15 +225,38 @@ def run( is_flag=True, help="Installs external dependencies for 3rd party plugins.", ) +@click.option( + "--debug", is_flag=True, help="Implies --log-level=DEBUG --log-format=debug" +) +@click.option("--log-level", type=click.Choice([*logLevelMap.keys()])) +@click.option( + "--log-format", + help=( + "Choose a log format; defaults to 'simple'." + " Also implies --log-file-format, unless it is specified explicitly." + " Using the 'structured_google_cloud' format disables log file output." + ), + type=click.Choice([i.value for i in LogFormatName]), +) +@click.option( + "--log-file-format", + help=( + "Override the format used for the log file output." + " Defaults to the application's global --log-format." + ), + type=click.Choice([i.value for i in LogFormatName]), +) def serve( prompt_settings: Optional[Path], - debug: bool, gpt3only: bool, gpt4only: bool, - memory_type: str, - browser_name: str, + browser_name: Optional[str], allow_downloads: bool, install_plugin_deps: bool, + debug: bool, + log_level: Optional[str], + log_format: Optional[str], + log_file_format: Optional[str], ) -> None: """ Starts an Agent Protocol compliant AutoGPT server, which creates a custom agent for @@ -233,9 +268,11 @@ def serve( run_auto_gpt_server( prompt_settings=prompt_settings, debug=debug, + log_level=log_level, + log_format=log_format, + log_file_format=log_file_format, gpt3only=gpt3only, gpt4only=gpt4only, - memory_type=memory_type, browser_name=browser_name, allow_downloads=allow_downloads, install_plugin_deps=install_plugin_deps, diff --git a/autogpts/autogpt/autogpt/app/configurator.py b/autogpts/autogpt/autogpt/app/configurator.py index 54f4b1e37..cd7890021 100644 --- a/autogpts/autogpt/autogpt/app/configurator.py +++ b/autogpts/autogpt/autogpt/app/configurator.py @@ -3,7 +3,7 @@ from __future__ import annotations import logging from pathlib import Path -from typing import Literal, Optional +from typing import TYPE_CHECKING, Literal, Optional import click from colorama import Back, Fore, Style @@ -12,9 +12,13 @@ from autogpt import utils from autogpt.config import Config from autogpt.config.config import GPT_3_MODEL, GPT_4_MODEL from autogpt.llm.api_manager import ApiManager -from autogpt.logs.helpers import print_attribute, request_user_double_check +from autogpt.logs.config import LogFormatName +from autogpt.logs.helpers import request_user_double_check from autogpt.memory.vector import get_supported_memory_backends +if TYPE_CHECKING: + from autogpt.core.resource.model_providers.openai import OpenAICredentials + logger = logging.getLogger(__name__) @@ -27,40 +31,53 @@ def apply_overrides_to_config( skip_reprompt: bool = False, speak: bool = False, debug: bool = False, + log_level: Optional[str] = None, + log_format: Optional[str] = None, + log_file_format: Optional[str] = None, gpt3only: bool = False, gpt4only: bool = False, - memory_type: str = "", - browser_name: str = "", + memory_type: Optional[str] = None, + browser_name: Optional[str] = None, allow_downloads: bool = False, skip_news: bool = False, ) -> None: """Updates the config object with the given arguments. Args: - continuous (bool): Whether to run in continuous mode - continuous_limit (int): The number of times to run in continuous mode - ai_settings_file (Path): The path to the ai_settings.yaml file - prompt_settings_file (Path): The path to the prompt_settings.yaml file - skip_reprompt (bool): Whether to skip the re-prompting messages at the beginning of the script - speak (bool): Whether to enable speak mode - debug (bool): Whether to enable debug mode - gpt3only (bool): Whether to enable GPT3.5 only mode - gpt4only (bool): Whether to enable GPT4 only mode - memory_type (str): The type of memory backend to use - browser_name (str): The name of the browser to use when using selenium to scrape the web - allow_downloads (bool): Whether to allow AutoGPT to download files natively - skips_news (bool): Whether to suppress the output of latest news on startup + config (Config): The config object to update. + continuous (bool): Whether to run in continuous mode. + continuous_limit (int): The number of times to run in continuous mode. + ai_settings_file (Path): The path to the ai_settings.yaml file. + prompt_settings_file (Path): The path to the prompt_settings.yaml file. + skip_reprompt (bool): Whether to skip the re-prompting messages on start. + speak (bool): Whether to enable speak mode. + debug (bool): Whether to enable debug mode. + log_level (int): The global log level for the application. + log_format (str): The format for the log(s). + log_file_format (str): Override the format for the log file. + gpt3only (bool): Whether to enable GPT3.5 only mode. + gpt4only (bool): Whether to enable GPT4 only mode. + memory_type (str): The type of memory backend to use. + browser_name (str): The name of the browser to use for scraping the web. + allow_downloads (bool): Whether to allow AutoGPT to download files natively. + skips_news (bool): Whether to suppress the output of latest news on startup. """ - config.debug_mode = False config.continuous_mode = False config.tts_config.speak_mode = False + # Set log level if debug: - print_attribute("Debug mode", "ENABLED") - config.debug_mode = True + config.logging.level = logging.DEBUG + elif log_level and type(_level := logging.getLevelName(log_level.upper())) is int: + config.logging.level = _level + + # Set log format + if log_format and log_format in LogFormatName._value2member_map_: + config.logging.log_format = LogFormatName(log_format) + if log_file_format and log_file_format in LogFormatName._value2member_map_: + config.logging.log_file_format = LogFormatName(log_file_format) if continuous: - print_attribute("Continuous Mode", "ENABLED", title_color=Fore.YELLOW) logger.warning( "Continuous mode is not recommended. It is potentially dangerous and may" " cause your AI to run forever or carry out actions you would not usually" @@ -69,7 +86,6 @@ def apply_overrides_to_config( config.continuous_mode = True if continuous_limit: - print_attribute("Continuous Limit", continuous_limit) config.continuous_limit = continuous_limit # Check if continuous limit is used without continuous mode @@ -77,27 +93,32 @@ def apply_overrides_to_config( raise click.UsageError("--continuous-limit can only be used with --continuous") if speak: - print_attribute("Speak Mode", "ENABLED") config.tts_config.speak_mode = True # Set the default LLM models if gpt3only: - print_attribute("GPT3.5 Only Mode", "ENABLED") # --gpt3only should always use gpt-3.5-turbo, despite user's FAST_LLM config config.fast_llm = GPT_3_MODEL config.smart_llm = GPT_3_MODEL elif ( gpt4only - and check_model(GPT_4_MODEL, model_type="smart_llm", config=config) + and check_model( + GPT_4_MODEL, + model_type="smart_llm", + api_credentials=config.openai_credentials, + ) == GPT_4_MODEL ): - print_attribute("GPT4 Only Mode", "ENABLED") # --gpt4only should always use gpt-4, despite user's SMART_LLM config config.fast_llm = GPT_4_MODEL config.smart_llm = GPT_4_MODEL else: - config.fast_llm = check_model(config.fast_llm, "fast_llm", config=config) - config.smart_llm = check_model(config.smart_llm, "smart_llm", config=config) + config.fast_llm = check_model( + config.fast_llm, "fast_llm", api_credentials=config.openai_credentials + ) + config.smart_llm = check_model( + config.smart_llm, "smart_llm", api_credentials=config.openai_credentials + ) if memory_type: supported_memory = get_supported_memory_backends() @@ -110,14 +131,10 @@ def apply_overrides_to_config( }, msg=f"{supported_memory}", ) - print_attribute( - "Defaulting to", config.memory_backend, title_color=Fore.YELLOW - ) else: config.memory_backend = chosen if skip_reprompt: - print_attribute("Skip Re-prompt", "ENABLED") config.skip_reprompt = True if ai_settings_file: @@ -130,7 +147,6 @@ def apply_overrides_to_config( request_user_double_check() exit(1) - print_attribute("Using AI Settings File", file) config.ai_settings_file = config.project_root / file config.skip_reprompt = True @@ -144,20 +160,22 @@ def apply_overrides_to_config( request_user_double_check() exit(1) - print_attribute("Using Prompt Settings File", file) config.prompt_settings_file = config.project_root / file if browser_name: config.selenium_web_browser = browser_name if allow_downloads: - print_attribute("Native Downloading", "ENABLED") - logger.warn( - msg=f"{Back.LIGHTYELLOW_EX}AutoGPT will now be able to download and save files to your machine.{Back.RESET}" + logger.warning( + msg=f"{Back.LIGHTYELLOW_EX}" + "AutoGPT will now be able to download and save files to your machine." + f"{Back.RESET}" " It is recommended that you monitor any files it downloads carefully.", ) - logger.warn( - msg=f"{Back.RED + Style.BRIGHT}ALWAYS REMEMBER TO NEVER OPEN FILES YOU AREN'T SURE OF!{Style.RESET_ALL}", + logger.warning( + msg=f"{Back.RED + Style.BRIGHT}" + "NEVER OPEN FILES YOU AREN'T SURE OF!" + f"{Style.RESET_ALL}", ) config.allow_downloads = True @@ -168,17 +186,16 @@ def apply_overrides_to_config( def check_model( model_name: str, model_type: Literal["smart_llm", "fast_llm"], - config: Config, + api_credentials: OpenAICredentials, ) -> str: """Check if model is available for use. If not, return gpt-3.5-turbo.""" - openai_credentials = config.get_openai_credentials(model_name) api_manager = ApiManager() - models = api_manager.get_models(**openai_credentials) + models = api_manager.get_models(api_credentials) - if any(model_name in m["id"] for m in models): + if any(model_name == m.id for m in models): return model_name - logger.warn( - f"You do not have access to {model_name}. Setting {model_type} to gpt-3.5-turbo." + logger.warning( + f"You don't have access to {model_name}. Setting {model_type} to gpt-3.5-turbo." ) return "gpt-3.5-turbo" diff --git a/autogpts/autogpt/autogpt/app/main.py b/autogpts/autogpt/autogpt/app/main.py index 683793a70..20f1d9872 100644 --- a/autogpts/autogpt/autogpt/app/main.py +++ b/autogpts/autogpt/autogpt/app/main.py @@ -1,7 +1,10 @@ -"""The application entry point. Can be invoked by a CLI or any other front end application.""" +""" +The application entry point. Can be invoked by a CLI or any other front end application. +""" import enum import logging import math +import os import re import signal import sys @@ -11,7 +14,6 @@ from typing import TYPE_CHECKING, Optional from colorama import Fore, Style from forge.sdk.db import AgentDB -from pydantic import SecretStr if TYPE_CHECKING: from autogpt.agents.agent import Agent @@ -28,7 +30,6 @@ from autogpt.config import ( ConfigBuilder, assert_config_has_openai_api_key, ) -from autogpt.core.resource.model_providers import ModelProviderCredentials from autogpt.core.resource.model_providers.openai import OpenAIProvider from autogpt.core.runner.client_lib.utils import coroutine from autogpt.logs.config import configure_chat_plugins, configure_logging @@ -51,23 +52,25 @@ from .utils import ( @coroutine async def run_auto_gpt( - continuous: bool, - continuous_limit: int, - ai_settings: Optional[Path], - prompt_settings: Optional[Path], - skip_reprompt: bool, - speak: bool, - debug: bool, - gpt3only: bool, - gpt4only: bool, - memory_type: str, - browser_name: str, - allow_downloads: bool, - skip_news: bool, - workspace_directory: Path, - install_plugin_deps: bool, - override_ai_name: str = "", - override_ai_role: str = "", + continuous: bool = False, + continuous_limit: Optional[int] = None, + ai_settings: Optional[Path] = None, + prompt_settings: Optional[Path] = None, + skip_reprompt: bool = False, + speak: bool = False, + debug: bool = False, + log_level: Optional[str] = None, + log_format: Optional[str] = None, + log_file_format: Optional[str] = None, + gpt3only: bool = False, + gpt4only: bool = False, + browser_name: Optional[str] = None, + allow_downloads: bool = False, + skip_news: bool = False, + workspace_directory: Optional[Path] = None, + install_plugin_deps: bool = False, + override_ai_name: Optional[str] = None, + override_ai_role: Optional[str] = None, resources: Optional[list[str]] = None, constraints: Optional[list[str]] = None, best_practices: Optional[list[str]] = None, @@ -87,9 +90,11 @@ async def run_auto_gpt( skip_reprompt=skip_reprompt, speak=speak, debug=debug, + log_level=log_level, + log_format=log_format, + log_file_format=log_file_format, gpt3only=gpt3only, gpt4only=gpt4only, - memory_type=memory_type, browser_name=browser_name, allow_downloads=allow_downloads, skip_news=skip_news, @@ -97,8 +102,7 @@ async def run_auto_gpt( # Set up logging module configure_logging( - debug_mode=debug, - plain_output=config.plain_output, + **config.logging.dict(), tts_config=config.tts_config, ) @@ -108,7 +112,7 @@ async def run_auto_gpt( if config.continuous_mode: for line in get_legal_warning().split("\n"): - logger.warn( + logger.warning( extra={ "title": "LEGAL:", "title_color": Fore.RED, @@ -121,11 +125,26 @@ async def run_auto_gpt( print_motd(config, logger) print_git_branch_info(logger) print_python_version_info(logger) + print_attribute("Smart LLM", config.smart_llm) + print_attribute("Fast LLM", config.fast_llm) + print_attribute("Browser", config.selenium_web_browser) + if config.continuous_mode: + print_attribute("Continuous Mode", "ENABLED", title_color=Fore.YELLOW) + if continuous_limit: + print_attribute("Continuous Limit", config.continuous_limit) + if config.tts_config.speak_mode: + print_attribute("Speak Mode", "ENABLED") + if ai_settings: + print_attribute("Using AI Settings File", ai_settings) + if prompt_settings: + print_attribute("Using Prompt Settings File", prompt_settings) + if config.allow_downloads: + print_attribute("Native Downloading", "ENABLED") if install_plugin_deps: install_plugin_dependencies() - config.plugins = scan_plugins(config, config.debug_mode) + config.plugins = scan_plugins(config) configure_chat_plugins(config) # Let user choose an existing agent to run @@ -139,7 +158,8 @@ async def run_auto_gpt( ) load_existing_agent = await clean_input( config, - "Enter the number or name of the agent to run, or hit enter to create a new one:", + "Enter the number or name of the agent to run," + " or hit enter to create a new one:", ) if re.match(r"^\d+$", load_existing_agent): load_existing_agent = existing_agents[int(load_existing_agent) - 1] @@ -259,8 +279,9 @@ async def run_auto_gpt( if not agent.config.allow_fs_access: logger.info( - f"{Fore.YELLOW}NOTE: All files/directories created by this agent" - f" can be found inside its workspace at:{Fore.RESET} {agent.workspace.root}", + f"{Fore.YELLOW}" + "NOTE: All files/directories created by this agent can be found " + f"inside its workspace at:{Fore.RESET} {agent.workspace.root}", extra={"preserve_color": True}, ) @@ -277,7 +298,8 @@ async def run_auto_gpt( save_as_id = ( await clean_input( config, - f"Press enter to save as '{agent_id}', or enter a different ID to save to:", + f"Press enter to save as '{agent_id}'," + " or enter a different ID to save to:", ) or agent_id ) @@ -294,14 +316,16 @@ async def run_auto_gpt( @coroutine async def run_auto_gpt_server( - prompt_settings: Optional[Path], - debug: bool, - gpt3only: bool, - gpt4only: bool, - memory_type: str, - browser_name: str, - allow_downloads: bool, - install_plugin_deps: bool, + prompt_settings: Optional[Path] = None, + debug: bool = False, + log_level: Optional[str] = None, + log_format: Optional[str] = None, + log_file_format: Optional[str] = None, + gpt3only: bool = False, + gpt4only: bool = False, + browser_name: Optional[str] = None, + allow_downloads: bool = False, + install_plugin_deps: bool = False, ): from .agent_protocol_server import AgentProtocolServer @@ -314,17 +338,18 @@ async def run_auto_gpt_server( config=config, prompt_settings_file=prompt_settings, debug=debug, + log_level=log_level, + log_format=log_format, + log_file_format=log_file_format, gpt3only=gpt3only, gpt4only=gpt4only, - memory_type=memory_type, browser_name=browser_name, allow_downloads=allow_downloads, ) # Set up logging module configure_logging( - debug_mode=debug, - plain_output=config.plain_output, + **config.logging.dict(), tts_config=config.tts_config, ) @@ -333,14 +358,23 @@ async def run_auto_gpt_server( if install_plugin_deps: install_plugin_dependencies() - config.plugins = scan_plugins(config, config.debug_mode) + config.plugins = scan_plugins(config) # Set up & start server - database = AgentDB("sqlite:///data/ap_server.db", debug_enabled=False) + database = AgentDB( + database_string=os.getenv("AP_SERVER_DB_URL", "sqlite:///data/ap_server.db"), + debug_enabled=debug, + ) + port: int = int(os.getenv("AP_SERVER_PORT", default=8000)) server = AgentProtocolServer( app_config=config, database=database, llm_provider=llm_provider ) - await server.start() + await server.start(port=port) + + logging.getLogger().info( + f"Total OpenAI session cost: " + f"${round(sum(b.total_cost for b in server._task_budgets.values()), 2)}" + ) def _configure_openai_provider(config: Config) -> OpenAIProvider: @@ -352,19 +386,11 @@ def _configure_openai_provider(config: Config) -> OpenAIProvider: Returns: A configured OpenAIProvider object. """ - if config.openai_api_key is None: + if config.openai_credentials is None: raise RuntimeError("OpenAI key is not configured") openai_settings = OpenAIProvider.default_settings.copy(deep=True) - openai_settings.credentials = ModelProviderCredentials( - api_key=SecretStr(config.openai_api_key), - # TODO: support OpenAI Azure credentials - api_base=SecretStr(config.openai_api_base) if config.openai_api_base else None, - api_type=SecretStr(config.openai_api_type) if config.openai_api_type else None, - api_version=SecretStr(config.openai_api_version) - if config.openai_api_version - else None, - ) + openai_settings.credentials = config.openai_credentials return OpenAIProvider( settings=openai_settings, logger=logging.getLogger("OpenAIProvider"), @@ -410,7 +436,9 @@ async def run_interaction_loop( cycle_budget = cycles_remaining = _get_cycle_budget( legacy_config.continuous_mode, legacy_config.continuous_limit ) - spinner = Spinner("Thinking...", plain_output=legacy_config.plain_output) + spinner = Spinner( + "Thinking...", plain_output=legacy_config.logging.plain_console_output + ) stop_reason = None def graceful_agent_interrupt(signum: int, frame: Optional[FrameType]) -> None: @@ -466,7 +494,7 @@ async def run_interaction_loop( assistant_reply_dict, ) = await agent.propose_action() except InvalidAgentResponseError as e: - logger.warn(f"The agent's thoughts could not be parsed: {e}") + logger.warning(f"The agent's thoughts could not be parsed: {e}") consecutive_failures += 1 if consecutive_failures >= 3: logger.error( @@ -528,7 +556,7 @@ async def run_interaction_loop( extra={"color": Fore.MAGENTA}, ) elif user_feedback == UserFeedback.EXIT: - logger.warn("Exiting...") + logger.warning("Exiting...") exit() else: # user_feedback == UserFeedback.TEXT command_name = "human_feedback" @@ -564,8 +592,9 @@ async def run_interaction_loop( result, extra={"title": "SYSTEM:", "title_color": Fore.YELLOW} ) elif result.status == "error": - logger.warn( - f"Command {command_name} returned an error: {result.error or result.reason}" + logger.warning( + f"Command {command_name} returned an error: " + f"{result.error or result.reason}" ) @@ -652,13 +681,13 @@ async def get_user_feedback( if console_input.lower().strip() == config.authorise_key: user_feedback = UserFeedback.AUTHORIZE elif console_input.lower().strip() == "": - logger.warn("Invalid input format.") + logger.warning("Invalid input format.") elif console_input.lower().startswith(f"{config.authorise_key} -"): try: user_feedback = UserFeedback.AUTHORIZE new_cycles_remaining = abs(int(console_input.split(" ")[1])) except ValueError: - logger.warn( + logger.warning( f"Invalid input format. " f"Please enter '{config.authorise_key} -N'" " where N is the number of continuous tasks." diff --git a/autogpts/autogpt/autogpt/app/setup.py b/autogpts/autogpt/autogpt/app/setup.py index 6410fc9b3..8a271d26f 100644 --- a/autogpts/autogpt/autogpt/app/setup.py +++ b/autogpts/autogpt/autogpt/app/setup.py @@ -12,8 +12,8 @@ logger = logging.getLogger(__name__) def apply_overrides_to_ai_settings( ai_profile: AIProfile, directives: AIDirectives, - override_name: str = "", - override_role: str = "", + override_name: Optional[str] = "", + override_role: Optional[str] = "", replace_directives: bool = False, resources: Optional[list[str]] = None, constraints: Optional[list[str]] = None, @@ -94,7 +94,8 @@ async def interactively_revise_ai_settings( new_constraint = ( await clean_input( app_config, - f"Enter new constraint {i+1} (press enter to keep current, or '-' to remove):", + f"Enter new constraint {i+1}" + " (press enter to keep current, or '-' to remove):", ) or constraint ) @@ -119,7 +120,8 @@ async def interactively_revise_ai_settings( new_resource = ( await clean_input( app_config, - f"Enter new resource {i+1} (press enter to keep current, or '-' to remove):", + f"Enter new resource {i+1}" + " (press enter to keep current, or '-' to remove):", ) or resource ) @@ -144,7 +146,8 @@ async def interactively_revise_ai_settings( new_best_practice = ( await clean_input( app_config, - f"Enter new best practice {i+1} (press enter to keep current, or '-' to remove):", + f"Enter new best practice {i+1}" + " (press enter to keep current, or '-' to remove):", ) or best_practice ) diff --git a/autogpts/autogpt/autogpt/app/utils.py b/autogpts/autogpt/autogpt/app/utils.py index e5fbaa60d..6b21f180d 100644 --- a/autogpts/autogpt/autogpt/app/utils.py +++ b/autogpts/autogpt/autogpt/app/utils.py @@ -5,7 +5,7 @@ import sys import requests from colorama import Fore, Style -from git.repo import Repo +from git import InvalidGitRepositoryError, Repo from prompt_toolkit import ANSI, PromptSession from prompt_toolkit.history import InMemoryHistory @@ -62,7 +62,7 @@ async def clean_input(config: Config, prompt: str = ""): def get_bulletin_from_web(): try: response = requests.get( - "https://raw.githubusercontent.com/Significant-Gravitas/AutoGPT/master/autogpts/autogpt/BULLETIN.md" + "https://raw.githubusercontent.com/Significant-Gravitas/AutoGPT/master/autogpts/autogpt/BULLETIN.md" # noqa: E501 ) if response.status_code == 200: return response.text @@ -77,7 +77,7 @@ def get_current_git_branch() -> str: repo = Repo(search_parent_directories=True) branch = repo.active_branch return branch.name - except: + except InvalidGitRepositoryError: return "" @@ -94,7 +94,7 @@ def get_latest_bulletin() -> tuple[str, bool]: news_header = Fore.YELLOW + "Welcome to AutoGPT!\n" if new_bulletin or current_bulletin: news_header += ( - "Below you'll find the latest AutoGPT News and updates regarding features!\n" + "Below you'll find the latest AutoGPT News and feature updates!\n" "If you don't wish to see this message, you " "can run AutoGPT with the *--skip-news* flag.\n" ) @@ -145,7 +145,7 @@ behalf. You acknowledge that using the System could expose you to potential liab ## Indemnification By using the System, you agree to indemnify, defend, and hold harmless the Project Parties from and against any and all claims, liabilities, damages, losses, or expenses (including reasonable attorneys' fees and costs) arising out of or in connection with your use of the System, including, without limitation, any actions taken by the System on your behalf, any failure to properly supervise or monitor the System, and any resulting harm or unintended consequences. - """ + """ # noqa: E501 return legal_text @@ -174,7 +174,7 @@ def print_motd(config: Config, logger: logging.Logger): def print_git_branch_info(logger: logging.Logger): git_branch = get_current_git_branch() if git_branch and git_branch != "master": - logger.warn( + logger.warning( f"You are running on `{git_branch}` branch" " - this is not a supported branch." ) diff --git a/autogpts/autogpt/autogpt/command_decorator.py b/autogpts/autogpt/autogpt/command_decorator.py index 97e0b5419..70a519a42 100644 --- a/autogpts/autogpt/autogpt/command_decorator.py +++ b/autogpts/autogpt/autogpt/command_decorator.py @@ -27,7 +27,9 @@ def command( aliases: list[str] = [], available: Literal[True] | Callable[[BaseAgent], bool] = True, ) -> Callable[[Callable[P, CO]], Callable[P, CO]]: - """The command decorator is used to create Command objects from ordinary functions.""" + """ + The command decorator is used to create Command objects from ordinary functions. + """ def decorator(func: Callable[P, CO]) -> Callable[P, CO]: typed_parameters = [ diff --git a/autogpts/autogpt/autogpt/commands/decorators.py b/autogpts/autogpt/autogpt/commands/decorators.py index afd447614..39793a25a 100644 --- a/autogpts/autogpt/autogpt/commands/decorators.py +++ b/autogpts/autogpt/autogpt/commands/decorators.py @@ -23,7 +23,8 @@ def sanitize_path_arg( arg_index = list(func.__annotations__.keys()).index(arg_name) except ValueError: raise TypeError( - f"Sanitized parameter '{arg_name}' absent or not annotated on function '{func.__name__}'" + f"Sanitized parameter '{arg_name}' absent or not annotated" + f" on function '{func.__name__}'" ) # Get position of agent parameter, in case it is passed as a positional argument @@ -31,7 +32,8 @@ def sanitize_path_arg( agent_arg_index = list(func.__annotations__.keys()).index("agent") except ValueError: raise TypeError( - f"Parameter 'agent' absent or not annotated on function '{func.__name__}'" + f"Parameter 'agent' absent or not annotated" + f" on function '{func.__name__}'" ) @functools.wraps(func) diff --git a/autogpts/autogpt/autogpt/commands/execute_code.py b/autogpts/autogpt/autogpt/commands/execute_code.py index a5b48a7f1..93bfd53d4 100644 --- a/autogpts/autogpt/autogpt/commands/execute_code.py +++ b/autogpts/autogpt/autogpt/commands/execute_code.py @@ -1,8 +1,5 @@ """Commands to execute code""" -COMMAND_CATEGORY = "execute_code" -COMMAND_CATEGORY_TITLE = "Execute Code" - import logging import os import subprocess @@ -26,6 +23,10 @@ from autogpt.core.utils.json_schema import JSONSchema from .decorators import sanitize_path_arg +COMMAND_CATEGORY = "execute_code" +COMMAND_CATEGORY_TITLE = "Execute Code" + + logger = logging.getLogger(__name__) ALLOWLIST_CONTROL = "allowlist" @@ -45,15 +46,18 @@ DENYLIST_CONTROL = "denylist" }, ) def execute_python_code(code: str, agent: Agent) -> str: - """Create and execute a Python file in a Docker container and return the STDOUT of the - executed code. If there is any data that needs to be captured use a print statement + """ + Create and execute a Python file in a Docker container and return the STDOUT of the + executed code. + + If the code generates any data that needs to be captured, use a print statement. Args: - code (str): The Python code to run - name (str): A name to be given to the Python file + code (str): The Python code to run. + agent (Agent): The Agent executing the command. Returns: - str: The STDOUT captured from the code when it ran + str: The STDOUT captured from the code when it ran. """ tmp_code_file = NamedTemporaryFile( @@ -63,7 +67,7 @@ def execute_python_code(code: str, agent: Agent) -> str: tmp_code_file.flush() try: - return execute_python_file(tmp_code_file.name, agent) + return execute_python_file(tmp_code_file.name, agent) # type: ignore except Exception as e: raise CommandExecutionError(*e.args) finally: @@ -102,7 +106,8 @@ def execute_python_file( str: The output of the file """ logger.info( - f"Executing python file '{filename}' in working directory '{agent.workspace.root}'" + f"Executing python file '{filename}' " + f"in working directory '{agent.workspace.root}'" ) if isinstance(args, str): @@ -113,14 +118,16 @@ def execute_python_file( file_path = filename if not file_path.is_file(): - # Mimic the response that you get from the command line so that it's easier to identify + # Mimic the response that you get from the command line to make it + # intuitively understandable for the LLM raise FileNotFoundError( f"python: can't open file '{filename}': [Errno 2] No such file or directory" ) if we_are_running_in_a_docker_container(): logger.debug( - f"AutoGPT is running in a Docker container; executing {file_path} directly..." + "AutoGPT is running in a Docker container; " + f"executing {file_path} directly..." ) result = subprocess.run( ["python", "-B", str(file_path)] + args, @@ -145,14 +152,17 @@ def execute_python_file( container_is_fresh = False container_name = f"{agent.state.agent_id}_sandbox" try: - container: DockerContainer = client.containers.get(container_name) # type: ignore + container: DockerContainer = client.containers.get( + container_name + ) # type: ignore except NotFound: try: client.images.get(image_name) logger.debug(f"Image '{image_name}' found locally") except ImageNotFound: logger.info( - f"Image '{image_name}' not found locally, pulling from Docker Hub..." + f"Image '{image_name}' not found locally," + " pulling from Docker Hub..." ) # Use the low-level API to stream the pull response low_level_client = docker.APIClient() @@ -206,8 +216,10 @@ def execute_python_file( return exec_result.output.decode("utf-8") except DockerException as e: - logger.warn( - "Could not run the script in a container. If you haven't already, please install Docker https://docs.docker.com/get-docker/" + logger.warning( + "Could not run the script in a container. " + "If you haven't already, please install Docker: " + "https://docs.docker.com/get-docker/" ) raise CommandExecutionError(f"Could not run the script in a container: {e}") diff --git a/autogpts/autogpt/autogpt/commands/file_context.py b/autogpts/autogpt/autogpt/commands/file_context.py index db49ea128..004ed1039 100644 --- a/autogpts/autogpt/autogpt/commands/file_context.py +++ b/autogpts/autogpt/autogpt/commands/file_context.py @@ -2,16 +2,10 @@ from __future__ import annotations -COMMAND_CATEGORY = "file_operations" -COMMAND_CATEGORY_TITLE = "File Operations" - import contextlib from pathlib import Path from typing import TYPE_CHECKING -if TYPE_CHECKING: - from autogpt.agents import Agent, BaseAgent - from autogpt.agents.features.context import ContextMixin, get_agent_context from autogpt.agents.utils.exceptions import ( CommandExecutionError, @@ -23,6 +17,13 @@ from autogpt.models.context_item import FileContextItem, FolderContextItem from .decorators import sanitize_path_arg +COMMAND_CATEGORY = "file_operations" +COMMAND_CATEGORY_TITLE = "File Operations" + + +if TYPE_CHECKING: + from autogpt.agents import Agent, BaseAgent + def agent_implements_context(agent: BaseAgent) -> bool: return isinstance(agent, ContextMixin) @@ -30,8 +31,9 @@ def agent_implements_context(agent: BaseAgent) -> bool: @command( "open_file", - "Open a file for editing or continued viewing; create it if it does not exist yet." - " Note: if you only need to read or write a file once, use `write_to_file` instead.", + "Opens a file for editing or continued viewing;" + " creates it if it does not exist yet. " + "Note: If you only need to read or write a file once, use `write_to_file` instead.", { "file_path": JSONSchema( type=JSONSchema.Type.STRING, @@ -76,7 +78,8 @@ def open_file(file_path: Path, agent: Agent) -> tuple[str, FileContextItem]: raise DuplicateOperationError(f"The file {file_path} is already open") return ( - f"File {file_path}{' created,' if created else ''} has been opened and added to the context ✅", + f"File {file_path}{' created,' if created else ''} has been opened" + " and added to the context ✅", file, ) diff --git a/autogpts/autogpt/autogpt/commands/file_operations.py b/autogpts/autogpt/autogpt/commands/file_operations.py index 29935dc87..29c92b346 100644 --- a/autogpts/autogpt/autogpt/commands/file_operations.py +++ b/autogpts/autogpt/autogpt/commands/file_operations.py @@ -2,10 +2,6 @@ from __future__ import annotations -COMMAND_CATEGORY = "file_operations" -COMMAND_CATEGORY_TITLE = "File Operations" - -import contextlib import hashlib import logging import os @@ -17,11 +13,16 @@ from autogpt.agents.agent import Agent from autogpt.agents.utils.exceptions import DuplicateOperationError from autogpt.command_decorator import command from autogpt.core.utils.json_schema import JSONSchema -from autogpt.memory.vector import MemoryItem, VectorMemory +from autogpt.memory.vector import MemoryItemFactory, VectorMemory from .decorators import sanitize_path_arg +from .file_operations_utils import decode_textual_file + +COMMAND_CATEGORY = "file_operations" +COMMAND_CATEGORY_TITLE = "File Operations" + + from .file_context import open_file, open_folder # NOQA -from .file_operations_utils import read_textual_file logger = logging.getLogger(__name__) @@ -82,7 +83,7 @@ def file_operations_state(log_path: str | Path) -> dict[str, str]: return state -@sanitize_path_arg("file_path") +@sanitize_path_arg("file_path", make_relative=True) def is_duplicate_operation( operation: Operation, file_path: Path, agent: Agent, checksum: str | None = None ) -> bool: @@ -97,10 +98,6 @@ def is_duplicate_operation( Returns: True if the operation has already been performed on the file """ - # Make the file path into a relative path if possible - with contextlib.suppress(ValueError): - file_path = file_path.relative_to(agent.workspace.root) - state = file_operations_state(agent.file_manager.file_ops_log_path) if operation == "delete" and str(file_path) not in state: return True @@ -109,9 +106,12 @@ def is_duplicate_operation( return False -@sanitize_path_arg("file_path") +@sanitize_path_arg("file_path", make_relative=True) def log_operation( - operation: Operation, file_path: Path, agent: Agent, checksum: str | None = None + operation: Operation, + file_path: str | Path, + agent: Agent, + checksum: str | None = None, ) -> None: """Log the file operation to the file_logger.log @@ -120,10 +120,6 @@ def log_operation( file_path: The name of the file the operation was performed on checksum: The checksum of the contents to be written """ - # Make the file path into a relative path if possible - with contextlib.suppress(ValueError): - file_path = file_path.relative_to(agent.workspace.root) - log_entry = f"{operation}: {file_path}" if checksum is not None: log_entry += f" #{checksum}" @@ -144,8 +140,7 @@ def log_operation( ) }, ) -@sanitize_path_arg("filename") -def read_file(filename: Path, agent: Agent) -> str: +def read_file(filename: str | Path, agent: Agent) -> str: """Read a file and return the contents Args: @@ -154,8 +149,8 @@ def read_file(filename: Path, agent: Agent) -> str: Returns: str: The contents of the file """ - content = read_textual_file(filename, logger) - # TODO: content = agent.workspace.read_file(filename) + file = agent.workspace.open_file(filename, binary=True) + content = decode_textual_file(file, os.path.splitext(filename)[1], logger) # # TODO: invalidate/update memory when file is edited # file_memory = MemoryItem.from_text_file(content, str(filename), agent.config) @@ -182,13 +177,13 @@ def ingest_file( content = read_file(filename) # TODO: differentiate between different types of files - file_memory = MemoryItem.from_text_file(content, filename) + file_memory = MemoryItemFactory.from_text_file(content, filename) logger.debug(f"Created memory: {file_memory.dump(True)}") memory.add(file_memory) logger.info(f"Ingested {len(file_memory.e_chunks)} chunks from {filename}") except Exception as err: - logger.warn(f"Error while ingesting file '{filename}': {err}") + logger.warning(f"Error while ingesting file '{filename}': {err}") @command( @@ -208,8 +203,7 @@ def ingest_file( }, aliases=["create_file"], ) -@sanitize_path_arg("filename") -async def write_to_file(filename: Path, contents: str, agent: Agent) -> str: +async def write_to_file(filename: str | Path, contents: str, agent: Agent) -> str: """Write contents to a file Args: @@ -220,14 +214,14 @@ async def write_to_file(filename: Path, contents: str, agent: Agent) -> str: str: A message indicating success or failure """ checksum = text_checksum(contents) - if is_duplicate_operation("write", filename, agent, checksum): - raise DuplicateOperationError(f"File {filename.name} has already been updated.") + if is_duplicate_operation("write", Path(filename), agent, checksum): + raise DuplicateOperationError(f"File {filename} has already been updated.") - directory = os.path.dirname(filename) - os.makedirs(directory, exist_ok=True) + if directory := os.path.dirname(filename): + agent.workspace.get_path(directory).mkdir(exist_ok=True) await agent.workspace.write_file(filename, contents) log_operation("write", filename, agent, checksum) - return f"File {filename.name} has been written successfully." + return f"File {filename} has been written successfully." def append_to_file( @@ -262,8 +256,7 @@ def append_to_file( ) }, ) -@sanitize_path_arg("folder") -def list_folder(folder: Path, agent: Agent) -> list[str]: +def list_folder(folder: str | Path, agent: Agent) -> list[str]: """Lists files in a folder recursively Args: @@ -272,15 +265,4 @@ def list_folder(folder: Path, agent: Agent) -> list[str]: Returns: list[str]: A list of files found in the folder """ - found_files = [] - - for root, _, files in os.walk(folder): - for file in files: - if file.startswith("."): - continue - relative_path = os.path.relpath( - os.path.join(root, file), agent.workspace.root - ) - found_files.append(relative_path) - - return found_files + return [str(p) for p in agent.workspace.list(folder)] diff --git a/autogpts/autogpt/autogpt/commands/file_operations_utils.py b/autogpts/autogpt/autogpt/commands/file_operations_utils.py index bbf3706aa..da65bafaa 100644 --- a/autogpts/autogpt/autogpt/commands/file_operations_utils.py +++ b/autogpts/autogpt/autogpt/commands/file_operations_utils.py @@ -1,12 +1,11 @@ import json import logging -import os -from pathlib import Path +from abc import ABC, abstractmethod +from typing import BinaryIO import charset_normalizer import docx -import markdown -import PyPDF2 +import pypdf import yaml from bs4 import BeautifulSoup from pylatexenc.latex2text import LatexNodes2Text @@ -14,23 +13,27 @@ from pylatexenc.latex2text import LatexNodes2Text logger = logging.getLogger(__name__) -class ParserStrategy: - def read(self, file_path: Path) -> str: - raise NotImplementedError +class ParserStrategy(ABC): + @abstractmethod + def read(self, file: BinaryIO) -> str: + ... # Basic text file reading class TXTParser(ParserStrategy): - def read(self, file_path: Path) -> str: - charset_match = charset_normalizer.from_path(file_path).best() - logger.debug(f"Reading '{file_path}' with encoding '{charset_match.encoding}'") + def read(self, file: BinaryIO) -> str: + charset_match = charset_normalizer.from_bytes(file.read()).best() + logger.debug( + f"Reading {getattr(file, 'name', 'file')} " + f"with encoding '{charset_match.encoding}'" + ) return str(charset_match) # Reading text from binary file using pdf parser class PDFParser(ParserStrategy): - def read(self, file_path: Path) -> str: - parser = PyPDF2.PdfReader(file_path) + def read(self, file: BinaryIO) -> str: + parser = pypdf.PdfReader(file) text = "" for page_idx in range(len(parser.pages)): text += parser.pages[page_idx].extract_text() @@ -39,8 +42,8 @@ class PDFParser(ParserStrategy): # Reading text from binary file using docs parser class DOCXParser(ParserStrategy): - def read(self, file_path: Path) -> str: - doc_file = docx.Document(file_path) + def read(self, file: BinaryIO) -> str: + doc_file = docx.Document(file) text = "" for para in doc_file.paragraphs: text += para.text @@ -49,50 +52,37 @@ class DOCXParser(ParserStrategy): # Reading as dictionary and returning string format class JSONParser(ParserStrategy): - def read(self, file_path: Path) -> str: - with open(file_path, "r") as f: - data = json.load(f) - text = str(data) + def read(self, file: BinaryIO) -> str: + data = json.load(file) + text = str(data) return text class XMLParser(ParserStrategy): - def read(self, file_path: Path) -> str: - with open(file_path, "r") as f: - soup = BeautifulSoup(f, "xml") - text = soup.get_text() + def read(self, file: BinaryIO) -> str: + soup = BeautifulSoup(file, "xml") + text = soup.get_text() return text # Reading as dictionary and returning string format class YAMLParser(ParserStrategy): - def read(self, file_path: Path) -> str: - with open(file_path, "r") as f: - data = yaml.load(f, Loader=yaml.FullLoader) - text = str(data) + def read(self, file: BinaryIO) -> str: + data = yaml.load(file, Loader=yaml.FullLoader) + text = str(data) return text class HTMLParser(ParserStrategy): - def read(self, file_path: Path) -> str: - with open(file_path, "r") as f: - soup = BeautifulSoup(f, "html.parser") - text = soup.get_text() - return text - - -class MarkdownParser(ParserStrategy): - def read(self, file_path: Path) -> str: - with open(file_path, "r") as f: - html = markdown.markdown(f.read()) - text = "".join(BeautifulSoup(html, "html.parser").findAll(string=True)) + def read(self, file: BinaryIO) -> str: + soup = BeautifulSoup(file, "html.parser") + text = soup.get_text() return text class LaTeXParser(ParserStrategy): - def read(self, file_path: Path) -> str: - with open(file_path, "r") as f: - latex = f.read() + def read(self, file: BinaryIO) -> str: + latex = file.read().decode() text = LatexNodes2Text().latex_to_text(latex) return text @@ -106,13 +96,17 @@ class FileContext: self.logger.debug(f"Setting Context Parser to {parser}") self.parser = parser - def read_file(self, file_path) -> str: - self.logger.debug(f"Reading file {file_path} with parser {self.parser}") - return self.parser.read(file_path) + def decode_file(self, file: BinaryIO) -> str: + self.logger.debug( + f"Reading {getattr(file, 'name', 'file')} with parser {self.parser}" + ) + return self.parser.read(file) extension_to_parser = { ".txt": TXTParser(), + ".md": TXTParser(), + ".markdown": TXTParser(), ".csv": TXTParser(), ".pdf": PDFParser(), ".docx": DOCXParser(), @@ -123,47 +117,35 @@ extension_to_parser = { ".html": HTMLParser(), ".htm": HTMLParser(), ".xhtml": HTMLParser(), - ".md": MarkdownParser(), - ".markdown": MarkdownParser(), ".tex": LaTeXParser(), } -def is_file_binary_fn(file_path: Path): +def is_file_binary_fn(file: BinaryIO): """Given a file path load all its content and checks if the null bytes is present Args: - file_path (_type_): _description_ + file (_type_): _description_ Returns: bool: is_binary """ - with open(file_path, "rb") as f: - file_data = f.read() + file_data = file.read() + file.seek(0) if b"\x00" in file_data: return True return False -def read_textual_file(file_path: Path, logger: logging.Logger) -> str: - if not file_path.is_absolute(): - raise ValueError("File path must be absolute") - - if not file_path.is_file(): - if not file_path.exists(): - raise FileNotFoundError( - f"read_file {file_path} failed: no such file or directory" - ) - else: - raise ValueError(f"read_file failed: {file_path} is not a file") +def decode_textual_file(file: BinaryIO, ext: str, logger: logging.Logger) -> str: + if not file.readable(): + raise ValueError(f"{repr(file)} is not readable") - is_binary = is_file_binary_fn(file_path) - file_extension = os.path.splitext(file_path)[1].lower() - parser = extension_to_parser.get(file_extension) + parser = extension_to_parser.get(ext.lower()) if not parser: - if is_binary: - raise ValueError(f"Unsupported binary file format: {file_extension}") + if is_file_binary_fn(file): + raise ValueError(f"Unsupported binary file format: {ext}") # fallback to txt file parser (to support script and code files loading) parser = TXTParser() file_context = FileContext(parser, logger) - return file_context.read_file(file_path) + return file_context.decode_file(file) diff --git a/autogpts/autogpt/autogpt/commands/git_operations.py b/autogpts/autogpt/autogpt/commands/git_operations.py index bc8abc13f..01930e420 100644 --- a/autogpts/autogpt/autogpt/commands/git_operations.py +++ b/autogpts/autogpt/autogpt/commands/git_operations.py @@ -1,8 +1,5 @@ """Commands to perform Git operations""" -COMMAND_CATEGORY = "git_operations" -COMMAND_CATEGORY_TITLE = "Git Operations" - from pathlib import Path from git.repo import Repo @@ -15,6 +12,9 @@ from autogpt.url_utils.validators import validate_url from .decorators import sanitize_path_arg +COMMAND_CATEGORY = "git_operations" +COMMAND_CATEGORY_TITLE = "Git Operations" + @command( "clone_repository", @@ -47,7 +47,7 @@ def clone_repository(url: str, clone_path: Path, agent: Agent) -> str: str: The result of the clone operation. """ split_url = url.split("//") - auth_repo_url = f"//{agent.legacy_config.github_username}:{agent.legacy_config.github_api_key}@".join( + auth_repo_url = f"//{agent.legacy_config.github_username}:{agent.legacy_config.github_api_key}@".join( # noqa: E501 split_url ) try: diff --git a/autogpts/autogpt/autogpt/commands/image_gen.py b/autogpts/autogpt/autogpt/commands/image_gen.py index ba771635f..957c2ac5a 100644 --- a/autogpts/autogpt/autogpt/commands/image_gen.py +++ b/autogpts/autogpt/autogpt/commands/image_gen.py @@ -1,23 +1,25 @@ """Commands to generate images based on text input""" -COMMAND_CATEGORY = "text_to_image" -COMMAND_CATEGORY_TITLE = "Text to Image" - import io import json import logging import time import uuid from base64 import b64decode +from pathlib import Path -import openai import requests +from openai import OpenAI from PIL import Image from autogpt.agents.agent import Agent from autogpt.command_decorator import command from autogpt.core.utils.json_schema import JSONSchema +COMMAND_CATEGORY = "text_to_image" +COMMAND_CATEGORY_TITLE = "Text to Image" + + logger = logging.getLogger(__name__) @@ -39,7 +41,8 @@ def generate_image(prompt: str, agent: Agent, size: int = 256) -> str: Args: prompt (str): The prompt to use - size (int, optional): The size of the image. Defaults to 256. (Not supported by HuggingFace) + size (int, optional): The size of the image. Defaults to 256. + Not supported by HuggingFace. Returns: str: The filename of the image @@ -58,17 +61,17 @@ def generate_image(prompt: str, agent: Agent, size: int = 256) -> str: return "No Image Provider Set" -def generate_image_with_hf(prompt: str, filename: str, agent: Agent) -> str: +def generate_image_with_hf(prompt: str, output_file: Path, agent: Agent) -> str: """Generate an image with HuggingFace's API. Args: prompt (str): The prompt to use - filename (str): The filename to save the image to + filename (Path): The filename to save the image to Returns: str: The filename of the image """ - API_URL = f"https://api-inference.huggingface.co/models/{agent.legacy_config.huggingface_image_model}" + API_URL = f"https://api-inference.huggingface.co/models/{agent.legacy_config.huggingface_image_model}" # noqa: E501 if agent.legacy_config.huggingface_api_token is None: raise ValueError( "You need to set your Hugging Face API token in the config file." @@ -92,8 +95,8 @@ def generate_image_with_hf(prompt: str, filename: str, agent: Agent) -> str: try: image = Image.open(io.BytesIO(response.content)) logger.info(f"Image Generated for prompt:{prompt}") - image.save(filename) - return f"Saved to disk:{filename}" + image.save(output_file) + return f"Saved to disk: {output_file}" except Exception as e: logger.error(e) break @@ -113,17 +116,17 @@ def generate_image_with_hf(prompt: str, filename: str, agent: Agent) -> str: retry_count += 1 - return f"Error creating image." + return "Error creating image." def generate_image_with_dalle( - prompt: str, filename: str, size: int, agent: Agent + prompt: str, output_file: Path, size: int, agent: Agent ) -> str: """Generate an image with DALL-E. Args: prompt (str): The prompt to use - filename (str): The filename to save the image to + filename (Path): The filename to save the image to size (int): The size of the image Returns: @@ -134,31 +137,33 @@ def generate_image_with_dalle( if size not in [256, 512, 1024]: closest = min([256, 512, 1024], key=lambda x: abs(x - size)) logger.info( - f"DALL-E only supports image sizes of 256x256, 512x512, or 1024x1024. Setting to {closest}, was {size}." + "DALL-E only supports image sizes of 256x256, 512x512, or 1024x1024. " + f"Setting to {closest}, was {size}." ) size = closest - response = openai.Image.create( + response = OpenAI( + api_key=agent.legacy_config.openai_credentials.api_key.get_secret_value() + ).images.generate( prompt=prompt, n=1, size=f"{size}x{size}", response_format="b64_json", - api_key=agent.legacy_config.openai_api_key, ) logger.info(f"Image Generated for prompt:{prompt}") - image_data = b64decode(response["data"][0]["b64_json"]) + image_data = b64decode(response.data[0].b64_json) - with open(filename, mode="wb") as png: + with open(output_file, mode="wb") as png: png.write(image_data) - return f"Saved to disk:{filename}" + return f"Saved to disk: {output_file}" def generate_image_with_sd_webui( prompt: str, - filename: str, + output_file: Path, agent: Agent, size: int = 512, negative_prompt: str = "", @@ -196,12 +201,12 @@ def generate_image_with_sd_webui( }, ) - logger.info(f"Image Generated for prompt:{prompt}") + logger.info(f"Image Generated for prompt: '{prompt}'") # Save the image to disk response = response.json() b64 = b64decode(response["images"][0].split(",", 1)[0]) image = Image.open(io.BytesIO(b64)) - image.save(filename) + image.save(output_file) - return f"Saved to disk:{filename}" + return f"Saved to disk: {output_file}" diff --git a/autogpts/autogpt/autogpt/commands/system.py b/autogpts/autogpt/autogpt/commands/system.py index f484d700d..bd184122f 100644 --- a/autogpts/autogpt/autogpt/commands/system.py +++ b/autogpts/autogpt/autogpt/commands/system.py @@ -2,20 +2,22 @@ from __future__ import annotations -COMMAND_CATEGORY = "system" -COMMAND_CATEGORY_TITLE = "System" - import logging from typing import TYPE_CHECKING -if TYPE_CHECKING: - from autogpt.agents.agent import Agent - from autogpt.agents.features.context import get_agent_context from autogpt.agents.utils.exceptions import AgentTerminated, InvalidArgumentError from autogpt.command_decorator import command from autogpt.core.utils.json_schema import JSONSchema +COMMAND_CATEGORY = "system" +COMMAND_CATEGORY_TITLE = "System" + + +if TYPE_CHECKING: + from autogpt.agents.agent import Agent + + logger = logging.getLogger(__name__) diff --git a/autogpts/autogpt/autogpt/commands/user_interaction.py b/autogpts/autogpt/autogpt/commands/user_interaction.py index bb5055fd6..c53213c7f 100644 --- a/autogpts/autogpt/autogpt/commands/user_interaction.py +++ b/autogpts/autogpt/autogpt/commands/user_interaction.py @@ -2,14 +2,14 @@ from __future__ import annotations -COMMAND_CATEGORY = "user_interaction" -COMMAND_CATEGORY_TITLE = "User Interaction" - from autogpt.agents.agent import Agent from autogpt.app.utils import clean_input from autogpt.command_decorator import command from autogpt.core.utils.json_schema import JSONSchema +COMMAND_CATEGORY = "user_interaction" +COMMAND_CATEGORY_TITLE = "User Interaction" + @command( "ask_user", diff --git a/autogpts/autogpt/autogpt/commands/web_search.py b/autogpts/autogpt/autogpt/commands/web_search.py index c4411d936..e39bfffc6 100644 --- a/autogpts/autogpt/autogpt/commands/web_search.py +++ b/autogpts/autogpt/autogpt/commands/web_search.py @@ -2,9 +2,6 @@ from __future__ import annotations -COMMAND_CATEGORY = "web_search" -COMMAND_CATEGORY_TITLE = "Web Search" - import json import time from itertools import islice @@ -16,6 +13,10 @@ from autogpt.agents.utils.exceptions import ConfigurationError from autogpt.command_decorator import command from autogpt.core.utils.json_schema import JSONSchema +COMMAND_CATEGORY = "web_search" +COMMAND_CATEGORY_TITLE = "Web Search" + + DUCKDUCKGO_MAX_ATTEMPTS = 3 diff --git a/autogpts/autogpt/autogpt/commands/web_selenium.py b/autogpts/autogpt/autogpt/commands/web_selenium.py index a60dd911e..57f650fb9 100644 --- a/autogpts/autogpt/autogpt/commands/web_selenium.py +++ b/autogpts/autogpt/autogpt/commands/web_selenium.py @@ -2,9 +2,6 @@ from __future__ import annotations -COMMAND_CATEGORY = "web_browse" -COMMAND_CATEGORY_TITLE = "Web Browsing" - import logging import re from pathlib import Path @@ -33,10 +30,6 @@ from webdriver_manager.chrome import ChromeDriverManager from webdriver_manager.firefox import GeckoDriverManager from webdriver_manager.microsoft import EdgeChromiumDriverManager as EdgeDriverManager -if TYPE_CHECKING: - from autogpt.config import Config - from autogpt.agents.agent import Agent - from autogpt.agents.utils.exceptions import CommandExecutionError from autogpt.command_decorator import command from autogpt.core.utils.json_schema import JSONSchema @@ -44,6 +37,15 @@ from autogpt.processing.html import extract_hyperlinks, format_hyperlinks from autogpt.processing.text import summarize_text from autogpt.url_utils.validators import validate_url +COMMAND_CATEGORY = "web_browse" +COMMAND_CATEGORY_TITLE = "Web Browsing" + + +if TYPE_CHECKING: + from autogpt.agents.agent import Agent + from autogpt.config import Config + + logger = logging.getLogger(__name__) FILE_DIR = Path(__file__).parent.parent @@ -57,9 +59,12 @@ class BrowsingError(CommandExecutionError): @command( "read_webpage", - "Read a webpage, and extract specific information from it if a question is specified." - " If you are looking to extract specific information from the webpage, you should" - " specify a question.", + ( + "Read a webpage, and extract specific information from it" + " if a question is specified." + " If you are looking to extract specific information from the webpage," + " you should specify a question." + ), { "url": JSONSchema( type=JSONSchema.Type.STRING, @@ -68,7 +73,9 @@ class BrowsingError(CommandExecutionError): ), "question": JSONSchema( type=JSONSchema.Type.STRING, - description="A question that you want to answer using the content of the webpage.", + description=( + "A question that you want to answer using the content of the webpage." + ), required=False, ), }, @@ -124,8 +131,8 @@ async def read_webpage(url: str, agent: Agent, question: str = "") -> str: msg = e.msg.split("\n")[0] if "net::" in msg: raise BrowsingError( - f"A networking error occurred while trying to load the page: " - + re.sub(r"^unknown error: ", "", msg) + "A networking error occurred while trying to load the page: %s" + % re.sub(r"^unknown error: ", "", msg) ) raise CommandExecutionError(msg) finally: @@ -198,9 +205,7 @@ def open_page_in_browser(url: str, config: Config) -> WebDriver: } options: BrowserOptions = options_available[config.selenium_web_browser]() - options.add_argument( - "user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.5615.49 Safari/537.36" - ) + options.add_argument(f"user-agent={config.user_agent}") if config.selenium_web_browser == "firefox": if config.selenium_headless: @@ -214,8 +219,8 @@ def open_page_in_browser(url: str, config: Config) -> WebDriver: service=EdgeDriverService(EdgeDriverManager().install()), options=options ) elif config.selenium_web_browser == "safari": - # Requires a bit more setup on the users end - # See https://developer.apple.com/documentation/webkit/testing_with_webdriver_in_safari + # Requires a bit more setup on the users end. + # See https://developer.apple.com/documentation/webkit/testing_with_webdriver_in_safari # noqa: E501 driver = SafariDriver(options=options) else: if platform == "linux" or platform == "linux2": @@ -282,7 +287,12 @@ async def summarize_memorize_webpage( # memory = get_memory(agent.legacy_config) - # new_memory = MemoryItem.from_webpage(text, url, agent.legacy_config, question=question) + # new_memory = MemoryItem.from_webpage( + # content=text, + # url=url, + # config=agent.legacy_config, + # question=question, + # ) # memory.add(new_memory) summary, _ = await summarize_text( diff --git a/autogpts/autogpt/autogpt/config/ai_profile.py b/autogpts/autogpt/autogpt/config/ai_profile.py index ac4e3e591..970f8278c 100644 --- a/autogpts/autogpt/autogpt/config/ai_profile.py +++ b/autogpts/autogpt/autogpt/config/ai_profile.py @@ -24,7 +24,7 @@ class AIProfile(BaseModel): def load(ai_settings_file: str | Path) -> "AIProfile": """ Returns class object with parameters (ai_name, ai_role, ai_goals, api_budget) - loaded from yaml file if yaml file exists, else returns class with no parameters. + loaded from yaml file if it exists, else returns class with no parameters. Parameters: ai_settings_file (Path): The path to the config yaml file. diff --git a/autogpts/autogpt/autogpt/config/config.py b/autogpts/autogpt/autogpt/config/config.py index 871479e88..ff0053a76 100644 --- a/autogpts/autogpt/autogpt/config/config.py +++ b/autogpts/autogpt/autogpt/config/config.py @@ -1,20 +1,27 @@ """Configuration class to store the state of bools for different scripts access.""" from __future__ import annotations -import contextlib import os import re from pathlib import Path -from typing import Any, Dict, Optional, Union +from typing import Any, Optional, Union -import yaml from auto_gpt_plugin_template import AutoGPTPluginTemplate from colorama import Fore -from pydantic import Field, validator +from pydantic import Field, SecretStr, validator import autogpt -from autogpt.core.configuration.schema import Configurable, SystemSettings -from autogpt.core.resource.model_providers.openai import OPEN_AI_CHAT_MODELS +from autogpt.core.configuration.schema import ( + Configurable, + SystemSettings, + UserConfigurable, +) +from autogpt.core.resource.model_providers.openai import ( + OPEN_AI_CHAT_MODELS, + OpenAICredentials, +) +from autogpt.file_workspace import FileWorkspaceBackendName +from autogpt.logs.config import LoggingConfig from autogpt.plugins.plugins_config import PluginsConfig from autogpt.speech import TTSConfig @@ -31,6 +38,7 @@ GPT_3_MODEL = "gpt-3.5-turbo" class Config(SystemSettings, arbitrary_types_allowed=True): name: str = "Auto-GPT configuration" description: str = "Default configuration for the Auto-GPT application." + ######################## # Application Settings # ######################## @@ -38,28 +46,61 @@ class Config(SystemSettings, arbitrary_types_allowed=True): app_data_dir: Path = project_root / "data" skip_news: bool = False skip_reprompt: bool = False - authorise_key: str = "y" - exit_key: str = "n" - debug_mode: bool = False - plain_output: bool = False + authorise_key: str = UserConfigurable(default="y", from_env="AUTHORISE_COMMAND_KEY") + exit_key: str = UserConfigurable(default="n", from_env="EXIT_KEY") noninteractive_mode: bool = False - chat_messages_enabled: bool = True + chat_messages_enabled: bool = UserConfigurable( + default=True, from_env=lambda: os.getenv("CHAT_MESSAGES_ENABLED") == "True" + ) + # TTS configuration tts_config: TTSConfig = TTSConfig() + logging: LoggingConfig = LoggingConfig() + + # Workspace + workspace_backend: FileWorkspaceBackendName = UserConfigurable( + default=FileWorkspaceBackendName.LOCAL, + from_env=lambda: FileWorkspaceBackendName(v) + if (v := os.getenv("WORKSPACE_BACKEND")) + else None, + ) ########################## # Agent Control Settings # ########################## # Paths - ai_settings_file: Path = project_root / AI_SETTINGS_FILE - prompt_settings_file: Path = project_root / PROMPT_SETTINGS_FILE + ai_settings_file: Path = UserConfigurable( + default=AI_SETTINGS_FILE, + from_env=lambda: Path(f) if (f := os.getenv("AI_SETTINGS_FILE")) else None, + ) + prompt_settings_file: Path = UserConfigurable( + default=PROMPT_SETTINGS_FILE, + from_env=lambda: Path(f) if (f := os.getenv("PROMPT_SETTINGS_FILE")) else None, + ) + # Model configuration - fast_llm: str = "gpt-3.5-turbo-16k" - smart_llm: str = "gpt-4" - temperature: float = 0 - openai_functions: bool = False - embedding_model: str = "text-embedding-ada-002" - browse_spacy_language_model: str = "en_core_web_sm" + fast_llm: str = UserConfigurable( + default="gpt-3.5-turbo-16k", + from_env=lambda: os.getenv("FAST_LLM"), + ) + smart_llm: str = UserConfigurable( + default="gpt-4", + from_env=lambda: os.getenv("SMART_LLM"), + ) + temperature: float = UserConfigurable( + default=0, + from_env=lambda: float(v) if (v := os.getenv("TEMPERATURE")) else None, + ) + openai_functions: bool = UserConfigurable( + default=False, from_env=lambda: os.getenv("OPENAI_FUNCTIONS", "False") == "True" + ) + embedding_model: str = UserConfigurable( + default="text-embedding-ada-002", from_env="EMBEDDING_MODEL" + ) + browse_spacy_language_model: str = UserConfigurable( + default="en_core_web_sm", from_env="BROWSE_SPACY_LANGUAGE_MODEL" + ) + # Run loop configuration continuous_mode: bool = False continuous_limit: int = 0 @@ -67,74 +108,138 @@ class Config(SystemSettings, arbitrary_types_allowed=True): ########## # Memory # ########## - memory_backend: str = "json_file" - memory_index: str = "auto-gpt-memory" - redis_host: str = "localhost" - redis_port: int = 6379 - redis_password: str = "" - wipe_redis_on_start: bool = True + memory_backend: str = UserConfigurable("json_file", from_env="MEMORY_BACKEND") + memory_index: str = UserConfigurable("auto-gpt-memory", from_env="MEMORY_INDEX") + redis_host: str = UserConfigurable("localhost", from_env="REDIS_HOST") + redis_port: int = UserConfigurable( + default=6379, + from_env=lambda: int(v) if (v := os.getenv("REDIS_PORT")) else None, + ) + redis_password: str = UserConfigurable("", from_env="REDIS_PASSWORD") + wipe_redis_on_start: bool = UserConfigurable( + default=True, + from_env=lambda: os.getenv("WIPE_REDIS_ON_START", "True") == "True", + ) ############ # Commands # ############ # General - disabled_command_categories: list[str] = Field(default_factory=list) + disabled_command_categories: list[str] = UserConfigurable( + default_factory=list, + from_env=lambda: _safe_split(os.getenv("DISABLED_COMMAND_CATEGORIES")), + ) + # File ops - restrict_to_workspace: bool = True + restrict_to_workspace: bool = UserConfigurable( + default=True, + from_env=lambda: os.getenv("RESTRICT_TO_WORKSPACE", "True") == "True", + ) allow_downloads: bool = False + # Shell commands - shell_command_control: str = "denylist" - execute_local_commands: bool = False - shell_denylist: list[str] = Field(default_factory=lambda: ["sudo", "su"]) - shell_allowlist: list[str] = Field(default_factory=list) + shell_command_control: str = UserConfigurable( + default="denylist", from_env="SHELL_COMMAND_CONTROL" + ) + execute_local_commands: bool = UserConfigurable( + default=False, + from_env=lambda: os.getenv("EXECUTE_LOCAL_COMMANDS", "False") == "True", + ) + shell_denylist: list[str] = UserConfigurable( + default_factory=lambda: ["sudo", "su"], + from_env=lambda: _safe_split( + os.getenv("SHELL_DENYLIST", os.getenv("DENY_COMMANDS")) + ), + ) + shell_allowlist: list[str] = UserConfigurable( + default_factory=list, + from_env=lambda: _safe_split( + os.getenv("SHELL_ALLOWLIST", os.getenv("ALLOW_COMMANDS")) + ), + ) + # Text to image - image_provider: Optional[str] = None - huggingface_image_model: str = "CompVis/stable-diffusion-v1-4" - sd_webui_url: Optional[str] = "http://localhost:7860" - image_size: int = 256 + image_provider: Optional[str] = UserConfigurable(from_env="IMAGE_PROVIDER") + huggingface_image_model: str = UserConfigurable( + default="CompVis/stable-diffusion-v1-4", from_env="HUGGINGFACE_IMAGE_MODEL" + ) + sd_webui_url: Optional[str] = UserConfigurable( + default="http://localhost:7860", from_env="SD_WEBUI_URL" + ) + image_size: int = UserConfigurable( + default=256, + from_env=lambda: int(v) if (v := os.getenv("IMAGE_SIZE")) else None, + ) + # Audio to text - audio_to_text_provider: str = "huggingface" - huggingface_audio_to_text_model: Optional[str] = None + audio_to_text_provider: str = UserConfigurable( + default="huggingface", from_env="AUDIO_TO_TEXT_PROVIDER" + ) + huggingface_audio_to_text_model: Optional[str] = UserConfigurable( + from_env="HUGGINGFACE_AUDIO_TO_TEXT_MODEL" + ) + # Web browsing - selenium_web_browser: str = "chrome" - selenium_headless: bool = True - user_agent: str = "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36" + selenium_web_browser: str = UserConfigurable("chrome", from_env="USE_WEB_BROWSER") + selenium_headless: bool = UserConfigurable( + default=True, from_env=lambda: os.getenv("HEADLESS_BROWSER", "True") == "True" + ) + user_agent: str = UserConfigurable( + default="Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36", # noqa: E501 + from_env="USER_AGENT", + ) ################### # Plugin Settings # ################### - plugins_dir: str = "plugins" - plugins_config_file: Path = project_root / PLUGINS_CONFIG_FILE + plugins_dir: str = UserConfigurable("plugins", from_env="PLUGINS_DIR") + plugins_config_file: Path = UserConfigurable( + default=PLUGINS_CONFIG_FILE, + from_env=lambda: Path(f) if (f := os.getenv("PLUGINS_CONFIG_FILE")) else None, + ) plugins_config: PluginsConfig = Field( default_factory=lambda: PluginsConfig(plugins={}) ) plugins: list[AutoGPTPluginTemplate] = Field(default_factory=list, exclude=True) - plugins_allowlist: list[str] = Field(default_factory=list) - plugins_denylist: list[str] = Field(default_factory=list) - plugins_openai: list[str] = Field(default_factory=list) + plugins_allowlist: list[str] = UserConfigurable( + default_factory=list, + from_env=lambda: _safe_split(os.getenv("ALLOWLISTED_PLUGINS")), + ) + plugins_denylist: list[str] = UserConfigurable( + default_factory=list, + from_env=lambda: _safe_split(os.getenv("DENYLISTED_PLUGINS")), + ) + plugins_openai: list[str] = UserConfigurable( + default_factory=list, from_env=lambda: _safe_split(os.getenv("OPENAI_PLUGINS")) + ) ############### # Credentials # ############### # OpenAI - openai_api_key: Optional[str] = None - openai_api_type: Optional[str] = None - openai_api_base: Optional[str] = None - openai_api_version: Optional[str] = None - openai_organization: Optional[str] = None - use_azure: bool = False - azure_config_file: Optional[Path] = project_root / AZURE_CONFIG_FILE - azure_model_to_deployment_id_map: Optional[Dict[str, str]] = None + openai_credentials: Optional[OpenAICredentials] = None + azure_config_file: Optional[Path] = UserConfigurable( + default=AZURE_CONFIG_FILE, + from_env=lambda: Path(f) if (f := os.getenv("AZURE_CONFIG_FILE")) else None, + ) + # Github - github_api_key: Optional[str] = None - github_username: Optional[str] = None + github_api_key: Optional[str] = UserConfigurable(from_env="GITHUB_API_KEY") + github_username: Optional[str] = UserConfigurable(from_env="GITHUB_USERNAME") + # Google - google_api_key: Optional[str] = None - google_custom_search_engine_id: Optional[str] = None + google_api_key: Optional[str] = UserConfigurable(from_env="GOOGLE_API_KEY") + google_custom_search_engine_id: Optional[str] = UserConfigurable( + from_env=lambda: os.getenv("GOOGLE_CUSTOM_SEARCH_ENGINE_ID"), + ) + # Huggingface - huggingface_api_token: Optional[str] = None + huggingface_api_token: Optional[str] = UserConfigurable( + from_env="HUGGINGFACE_API_TOKEN" + ) + # Stable Diffusion - sd_webui_auth: Optional[str] = None + sd_webui_auth: Optional[str] = UserConfigurable(from_env="SD_WEBUI_AUTH") @validator("plugins", each_item=True) def validate_plugins(cls, p: AutoGPTPluginTemplate | Any): @@ -156,67 +261,6 @@ class Config(SystemSettings, arbitrary_types_allowed=True): ) return v - def get_openai_credentials(self, model: str) -> dict[str, str]: - credentials = { - "api_key": self.openai_api_key, - "api_base": self.openai_api_base, - "organization": self.openai_organization, - } - if self.use_azure: - azure_credentials = self.get_azure_credentials(model) - credentials.update(azure_credentials) - return credentials - - def get_azure_credentials(self, model: str) -> dict[str, str]: - """Get the kwargs for the Azure API.""" - - # Fix --gpt3only and --gpt4only in combination with Azure - fast_llm = ( - self.fast_llm - if not ( - self.fast_llm == self.smart_llm - and self.fast_llm.startswith(GPT_4_MODEL) - ) - else f"not_{self.fast_llm}" - ) - smart_llm = ( - self.smart_llm - if not ( - self.smart_llm == self.fast_llm - and self.smart_llm.startswith(GPT_3_MODEL) - ) - else f"not_{self.smart_llm}" - ) - - deployment_id = { - fast_llm: self.azure_model_to_deployment_id_map.get( - "fast_llm_deployment_id", - self.azure_model_to_deployment_id_map.get( - "fast_llm_model_deployment_id" # backwards compatibility - ), - ), - smart_llm: self.azure_model_to_deployment_id_map.get( - "smart_llm_deployment_id", - self.azure_model_to_deployment_id_map.get( - "smart_llm_model_deployment_id" # backwards compatibility - ), - ), - self.embedding_model: self.azure_model_to_deployment_id_map.get( - "embedding_model_deployment_id" - ), - }.get(model, None) - - kwargs = { - "api_type": self.openai_api_type, - "api_base": self.openai_api_base, - "api_version": self.openai_api_version, - } - if model == self.embedding_model: - kwargs["engine"] = deployment_id - else: - kwargs["deployment_id"] = deployment_id - return kwargs - class ConfigBuilder(Configurable[Config]): default_settings = Config() @@ -224,124 +268,25 @@ class ConfigBuilder(Configurable[Config]): @classmethod def build_config_from_env(cls, project_root: Path = PROJECT_ROOT) -> Config: """Initialize the Config class""" - config_dict = { - "project_root": project_root, - "authorise_key": os.getenv("AUTHORISE_COMMAND_KEY"), - "exit_key": os.getenv("EXIT_KEY"), - "plain_output": os.getenv("PLAIN_OUTPUT", "False") == "True", - "shell_command_control": os.getenv("SHELL_COMMAND_CONTROL"), - "ai_settings_file": project_root - / Path(os.getenv("AI_SETTINGS_FILE", AI_SETTINGS_FILE)), - "prompt_settings_file": project_root - / Path(os.getenv("PROMPT_SETTINGS_FILE", PROMPT_SETTINGS_FILE)), - "fast_llm": os.getenv("FAST_LLM", os.getenv("FAST_LLM_MODEL")), - "smart_llm": os.getenv("SMART_LLM", os.getenv("SMART_LLM_MODEL")), - "embedding_model": os.getenv("EMBEDDING_MODEL"), - "browse_spacy_language_model": os.getenv("BROWSE_SPACY_LANGUAGE_MODEL"), - "openai_api_key": os.getenv("OPENAI_API_KEY"), - "use_azure": os.getenv("USE_AZURE") == "True", - "azure_config_file": project_root - / Path(os.getenv("AZURE_CONFIG_FILE", AZURE_CONFIG_FILE)), - "execute_local_commands": os.getenv("EXECUTE_LOCAL_COMMANDS", "False") - == "True", - "restrict_to_workspace": os.getenv("RESTRICT_TO_WORKSPACE", "True") - == "True", - "openai_functions": os.getenv("OPENAI_FUNCTIONS", "False") == "True", - "tts_config": { - "provider": os.getenv("TEXT_TO_SPEECH_PROVIDER"), - }, - "github_api_key": os.getenv("GITHUB_API_KEY"), - "github_username": os.getenv("GITHUB_USERNAME"), - "google_api_key": os.getenv("GOOGLE_API_KEY"), - "image_provider": os.getenv("IMAGE_PROVIDER"), - "huggingface_api_token": os.getenv("HUGGINGFACE_API_TOKEN"), - "huggingface_image_model": os.getenv("HUGGINGFACE_IMAGE_MODEL"), - "audio_to_text_provider": os.getenv("AUDIO_TO_TEXT_PROVIDER"), - "huggingface_audio_to_text_model": os.getenv( - "HUGGINGFACE_AUDIO_TO_TEXT_MODEL" - ), - "sd_webui_url": os.getenv("SD_WEBUI_URL"), - "sd_webui_auth": os.getenv("SD_WEBUI_AUTH"), - "selenium_web_browser": os.getenv("USE_WEB_BROWSER"), - "selenium_headless": os.getenv("HEADLESS_BROWSER", "True") == "True", - "user_agent": os.getenv("USER_AGENT"), - "memory_backend": os.getenv("MEMORY_BACKEND"), - "memory_index": os.getenv("MEMORY_INDEX"), - "redis_host": os.getenv("REDIS_HOST"), - "redis_password": os.getenv("REDIS_PASSWORD"), - "wipe_redis_on_start": os.getenv("WIPE_REDIS_ON_START", "True") == "True", - "plugins_dir": os.getenv("PLUGINS_DIR"), - "plugins_config_file": project_root - / Path(os.getenv("PLUGINS_CONFIG_FILE", PLUGINS_CONFIG_FILE)), - "chat_messages_enabled": os.getenv("CHAT_MESSAGES_ENABLED") == "True", - } - - config_dict["disabled_command_categories"] = _safe_split( - os.getenv("DISABLED_COMMAND_CATEGORIES") - ) - config_dict["shell_denylist"] = _safe_split( - os.getenv("SHELL_DENYLIST", os.getenv("DENY_COMMANDS")) - ) - config_dict["shell_allowlist"] = _safe_split( - os.getenv("SHELL_ALLOWLIST", os.getenv("ALLOW_COMMANDS")) - ) - - config_dict["google_custom_search_engine_id"] = os.getenv( - "GOOGLE_CUSTOM_SEARCH_ENGINE_ID", os.getenv("CUSTOM_SEARCH_ENGINE_ID") - ) - - if os.getenv("ELEVENLABS_API_KEY"): - config_dict["tts_config"]["elevenlabs"] = { - "api_key": os.getenv("ELEVENLABS_API_KEY"), - "voice_id": os.getenv("ELEVENLABS_VOICE_ID", ""), - } - if os.getenv("STREAMELEMENTS_VOICE"): - config_dict["tts_config"]["streamelements"] = { - "voice": os.getenv("STREAMELEMENTS_VOICE"), - } - - if not config_dict["tts_config"]["provider"]: - if os.getenv("USE_MAC_OS_TTS"): - default_tts_provider = "macos" - elif "elevenlabs" in config_dict["tts_config"]: - default_tts_provider = "elevenlabs" - elif os.getenv("USE_BRIAN_TTS"): - default_tts_provider = "streamelements" - else: - default_tts_provider = "gtts" - config_dict["tts_config"]["provider"] = default_tts_provider - - config_dict["plugins_allowlist"] = _safe_split(os.getenv("ALLOWLISTED_PLUGINS")) - config_dict["plugins_denylist"] = _safe_split(os.getenv("DENYLISTED_PLUGINS")) - - with contextlib.suppress(TypeError): - config_dict["image_size"] = int(os.getenv("IMAGE_SIZE")) - with contextlib.suppress(TypeError): - config_dict["redis_port"] = int(os.getenv("REDIS_PORT")) - with contextlib.suppress(TypeError): - config_dict["temperature"] = float(os.getenv("TEMPERATURE")) - - if config_dict["use_azure"]: - azure_config = cls.load_azure_config( - project_root / config_dict["azure_config_file"] - ) - config_dict.update(azure_config) - - elif os.getenv("OPENAI_API_BASE_URL"): - config_dict["openai_api_base"] = os.getenv("OPENAI_API_BASE_URL") - - openai_organization = os.getenv("OPENAI_ORGANIZATION") - if openai_organization is not None: - config_dict["openai_organization"] = openai_organization - - config_dict_without_none_values = { - k: v for k, v in config_dict.items() if v is not None - } - - config = cls.build_agent_configuration(config_dict_without_none_values) - - # Set secondary config variables (that depend on other config variables) + config = cls.build_agent_configuration() + config.project_root = project_root + + # Make relative paths absolute + for k in { + "ai_settings_file", # TODO: deprecate or repurpose + "prompt_settings_file", # TODO: deprecate or repurpose + "plugins_config_file", # TODO: move from project root + "azure_config_file", # TODO: move from project root + }: + setattr(config, k, project_root / getattr(config, k)) + + if ( + config.openai_credentials + and config.openai_credentials.api_type == "azure" + and (config_file := config.azure_config_file) + ): + config.openai_credentials.load_azure_config(config_file) config.plugins_config = PluginsConfig.load_config( config.plugins_config_file, @@ -351,36 +296,10 @@ class ConfigBuilder(Configurable[Config]): return config - @classmethod - def load_azure_config(cls, config_file: Path) -> Dict[str, str]: - """ - Loads the configuration parameters for Azure hosting from the specified file - path as a yaml file. - - Parameters: - config_file (Path): The path to the config yaml file. - - Returns: - Dict - """ - with open(config_file) as file: - config_params = yaml.load(file, Loader=yaml.FullLoader) or {} - - return { - "openai_api_type": config_params.get("azure_api_type", "azure"), - "openai_api_base": config_params.get("azure_api_base", ""), - "openai_api_version": config_params.get( - "azure_api_version", "2023-03-15-preview" - ), - "azure_model_to_deployment_id_map": config_params.get( - "azure_model_map", {} - ), - } - def assert_config_has_openai_api_key(config: Config) -> None: """Check if the OpenAI API key is set in config.py or as an environment variable.""" - if not config.openai_api_key: + if not config.openai_credentials: print( Fore.RED + "Please set your OpenAI API key in .env or as an environment variable." @@ -394,7 +313,9 @@ def assert_config_has_openai_api_key(config: Config) -> None: openai_api_key = openai_api_key.strip() if re.search(key_pattern, openai_api_key): os.environ["OPENAI_API_KEY"] = openai_api_key - config.openai_api_key = openai_api_key + config.openai_credentials = OpenAICredentials( + api_key=SecretStr(openai_api_key) + ) print( Fore.GREEN + "OpenAI API key successfully set!\n" diff --git a/autogpts/autogpt/autogpt/core/ability/__init__.py b/autogpts/autogpt/autogpt/core/ability/__init__.py index a186d9ace..3709b9277 100644 --- a/autogpts/autogpt/autogpt/core/ability/__init__.py +++ b/autogpts/autogpt/autogpt/core/ability/__init__.py @@ -6,3 +6,13 @@ from autogpt.core.ability.simple import ( AbilityRegistrySettings, SimpleAbilityRegistry, ) + +__all__ = [ + "Ability", + "AbilityConfiguration", + "AbilityRegistry", + "AbilityResult", + "AbilityRegistryConfiguration", + "AbilityRegistrySettings", + "SimpleAbilityRegistry", +] diff --git a/autogpts/autogpt/autogpt/core/ability/builtins/__init__.py b/autogpts/autogpt/autogpt/core/ability/builtins/__init__.py index 0572605a1..93936dbc6 100644 --- a/autogpts/autogpt/autogpt/core/ability/builtins/__init__.py +++ b/autogpts/autogpt/autogpt/core/ability/builtins/__init__.py @@ -4,3 +4,9 @@ from autogpt.core.ability.builtins.query_language_model import QueryLanguageMode BUILTIN_ABILITIES = { QueryLanguageModel.name(): QueryLanguageModel, } + +__all__ = [ + "BUILTIN_ABILITIES", + "CreateNewAbility", + "QueryLanguageModel", +] diff --git a/autogpts/autogpt/autogpt/core/ability/builtins/create_new_ability.py b/autogpts/autogpt/autogpt/core/ability/builtins/create_new_ability.py index e8526d3c5..55550cafc 100644 --- a/autogpts/autogpt/autogpt/core/ability/builtins/create_new_ability.py +++ b/autogpts/autogpt/autogpt/core/ability/builtins/create_new_ability.py @@ -32,7 +32,10 @@ class CreateNewAbility(Ability): required=True, ), "description": JSONSchema( - description="A detailed description of the ability and its uses, including any limitations.", + description=( + "A detailed description of the ability and its uses, " + "including any limitations." + ), type=JSONSchema.Type.STRING, required=True, ), @@ -47,11 +50,16 @@ class CreateNewAbility(Ability): type=JSONSchema.Type.STRING, ), "type": JSONSchema( - description="The type of the argument. Must be a standard json schema type.", + description=( + "The type of the argument. " + "Must be a standard json schema type." + ), type=JSONSchema.Type.STRING, ), "description": JSONSchema( - description="A detailed description of the argument and its uses.", + description=( + "A detailed description of the argument and its uses." + ), type=JSONSchema.Type.STRING, ), }, @@ -66,15 +74,22 @@ class CreateNewAbility(Ability): ), ), "package_requirements": JSONSchema( - description="A list of the names of the Python packages that are required to execute the ability.", + description=( + "A list of the names of the Python packages that are required to " + "execute the ability." + ), type=JSONSchema.Type.ARRAY, items=JSONSchema( - description="The of the Python package that is required to execute the ability.", + description=( + "The of the Python package that is required to execute the ability." + ), type=JSONSchema.Type.STRING, ), ), "code": JSONSchema( - description="The Python code that will be executed when the ability is called.", + description=( + "The Python code that will be executed when the ability is called." + ), type=JSONSchema.Type.STRING, required=True, ), diff --git a/autogpts/autogpt/autogpt/core/ability/builtins/query_language_model.py b/autogpts/autogpt/autogpt/core/ability/builtins/query_language_model.py index 67d51087f..7a6ae68ee 100644 --- a/autogpts/autogpt/autogpt/core/ability/builtins/query_language_model.py +++ b/autogpts/autogpt/autogpt/core/ability/builtins/query_language_model.py @@ -45,7 +45,10 @@ class QueryLanguageModel(Ability): parameters: ClassVar[dict[str, JSONSchema]] = { "query": JSONSchema( type=JSONSchema.Type.STRING, - description="A query for a language model. A query should contain a question and any relevant context.", + description=( + "A query for a language model. " + "A query should contain a question and any relevant context." + ), ) } @@ -59,5 +62,5 @@ class QueryLanguageModel(Ability): ability_name=self.name(), ability_args={"query": query}, success=True, - message=model_response.response["content"], + message=model_response.response.content or "", ) diff --git a/autogpts/autogpt/autogpt/core/agent/__init__.py b/autogpts/autogpt/autogpt/core/agent/__init__.py index 9324042b1..f4e7a5a73 100644 --- a/autogpts/autogpt/autogpt/core/agent/__init__.py +++ b/autogpts/autogpt/autogpt/core/agent/__init__.py @@ -1,3 +1,9 @@ """The Agent is an autonomouos entity guided by a LLM provider.""" from autogpt.core.agent.base import Agent from autogpt.core.agent.simple import AgentSettings, SimpleAgent + +__all__ = [ + "Agent", + "AgentSettings", + "SimpleAgent", +] diff --git a/autogpts/autogpt/autogpt/core/agent/simple.py b/autogpts/autogpt/autogpt/core/agent/simple.py index a66ca5cc4..ea113dafc 100644 --- a/autogpts/autogpt/autogpt/core/agent/simple.py +++ b/autogpts/autogpt/autogpt/core/agent/simple.py @@ -92,7 +92,9 @@ class SimpleAgent(Agent, Configurable): ), openai_provider=PluginLocation( storage_format=PluginStorageFormat.INSTALLED_PACKAGE, - storage_route="autogpt.core.resource.model_providers.OpenAIProvider", + storage_route=( + "autogpt.core.resource.model_providers.OpenAIProvider" + ), ), planning=PluginLocation( storage_format=PluginStorageFormat.INSTALLED_PACKAGE, @@ -184,7 +186,7 @@ class SimpleAgent(Agent, Configurable): ) tasks = [Task.parse_obj(task) for task in plan.parsed_result["task_list"]] - # TODO: Should probably do a step to evaluate the quality of the generated tasks, + # TODO: Should probably do a step to evaluate the quality of the generated tasks # and ensure that they have actionable ready and acceptance criteria self._task_queue.extend(tasks) @@ -235,7 +237,7 @@ class SimpleAgent(Agent, Configurable): else: self._logger.debug(f"Evaluating task {task} and adding relevant context.") # TODO: Look up relevant memories (need working memory system) - # TODO: Evaluate whether there is enough information to start the task (language model call). + # TODO: Eval whether there is enough information to start the task (w/ LLM). task.context.enough_info = True task.context.status = TaskStatus.IN_PROGRESS return task @@ -248,10 +250,12 @@ class SimpleAgent(Agent, Configurable): """Choose the next ability to use for the task.""" self._logger.debug(f"Choosing next ability for task {task}.") if task.context.cycle_count > self._configuration.max_task_cycle_count: - # Don't hit the LLM, just set the next action as "breakdown_task" with an appropriate reason + # Don't hit the LLM, just set the next action as "breakdown_task" + # with an appropriate reason raise NotImplementedError elif not task.context.enough_info: - # Don't ask the LLM, just set the next action as "breakdown_task" with an appropriate reason + # Don't ask the LLM, just set the next action as "breakdown_task" + # with an appropriate reason raise NotImplementedError else: next_ability = await self._planning.determine_next_ability( @@ -378,7 +382,8 @@ class SimpleAgent(Agent, Configurable): def _prune_empty_dicts(d: dict) -> dict: """ - Prune branches from a nested dictionary if the branch only contains empty dictionaries at the leaves. + Prune branches from a nested dictionary if the branch only contains empty + dictionaries at the leaves. Args: d: The dictionary to prune. diff --git a/autogpts/autogpt/autogpt/core/configuration/__init__.py b/autogpts/autogpt/autogpt/core/configuration/__init__.py index b6fee7493..231819299 100644 --- a/autogpts/autogpt/autogpt/core/configuration/__init__.py +++ b/autogpts/autogpt/autogpt/core/configuration/__init__.py @@ -5,3 +5,10 @@ from autogpt.core.configuration.schema import ( SystemSettings, UserConfigurable, ) + +__all__ = [ + "Configurable", + "SystemConfiguration", + "SystemSettings", + "UserConfigurable", +] diff --git a/autogpts/autogpt/autogpt/core/configuration/schema.py b/autogpts/autogpt/autogpt/core/configuration/schema.py index eebb7ba9d..5bc95ffac 100644 --- a/autogpts/autogpt/autogpt/core/configuration/schema.py +++ b/autogpts/autogpt/autogpt/core/configuration/schema.py @@ -1,24 +1,73 @@ import abc -import functools +import os import typing -from typing import Any, Generic, TypeVar +from typing import Any, Callable, Generic, Optional, Type, TypeVar, get_args -from pydantic import BaseModel, Field +from pydantic import BaseModel, Field, ValidationError +from pydantic.fields import ModelField, Undefined, UndefinedType +from pydantic.main import ModelMetaclass +T = TypeVar("T") +M = TypeVar("M", bound=BaseModel) -@functools.wraps(Field) -def UserConfigurable(*args, **kwargs): - return Field(*args, **kwargs, user_configurable=True) + +def UserConfigurable( + default: T | UndefinedType = Undefined, + *args, + default_factory: Optional[Callable[[], T]] = None, + from_env: Optional[str | Callable[[], T | None]] = None, + description: str = "", + **kwargs, +) -> T: # TODO: use this to auto-generate docs for the application configuration + return Field( + default, + *args, + default_factory=default_factory, + from_env=from_env, + description=description, + **kwargs, + user_configurable=True, + ) class SystemConfiguration(BaseModel): def get_user_config(self) -> dict[str, Any]: - return _get_user_config_fields(self) + return _recurse_user_config_values(self) + + @classmethod + def from_env(cls): + """ + Initializes the config object from environment variables. + + Environment variables are mapped to UserConfigurable fields using the from_env + attribute that can be passed to UserConfigurable. + """ + + def infer_field_value(field: ModelField): + field_info = field.field_info + default_value = ( + field.default + if field.default not in (None, Undefined) + else (field.default_factory() if field.default_factory else Undefined) + ) + if from_env := field_info.extra.get("from_env"): + val_from_env = ( + os.getenv(from_env) if type(from_env) is str else from_env() + ) + if val_from_env is not None: + return val_from_env + return default_value + + return _recursive_init_model(cls, infer_field_value) class Config: extra = "forbid" use_enum_values = True + validate_assignment = True + + +SC = TypeVar("SC", bound=SystemConfiguration) class SystemSettings(BaseModel): @@ -30,6 +79,7 @@ class SystemSettings(BaseModel): class Config: extra = "forbid" use_enum_values = True + validate_assignment = True S = TypeVar("S", bound=SystemSettings) @@ -43,55 +93,238 @@ class Configurable(abc.ABC, Generic[S]): @classmethod def get_user_config(cls) -> dict[str, Any]: - return _get_user_config_fields(cls.default_settings) + return _recurse_user_config_values(cls.default_settings) @classmethod - def build_agent_configuration(cls, configuration: dict) -> S: + def build_agent_configuration(cls, overrides: dict = {}) -> S: """Process the configuration for this object.""" - defaults = cls.default_settings.dict() - final_configuration = deep_update(defaults, configuration) + base_config = _update_user_config_from_env(cls.default_settings) + final_configuration = deep_update(base_config, overrides) return cls.default_settings.__class__.parse_obj(final_configuration) -def _get_user_config_fields(instance: BaseModel) -> dict[str, Any]: +def _update_user_config_from_env(instance: BaseModel) -> dict[str, Any]: """ - Get the user config fields of a Pydantic model instance. + Update config fields of a Pydantic model instance from environment variables. + + Precedence: + 1. Non-default value already on the instance + 2. Value returned by `from_env()` + 3. Default value for the field - Args: + Params: instance: The Pydantic model instance. Returns: The user config fields of the instance. """ + + def infer_field_value(field: ModelField, value): + field_info = field.field_info + default_value = ( + field.default + if field.default not in (None, Undefined) + else (field.default_factory() if field.default_factory else None) + ) + if value == default_value and (from_env := field_info.extra.get("from_env")): + val_from_env = os.getenv(from_env) if type(from_env) is str else from_env() + if val_from_env is not None: + return val_from_env + return value + + def init_sub_config(model: Type[SC]) -> SC | None: + try: + return model.from_env() + except ValidationError as e: + # Gracefully handle missing fields + if all(e["type"] == "value_error.missing" for e in e.errors()): + return None + raise + + return _recurse_user_config_fields(instance, infer_field_value, init_sub_config) + + +def _recursive_init_model( + model: Type[M], + infer_field_value: Callable[[ModelField], Any], +) -> M: + """ + Recursively initialize the user configuration fields of a Pydantic model. + + Parameters: + model: The Pydantic model type. + infer_field_value: A callback function to infer the value of each field. + Parameters: + ModelField: The Pydantic ModelField object describing the field. + + Returns: + BaseModel: An instance of the model with the initialized configuration. + """ user_config_fields = {} + for name, field in model.__fields__.items(): + if "user_configurable" in field.field_info.extra: + user_config_fields[name] = infer_field_value(field) + elif type(field.outer_type_) is ModelMetaclass and issubclass( + field.outer_type_, SystemConfiguration + ): + try: + user_config_fields[name] = _recursive_init_model( + model=field.outer_type_, + infer_field_value=infer_field_value, + ) + except ValidationError as e: + # Gracefully handle missing fields + if all(e["type"] == "value_error.missing" for e in e.errors()): + user_config_fields[name] = None + raise - for name, value in instance.__dict__.items(): - field_info = instance.__fields__[name] - if "user_configurable" in field_info.field_info.extra: - user_config_fields[name] = value + user_config_fields = remove_none_items(user_config_fields) + + return model.parse_obj(user_config_fields) + + +def _recurse_user_config_fields( + model: BaseModel, + infer_field_value: Callable[[ModelField, Any], Any], + init_sub_config: Optional[ + Callable[[Type[SystemConfiguration]], SystemConfiguration | None] + ] = None, +) -> dict[str, Any]: + """ + Recursively process the user configuration fields of a Pydantic model instance. + + Params: + model: The Pydantic model to iterate over. + infer_field_value: A callback function to process each field. + Params: + ModelField: The Pydantic ModelField object describing the field. + Any: The current value of the field. + init_sub_config: An optional callback function to initialize a sub-config. + Params: + Type[SystemConfiguration]: The type of the sub-config to initialize. + + Returns: + dict[str, Any]: The processed user configuration fields of the instance. + """ + user_config_fields = {} + + for name, field in model.__fields__.items(): + value = getattr(model, name) + + # Handle individual field + if "user_configurable" in field.field_info.extra: + user_config_fields[name] = infer_field_value(field, value) + + # Recurse into nested config object elif isinstance(value, SystemConfiguration): - user_config_fields[name] = value.get_user_config() + user_config_fields[name] = _recurse_user_config_fields( + model=value, + infer_field_value=infer_field_value, + init_sub_config=init_sub_config, + ) + + # Recurse into optional nested config object + elif value is None and init_sub_config: + field_type = get_args(field.annotation)[0] # Optional[T] -> T + if type(field_type) is ModelMetaclass and issubclass( + field_type, SystemConfiguration + ): + sub_config = init_sub_config(field_type) + if sub_config: + user_config_fields[name] = _recurse_user_config_fields( + model=sub_config, + infer_field_value=infer_field_value, + init_sub_config=init_sub_config, + ) + elif isinstance(value, list) and all( isinstance(i, SystemConfiguration) for i in value ): - user_config_fields[name] = [i.get_user_config() for i in value] + user_config_fields[name] = [ + _recurse_user_config_fields(i, infer_field_value, init_sub_config) + for i in value + ] elif isinstance(value, dict) and all( isinstance(i, SystemConfiguration) for i in value.values() ): user_config_fields[name] = { - k: v.get_user_config() for k, v in value.items() + k: _recurse_user_config_fields(v, infer_field_value, init_sub_config) + for k, v in value.items() } return user_config_fields +def _recurse_user_config_values( + instance: BaseModel, + get_field_value: Callable[[ModelField, T], T] = lambda _, v: v, +) -> dict[str, Any]: + """ + This function recursively traverses the user configuration values in a Pydantic + model instance. + + Params: + instance: A Pydantic model instance. + get_field_value: A callback function to process each field. Parameters: + ModelField: The Pydantic ModelField object that describes the field. + Any: The current value of the field. + + Returns: + A dictionary containing the processed user configuration fields of the instance. + """ + user_config_values = {} + + for name, value in instance.__dict__.items(): + field = instance.__fields__[name] + if "user_configurable" in field.field_info.extra: + user_config_values[name] = get_field_value(field, value) + elif isinstance(value, SystemConfiguration): + user_config_values[name] = _recurse_user_config_values( + instance=value, get_field_value=get_field_value + ) + elif isinstance(value, list) and all( + isinstance(i, SystemConfiguration) for i in value + ): + user_config_values[name] = [ + _recurse_user_config_values(i, get_field_value) for i in value + ] + elif isinstance(value, dict) and all( + isinstance(i, SystemConfiguration) for i in value.values() + ): + user_config_values[name] = { + k: _recurse_user_config_values(v, get_field_value) + for k, v in value.items() + } + + return user_config_values + + +def _get_non_default_user_config_values(instance: BaseModel) -> dict[str, Any]: + """ + Get the non-default user config fields of a Pydantic model instance. + + Params: + instance: The Pydantic model instance. + + Returns: + dict[str, Any]: The non-default user config values on the instance. + """ + + def get_field_value(field: ModelField, value): + default = field.default_factory() if field.default_factory else field.default + if value != default: + return value + + return remove_none_items(_recurse_user_config_values(instance, get_field_value)) + + def deep_update(original_dict: dict, update_dict: dict) -> dict: """ Recursively update a dictionary. - Args: + Params: original_dict (dict): The dictionary to be updated. update_dict (dict): The dictionary to update with. @@ -108,3 +341,11 @@ def deep_update(original_dict: dict, update_dict: dict) -> dict: else: original_dict[key] = value return original_dict + + +def remove_none_items(d): + if isinstance(d, dict): + return { + k: remove_none_items(v) for k, v in d.items() if v not in (None, Undefined) + } + return d diff --git a/autogpts/autogpt/autogpt/core/memory/__init__.py b/autogpts/autogpt/autogpt/core/memory/__init__.py index eeba203a6..f77b61039 100644 --- a/autogpts/autogpt/autogpt/core/memory/__init__.py +++ b/autogpts/autogpt/autogpt/core/memory/__init__.py @@ -1,3 +1,9 @@ """The memory subsystem manages the Agent's long-term memory.""" from autogpt.core.memory.base import Memory from autogpt.core.memory.simple import MemorySettings, SimpleMemory + +__all__ = [ + "Memory", + "MemorySettings", + "SimpleMemory", +] diff --git a/autogpts/autogpt/autogpt/core/planning/__init__.py b/autogpts/autogpt/autogpt/core/planning/__init__.py index 517aa91a4..99ab573f8 100644 --- a/autogpts/autogpt/autogpt/core/planning/__init__.py +++ b/autogpts/autogpt/autogpt/core/planning/__init__.py @@ -1,3 +1,11 @@ """The planning system organizes the Agent's activities.""" from autogpt.core.planning.schema import Task, TaskStatus, TaskType from autogpt.core.planning.simple import PlannerSettings, SimplePlanner + +__all__ = [ + "PlannerSettings", + "SimplePlanner", + "Task", + "TaskStatus", + "TaskType", +] diff --git a/autogpts/autogpt/autogpt/core/planning/base.py b/autogpts/autogpt/autogpt/core/planning/base.py index a46c8074b..7993c490b 100644 --- a/autogpts/autogpt/autogpt/core/planning/base.py +++ b/autogpts/autogpt/autogpt/core/planning/base.py @@ -1,5 +1,8 @@ # class Planner(abc.ABC): -# """Manages the agent's planning and goal-setting by constructing language model prompts.""" +# """ +# Manages the agent's planning and goal-setting +# by constructing language model prompts. +# """ # # @staticmethod # @abc.abstractmethod diff --git a/autogpts/autogpt/autogpt/core/planning/prompt_strategies/__init__.py b/autogpts/autogpt/autogpt/core/planning/prompt_strategies/__init__.py index 789756dec..7b62279a7 100644 --- a/autogpts/autogpt/autogpt/core/planning/prompt_strategies/__init__.py +++ b/autogpts/autogpt/autogpt/core/planning/prompt_strategies/__init__.py @@ -1,3 +1,12 @@ from .initial_plan import InitialPlan, InitialPlanConfiguration from .name_and_goals import NameAndGoals, NameAndGoalsConfiguration from .next_ability import NextAbility, NextAbilityConfiguration + +__all__ = [ + "InitialPlan", + "InitialPlanConfiguration", + "NameAndGoals", + "NameAndGoalsConfiguration", + "NextAbility", + "NextAbilityConfiguration", +] diff --git a/autogpts/autogpt/autogpt/core/planning/prompt_strategies/initial_plan.py b/autogpts/autogpt/autogpt/core/planning/prompt_strategies/initial_plan.py index 6f00276cf..9912fb6e2 100644 --- a/autogpts/autogpt/autogpt/core/planning/prompt_strategies/initial_plan.py +++ b/autogpts/autogpt/autogpt/core/planning/prompt_strategies/initial_plan.py @@ -6,7 +6,7 @@ from autogpt.core.prompting import PromptStrategy from autogpt.core.prompting.schema import ChatPrompt, LanguageModelClassification from autogpt.core.prompting.utils import json_loads, to_numbered_list from autogpt.core.resource.model_providers import ( - AssistantChatMessageDict, + AssistantChatMessage, ChatMessage, CompletionModelFunction, ) @@ -25,13 +25,18 @@ class InitialPlanConfiguration(SystemConfiguration): class InitialPlan(PromptStrategy): DEFAULT_SYSTEM_PROMPT_TEMPLATE = ( - "You are an expert project planner. You're responsibility is to create work plans for autonomous agents. " - "You will be given a name, a role, set of goals for the agent to accomplish. Your job is to " - "break down those goals into a set of tasks that the agent can accomplish to achieve those goals. " - "Agents are resourceful, but require clear instructions. Each task you create should have clearly defined " - "`ready_criteria` that the agent can check to see if the task is ready to be started. Each task should " - "also have clearly defined `acceptance_criteria` that the agent can check to evaluate if the task is complete. " - "You should create as many tasks as you think is necessary to accomplish the goals.\n\n" + "You are an expert project planner. " + "Your responsibility is to create work plans for autonomous agents. " + "You will be given a name, a role, set of goals for the agent to accomplish. " + "Your job is to break down those goals into a set of tasks that the agent can" + " accomplish to achieve those goals. " + "Agents are resourceful, but require clear instructions." + " Each task you create should have clearly defined `ready_criteria` that the" + " agent can check to see if the task is ready to be started." + " Each task should also have clearly defined `acceptance_criteria` that the" + " agent can check to evaluate if the task is complete. " + "You should create as many tasks as you think is necessary to accomplish" + " the goals.\n\n" "System Info:\n{system_info}" ) @@ -47,7 +52,9 @@ class InitialPlan(PromptStrategy): DEFAULT_CREATE_PLAN_FUNCTION = CompletionModelFunction( name="create_initial_agent_plan", - description="Creates a set of tasks that forms the initial plan for an autonomous agent.", + description=( + "Creates a set of tasks that forms the initial plan of an autonomous agent." + ), parameters={ "task_list": JSONSchema( type=JSONSchema.Type.ARRAY, @@ -56,7 +63,10 @@ class InitialPlan(PromptStrategy): properties={ "objective": JSONSchema( type=JSONSchema.Type.STRING, - description="An imperative verb phrase that succinctly describes the task.", + description=( + "An imperative verb phrase that succinctly describes " + "the task." + ), ), "type": JSONSchema( type=JSONSchema.Type.STRING, @@ -67,12 +77,19 @@ class InitialPlan(PromptStrategy): type=JSONSchema.Type.ARRAY, items=JSONSchema( type=JSONSchema.Type.STRING, - description="A list of measurable and testable criteria that must be met for the task to be considered complete.", + description=( + "A list of measurable and testable criteria that " + "must be met for the task to be considered " + "complete." + ), ), ), "priority": JSONSchema( type=JSONSchema.Type.INTEGER, - description="A number between 1 and 10 indicating the priority of the task relative to other generated tasks.", + description=( + "A number between 1 and 10 indicating the priority of " + "the task relative to other generated tasks." + ), minimum=1, maximum=10, ), @@ -80,7 +97,10 @@ class InitialPlan(PromptStrategy): type=JSONSchema.Type.ARRAY, items=JSONSchema( type=JSONSchema.Type.STRING, - description="A list of measurable and testable criteria that must be met before the task can be started.", + description=( + "A list of measurable and testable criteria that " + "must be met before the task can be started." + ), ), ), }, @@ -158,7 +178,7 @@ class InitialPlan(PromptStrategy): def parse_response_content( self, - response_content: AssistantChatMessageDict, + response_content: AssistantChatMessage, ) -> dict: """Parse the actual text response from the objective model. @@ -169,8 +189,13 @@ class InitialPlan(PromptStrategy): The parsed response. """ try: - parsed_response = json_loads( - response_content["tool_calls"][0]["function"]["arguments"] + if not response_content.tool_calls: + raise ValueError( + f"LLM did not call {self._create_plan_function.name} function; " + "plan creation failed" + ) + parsed_response: object = json_loads( + response_content.tool_calls[0].function.arguments ) parsed_response["task_list"] = [ Task.parse_obj(task) for task in parsed_response["task_list"] diff --git a/autogpts/autogpt/autogpt/core/planning/prompt_strategies/name_and_goals.py b/autogpts/autogpt/autogpt/core/planning/prompt_strategies/name_and_goals.py index 360821b50..907a9717b 100644 --- a/autogpts/autogpt/autogpt/core/planning/prompt_strategies/name_and_goals.py +++ b/autogpts/autogpt/autogpt/core/planning/prompt_strategies/name_and_goals.py @@ -5,7 +5,7 @@ from autogpt.core.prompting import PromptStrategy from autogpt.core.prompting.schema import ChatPrompt, LanguageModelClassification from autogpt.core.prompting.utils import json_loads from autogpt.core.resource.model_providers import ( - AssistantChatMessageDict, + AssistantChatMessage, ChatMessage, CompletionModelFunction, ) @@ -61,7 +61,9 @@ class NameAndGoals(PromptStrategy): ), "agent_role": JSONSchema( type=JSONSchema.Type.STRING, - description="An informative one sentence description of what the AI agent does", + description=( + "An informative one sentence description of what the AI agent does" + ), ), "agent_goals": JSONSchema( type=JSONSchema.Type.ARRAY, @@ -71,8 +73,9 @@ class NameAndGoals(PromptStrategy): type=JSONSchema.Type.STRING, ), description=( - "One to five highly effective goals that are optimally aligned with the completion of a " - "specific task. The number and complexity of the goals should correspond to the " + "One to five highly effective goals that are optimally aligned " + "with the completion of a specific task. " + "The number and complexity of the goals should correspond to the " "complexity of the agent's primary objective." ), ), @@ -121,7 +124,7 @@ class NameAndGoals(PromptStrategy): def parse_response_content( self, - response_content: AssistantChatMessageDict, + response_content: AssistantChatMessage, ) -> dict: """Parse the actual text response from the objective model. @@ -133,8 +136,13 @@ class NameAndGoals(PromptStrategy): """ try: + if not response_content.tool_calls: + raise ValueError( + f"LLM did not call {self._create_agent_function} function; " + "agent profile creation failed" + ) parsed_response = json_loads( - response_content["tool_calls"][0]["function"]["arguments"] + response_content.tool_calls[0].function.arguments ) except KeyError: logger.debug(f"Failed to parse this response content: {response_content}") diff --git a/autogpts/autogpt/autogpt/core/planning/prompt_strategies/next_ability.py b/autogpts/autogpt/autogpt/core/planning/prompt_strategies/next_ability.py index 6efed7bee..9672f8e5b 100644 --- a/autogpts/autogpt/autogpt/core/planning/prompt_strategies/next_ability.py +++ b/autogpts/autogpt/autogpt/core/planning/prompt_strategies/next_ability.py @@ -6,7 +6,7 @@ from autogpt.core.prompting import PromptStrategy from autogpt.core.prompting.schema import ChatPrompt, LanguageModelClassification from autogpt.core.prompting.utils import json_loads, to_numbered_list from autogpt.core.resource.model_providers import ( - AssistantChatMessageDict, + AssistantChatMessage, ChatMessage, CompletionModelFunction, ) @@ -41,25 +41,36 @@ class NextAbility(PromptStrategy): "{additional_info}\n\n" "Additionally, you should consider the following:\n" "{user_input}\n\n" - "Your task of {task_objective} is complete when the following acceptance criteria have been met:\n" + "Your task of {task_objective} is complete when the following acceptance" + " criteria have been met:\n" "{acceptance_criteria}\n\n" "Please choose one of the provided functions to accomplish this task. " - "Some tasks may require multiple functions to accomplish. If that is the case, choose the function that " - "you think is most appropriate for the current situation given your progress so far." + "Some tasks may require multiple functions to accomplish. If that is the case," + " choose the function that you think is most appropriate for the current" + " situation given your progress so far." ) DEFAULT_ADDITIONAL_ABILITY_ARGUMENTS = { "motivation": JSONSchema( type=JSONSchema.Type.STRING, - description="Your justification for choosing choosing this function instead of a different one.", + description=( + "Your justification for choosing choosing this function instead of a " + "different one." + ), ), "self_criticism": JSONSchema( type=JSONSchema.Type.STRING, - description="Thoughtful self-criticism that explains why this function may not be the best choice.", + description=( + "Thoughtful self-criticism that explains why this function may not be " + "the best choice." + ), ), "reasoning": JSONSchema( type=JSONSchema.Type.STRING, - description="Your reasoning for choosing this function taking into account the `motivation` and weighing the `self_criticism`.", + description=( + "Your reasoning for choosing this function taking into account the " + "`motivation` and weighing the `self_criticism`." + ), ), } @@ -124,7 +135,9 @@ class NextAbility(PromptStrategy): template_kwargs["additional_info"] = to_numbered_list( [memory.summary() for memory in task.context.memories] + [info for info in task.context.supplementary_info], - no_items_response="There is no additional information available at this time.", + no_items_response=( + "There is no additional information available at this time." + ), **template_kwargs, ) template_kwargs["user_input"] = to_numbered_list( @@ -158,7 +171,7 @@ class NextAbility(PromptStrategy): def parse_response_content( self, - response_content: AssistantChatMessageDict, + response_content: AssistantChatMessage, ) -> dict: """Parse the actual text response from the objective model. @@ -170,9 +183,12 @@ class NextAbility(PromptStrategy): """ try: - function_name = response_content["tool_calls"][0]["function"]["name"] + if not response_content.tool_calls: + raise ValueError("LLM did not call any function") + + function_name = response_content.tool_calls[0].function.name function_arguments = json_loads( - response_content["tool_calls"][0]["function"]["arguments"] + response_content.tool_calls[0].function.arguments ) parsed_response = { "motivation": function_arguments.pop("motivation"), diff --git a/autogpts/autogpt/autogpt/core/planning/schema.py b/autogpts/autogpt/autogpt/core/planning/schema.py index 0af4cbcc1..b9ba81827 100644 --- a/autogpts/autogpt/autogpt/core/planning/schema.py +++ b/autogpts/autogpt/autogpt/core/planning/schema.py @@ -43,5 +43,6 @@ class Task(BaseModel): context: TaskContext = Field(default_factory=TaskContext) -# Need to resolve the circular dependency between Task and TaskContext once both models are defined. +# Need to resolve the circular dependency between Task and TaskContext +# once both models are defined. TaskContext.update_forward_refs() diff --git a/autogpts/autogpt/autogpt/core/planning/simple.py b/autogpts/autogpt/autogpt/core/planning/simple.py index 7306a3ab4..356e6712e 100644 --- a/autogpts/autogpt/autogpt/core/planning/simple.py +++ b/autogpts/autogpt/autogpt/core/planning/simple.py @@ -53,11 +53,17 @@ class PlannerSettings(SystemSettings): class SimplePlanner(Configurable): - """Manages the agent's planning and goal-setting by constructing language model prompts.""" + """ + Manages the agent's planning and goal-setting + by constructing language model prompts. + """ default_settings = PlannerSettings( name="planner", - description="Manages the agent's planning and goal-setting by constructing language model prompts.", + description=( + "Manages the agent's planning and goal-setting " + "by constructing language model prompts." + ), configuration=PlannerConfiguration( models={ LanguageModelClassification.FAST_MODEL: LanguageModelConfiguration( diff --git a/autogpts/autogpt/autogpt/core/planning/templates.py b/autogpts/autogpt/autogpt/core/planning/templates.py index 30df0a986..6464c8b8a 100644 --- a/autogpts/autogpt/autogpt/core/planning/templates.py +++ b/autogpts/autogpt/autogpt/core/planning/templates.py @@ -13,23 +13,6 @@ USER_OBJECTIVE = ( ) -ABILITIES = ( - 'analyze_code: Analyze Code, args: "code": "<full_code_string>"', - 'execute_python_file: Execute Python File, args: "filename": "<filename>"', - 'append_to_file: Append to file, args: "filename": "<filename>", "text": "<text>"', - 'list_files: List Files in Directory, args: "directory": "<directory>"', - 'read_file: Read a file, args: "filename": "<filename>"', - 'write_to_file: Write to file, args: "filename": "<filename>", "text": "<text>"', - 'google: Google Search, args: "query": "<query>"', - 'improve_code: Get Improved Code, args: "suggestions": "<list_of_suggestions>", "code": "<full_code_string>"', - 'browse_website: Browse Website, args: "url": "<url>", "question": "<what_you_want_to_find_on_website>"', - 'write_tests: Write Tests, args: "code": "<full_code_string>", "focus": "<list_of_focus_areas>"', - 'get_hyperlinks: Get hyperlinks, args: "url": "<url>"', - 'get_text_summary: Get text summary, args: "url": "<url>", "question": "<question>"', - 'task_complete: Task Complete (Shutdown), args: "reason": "<reason>"', -) - - # Plan Prompt # ----------- diff --git a/autogpts/autogpt/autogpt/core/plugin/__init__.py b/autogpts/autogpt/autogpt/core/plugin/__init__.py index dfa192591..b850114b3 100644 --- a/autogpts/autogpt/autogpt/core/plugin/__init__.py +++ b/autogpts/autogpt/autogpt/core/plugin/__init__.py @@ -1,2 +1,6 @@ """The plugin system allows the Agent to be extended with new functionality.""" from autogpt.core.plugin.base import PluginService + +__all__ = [ + "PluginService", +] diff --git a/autogpts/autogpt/autogpt/core/plugin/base.py b/autogpts/autogpt/autogpt/core/plugin/base.py index 4823dd260..4066a18c0 100644 --- a/autogpts/autogpt/autogpt/core/plugin/base.py +++ b/autogpts/autogpt/autogpt/core/plugin/base.py @@ -34,12 +34,19 @@ class PluginStorageFormat(str, enum.Enum): INSTALLED_PACKAGE = "installed_package" # Required now, loads system defaults WORKSPACE = "workspace" # Required now - # OPENAPI_URL = "open_api_url" # Soon (requires some tooling we don't have yet). + + # Soon (requires some tooling we don't have yet). + # OPENAPI_URL = "open_api_url" + # OTHER_FILE_PATH = "other_file_path" # Maybe later (maybe now) # GIT = "git" # Maybe later (or soon) # PYPI = "pypi" # Maybe later - # AUTOGPT_PLUGIN_SERVICE = "autogpt_plugin_service" # Long term solution, requires design - # AUTO = "auto" # Feature for later maybe, automatically find plugin. + + # Long term solution, requires design + # AUTOGPT_PLUGIN_SERVICE = "autogpt_plugin_service" + + # Feature for later maybe, automatically find plugin. + # AUTO = "auto" # Installed package example diff --git a/autogpts/autogpt/autogpt/core/plugin/simple.py b/autogpts/autogpt/autogpt/core/plugin/simple.py index aacf84aff..7f0e60608 100644 --- a/autogpts/autogpt/autogpt/core/plugin/simple.py +++ b/autogpts/autogpt/autogpt/core/plugin/simple.py @@ -28,7 +28,8 @@ class SimplePluginService(PluginService): ) else: raise NotImplementedError( - f"Plugin storage format {plugin_location.storage_format} is not implemented." + "Plugin storage format %s is not implemented." + % plugin_location.storage_format ) #################################### @@ -39,7 +40,7 @@ class SimplePluginService(PluginService): """Load a plugin from a file path.""" # TODO: Define an on disk storage format and implement this. # Can pull from existing zip file loading implementation - raise NotImplemented("Loading from file path is not implemented.") + raise NotImplementedError("Loading from file path is not implemented.") @staticmethod def load_from_import_path(plugin_route: PluginStorageRoute) -> "PluginType": @@ -56,7 +57,7 @@ class SimplePluginService(PluginService): # storage locations. E.g. if we know that path_type is a file path, we can # search the workspace for it. If it's an import path, we can check the core # system and the auto_gpt_plugins package. - raise NotImplemented("Resolving plugin name to path is not implemented.") + raise NotImplementedError("Resolving plugin name to path is not implemented.") ##################################### # High-level storage format loaders # diff --git a/autogpts/autogpt/autogpt/core/prompting/base.py b/autogpts/autogpt/autogpt/core/prompting/base.py index c983be987..19e315f69 100644 --- a/autogpts/autogpt/autogpt/core/prompting/base.py +++ b/autogpts/autogpt/autogpt/core/prompting/base.py @@ -1,7 +1,7 @@ import abc from autogpt.core.configuration import SystemConfiguration -from autogpt.core.resource.model_providers import AssistantChatMessageDict +from autogpt.core.resource.model_providers import AssistantChatMessage from .schema import ChatPrompt, LanguageModelClassification @@ -19,5 +19,5 @@ class PromptStrategy(abc.ABC): ... @abc.abstractmethod - def parse_response_content(self, response_content: AssistantChatMessageDict): + def parse_response_content(self, response_content: AssistantChatMessage): ... diff --git a/autogpts/autogpt/autogpt/core/prompting/utils.py b/autogpts/autogpt/autogpt/core/prompting/utils.py index a6c31cee7..4b1be47f4 100644 --- a/autogpts/autogpt/autogpt/core/prompting/utils.py +++ b/autogpts/autogpt/autogpt/core/prompting/utils.py @@ -14,9 +14,10 @@ def to_numbered_list( def json_loads(json_str: str): - # TODO: this is a hack function for now. Trying to see what errors show up in testing. - # Can hopefully just replace with a call to ast.literal_eval (the function api still - # sometimes returns json strings with minor issues like trailing commas). + # TODO: this is a hack function for now. We'll see what errors show up in testing. + # Can hopefully just replace with a call to ast.literal_eval. + # Can't use json.loads because the function API still sometimes returns json strings + # with minor issues like trailing commas. try: json_str = json_str[json_str.index("{") : json_str.rindex("}") + 1] return ast.literal_eval(json_str) diff --git a/autogpts/autogpt/autogpt/core/resource/__init__.py b/autogpts/autogpt/autogpt/core/resource/__init__.py index 12576c203..897e08777 100644 --- a/autogpts/autogpt/autogpt/core/resource/__init__.py +++ b/autogpts/autogpt/autogpt/core/resource/__init__.py @@ -5,3 +5,11 @@ from autogpt.core.resource.schema import ( ProviderUsage, ResourceType, ) + +__all__ = [ + "ProviderBudget", + "ProviderCredentials", + "ProviderSettings", + "ProviderUsage", + "ResourceType", +] diff --git a/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py b/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py index d242942ae..6d1eca5e5 100644 --- a/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py +++ b/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py @@ -1,21 +1,22 @@ import enum -import functools import logging import math -import time -from typing import Callable, Optional, ParamSpec, TypeVar +import os +from pathlib import Path +from typing import Callable, Coroutine, Iterator, Optional, ParamSpec, TypeVar -import openai +import tenacity import tiktoken -from openai.error import APIError, RateLimitError +import yaml +from openai._exceptions import APIStatusError, RateLimitError +from openai.types import CreateEmbeddingResponse +from openai.types.chat import ChatCompletion +from pydantic import SecretStr -from autogpt.core.configuration import ( - Configurable, - SystemConfiguration, - UserConfigurable, -) +from autogpt.core.configuration import Configurable, UserConfigurable from autogpt.core.resource.model_providers.schema import ( - AssistantChatMessageDict, + AssistantChatMessage, + AssistantToolCall, AssistantToolCallDict, ChatMessage, ChatModelInfo, @@ -27,6 +28,7 @@ from autogpt.core.resource.model_providers.schema import ( EmbeddingModelProvider, EmbeddingModelResponse, ModelProviderBudget, + ModelProviderConfiguration, ModelProviderCredentials, ModelProviderName, ModelProviderService, @@ -60,8 +62,10 @@ class OpenAIModelName(str, enum.Enum): GPT4_v2 = "gpt-4-0613" GPT4_v2_32k = "gpt-4-32k-0613" GPT4_v3 = "gpt-4-1106-preview" + GPT4_v4 = "gpt-4-0125-preview" GPT4_ROLLING = "gpt-4" GPT4_ROLLING_32k = "gpt-4-32k" + GPT4_TURBO = "gpt-4-turbo-preview" GPT4_VISION = "gpt-4-vision-preview" GPT4 = GPT4_ROLLING GPT4_32k = GPT4_ROLLING_32k @@ -128,7 +132,7 @@ OPEN_AI_CHAT_MODELS = { has_function_call_api=True, ), ChatModelInfo( - name=OpenAIModelName.GPT4_v3, + name=OpenAIModelName.GPT4_TURBO, service=ModelProviderService.CHAT, provider_name=ModelProviderName.OPENAI, prompt_token_cost=0.01 / 1000, @@ -147,6 +151,7 @@ chat_model_mapping = { OpenAIModelName.GPT4_v1_32k, OpenAIModelName.GPT4_v2_32k, ], + OpenAIModelName.GPT4_TURBO: [OpenAIModelName.GPT4_v3, OpenAIModelName.GPT4_v4], } for base, copies in chat_model_mapping.items(): for copy in copies: @@ -163,19 +168,86 @@ OPEN_AI_MODELS = { } -class OpenAIConfiguration(SystemConfiguration): - retries_per_request: int = UserConfigurable() +class OpenAIConfiguration(ModelProviderConfiguration): + fix_failed_parse_tries: int = UserConfigurable(3) + + +class OpenAICredentials(ModelProviderCredentials): + """Credentials for OpenAI.""" + + api_key: SecretStr = UserConfigurable(from_env="OPENAI_API_KEY") + api_base: Optional[SecretStr] = UserConfigurable( + default=None, from_env="OPENAI_API_BASE_URL" + ) + organization: Optional[SecretStr] = UserConfigurable(from_env="OPENAI_ORGANIZATION") + + api_type: str = UserConfigurable( + default="", + from_env=lambda: ( + "azure" + if os.getenv("USE_AZURE") == "True" + else os.getenv("OPENAI_API_TYPE") + ), + ) + api_version: str = UserConfigurable("", from_env="OPENAI_API_VERSION") + azure_endpoint: Optional[SecretStr] = None + azure_model_to_deploy_id_map: Optional[dict[str, str]] = None + + def get_api_access_kwargs(self) -> dict[str, str]: + kwargs = { + k: (v.get_secret_value() if type(v) is SecretStr else v) + for k, v in { + "api_key": self.api_key, + "base_url": self.api_base, + "organization": self.organization, + }.items() + if v is not None + } + if self.api_type == "azure": + kwargs["api_version"] = self.api_version + kwargs["azure_endpoint"] = self.azure_endpoint + return kwargs + + def get_model_access_kwargs(self, model: str) -> dict[str, str]: + kwargs = {"model": model} + if self.api_type == "azure" and model: + azure_kwargs = self._get_azure_access_kwargs(model) + kwargs.update(azure_kwargs) + return kwargs + + def load_azure_config(self, config_file: Path) -> None: + with open(config_file) as file: + config_params = yaml.load(file, Loader=yaml.FullLoader) or {} + + try: + assert config_params.get( + "azure_model_map", {} + ), "Azure model->deployment_id map is empty" + except AssertionError as e: + raise ValueError(*e.args) + self.api_type = config_params.get("azure_api_type", "azure") + self.api_version = config_params.get("azure_api_version", "") + self.azure_endpoint = config_params.get("azure_endpoint") + self.azure_model_to_deploy_id_map = config_params.get("azure_model_map") -class OpenAIModelProviderBudget(ModelProviderBudget): - graceful_shutdown_threshold: float = UserConfigurable() - warning_threshold: float = UserConfigurable() + def _get_azure_access_kwargs(self, model: str) -> dict[str, str]: + """Get the kwargs for the Azure API.""" + + if not self.azure_model_to_deploy_id_map: + raise ValueError("Azure model deployment map not configured") + + if model not in self.azure_model_to_deploy_id_map: + raise ValueError(f"No Azure deployment ID configured for model '{model}'") + deployment_id = self.azure_model_to_deploy_id_map[model] + + return {"model": deployment_id} class OpenAISettings(ModelProviderSettings): configuration: OpenAIConfiguration - credentials: ModelProviderCredentials - budget: OpenAIModelProviderBudget + credentials: Optional[OpenAICredentials] + budget: ModelProviderBudget class OpenAIProvider( @@ -187,8 +259,8 @@ class OpenAIProvider( configuration=OpenAIConfiguration( retries_per_request=10, ), - credentials=ModelProviderCredentials(), - budget=OpenAIModelProviderBudget( + credentials=None, + budget=ModelProviderBudget( total_budget=math.inf, total_cost=0.0, remaining_budget=math.inf, @@ -197,38 +269,41 @@ class OpenAIProvider( completion_tokens=0, total_tokens=0, ), - graceful_shutdown_threshold=0.005, - warning_threshold=0.01, ), ) + _budget: ModelProviderBudget + _configuration: OpenAIConfiguration + def __init__( self, settings: OpenAISettings, logger: logging.Logger, ): + self._settings = settings + + assert settings.credentials, "Cannot create OpenAIProvider without credentials" self._configuration = settings.configuration self._credentials = settings.credentials self._budget = settings.budget - self._logger = logger + if self._credentials.api_type == "azure": + from openai import AsyncAzureOpenAI - retry_handler = _OpenAIRetryHandler( - logger=self._logger, - num_retries=self._configuration.retries_per_request, - ) + # API key and org (if configured) are passed, the rest of the required + # credentials is loaded from the environment by the AzureOpenAI client. + self._client = AsyncAzureOpenAI(**self._credentials.get_api_access_kwargs()) + else: + from openai import AsyncOpenAI + + self._client = AsyncOpenAI(**self._credentials.get_api_access_kwargs()) - self._create_chat_completion = retry_handler(_create_chat_completion) - self._create_embedding = retry_handler(_create_embedding) + self._logger = logger def get_token_limit(self, model_name: str) -> int: """Get the token limit for a given model.""" return OPEN_AI_MODELS[model_name].max_tokens - def get_remaining_budget(self) -> float: - """Get the remaining budget.""" - return self._budget.remaining_budget - @classmethod def get_tokenizer(cls, model_name: OpenAIModelName) -> ModelTokenizer: return tiktoken.encoding_for_model(model_name) @@ -266,7 +341,7 @@ class OpenAIProvider( try: encoding = tiktoken.encoding_for_model(encoding_model) except KeyError: - cls._logger.warn( + logging.getLogger(__class__.__name__).warning( f"Model {model_name} not found. Defaulting to cl100k_base encoding." ) encoding = tiktoken.get_encoding("cl100k_base") @@ -285,7 +360,7 @@ class OpenAIProvider( self, model_prompt: list[ChatMessage], model_name: OpenAIModelName, - completion_parser: Callable[[AssistantChatMessageDict], _T] = lambda _: None, + completion_parser: Callable[[AssistantChatMessage], _T] = lambda _: None, functions: Optional[list[CompletionModelFunction]] = None, **kwargs, ) -> ChatModelResponse[_T]: @@ -297,27 +372,68 @@ class OpenAIProvider( model_prompt += completion_kwargs["messages"] del completion_kwargs["messages"] - response = await self._create_chat_completion( - messages=model_prompt, - **completion_kwargs, - ) - response_args = { - "model_info": OPEN_AI_CHAT_MODELS[model_name], - "prompt_tokens_used": response.usage.prompt_tokens, - "completion_tokens_used": response.usage.completion_tokens, - } + cost = 0.0 + attempts = 0 + while True: + _response = await self._create_chat_completion( + messages=model_prompt, + **completion_kwargs, + ) - response_message = response.choices[0].message.to_dict_recursive() - if tool_calls_compat_mode: - response_message["tool_calls"] = _tool_calls_compat_extract_calls( - response_message["content"] + _assistant_msg = _response.choices[0].message + assistant_msg = AssistantChatMessage( + content=_assistant_msg.content, + tool_calls=( + [AssistantToolCall(**tc.dict()) for tc in _assistant_msg.tool_calls] + if _assistant_msg.tool_calls + else None + ), ) - response = ChatModelResponse( - response=response_message, - parsed_result=completion_parser(response_message), - **response_args, - ) - self._budget.update_usage_and_cost(response) + response = ChatModelResponse( + response=assistant_msg, + model_info=OPEN_AI_CHAT_MODELS[model_name], + prompt_tokens_used=( + _response.usage.prompt_tokens if _response.usage else 0 + ), + completion_tokens_used=( + _response.usage.completion_tokens if _response.usage else 0 + ), + ) + cost += self._budget.update_usage_and_cost(response) + self._logger.debug( + f"Completion usage: {response.prompt_tokens_used} input, " + f"{response.completion_tokens_used} output - ${round(cost, 5)}" + ) + + # If parsing the response fails, append the error to the prompt, and let the + # LLM fix its mistake(s). + try: + attempts += 1 + + if ( + tool_calls_compat_mode + and assistant_msg.content + and not assistant_msg.tool_calls + ): + assistant_msg.tool_calls = list( + _tool_calls_compat_extract_calls(assistant_msg.content) + ) + + response.parsed_result = completion_parser(assistant_msg) + break + except Exception as e: + self._logger.warning(f"Parsing attempt #{attempts} failed: {e}") + self._logger.debug(f"Parsing failed on response: '''{assistant_msg}'''") + if attempts < self._configuration.fix_failed_parse_tries: + model_prompt.append( + ChatMessage.system(f"ERROR PARSING YOUR RESPONSE:\n\n{e}") + ) + else: + raise + + if attempts > 1: + self._logger.debug(f"Total cost for {attempts} attempts: ${round(cost, 5)}") + return response async def create_embedding( @@ -331,14 +447,11 @@ class OpenAIProvider( embedding_kwargs = self._get_embedding_kwargs(model_name, **kwargs) response = await self._create_embedding(text=text, **embedding_kwargs) - response_args = { - "model_info": OPEN_AI_EMBEDDING_MODELS[model_name], - "prompt_tokens_used": response.usage.prompt_tokens, - "completion_tokens_used": response.usage.completion_tokens, - } response = EmbeddingModelResponse( - **response_args, - embedding=embedding_parser(response.embeddings[0]), + embedding=embedding_parser(response.data[0].embedding), + model_info=OPEN_AI_EMBEDDING_MODELS[model_name], + prompt_tokens_used=response.usage.prompt_tokens, + completion_tokens_used=0, ) self._budget.update_usage_and_cost(response) return response @@ -359,28 +472,29 @@ class OpenAIProvider( The kwargs for the chat API call. """ - completion_kwargs = { - "model": model_name, - **kwargs, - **self._credentials.unmasked(), - } + kwargs.update(self._credentials.get_model_access_kwargs(model_name)) if functions: if OPEN_AI_CHAT_MODELS[model_name].has_function_call_api: - completion_kwargs["tools"] = [ + kwargs["tools"] = [ {"type": "function", "function": f.schema} for f in functions ] if len(functions) == 1: # force the model to call the only specified function - completion_kwargs["tool_choice"] = { + kwargs["tool_choice"] = { "type": "function", "function": {"name": functions[0].name}, } else: # Provide compatibility with older models - _functions_compat_fix_kwargs(functions, completion_kwargs) + _functions_compat_fix_kwargs(functions, kwargs) + + if extra_headers := self._configuration.extra_request_headers: + kwargs["extra_headers"] = kwargs.get("extra_headers", {}).update( + extra_headers.copy() + ) - return completion_kwargs + return kwargs def _get_embedding_kwargs( self, @@ -397,114 +511,82 @@ class OpenAIProvider( The kwargs for the embedding API call. """ - embedding_kwargs = { - "model": model_name, - **kwargs, - **self._credentials.unmasked(), - } + kwargs.update(self._credentials.get_model_access_kwargs(model_name)) - return embedding_kwargs - - def __repr__(self): - return "OpenAIProvider()" - - -async def _create_embedding(text: str, *_, **kwargs) -> openai.Embedding: - """Embed text using the OpenAI API. - - Args: - text str: The text to embed. - model str: The name of the model to use. - - Returns: - str: The embedding. - """ - return await openai.Embedding.acreate( - input=[text], - **kwargs, - ) - - -async def _create_chat_completion( - messages: list[ChatMessage], *_, **kwargs -) -> openai.Completion: - """Create a chat completion using the OpenAI API. - - Args: - messages: The prompt to use. - - Returns: - The completion. - """ - raw_messages = [ - message.dict(include={"role", "content", "tool_calls", "name"}) - for message in messages - ] - return await openai.ChatCompletion.acreate( - messages=raw_messages, - **kwargs, - ) - - -class _OpenAIRetryHandler: - """Retry Handler for OpenAI API call. - - Args: - num_retries int: Number of retries. Defaults to 10. - backoff_base float: Base for exponential backoff. Defaults to 2. - warn_user bool: Whether to warn the user. Defaults to True. - """ - - _retry_limit_msg = "Error: Reached rate limit, passing..." - _api_key_error_msg = ( - "Please double check that you have setup a PAID OpenAI API Account. You can " - "read more here: https://docs.agpt.co/setup/#getting-an-api-key" - ) - _backoff_msg = "Error: API Bad gateway. Waiting {backoff} seconds..." - - def __init__( - self, - logger: logging.Logger, - num_retries: int = 10, - backoff_base: float = 2.0, - warn_user: bool = True, - ): - self._logger = logger - self._num_retries = num_retries - self._backoff_base = backoff_base - self._warn_user = warn_user - - def _log_rate_limit_error(self) -> None: - self._logger.debug(self._retry_limit_msg) - if self._warn_user: - self._logger.warning(self._api_key_error_msg) - self._warn_user = False + if extra_headers := self._configuration.extra_request_headers: + kwargs["extra_headers"] = kwargs.get("extra_headers", {}).update( + extra_headers.copy() + ) - def _backoff(self, attempt: int) -> None: - backoff = self._backoff_base ** (attempt + 2) - self._logger.debug(self._backoff_msg.format(backoff=backoff)) - time.sleep(backoff) + return kwargs + + def _create_chat_completion( + self, messages: list[ChatMessage], *_, **kwargs + ) -> Coroutine[None, None, ChatCompletion]: + """Create a chat completion using the OpenAI API with retry handling.""" + + @self._retry_api_request + async def _create_chat_completion_with_retry( + messages: list[ChatMessage], *_, **kwargs + ) -> ChatCompletion: + raw_messages = [ + message.dict(include={"role", "content", "tool_calls", "name"}) + for message in messages + ] + return await self._client.chat.completions.create( + messages=raw_messages, # type: ignore + **kwargs, + ) - def __call__(self, func: Callable[_P, _T]) -> Callable[_P, _T]: - @functools.wraps(func) - async def _wrapped(*args: _P.args, **kwargs: _P.kwargs) -> _T: - num_attempts = self._num_retries + 1 # +1 for the first attempt - for attempt in range(1, num_attempts + 1): - try: - return await func(*args, **kwargs) + return _create_chat_completion_with_retry(messages, *_, **kwargs) - except RateLimitError: - if attempt == num_attempts: - raise - self._log_rate_limit_error() + def _create_embedding( + self, text: str, *_, **kwargs + ) -> Coroutine[None, None, CreateEmbeddingResponse]: + """Create an embedding using the OpenAI API with retry handling.""" - except APIError as e: - if (e.http_status != 502) or (attempt == num_attempts): - raise + @self._retry_api_request + async def _create_embedding_with_retry( + text: str, *_, **kwargs + ) -> CreateEmbeddingResponse: + return await self._client.embeddings.create( + input=[text], + **kwargs, + ) - self._backoff(attempt) + return _create_embedding_with_retry(text, *_, **kwargs) + + def _retry_api_request(self, func: Callable[_P, _T]) -> Callable[_P, _T]: + _log_retry_debug_message = tenacity.after_log(self._logger, logging.DEBUG) + + def _log_on_fail(retry_state: tenacity.RetryCallState) -> None: + _log_retry_debug_message(retry_state) + + if ( + retry_state.attempt_number == 0 + and retry_state.outcome + and isinstance(retry_state.outcome.exception(), RateLimitError) + ): + self._logger.warning( + "Please double check that you have setup a PAID OpenAI API Account." + " You can read more here: " + "https://docs.agpt.co/setup/#getting-an-openai-api-key" + ) + + return tenacity.retry( + retry=( + tenacity.retry_if_exception_type(RateLimitError) + | tenacity.retry_if_exception( + lambda e: isinstance(e, APIStatusError) and e.status_code == 502 + ) + ), + wait=tenacity.wait_exponential(), + stop=tenacity.stop_after_attempt(self._configuration.retries_per_request), + after=_log_on_fail, + )(func) - return _wrapped + def __repr__(self): + return "OpenAIProvider()" def format_function_specs_as_typescript_ns( @@ -572,10 +654,12 @@ def count_openai_functions_tokens( ) -> int: """Returns the number of tokens taken up by a set of function definitions - Reference: https://community.openai.com/t/how-to-calculate-the-tokens-when-using-function-call/266573/18 + Reference: https://community.openai.com/t/how-to-calculate-the-tokens-when-using-function-call/266573/18 # noqa: E501 """ return count_tokens( - f"# Tools\n\n## functions\n\n{format_function_specs_as_typescript_ns(functions)}" + "# Tools\n\n" + "## functions\n\n" + f"{format_function_specs_as_typescript_ns(functions)}" ) @@ -628,7 +712,7 @@ def _functions_compat_fix_kwargs( ] -def _tool_calls_compat_extract_calls(response: str) -> list[AssistantToolCallDict]: +def _tool_calls_compat_extract_calls(response: str) -> Iterator[AssistantToolCall]: import json import re @@ -639,10 +723,10 @@ def _tool_calls_compat_extract_calls(response: str) -> list[AssistantToolCallDic else: block = re.search(r"```(?:tool_calls)?\n(.*)\n```\s*$", response, re.DOTALL) if not block: - raise ValueError("Could not find tool calls block in response") + raise ValueError("Could not find tool_calls block in response") tool_calls: list[AssistantToolCallDict] = json.loads(block.group(1)) for t in tool_calls: t["function"]["arguments"] = str(t["function"]["arguments"]) # HACK - return tool_calls + yield AssistantToolCall.parse_obj(t) diff --git a/autogpts/autogpt/autogpt/core/resource/model_providers/schema.py b/autogpts/autogpt/autogpt/core/resource/model_providers/schema.py index ccf3255b4..2ed667725 100644 --- a/autogpts/autogpt/autogpt/core/resource/model_providers/schema.py +++ b/autogpts/autogpt/autogpt/core/resource/model_providers/schema.py @@ -1,5 +1,6 @@ import abc import enum +import math from typing import ( Callable, ClassVar, @@ -13,7 +14,7 @@ from typing import ( from pydantic import BaseModel, Field, SecretStr, validator -from autogpt.core.configuration import UserConfigurable +from autogpt.core.configuration import SystemConfiguration, UserConfigurable from autogpt.core.resource.schema import ( Embedding, ProviderBudget, @@ -90,7 +91,7 @@ class AssistantToolCallDict(TypedDict): class AssistantChatMessage(ChatMessage): - role: Literal["assistant"] + role: Literal["assistant"] = "assistant" content: Optional[str] tool_calls: Optional[list[AssistantToolCall]] @@ -163,6 +164,11 @@ class ModelResponse(BaseModel): model_info: ModelInfo +class ModelProviderConfiguration(SystemConfiguration): + retries_per_request: int = UserConfigurable() + extra_request_headers: dict[str, str] = Field(default_factory=dict) + + class ModelProviderCredentials(ProviderCredentials): """Credentials for a model provider.""" @@ -172,24 +178,10 @@ class ModelProviderCredentials(ProviderCredentials): api_version: SecretStr | None = UserConfigurable(default=None) deployment_id: SecretStr | None = UserConfigurable(default=None) - def unmasked(self) -> dict: - return unmask(self) - class Config: extra = "ignore" -def unmask(model: BaseModel): - unmasked_fields = {} - for field_name, field in model.__fields__.items(): - value = getattr(model, field_name) - if isinstance(value, SecretStr): - unmasked_fields[field_name] = value.get_secret_value() - else: - unmasked_fields[field_name] = value - return unmasked_fields - - class ModelProviderUsage(ProviderUsage): """Usage for a particular model from a model provider.""" @@ -217,8 +209,12 @@ class ModelProviderBudget(ProviderBudget): def update_usage_and_cost( self, model_response: ModelResponse, - ) -> None: - """Update the usage and cost of the provider.""" + ) -> float: + """Update the usage and cost of the provider. + + Returns: + float: The (calculated) cost of the given model response. + """ model_info = model_response.model_info self.usage.update_usage(model_response) incurred_cost = ( @@ -227,10 +223,12 @@ class ModelProviderBudget(ProviderBudget): ) self.total_cost += incurred_cost self.remaining_budget -= incurred_cost + return incurred_cost class ModelProviderSettings(ProviderSettings): resource_type: ResourceType = ResourceType.MODEL + configuration: ModelProviderConfiguration credentials: ModelProviderCredentials budget: ModelProviderBudget @@ -240,6 +238,9 @@ class ModelProvider(abc.ABC): default_settings: ClassVar[ModelProviderSettings] + _budget: Optional[ModelProviderBudget] + _configuration: ModelProviderConfiguration + @abc.abstractmethod def count_tokens(self, text: str, model_name: str) -> int: ... @@ -252,9 +253,15 @@ class ModelProvider(abc.ABC): def get_token_limit(self, model_name: str) -> int: ... - @abc.abstractmethod + def get_incurred_cost(self) -> float: + if self._budget: + return self._budget.total_cost + return 0 + def get_remaining_budget(self) -> float: - ... + if self._budget: + return self._budget.remaining_budget + return math.inf class ModelTokenizer(Protocol): @@ -326,7 +333,7 @@ _T = TypeVar("_T") class ChatModelResponse(ModelResponse, Generic[_T]): """Standard response struct for a response from a language model.""" - response: AssistantChatMessageDict + response: AssistantChatMessage parsed_result: _T = None @@ -344,7 +351,7 @@ class ChatModelProvider(ModelProvider): self, model_prompt: list[ChatMessage], model_name: str, - completion_parser: Callable[[AssistantChatMessageDict], _T] = lambda _: None, + completion_parser: Callable[[AssistantChatMessage], _T] = lambda _: None, functions: Optional[list[CompletionModelFunction]] = None, **kwargs, ) -> ChatModelResponse[_T]: diff --git a/autogpts/autogpt/autogpt/core/resource/schema.py b/autogpts/autogpt/autogpt/core/resource/schema.py index 0f97aedb0..d8cc1de31 100644 --- a/autogpts/autogpt/autogpt/core/resource/schema.py +++ b/autogpts/autogpt/autogpt/core/resource/schema.py @@ -1,7 +1,7 @@ import abc import enum -from pydantic import SecretBytes, SecretField, SecretStr +from pydantic import BaseModel, SecretBytes, SecretField, SecretStr from autogpt.core.configuration import ( SystemConfiguration, @@ -31,14 +31,21 @@ class ProviderBudget(SystemConfiguration): usage: ProviderUsage @abc.abstractmethod - def update_usage_and_cost(self, *args, **kwargs) -> None: - """Update the usage and cost of the resource.""" + def update_usage_and_cost(self, *args, **kwargs) -> float: + """Update the usage and cost of the provider. + + Returns: + float: The (calculated) cost of the given model response. + """ ... class ProviderCredentials(SystemConfiguration): """Struct for credentials.""" + def unmasked(self) -> dict: + return unmask(self) + class Config: json_encoders = { SecretStr: lambda v: v.get_secret_value() if v else None, @@ -47,6 +54,17 @@ class ProviderCredentials(SystemConfiguration): } +def unmask(model: BaseModel): + unmasked_fields = {} + for field_name, _ in model.__fields__.items(): + value = getattr(model, field_name) + if isinstance(value, SecretStr): + unmasked_fields[field_name] = value.get_secret_value() + else: + unmasked_fields[field_name] = value + return unmasked_fields + + class ProviderSettings(SystemSettings): resource_type: ResourceType credentials: ProviderCredentials | None = None diff --git a/autogpts/autogpt/autogpt/core/runner/cli_web_app/cli.py b/autogpts/autogpt/autogpt/core/runner/cli_web_app/cli.py index 4c5a33030..e00bb33b7 100644 --- a/autogpts/autogpt/autogpt/core/runner/cli_web_app/cli.py +++ b/autogpts/autogpt/autogpt/core/runner/cli_web_app/cli.py @@ -49,7 +49,9 @@ async def client(settings_file) -> None: if settings_file.exists(): settings = yaml.safe_load(settings_file.read_text()) - # TODO: Call the API server with the settings and task, using the Python API client for agent protocol. + settings + # TODO: Call the API server with the settings and task, + # using the Python API client for agent protocol. if __name__ == "__main__": diff --git a/autogpts/autogpt/autogpt/core/runner/cli_web_app/server/api.py b/autogpts/autogpt/autogpt/core/runner/cli_web_app/server/api.py index d1cbc2fdc..047cfd868 100644 --- a/autogpts/autogpt/autogpt/core/runner/cli_web_app/server/api.py +++ b/autogpts/autogpt/autogpt/core/runner/cli_web_app/server/api.py @@ -1,5 +1,4 @@ import logging -from pathlib import Path from agent_protocol import StepHandler, StepResult @@ -79,10 +78,10 @@ async def interaction_step( def bootstrap_agent(task, continuous_mode) -> Agent: config = ConfigBuilder.build_config_from_env() - config.debug_mode = True + config.logging.level = logging.DEBUG + config.logging.plain_console_output = True config.continuous_mode = continuous_mode config.temperature = 0 - config.plain_output = True command_registry = CommandRegistry.with_command_modules(COMMAND_CATEGORIES, config) config.memory_backend = "no_memory" ai_profile = AIProfile( diff --git a/autogpts/autogpt/autogpt/core/runner/client_lib/logging/config.py b/autogpts/autogpt/autogpt/core/runner/client_lib/logging/config.py index 52bfc76d0..56f79f5fe 100644 --- a/autogpts/autogpt/autogpt/core/runner/client_lib/logging/config.py +++ b/autogpts/autogpt/autogpt/core/runner/client_lib/logging/config.py @@ -2,7 +2,7 @@ import logging import sys from colorama import Fore, Style -from openai.util import logger as openai_logger +from openai._base_client import log as openai_logger SIMPLE_LOG_FORMAT = "%(asctime)s %(levelname)s %(message)s" DEBUG_LOG_FORMAT = ( @@ -51,7 +51,7 @@ class FancyConsoleFormatter(logging.Formatter): # Make sure `msg` is a string if not hasattr(record, "msg"): record.msg = "" - elif not type(record.msg) == str: + elif not type(record.msg) is str: record.msg = str(record.msg) # Determine default color based on error level diff --git a/autogpts/autogpt/autogpt/core/runner/client_lib/utils.py b/autogpts/autogpt/autogpt/core/runner/client_lib/utils.py index ebb03edb3..887683df7 100644 --- a/autogpts/autogpt/autogpt/core/runner/client_lib/utils.py +++ b/autogpts/autogpt/autogpt/core/runner/client_lib/utils.py @@ -17,9 +17,10 @@ def handle_exceptions( This is intended to be used as a wrapper for the main function of a CLI application. It will catch all errors and drop a user into a debugger if the error is not a - KeyboardInterrupt. If the error is a KeyboardInterrupt, it will raise the error. - If the error is not a KeyboardInterrupt, it will log the error and drop a user into a - debugger if with_debugger is True. If with_debugger is False, it will raise the error. + `KeyboardInterrupt`. If the error is a `KeyboardInterrupt`, it will raise the error. + If the error is not a `KeyboardInterrupt`, it will log the error and drop a user + into a debugger if `with_debugger` is `True`. + If `with_debugger` is `False`, it will raise the error. Parameters ---------- diff --git a/autogpts/autogpt/autogpt/core/utils/json_schema.py b/autogpts/autogpt/autogpt/core/utils/json_schema.py index 743d70d58..c9f9026e0 100644 --- a/autogpts/autogpt/autogpt/core/utils/json_schema.py +++ b/autogpts/autogpt/autogpt/core/utils/json_schema.py @@ -1,5 +1,4 @@ import enum -import json from logging import Logger from textwrap import indent from typing import Literal, Optional @@ -96,24 +95,15 @@ class JSONSchema(BaseModel): schema (JSONSchema): The JSONSchema to validate against. Returns: - tuple: A tuple where the first element is a boolean indicating whether the object is valid or not, - and the second element is a list of errors found in the object, or None if the object is valid. + tuple: A tuple where the first element is a boolean indicating whether the + object is valid or not, and the second element is a list of errors found + in the object, or None if the object is valid. """ validator = Draft7Validator(self.to_dict()) if errors := sorted(validator.iter_errors(object), key=lambda e: e.path): - for error in errors: - logger.debug(f"JSON Validation Error: {error}") - - logger.error(json.dumps(object, indent=4)) - logger.error("The following issues were found:") - - for error in errors: - logger.error(f"Error: {error.message}") return False, errors - logger.debug("The JSON object is valid.") - return True, None def to_typescript_object_interface(self, interface_name: str = "") -> str: diff --git a/autogpts/autogpt/autogpt/core/workspace/__init__.py b/autogpts/autogpt/autogpt/core/workspace/__init__.py index f474d4faa..ae1877dee 100644 --- a/autogpts/autogpt/autogpt/core/workspace/__init__.py +++ b/autogpts/autogpt/autogpt/core/workspace/__init__.py @@ -1,3 +1,9 @@ """The workspace is the central hub for the Agent's on disk resources.""" from autogpt.core.workspace.base import Workspace from autogpt.core.workspace.simple import SimpleWorkspace, WorkspaceSettings + +__all__ = [ + "SimpleWorkspace", + "Workspace", + "WorkspaceSettings", +] diff --git a/autogpts/autogpt/autogpt/core/workspace/simple.py b/autogpts/autogpt/autogpt/core/workspace/simple.py index 45e1f9dd6..1c7a3f903 100644 --- a/autogpts/autogpt/autogpt/core/workspace/simple.py +++ b/autogpts/autogpt/autogpt/core/workspace/simple.py @@ -136,7 +136,8 @@ class SimpleWorkspace(Configurable, Workspace): if relative_path.is_absolute(): raise ValueError( - f"Attempted to access absolute path '{relative_path}' in workspace '{root}'." + f"Attempted to access absolute path '{relative_path}' " + f"in workspace '{root}'." ) full_path = root.joinpath(relative_path).resolve() diff --git a/autogpts/autogpt/autogpt/file_workspace/__init__.py b/autogpts/autogpt/autogpt/file_workspace/__init__.py index 76a26eefe..a0e06e38f 100644 --- a/autogpts/autogpt/autogpt/file_workspace/__init__.py +++ b/autogpts/autogpt/autogpt/file_workspace/__init__.py @@ -1,5 +1,46 @@ -from .file_workspace import FileWorkspace +import enum +from pathlib import Path +from typing import Optional + +from .base import FileWorkspace + + +class FileWorkspaceBackendName(str, enum.Enum): + LOCAL = "local" + GCS = "gcs" + S3 = "s3" + + +def get_workspace( + backend: FileWorkspaceBackendName, *, id: str = "", root_path: Optional[Path] = None +) -> FileWorkspace: + assert bool(root_path) != bool(id), "Specify root_path or id to get workspace" + if root_path is None: + root_path = Path(f"/workspaces/{id}") + + match backend: + case FileWorkspaceBackendName.LOCAL: + from .local import FileWorkspaceConfiguration, LocalFileWorkspace + + config = FileWorkspaceConfiguration.from_env() + config.root = root_path + return LocalFileWorkspace(config) + case FileWorkspaceBackendName.S3: + from .s3 import S3FileWorkspace, S3FileWorkspaceConfiguration + + config = S3FileWorkspaceConfiguration.from_env() + config.root = root_path + return S3FileWorkspace(config) + case FileWorkspaceBackendName.GCS: + from .gcs import GCSFileWorkspace, GCSFileWorkspaceConfiguration + + config = GCSFileWorkspaceConfiguration.from_env() + config.root = root_path + return GCSFileWorkspace(config) + __all__ = [ "FileWorkspace", + "FileWorkspaceBackendName", + "get_workspace", ] diff --git a/autogpts/autogpt/autogpt/file_workspace/file_workspace.py b/autogpts/autogpt/autogpt/file_workspace/base.py index 61b3c42f1..865b34dd5 100644 --- a/autogpts/autogpt/autogpt/file_workspace/file_workspace.py +++ b/autogpts/autogpt/autogpt/file_workspace/base.py @@ -3,18 +3,24 @@ The FileWorkspace class provides an interface for interacting with a file worksp """ from __future__ import annotations -import inspect import logging +from abc import ABC, abstractmethod +from io import IOBase, TextIOBase from pathlib import Path -from typing import Any, Callable, Optional +from typing import IO, Any, BinaryIO, Callable, Literal, Optional, TextIO, overload + +from autogpt.core.configuration.schema import SystemConfiguration logger = logging.getLogger(__name__) -class FileWorkspace: - """A class that represents a file workspace.""" +class FileWorkspaceConfiguration(SystemConfiguration): + restrict_to_root: bool = True + root: Path = Path("/") - NULL_BYTES = ["\0", "\000", "\x00", "\u0000"] + +class FileWorkspace(ABC): + """A class that represents a file workspace.""" on_write_file: Callable[[Path], Any] | None = None """ @@ -24,22 +30,69 @@ class FileWorkspace: Path: The path of the file that was written, relative to the workspace root. """ - def __init__(self, root: str | Path, restrict_to_root: bool): - self._root = self._sanitize_path(root) - self._restrict_to_root = restrict_to_root - @property + @abstractmethod def root(self) -> Path: - """The root directory of the file workspace.""" - return self._root + """The root path of the file workspace.""" @property - def restrict_to_root(self): - """Whether to restrict generated paths to the root.""" - return self._restrict_to_root + @abstractmethod + def restrict_to_root(self) -> bool: + """Whether to restrict file access to within the workspace's root path.""" + @abstractmethod def initialize(self) -> None: - self.root.mkdir(exist_ok=True, parents=True) + """ + Calling `initialize()` should bring the workspace to a ready-to-use state. + For example, it can create the resource in which files will be stored, if it + doesn't exist yet. E.g. a folder on disk, or an S3 Bucket. + """ + + @overload + @abstractmethod + def open_file( + self, path: str | Path, binary: Literal[False] = False + ) -> TextIO | TextIOBase: + """Returns a readable text file-like object representing the file.""" + + @overload + @abstractmethod + def open_file( + self, path: str | Path, binary: Literal[True] = True + ) -> BinaryIO | IOBase: + """Returns a readable binary file-like object representing the file.""" + + @abstractmethod + def open_file(self, path: str | Path, binary: bool = False) -> IO | IOBase: + """Returns a readable file-like object representing the file.""" + + @overload + @abstractmethod + def read_file(self, path: str | Path, binary: Literal[False] = False) -> str: + """Read a file in the workspace as text.""" + ... + + @overload + @abstractmethod + def read_file(self, path: str | Path, binary: Literal[True] = True) -> bytes: + """Read a file in the workspace as binary.""" + ... + + @abstractmethod + def read_file(self, path: str | Path, binary: bool = False) -> str | bytes: + """Read a file in the workspace.""" + + @abstractmethod + async def write_file(self, path: str | Path, content: str | bytes) -> None: + """Write to a file in the workspace.""" + + @abstractmethod + def list(self, path: str | Path = ".") -> list[Path]: + """List all files (recursively) in a directory in the workspace.""" + + @abstractmethod + def delete_file(self, path: str | Path) -> None: + """Delete a file in the workspace.""" def get_path(self, relative_path: str | Path) -> Path: """Get the full path for an item in the workspace. @@ -50,44 +103,7 @@ class FileWorkspace: Returns: Path: The resolved path relative to the workspace. """ - return self._sanitize_path( - relative_path, - root=self.root, - restrict_to_root=self.restrict_to_root, - ) - - def open_file(self, path: str | Path, mode: str = "r"): - """Open a file in the workspace.""" - full_path = self.get_path(path) - return open(full_path, mode) - - def read_file(self, path: str | Path, binary: bool = False): - """Read a file in the workspace.""" - with self.open_file(path, "rb" if binary else "r") as file: - return file.read() - - async def write_file(self, path: str | Path, content: str | bytes): - """Write to a file in the workspace.""" - with self.open_file(path, "wb" if type(content) is bytes else "w") as file: - file.write(content) - - if self.on_write_file: - path = Path(path) - if path.is_absolute(): - path = path.relative_to(self.root) - res = self.on_write_file(path) - if inspect.isawaitable(res): - await res - - def list_files(self, path: str | Path = "."): - """List all files in a directory in the workspace.""" - full_path = self.get_path(path) - return [str(file) for file in full_path.glob("*") if file.is_file()] - - def delete_file(self, path: str | Path): - """Delete a file in the workspace.""" - full_path = self.get_path(path) - full_path.unlink() + return self._sanitize_path(relative_path, self.root) @staticmethod def _sanitize_path( @@ -113,9 +129,8 @@ class FileWorkspace: # Posix systems disallow null bytes in paths. Windows is agnostic about it. # Do an explicit check here for all sorts of null byte representations. - for null_byte in FileWorkspace.NULL_BYTES: - if null_byte in str(relative_path) or null_byte in str(root): - raise ValueError("embedded null byte") + if "\0" in str(relative_path) or "\0" in str(root): + raise ValueError("embedded null byte") if root is None: return Path(relative_path).resolve() @@ -133,7 +148,8 @@ class FileWorkspace: and not relative_path.is_relative_to(root) ): raise ValueError( - f"Attempted to access absolute path '{relative_path}' in workspace '{root}'." + f"Attempted to access absolute path '{relative_path}' " + f"in workspace '{root}'." ) full_path = root.joinpath(relative_path).resolve() diff --git a/autogpts/autogpt/autogpt/file_workspace/gcs.py b/autogpts/autogpt/autogpt/file_workspace/gcs.py new file mode 100644 index 000000000..f1203cd57 --- /dev/null +++ b/autogpts/autogpt/autogpt/file_workspace/gcs.py @@ -0,0 +1,113 @@ +""" +The GCSWorkspace class provides an interface for interacting with a file workspace, and +stores the files in a Google Cloud Storage bucket. +""" +from __future__ import annotations + +import inspect +import logging +from io import IOBase +from pathlib import Path + +from google.cloud import storage +from google.cloud.exceptions import NotFound + +from autogpt.core.configuration.schema import UserConfigurable + +from .base import FileWorkspace, FileWorkspaceConfiguration + +logger = logging.getLogger(__name__) + + +class GCSFileWorkspaceConfiguration(FileWorkspaceConfiguration): + bucket: str = UserConfigurable("autogpt", from_env="WORKSPACE_STORAGE_BUCKET") + + +class GCSFileWorkspace(FileWorkspace): + """A class that represents a Google Cloud Storage workspace.""" + + _bucket: storage.Bucket + + def __init__(self, config: GCSFileWorkspaceConfiguration): + self._bucket_name = config.bucket + self._root = config.root + assert self._root.is_absolute() + + self._gcs = storage.Client() + super().__init__() + + @property + def root(self) -> Path: + """The root directory of the file workspace.""" + return self._root + + @property + def restrict_to_root(self) -> bool: + """Whether to restrict generated paths to the root.""" + return True + + def initialize(self) -> None: + logger.debug(f"Initializing {repr(self)}...") + try: + self._bucket = self._gcs.get_bucket(self._bucket_name) + except NotFound: + logger.info(f"Bucket '{self._bucket_name}' does not exist; creating it...") + self._bucket = self._gcs.create_bucket(self._bucket_name) + + def get_path(self, relative_path: str | Path) -> Path: + return super().get_path(relative_path).relative_to("/") + + def _get_blob(self, path: str | Path) -> storage.Blob: + path = self.get_path(path) + return self._bucket.blob(str(path)) + + def open_file(self, path: str | Path, binary: bool = False) -> IOBase: + """Open a file in the workspace.""" + blob = self._get_blob(path) + blob.reload() # pin revision number to prevent version mixing while reading + return blob.open("rb" if binary else "r") + + def read_file(self, path: str | Path, binary: bool = False) -> str | bytes: + """Read a file in the workspace.""" + return self.open_file(path, binary).read() + + async def write_file(self, path: str | Path, content: str | bytes) -> None: + """Write to a file in the workspace.""" + blob = self._get_blob(path) + + blob.upload_from_string( + data=content, + content_type=( + "text/plain" + if type(content) is str + # TODO: get MIME type from file extension or binary content + else "application/octet-stream" + ), + ) + + if self.on_write_file: + path = Path(path) + if path.is_absolute(): + path = path.relative_to(self.root) + res = self.on_write_file(path) + if inspect.isawaitable(res): + await res + + def list(self, path: str | Path = ".") -> list[Path]: + """List all files (recursively) in a directory in the workspace.""" + path = self.get_path(path) + return [ + Path(blob.name).relative_to(path) + for blob in self._bucket.list_blobs( + prefix=f"{path}/" if path != Path(".") else None + ) + ] + + def delete_file(self, path: str | Path) -> None: + """Delete a file in the workspace.""" + path = self.get_path(path) + blob = self._bucket.blob(str(path)) + blob.delete() + + def __repr__(self) -> str: + return f"{__class__.__name__}(bucket='{self._bucket_name}', root={self._root})" diff --git a/autogpts/autogpt/autogpt/file_workspace/local.py b/autogpts/autogpt/autogpt/file_workspace/local.py new file mode 100644 index 000000000..8c2aa6521 --- /dev/null +++ b/autogpts/autogpt/autogpt/file_workspace/local.py @@ -0,0 +1,71 @@ +""" +The LocalFileWorkspace class implements a FileWorkspace that works with local files. +""" +from __future__ import annotations + +import inspect +import logging +from pathlib import Path +from typing import IO + +from .base import FileWorkspace, FileWorkspaceConfiguration + +logger = logging.getLogger(__name__) + + +class LocalFileWorkspace(FileWorkspace): + """A class that represents a file workspace.""" + + def __init__(self, config: FileWorkspaceConfiguration): + self._root = self._sanitize_path(config.root) + self._restrict_to_root = config.restrict_to_root + super().__init__() + + @property + def root(self) -> Path: + """The root directory of the file workspace.""" + return self._root + + @property + def restrict_to_root(self) -> bool: + """Whether to restrict generated paths to the root.""" + return self._restrict_to_root + + def initialize(self) -> None: + self.root.mkdir(exist_ok=True, parents=True) + + def open_file(self, path: str | Path, binary: bool = False) -> IO: + """Open a file in the workspace.""" + return self._open_file(path, "rb" if binary else "r") + + def _open_file(self, path: str | Path, mode: str = "r") -> IO: + full_path = self.get_path(path) + return open(full_path, mode) # type: ignore + + def read_file(self, path: str | Path, binary: bool = False) -> str | bytes: + """Read a file in the workspace.""" + with self._open_file(path, "rb" if binary else "r") as file: + return file.read() + + async def write_file(self, path: str | Path, content: str | bytes) -> None: + """Write to a file in the workspace.""" + with self._open_file(path, "wb" if type(content) is bytes else "w") as file: + file.write(content) + + if self.on_write_file: + path = Path(path) + if path.is_absolute(): + path = path.relative_to(self.root) + res = self.on_write_file(path) + if inspect.isawaitable(res): + await res + + def list(self, path: str | Path = ".") -> list[Path]: + """List all files (recursively) in a directory in the workspace.""" + path = self.get_path(path) + return [file.relative_to(path) for file in path.rglob("*") if file.is_file()] + + def delete_file(self, path: str | Path) -> None: + """Delete a file in the workspace.""" + full_path = self.get_path(path) + full_path.unlink() diff --git a/autogpts/autogpt/autogpt/file_workspace/s3.py b/autogpts/autogpt/autogpt/file_workspace/s3.py new file mode 100644 index 000000000..a60291374 --- /dev/null +++ b/autogpts/autogpt/autogpt/file_workspace/s3.py @@ -0,0 +1,128 @@ +""" +The S3Workspace class provides an interface for interacting with a file workspace, and +stores the files in an S3 bucket. +""" +from __future__ import annotations + +import contextlib +import inspect +import logging +import os +from io import IOBase, TextIOWrapper +from pathlib import Path +from typing import TYPE_CHECKING, Optional + +import boto3 +import botocore.exceptions +from pydantic import SecretStr + +from autogpt.core.configuration.schema import UserConfigurable + +from .base import FileWorkspace, FileWorkspaceConfiguration + +if TYPE_CHECKING: + import mypy_boto3_s3 + +logger = logging.getLogger(__name__) + + +class S3FileWorkspaceConfiguration(FileWorkspaceConfiguration): + bucket: str = UserConfigurable("autogpt", from_env="WORKSPACE_STORAGE_BUCKET") + s3_endpoint_url: Optional[SecretStr] = UserConfigurable( + from_env=lambda: SecretStr(v) if (v := os.getenv("S3_ENDPOINT_URL")) else None + ) + + +class S3FileWorkspace(FileWorkspace): + """A class that represents an S3 workspace.""" + + _bucket: mypy_boto3_s3.service_resource.Bucket + + def __init__(self, config: S3FileWorkspaceConfiguration): + self._bucket_name = config.bucket + self._root = config.root + assert self._root.is_absolute() + + # https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html + self._s3 = boto3.resource( + "s3", + endpoint_url=config.s3_endpoint_url.get_secret_value() + if config.s3_endpoint_url + else None, + ) + + super().__init__() + + @property + def root(self) -> Path: + """The root directory of the file workspace.""" + return self._root + + @property + def restrict_to_root(self): + """Whether to restrict generated paths to the root.""" + return True + + def initialize(self) -> None: + logger.debug(f"Initializing {repr(self)}...") + try: + self._s3.meta.client.head_bucket(Bucket=self._bucket_name) + self._bucket = self._s3.Bucket(self._bucket_name) + except botocore.exceptions.ClientError as e: + if "(404)" not in str(e): + raise + logger.info(f"Bucket '{self._bucket_name}' does not exist; creating it...") + self._bucket = self._s3.create_bucket(Bucket=self._bucket_name) + + def get_path(self, relative_path: str | Path) -> Path: + return super().get_path(relative_path).relative_to("/") + + def _get_obj(self, path: str | Path) -> mypy_boto3_s3.service_resource.Object: + """Get an S3 object.""" + path = self.get_path(path) + obj = self._bucket.Object(str(path)) + with contextlib.suppress(botocore.exceptions.ClientError): + obj.load() + return obj + + def open_file(self, path: str | Path, binary: bool = False) -> IOBase: + """Open a file in the workspace.""" + obj = self._get_obj(path) + return obj.get()["Body"] if binary else TextIOWrapper(obj.get()["Body"]) + + def read_file(self, path: str | Path, binary: bool = False) -> str | bytes: + """Read a file in the workspace.""" + return self.open_file(path, binary).read() + + async def write_file(self, path: str | Path, content: str | bytes) -> None: + """Write to a file in the workspace.""" + obj = self._get_obj(path) + obj.put(Body=content) + + if self.on_write_file: + path = Path(path) + if path.is_absolute(): + path = path.relative_to(self.root) + res = self.on_write_file(path) + if inspect.isawaitable(res): + await res + + def list(self, path: str | Path = ".") -> list[Path]: + """List all files (recursively) in a directory in the workspace.""" + path = self.get_path(path) + if path == Path("."): # root level of bucket + return [Path(obj.key) for obj in self._bucket.objects.all()] + else: + return [ + Path(obj.key).relative_to(path) + for obj in self._bucket.objects.filter(Prefix=f"{path}/") + ] + + def delete_file(self, path: str | Path) -> None: + """Delete a file in the workspace.""" + path = self.get_path(path) + obj = self._s3.Object(self._bucket_name, str(path)) + obj.delete() + + def __repr__(self) -> str: + return f"{__class__.__name__}(bucket='{self._bucket_name}', root={self._root})" diff --git a/autogpts/autogpt/autogpt/json_utils/utilities.py b/autogpts/autogpt/autogpt/json_utils/utilities.py index 876106ade..0521372e0 100644 --- a/autogpts/autogpt/autogpt/json_utils/utilities.py +++ b/autogpts/autogpt/autogpt/json_utils/utilities.py @@ -1,6 +1,7 @@ """Utilities for the json_fixes package.""" import ast import logging +import re from typing import Any logger = logging.getLogger(__name__) @@ -8,15 +9,25 @@ logger = logging.getLogger(__name__) def extract_dict_from_response(response_content: str) -> dict[str, Any]: # Sometimes the response includes the JSON in a code block with ``` - if response_content.startswith("```") and response_content.endswith("```"): - # Discard the first and last ```, then re-join in case the response naturally included ``` - response_content = "```".join(response_content.split("```")[1:-1]) + pattern = r"```(?:json|JSON)*([\s\S]*?)```" + match = re.search(pattern, response_content) - # response content comes from OpenAI as a Python `str(content_dict)`, literal_eval reverses this - try: - return ast.literal_eval(response_content) - except BaseException as e: - logger.info(f"Error parsing JSON response with literal_eval {e}") - logger.debug(f"Invalid JSON received in response: {response_content}") - # TODO: How to raise an error here without causing the program to exit? - return {} + if match: + response_content = match.group(1).strip() + else: + # The string may contain JSON. + json_pattern = r"{[\s\S]*}" + match = re.search(json_pattern, response_content) + + if match: + response_content = match.group() + + # Response content comes from OpenAI as a Python `str(content_dict)`. + # `literal_eval` does the reverse of `str(dict)`. + result = ast.literal_eval(response_content) + if not isinstance(result, dict): + raise ValueError( + f"Response '''{response_content}''' evaluated to " + f"non-dict value {repr(result)}" + ) + return result diff --git a/autogpts/autogpt/autogpt/llm/api_manager.py b/autogpts/autogpt/autogpt/llm/api_manager.py index 146263626..35d28d632 100644 --- a/autogpts/autogpt/autogpt/llm/api_manager.py +++ b/autogpts/autogpt/autogpt/llm/api_manager.py @@ -3,10 +3,13 @@ from __future__ import annotations import logging from typing import List, Optional -import openai -from openai import Model +from openai import OpenAI +from openai.types import Model -from autogpt.core.resource.model_providers.openai import OPEN_AI_MODELS +from autogpt.core.resource.model_providers.openai import ( + OPEN_AI_MODELS, + OpenAICredentials, +) from autogpt.core.resource.model_providers.schema import ChatModelInfo from autogpt.singleton import Singleton @@ -96,16 +99,17 @@ class ApiManager(metaclass=Singleton): """ return self.total_budget - def get_models(self, **openai_credentials) -> List[Model]: + def get_models(self, openai_credentials: OpenAICredentials) -> List[Model]: """ Get list of available GPT models. Returns: - list: List of available GPT models. - + list[Model]: List of available GPT models. """ if self.models is None: - all_models = openai.Model.list(**openai_credentials)["data"] - self.models = [model for model in all_models if "gpt" in model["id"]] + all_models = ( + OpenAI(**openai_credentials.get_api_access_kwargs()).models.list().data + ) + self.models = [model for model in all_models if "gpt" in model.id] return self.models diff --git a/autogpts/autogpt/autogpt/logs/__init__.py b/autogpts/autogpt/autogpt/logs/__init__.py index abcdac713..dc99649e5 100644 --- a/autogpts/autogpt/autogpt/logs/__init__.py +++ b/autogpts/autogpt/autogpt/logs/__init__.py @@ -1,3 +1,4 @@ +from .config import configure_chat_plugins, configure_logging from .helpers import user_friendly_output from .log_cycle import ( CURRENT_CONTEXT_FILE_NAME, @@ -9,3 +10,17 @@ from .log_cycle import ( USER_INPUT_FILE_NAME, LogCycleHandler, ) + +__all__ = [ + "configure_logging", + "configure_chat_plugins", + "user_friendly_output", + "CURRENT_CONTEXT_FILE_NAME", + "NEXT_ACTION_FILE_NAME", + "PROMPT_SUMMARY_FILE_NAME", + "PROMPT_SUPERVISOR_FEEDBACK_FILE_NAME", + "SUMMARY_FILE_NAME", + "SUPERVISOR_FEEDBACK_FILE_NAME", + "USER_INPUT_FILE_NAME", + "LogCycleHandler", +] diff --git a/autogpts/autogpt/autogpt/logs/config.py b/autogpts/autogpt/autogpt/logs/config.py index 7b8a043b1..ae483d0f8 100644 --- a/autogpts/autogpt/autogpt/logs/config.py +++ b/autogpts/autogpt/autogpt/logs/config.py @@ -1,21 +1,24 @@ """Logging module for Auto-GPT.""" from __future__ import annotations +import enum import logging +import os import sys from pathlib import Path from typing import TYPE_CHECKING, Optional from auto_gpt_plugin_template import AutoGPTPluginTemplate -from openai.util import logger as openai_logger +from openai._base_client import log as openai_logger if TYPE_CHECKING: from autogpt.config import Config from autogpt.speech import TTSConfig +from autogpt.core.configuration import SystemConfiguration, UserConfigurable from autogpt.core.runner.client_lib.logging import BelowLevelFilter -from .formatters import AutoGptFormatter +from .formatters import AutoGptFormatter, StructuredLoggingFormatter from .handlers import TTSHandler, TypingConsoleHandler LOG_DIR = Path(__file__).parent.parent.parent / "logs" @@ -34,80 +37,141 @@ USER_FRIENDLY_OUTPUT_LOGGER = "USER_FRIENDLY_OUTPUT" _chat_plugins: list[AutoGPTPluginTemplate] = [] +class LogFormatName(str, enum.Enum): + SIMPLE = "simple" + DEBUG = "debug" + STRUCTURED = "structured_google_cloud" + + +TEXT_LOG_FORMAT_MAP = { + LogFormatName.DEBUG: DEBUG_LOG_FORMAT, + LogFormatName.SIMPLE: SIMPLE_LOG_FORMAT, +} + + +class LoggingConfig(SystemConfiguration): + level: int = UserConfigurable( + default=logging.INFO, + from_env=lambda: logging.getLevelName(os.getenv("LOG_LEVEL", "INFO")), + ) + + # Console output + log_format: LogFormatName = UserConfigurable( + default=LogFormatName.SIMPLE, + from_env=lambda: LogFormatName(os.getenv("LOG_FORMAT", "simple")), + ) + plain_console_output: bool = UserConfigurable( + default=False, + from_env=lambda: os.getenv("PLAIN_OUTPUT", "False") == "True", + ) + + # File output + log_dir: Path = LOG_DIR + log_file_format: Optional[LogFormatName] = UserConfigurable( + default=LogFormatName.SIMPLE, + from_env=lambda: LogFormatName( + os.getenv("LOG_FILE_FORMAT", os.getenv("LOG_FORMAT", "simple")) + ), + ) + + def configure_logging( - debug_mode: bool = False, - plain_output: bool = False, - tts_config: Optional[TTSConfig] = None, + level: int = logging.INFO, log_dir: Path = LOG_DIR, + log_format: Optional[LogFormatName] = None, + log_file_format: Optional[LogFormatName] = None, + plain_console_output: bool = False, + tts_config: Optional[TTSConfig] = None, ) -> None: - """Configure the native logging module.""" + """Configure the native logging module. + + Should be usable as `configure_logging(**config.logging.dict())`, where + `config.logging` is a `LoggingConfig` object. + """ + + # Auto-adjust default log format based on log level + log_format = log_format or ( + LogFormatName.SIMPLE if level != logging.DEBUG else LogFormatName.DEBUG + ) + log_file_format = log_file_format or log_format + + structured_logging = log_format == LogFormatName.STRUCTURED + + if structured_logging: + plain_console_output = True + log_file_format = None # create log directory if it doesn't exist if not log_dir.exists(): log_dir.mkdir() - log_level = logging.DEBUG if debug_mode else logging.INFO - log_format = DEBUG_LOG_FORMAT if debug_mode else SIMPLE_LOG_FORMAT - console_formatter = AutoGptFormatter(log_format) + log_handlers: list[logging.Handler] = [] + + if log_format in (LogFormatName.DEBUG, LogFormatName.SIMPLE): + console_format_template = TEXT_LOG_FORMAT_MAP[log_format] + console_formatter = AutoGptFormatter(console_format_template) + else: + console_formatter = StructuredLoggingFormatter() + console_format_template = SIMPLE_LOG_FORMAT # Console output handlers stdout = logging.StreamHandler(stream=sys.stdout) - stdout.setLevel(log_level) + stdout.setLevel(level) stdout.addFilter(BelowLevelFilter(logging.WARNING)) stdout.setFormatter(console_formatter) stderr = logging.StreamHandler() stderr.setLevel(logging.WARNING) stderr.setFormatter(console_formatter) - - # INFO log file handler - activity_log_handler = logging.FileHandler(log_dir / LOG_FILE, "a", "utf-8") - activity_log_handler.setLevel(logging.INFO) - activity_log_handler.setFormatter( - AutoGptFormatter(SIMPLE_LOG_FORMAT, no_color=True) - ) - - if debug_mode: - # DEBUG log file handler - debug_log_handler = logging.FileHandler(log_dir / DEBUG_LOG_FILE, "a", "utf-8") - debug_log_handler.setLevel(logging.DEBUG) - debug_log_handler.setFormatter( - AutoGptFormatter(DEBUG_LOG_FORMAT, no_color=True) - ) - - # ERROR log file handler - error_log_handler = logging.FileHandler(log_dir / ERROR_LOG_FILE, "a", "utf-8") - error_log_handler.setLevel(logging.ERROR) - error_log_handler.setFormatter(AutoGptFormatter(DEBUG_LOG_FORMAT, no_color=True)) - - # Configure the root logger - logging.basicConfig( - format=log_format, - level=log_level, - handlers=( - [stdout, stderr, activity_log_handler, error_log_handler] - + ([debug_log_handler] if debug_mode else []) - ), - ) - - ## Set up user-friendly loggers + log_handlers += [stdout, stderr] # Console output handler which simulates typing typing_console_handler = TypingConsoleHandler(stream=sys.stdout) typing_console_handler.setLevel(logging.INFO) typing_console_handler.setFormatter(console_formatter) + # User friendly output logger (text + speech) user_friendly_output_logger = logging.getLogger(USER_FRIENDLY_OUTPUT_LOGGER) user_friendly_output_logger.setLevel(logging.INFO) user_friendly_output_logger.addHandler( - typing_console_handler if not plain_output else stdout + typing_console_handler if not plain_console_output else stdout ) if tts_config: user_friendly_output_logger.addHandler(TTSHandler(tts_config)) - user_friendly_output_logger.addHandler(activity_log_handler) - user_friendly_output_logger.addHandler(error_log_handler) user_friendly_output_logger.addHandler(stderr) user_friendly_output_logger.propagate = False + # File output handlers + if log_file_format is not None: + if level < logging.ERROR: + file_output_format_template = TEXT_LOG_FORMAT_MAP[log_file_format] + file_output_formatter = AutoGptFormatter( + file_output_format_template, no_color=True + ) + + # INFO log file handler + activity_log_handler = logging.FileHandler(log_dir / LOG_FILE, "a", "utf-8") + activity_log_handler.setLevel(level) + activity_log_handler.setFormatter(file_output_formatter) + log_handlers += [activity_log_handler] + user_friendly_output_logger.addHandler(activity_log_handler) + + # ERROR log file handler + error_log_handler = logging.FileHandler(log_dir / ERROR_LOG_FILE, "a", "utf-8") + error_log_handler.setLevel(logging.ERROR) + error_log_handler.setFormatter( + AutoGptFormatter(DEBUG_LOG_FORMAT, no_color=True) + ) + log_handlers += [error_log_handler] + user_friendly_output_logger.addHandler(error_log_handler) + + # Configure the root logger + logging.basicConfig( + format=console_format_template, + level=level, + handlers=log_handlers, + ) + + # Speech output speech_output_logger = logging.getLogger(SPEECH_OUTPUT_LOGGER) speech_output_logger.setLevel(logging.INFO) if tts_config: @@ -120,7 +184,7 @@ def configure_logging( json_logger.propagate = False # Disable debug logging from OpenAI library - openai_logger.setLevel(logging.INFO) + openai_logger.setLevel(logging.WARNING) def configure_chat_plugins(config: Config) -> None: diff --git a/autogpts/autogpt/autogpt/logs/formatters.py b/autogpts/autogpt/autogpt/logs/formatters.py index 4930d3c73..a51112573 100644 --- a/autogpts/autogpt/autogpt/logs/formatters.py +++ b/autogpts/autogpt/autogpt/logs/formatters.py @@ -1,6 +1,7 @@ import logging from colorama import Style +from google.cloud.logging_v2.handlers import CloudLoggingFilter, StructuredLogHandler from autogpt.core.runner.client_lib.logging import FancyConsoleFormatter @@ -16,7 +17,7 @@ class AutoGptFormatter(FancyConsoleFormatter): # Make sure `msg` is a string if not hasattr(record, "msg"): record.msg = "" - elif not type(record.msg) == str: + elif not type(record.msg) is str: record.msg = str(record.msg) # Strip color from the message to prevent color spoofing @@ -37,3 +38,16 @@ class AutoGptFormatter(FancyConsoleFormatter): return remove_color_codes(super().format(record)) else: return super().format(record) + + +class StructuredLoggingFormatter(StructuredLogHandler, logging.Formatter): + def __init__(self): + # Set up CloudLoggingFilter to add diagnostic info to the log records + self.cloud_logging_filter = CloudLoggingFilter() + + # Init StructuredLogHandler + super().__init__() + + def format(self, record: logging.LogRecord) -> str: + self.cloud_logging_filter.filter(record) + return super().format(record) diff --git a/autogpts/autogpt/autogpt/logs/helpers.py b/autogpts/autogpt/autogpt/logs/helpers.py index b19ee45b2..580e09a8a 100644 --- a/autogpts/autogpt/autogpt/logs/helpers.py +++ b/autogpts/autogpt/autogpt/logs/helpers.py @@ -53,10 +53,9 @@ def print_attribute( def request_user_double_check(additionalText: Optional[str] = None) -> None: if not additionalText: additionalText = ( - "Please ensure you've setup and configured everything" - " correctly. Read https://github.com/Significant-Gravitas/AutoGPT/autogpts/autogpt#readme to " - "double check. You can also create a github issue or join the discord" - " and ask there!" + "Please ensure you've setup and configured everything correctly. " + "Read https://docs.agpt.co/autogpt/setup/ to double check. " + "You can also create a github issue or join the discord and ask there!" ) user_friendly_output( diff --git a/autogpts/autogpt/autogpt/logs/utils.py b/autogpts/autogpt/autogpt/logs/utils.py index 0b92e2967..d9f39af30 100644 --- a/autogpts/autogpt/autogpt/logs/utils.py +++ b/autogpts/autogpt/autogpt/logs/utils.py @@ -3,3 +3,7 @@ import re def remove_color_codes(s: str) -> str: return re.sub(r"\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])", "", s) + + +def fmt_kwargs(kwargs: dict) -> str: + return ", ".join(f"{n}={repr(v)}" for n, v in kwargs.items()) diff --git a/autogpts/autogpt/autogpt/memory/vector/__init__.py b/autogpts/autogpt/autogpt/memory/vector/__init__.py index 238584e39..bcef31a41 100644 --- a/autogpts/autogpt/autogpt/memory/vector/__init__.py +++ b/autogpts/autogpt/autogpt/memory/vector/__init__.py @@ -1,8 +1,6 @@ -import logging - from autogpt.config import Config -from .memory_item import MemoryItem, MemoryItemRelevance +from .memory_item import MemoryItem, MemoryItemFactory, MemoryItemRelevance from .providers.base import VectorMemoryProvider as VectorMemory from .providers.json_file import JSONFileMemory from .providers.no_memory import NoMemory @@ -41,7 +39,8 @@ supported_memory = ["json_file", "no_memory"] def get_memory(config: Config) -> VectorMemory: - """Returns a memory object corresponding to the memory backend specified in the config. + """ + Returns a memory object corresponding to the memory backend specified in the config. The type of memory object returned depends on the value of the `memory_backend` attribute in the configuration. E.g. if `memory_backend` is set to "pinecone", a @@ -50,11 +49,11 @@ def get_memory(config: Config) -> VectorMemory: By default, a `JSONFileMemory` object is returned. Params: - config: A configuration object that contains information about the memory backend - to be used and other relevant parameters. + config: A configuration object that contains information about the memory + backend to be used and other relevant parameters. Returns: - VectorMemory: an instance of a memory object based on the configuration provided. + VectorMemory: an instance of a memory object based on the configuration provided """ memory = None @@ -65,12 +64,12 @@ def get_memory(config: Config) -> VectorMemory: case "pinecone": raise NotImplementedError( "The Pinecone memory backend has been rendered incompatible by work on " - "the memory system, and was removed. Whether support will be added back " - "in the future is subject to discussion, feel free to pitch in: " + "the memory system, and was removed. Whether support will be added " + "back in the future is subject to discussion, feel free to pitch in: " "https://github.com/Significant-Gravitas/AutoGPT/discussions/4280" ) # if not PineconeMemory: - # logger.warn( + # logger.warning( # "Error: Pinecone is not installed. Please install pinecone" # " to use Pinecone as a memory backend." # ) @@ -85,7 +84,7 @@ def get_memory(config: Config) -> VectorMemory: "the memory system, and has been removed temporarily." ) # if not RedisMemory: - # logger.warn( + # logger.warning( # "Error: Redis is not installed. Please install redis-py to" # " use Redis as a memory backend." # ) @@ -95,14 +94,14 @@ def get_memory(config: Config) -> VectorMemory: case "weaviate": raise NotImplementedError( "The Weaviate memory backend has been rendered incompatible by work on " - "the memory system, and was removed. Whether support will be added back " - "in the future is subject to discussion, feel free to pitch in: " + "the memory system, and was removed. Whether support will be added " + "back in the future is subject to discussion, feel free to pitch in: " "https://github.com/Significant-Gravitas/AutoGPT/discussions/4280" ) # if not WeaviateMemory: - # logger.warn( - # "Error: Weaviate is not installed. Please install weaviate-client to" - # " use Weaviate as a memory backend." + # logger.warning( + # "Error: Weaviate is not installed. Please install weaviate-client" + # " to use Weaviate as a memory backend." # ) # else: # memory = WeaviateMemory(config) @@ -110,14 +109,15 @@ def get_memory(config: Config) -> VectorMemory: case "milvus": raise NotImplementedError( "The Milvus memory backend has been rendered incompatible by work on " - "the memory system, and was removed. Whether support will be added back " - "in the future is subject to discussion, feel free to pitch in: " + "the memory system, and was removed. Whether support will be added " + "back in the future is subject to discussion, feel free to pitch in: " "https://github.com/Significant-Gravitas/AutoGPT/discussions/4280" ) # if not MilvusMemory: - # logger.warn( - # "Error: pymilvus sdk is not installed." - # "Please install pymilvus to use Milvus or Zilliz Cloud as memory backend." + # logger.warning( + # "Error: pymilvus sdk is not installed, but required " + # "to use Milvus or Zilliz as memory backend. " + # "Please install pymilvus." # ) # else: # memory = MilvusMemory(config) @@ -127,7 +127,8 @@ def get_memory(config: Config) -> VectorMemory: case _: raise ValueError( - f"Unknown memory backend '{config.memory_backend}'. Please check your config." + f"Unknown memory backend '{config.memory_backend}'." + " Please check your config." ) if memory is None: @@ -143,6 +144,7 @@ def get_supported_memory_backends(): __all__ = [ "get_memory", "MemoryItem", + "MemoryItemFactory", "MemoryItemRelevance", "JSONFileMemory", "NoMemory", diff --git a/autogpts/autogpt/autogpt/memory/vector/memory_item.py b/autogpts/autogpt/autogpt/memory/vector/memory_item.py index 7ca8c7880..8d03d0209 100644 --- a/autogpts/autogpt/autogpt/memory/vector/memory_item.py +++ b/autogpts/autogpt/autogpt/memory/vector/memory_item.py @@ -9,7 +9,11 @@ import numpy as np from pydantic import BaseModel from autogpt.config import Config -from autogpt.core.resource.model_providers import ChatMessage +from autogpt.core.resource.model_providers import ( + ChatMessage, + ChatModelProvider, + EmbeddingModelProvider, +) from autogpt.processing.text import chunk_content, split_text, summarize_text from .utils import Embedding, get_embedding @@ -19,7 +23,6 @@ logger = logging.getLogger(__name__) MemoryDocType = Literal["webpage", "text_file", "code_file", "agent_history"] -# FIXME: implement validators instead of allowing arbitrary types class MemoryItem(BaseModel, arbitrary_types_allowed=True): """Memory object containing raw content as well as embeddings""" @@ -34,8 +37,56 @@ class MemoryItem(BaseModel, arbitrary_types_allowed=True): def relevance_for(self, query: str, e_query: Embedding | None = None): return MemoryItemRelevance.of(self, query, e_query) - @staticmethod - def from_text( + def dump(self, calculate_length=False) -> str: + n_chunks = len(self.e_chunks) + return f""" +=============== MemoryItem =============== +Size: {n_chunks} chunks +Metadata: {json.dumps(self.metadata, indent=2)} +---------------- SUMMARY ----------------- +{self.summary} +------------------ RAW ------------------- +{self.raw_content} +========================================== +""" + + def __eq__(self, other: MemoryItem): + return ( + self.raw_content == other.raw_content + and self.chunks == other.chunks + and self.chunk_summaries == other.chunk_summaries + # Embeddings can either be list[float] or np.ndarray[float32], + # and for comparison they must be of the same type + and np.array_equal( + self.e_summary + if isinstance(self.e_summary, np.ndarray) + else np.array(self.e_summary, dtype=np.float32), + other.e_summary + if isinstance(other.e_summary, np.ndarray) + else np.array(other.e_summary, dtype=np.float32), + ) + and np.array_equal( + self.e_chunks + if isinstance(self.e_chunks[0], np.ndarray) + else [np.array(c, dtype=np.float32) for c in self.e_chunks], + other.e_chunks + if isinstance(other.e_chunks[0], np.ndarray) + else [np.array(c, dtype=np.float32) for c in other.e_chunks], + ) + ) + + +class MemoryItemFactory: + def __init__( + self, + llm_provider: ChatModelProvider, + embedding_provider: EmbeddingModelProvider, + ): + self.llm_provider = llm_provider + self.embedding_provider = embedding_provider + + async def from_text( + self, text: str, source_type: MemoryDocType, config: Config, @@ -52,9 +103,19 @@ class MemoryItem(BaseModel, arbitrary_types_allowed=True): chunks = [ chunk for chunk, _ in ( - split_text(text, config.embedding_model, config) + split_text( + text=text, + config=config, + max_chunk_length=1000, # arbitrary, but shorter ~= better + tokenizer=self.llm_provider.get_tokenizer(config.fast_llm), + ) if source_type != "code_file" - else chunk_content(text, config.embedding_model) + # TODO: chunk code based on structure/outline + else chunk_content( + content=text, + max_chunk_length=1000, + tokenizer=self.llm_provider.get_tokenizer(config.fast_llm), + ) ) ] logger.debug("Chunks: " + str(chunks)) @@ -62,34 +123,38 @@ class MemoryItem(BaseModel, arbitrary_types_allowed=True): chunk_summaries = [ summary for summary, _ in [ - summarize_text( - text_chunk, - config, + await summarize_text( + text=text_chunk, instruction=how_to_summarize, question=question_for_summary, + llm_provider=self.llm_provider, + config=config, ) for text_chunk in chunks ] ] logger.debug("Chunk summaries: " + str(chunk_summaries)) - e_chunks = get_embedding(chunks, config) + e_chunks = get_embedding(chunks, config, self.embedding_provider) summary = ( chunk_summaries[0] if len(chunks) == 1 - else summarize_text( - "\n\n".join(chunk_summaries), - config, - instruction=how_to_summarize, - question=question_for_summary, + else ( + await summarize_text( + text="\n\n".join(chunk_summaries), + instruction=how_to_summarize, + question=question_for_summary, + llm_provider=self.llm_provider, + config=config, + ) )[0] ) logger.debug("Total summary: " + summary) # TODO: investigate search performance of weighted average vs summary # e_average = np.average(e_chunks, axis=0, weights=[len(c) for c in chunks]) - e_summary = get_embedding(summary, config) + e_summary = get_embedding(summary, config, self.embedding_provider) metadata["source_type"] = source_type @@ -103,17 +168,14 @@ class MemoryItem(BaseModel, arbitrary_types_allowed=True): metadata=metadata, ) - @staticmethod - def from_text_file(content: str, path: str, config: Config): - return MemoryItem.from_text(content, "text_file", config, {"location": path}) + def from_text_file(self, content: str, path: str, config: Config): + return self.from_text(content, "text_file", config, {"location": path}) - @staticmethod - def from_code_file(content: str, path: str): + def from_code_file(self, content: str, path: str): # TODO: implement tailored code memories - return MemoryItem.from_text(content, "code_file", {"location": path}) + return self.from_text(content, "code_file", {"location": path}) - @staticmethod - def from_ai_action(ai_message: ChatMessage, result_message: ChatMessage): + def from_ai_action(self, ai_message: ChatMessage, result_message: ChatMessage): # The result_message contains either user feedback # or the result of the command specified in ai_message @@ -138,17 +200,20 @@ class MemoryItem(BaseModel, arbitrary_types_allowed=True): f"Human Feedback: {user_input}" ) - return MemoryItem.from_text( + return self.from_text( text=memory_content, source_type="agent_history", - how_to_summarize="if possible, also make clear the link between the command in the assistant's response and the command result. Do not mention the human feedback if there is none", + how_to_summarize=( + "if possible, also make clear the link between the command in the" + " assistant's response and the command result. " + "Do not mention the human feedback if there is none.", + ), ) - @staticmethod def from_webpage( - content: str, url: str, config: Config, question: str | None = None + self, content: str, url: str, config: Config, question: str | None = None ): - return MemoryItem.from_text( + return self.from_text( text=content, source_type="webpage", config=config, @@ -156,47 +221,6 @@ class MemoryItem(BaseModel, arbitrary_types_allowed=True): question_for_summary=question, ) - def dump(self, calculate_length=False) -> str: - if calculate_length: - token_length = self.llm_provider.count_tokens( - self.raw_content, Config().embedding_model - ) - return f""" -=============== MemoryItem =============== -Size: {f'{token_length} tokens in ' if calculate_length else ''}{len(self.e_chunks)} chunks -Metadata: {json.dumps(self.metadata, indent=2)} ----------------- SUMMARY ----------------- -{self.summary} ------------------- RAW ------------------- -{self.raw_content} -========================================== -""" - - def __eq__(self, other: MemoryItem): - return ( - self.raw_content == other.raw_content - and self.chunks == other.chunks - and self.chunk_summaries == other.chunk_summaries - # Embeddings can either be list[float] or np.ndarray[float32], - # and for comparison they must be of the same type - and np.array_equal( - self.e_summary - if isinstance(self.e_summary, np.ndarray) - else np.array(self.e_summary, dtype=np.float32), - other.e_summary - if isinstance(other.e_summary, np.ndarray) - else np.array(other.e_summary, dtype=np.float32), - ) - and np.array_equal( - self.e_chunks - if isinstance(self.e_chunks[0], np.ndarray) - else [np.array(c, dtype=np.float32) for c in self.e_chunks], - other.e_chunks - if isinstance(other.e_chunks[0], np.ndarray) - else [np.array(c, dtype=np.float32) for c in other.e_chunks], - ) - ) - class MemoryItemRelevance(BaseModel): """ diff --git a/autogpts/autogpt/autogpt/memory/vector/providers/json_file.py b/autogpts/autogpt/autogpt/memory/vector/providers/json_file.py index 2d6733183..efab7e8f6 100644 --- a/autogpts/autogpt/autogpt/memory/vector/providers/json_file.py +++ b/autogpts/autogpt/autogpt/memory/vector/providers/json_file.py @@ -42,7 +42,7 @@ class JSONFileMemory(VectorMemoryProvider): self.load_index() logger.debug(f"Loaded {len(self.memories)} MemoryItems from file") except Exception as e: - logger.warn(f"Could not load MemoryItems from file: {e}") + logger.warning(f"Could not load MemoryItems from file: {e}") self.save_index() def __iter__(self) -> Iterator[MemoryItem]: @@ -63,7 +63,7 @@ class JSONFileMemory(VectorMemoryProvider): def discard(self, item: MemoryItem): try: self.remove(item) - except: + except ValueError: # item not in memory pass def clear(self): diff --git a/autogpts/autogpt/autogpt/memory/vector/utils.py b/autogpts/autogpt/autogpt/memory/vector/utils.py index 1023230c1..b8b87a491 100644 --- a/autogpts/autogpt/autogpt/memory/vector/utils.py +++ b/autogpts/autogpt/autogpt/memory/vector/utils.py @@ -5,6 +5,7 @@ from typing import Any, Sequence, overload import numpy as np from autogpt.config import Config +from autogpt.core.resource.model_providers import EmbeddingModelProvider logger = logging.getLogger(__name__) @@ -16,23 +17,32 @@ TText = Sequence[int] @overload -def get_embedding(input: str | TText, config: Config) -> Embedding: +async def get_embedding( + input: str | TText, config: Config, embedding_provider: EmbeddingModelProvider +) -> Embedding: ... @overload -def get_embedding(input: list[str] | list[TText], config: Config) -> list[Embedding]: +async def get_embedding( + input: list[str] | list[TText], + config: Config, + embedding_provider: EmbeddingModelProvider, +) -> list[Embedding]: ... -def get_embedding( - input: str | TText | list[str] | list[TText], config: Config +async def get_embedding( + input: str | TText | list[str] | list[TText], + config: Config, + embedding_provider: EmbeddingModelProvider, ) -> Embedding | list[Embedding]: """Get an embedding from the ada model. Args: input: Input text to get embeddings for, encoded as a string or array of tokens. Multiple inputs may be given as a list of strings or token arrays. + embedding_provider: The provider to create embeddings. Returns: List[float]: The embedding. @@ -52,25 +62,30 @@ def get_embedding( return [_get_embedding_with_plugin(i, config) for i in input] model = config.embedding_model - kwargs = {"model": model} - kwargs.update(config.get_openai_credentials(model)) logger.debug( f"Getting embedding{f's for {len(input)} inputs' if multiple else ''}" f" with model '{model}'" - + (f" via Azure deployment '{kwargs['engine']}'" if config.use_azure else "") ) - embeddings = embedding_provider.create_embedding( - input, - **kwargs, - ).data - if not multiple: - return embeddings[0]["embedding"] - - embeddings = sorted(embeddings, key=lambda x: x["index"]) - return [d["embedding"] for d in embeddings] + return ( + await embedding_provider.create_embedding( + text=input, + model_name=model, + embedding_parser=lambda e: e, + ) + ).embedding + else: + embeddings = [] + for text in input: + result = await embedding_provider.create_embedding( + text=text, + model_name=model, + embedding_parser=lambda e: e, + ) + embeddings.append(result.embedding) + return embeddings def _get_embedding_with_plugin(text: str, config: Config) -> Embedding: diff --git a/autogpts/autogpt/autogpt/models/action_history.py b/autogpts/autogpt/autogpt/models/action_history.py index a5ed8f28f..b36d7e540 100644 --- a/autogpts/autogpt/autogpt/models/action_history.py +++ b/autogpts/autogpt/autogpt/models/action_history.py @@ -13,7 +13,10 @@ class Action(BaseModel): reasoning: str def format_call(self) -> str: - return f"{self.name}({', '.join([f'{a}={repr(v)}' for a, v in self.args.items()])})" + return ( + f"{self.name}" + f"({', '.join([f'{a}={repr(v)}' for a, v in self.args.items()])})" + ) class ActionSuccessResult(BaseModel): @@ -69,7 +72,10 @@ class ActionInterruptedByHuman(BaseModel): status: Literal["interrupted_by_human"] = "interrupted_by_human" def __str__(self) -> str: - return f'The user interrupted the action with the following feedback: "{self.feedback}"' + return ( + 'The user interrupted the action with the following feedback: "%s"' + % self.feedback + ) ActionResult = ActionSuccessResult | ActionErrorResult | ActionInterruptedByHuman diff --git a/autogpts/autogpt/autogpt/models/command.py b/autogpts/autogpt/autogpt/models/command.py index 98b576037..90aa266cc 100644 --- a/autogpts/autogpt/autogpt/models/command.py +++ b/autogpts/autogpt/autogpt/models/command.py @@ -62,7 +62,11 @@ class Command: def __str__(self) -> str: params = [ - f"{param.name}: {param.spec.type.value if param.spec.required else f'Optional[{param.spec.type.value}]'}" + f"{param.name}: " + + ("%s" if param.spec.required else "Optional[%s]") % param.spec.type.value for param in self.parameters ] - return f"{self.name}: {self.description.rstrip('.')}. Params: ({', '.join(params)})" + return ( + f"{self.name}: {self.description.rstrip('.')}. " + f"Params: ({', '.join(params)})" + ) diff --git a/autogpts/autogpt/autogpt/models/command_parameter.py b/autogpts/autogpt/autogpt/models/command_parameter.py index 979b65173..402e870fc 100644 --- a/autogpts/autogpt/autogpt/models/command_parameter.py +++ b/autogpts/autogpt/autogpt/models/command_parameter.py @@ -9,4 +9,9 @@ class CommandParameter: spec: JSONSchema def __repr__(self): - return f"CommandParameter('{self.name}', '{self.spec.type}', '{self.spec.description}', {self.spec.required})" + return "CommandParameter('%s', '%s', '%s', %s)" % ( + self.name, + self.spec.type, + self.spec.description, + self.spec.required, + ) diff --git a/autogpts/autogpt/autogpt/models/command_registry.py b/autogpts/autogpt/autogpt/models/command_registry.py index eb61eb594..ec372c9f5 100644 --- a/autogpts/autogpt/autogpt/models/command_registry.py +++ b/autogpts/autogpt/autogpt/models/command_registry.py @@ -56,13 +56,13 @@ class CommandRegistry: def register(self, cmd: Command) -> None: if cmd.name in self.commands: - logger.warn( + logger.warning( f"Command '{cmd.name}' already registered and will be overwritten!" ) self.commands[cmd.name] = cmd if cmd.name in self.commands_aliases: - logger.warn( + logger.warning( f"Command '{cmd.name}' will overwrite alias with the same name of " f"'{self.commands_aliases[cmd.name]}'!" ) @@ -116,11 +116,14 @@ class CommandRegistry: yield cmd # def command_specs(self) -> str: - # """Returns a technical declaration of all commands in the registry for use in a prompt""" + # """ + # Returns a technical declaration of all commands in the registry, + # for use in a prompt. + # """ # - # Declaring functions or commands should be done in a model-specific way to achieve - # optimal results. For this reason, it should NOT be implemented here, but in an - # LLM provider module. + # Declaring functions or commands should be done in a model-specific way to + # achieve optimal results. For this reason, it should NOT be implemented here, + # but in an LLM provider module. # MUST take command AVAILABILITY into account. @staticmethod @@ -128,7 +131,8 @@ class CommandRegistry: new_registry = CommandRegistry() logger.debug( - f"The following command categories are disabled: {config.disabled_command_categories}" + "The following command categories are disabled: " + f"{config.disabled_command_categories}" ) enabled_command_modules = [ x for x in modules if x not in config.disabled_command_categories diff --git a/autogpts/autogpt/autogpt/models/context_item.py b/autogpts/autogpt/autogpt/models/context_item.py index 17a2a0b8e..a669bdcc8 100644 --- a/autogpts/autogpt/autogpt/models/context_item.py +++ b/autogpts/autogpt/autogpt/models/context_item.py @@ -1,11 +1,12 @@ import logging +import os.path from abc import ABC, abstractmethod from pathlib import Path from typing import Optional from pydantic import BaseModel, Field -from autogpt.commands.file_operations_utils import read_textual_file +from autogpt.commands.file_operations_utils import decode_textual_file logger = logging.getLogger(__name__) @@ -56,7 +57,9 @@ class FileContextItem(BaseModel, ContextItem): @property def content(self) -> str: - return read_textual_file(self.file_path, logger) + # TODO: use workspace.open_file() + with open(self.file_path, "rb") as file: + return decode_textual_file(file, os.path.splitext(file.name)[1], logger) class FolderContextItem(BaseModel, ContextItem): diff --git a/autogpts/autogpt/autogpt/plugins/__init__.py b/autogpts/autogpt/autogpt/plugins/__init__.py index 534c2f2d1..0b08a62e4 100644 --- a/autogpts/autogpt/autogpt/plugins/__init__.py +++ b/autogpts/autogpt/autogpt/plugins/__init__.py @@ -11,7 +11,7 @@ import zipfile from pathlib import Path from typing import TYPE_CHECKING, List from urllib.parse import urlparse -from zipimport import zipimporter +from zipimport import ZipImportError, zipimporter import openapi_python_client import requests @@ -26,7 +26,7 @@ from autogpt.models.base_open_ai_plugin import BaseOpenAIPlugin logger = logging.getLogger(__name__) -def inspect_zip_for_modules(zip_path: str, debug: bool = False) -> list[str]: +def inspect_zip_for_modules(zip_path: str) -> list[str]: """ Inspect a zipfile for a modules. @@ -78,12 +78,13 @@ def fetch_openai_plugins_manifest_and_spec(config: Config) -> dict: if response.status_code == 200: manifest = response.json() if manifest["schema_version"] != "v1": - logger.warn( - f"Unsupported manifest version: {manifest['schem_version']} for {url}" + logger.warning( + "Unsupported manifest version: " + f"{manifest['schem_version']} for {url}" ) continue if manifest["api"]["type"] != "openapi": - logger.warn( + logger.warning( f"Unsupported API type: {manifest['api']['type']} for {url}" ) continue @@ -91,11 +92,11 @@ def fetch_openai_plugins_manifest_and_spec(config: Config) -> dict: manifest, f"{openai_plugin_client_dir}/ai-plugin.json" ) else: - logger.warn( + logger.warning( f"Failed to fetch manifest for {url}: {response.status_code}" ) except requests.exceptions.RequestException as e: - logger.warn(f"Error while requesting manifest from {url}: {e}") + logger.warning(f"Error while requesting manifest from {url}: {e}") else: logger.info(f"Manifest for {url} already exists") manifest = json.load(open(f"{openai_plugin_client_dir}/ai-plugin.json")) @@ -127,16 +128,14 @@ def create_directory_if_not_exists(directory_path: str) -> bool: logger.debug(f"Created directory: {directory_path}") return True except OSError as e: - logger.warn(f"Error creating directory {directory_path}: {e}") + logger.warning(f"Error creating directory {directory_path}: {e}") return False else: logger.info(f"Directory {directory_path} already exists") return True -def initialize_openai_plugins( - manifests_specs: dict, config: Config, debug: bool = False -) -> dict: +def initialize_openai_plugins(manifests_specs: dict, config: Config) -> dict: """ Initialize OpenAI plugins. Args: @@ -168,7 +167,7 @@ def initialize_openai_plugins( config=_config, ) if client_results: - logger.warn( + logger.warning( f"Error creating OpenAPI client: {client_results[0].header} \n" f" details: {client_results[0].detail}" ) @@ -188,9 +187,7 @@ def initialize_openai_plugins( return manifests_specs -def instantiate_openai_plugin_clients( - manifests_specs_clients: dict, config: Config, debug: bool = False -) -> dict: +def instantiate_openai_plugin_clients(manifests_specs_clients: dict) -> dict: """ Instantiates BaseOpenAIPlugin instances for each OpenAI plugin. Args: @@ -207,7 +204,7 @@ def instantiate_openai_plugin_clients( return plugins -def scan_plugins(config: Config, debug: bool = False) -> List[AutoGPTPluginTemplate]: +def scan_plugins(config: Config) -> List[AutoGPTPluginTemplate]: """Scan the plugins directory for plugins and loads them. Args: @@ -234,14 +231,16 @@ def scan_plugins(config: Config, debug: bool = False) -> List[AutoGPTPluginTempl try: __import__(qualified_module_name) - except: + except ImportError: logger.error(f"Failed to load {qualified_module_name}") continue plugin = sys.modules[qualified_module_name] if not plugins_config.is_enabled(plugin_module_name): - logger.warn( - f"Plugin folder {plugin_module_name} found but not configured. If this is a legitimate plugin, please add it to plugins_config.yaml (key: {plugin_module_name})." + logger.warning( + f"Plugin folder {plugin_module_name} found but not configured. " + "If this is a legitimate plugin, please add it to plugins_config.yaml " + f"(key: {plugin_module_name})." ) continue @@ -254,7 +253,7 @@ def scan_plugins(config: Config, debug: bool = False) -> List[AutoGPTPluginTempl # Zip-based plugins for plugin in plugins_path.glob("*.zip"): - if moduleList := inspect_zip_for_modules(str(plugin), debug): + if moduleList := inspect_zip_for_modules(str(plugin)): for module in moduleList: plugin = Path(plugin) module = Path(module) @@ -262,8 +261,9 @@ def scan_plugins(config: Config, debug: bool = False) -> List[AutoGPTPluginTempl zipped_package = zipimporter(str(plugin)) try: zipped_module = zipped_package.load_module(str(module.parent)) - except: + except ZipImportError: logger.error(f"Failed to load {str(module.parent)}") + continue for key in dir(zipped_module): if key.startswith("__"): @@ -283,37 +283,41 @@ def scan_plugins(config: Config, debug: bool = False) -> List[AutoGPTPluginTempl if plugin_configured and plugin_enabled: logger.debug( - f"Loading plugin {plugin_name}. Enabled in plugins_config.yaml." + f"Loading plugin {plugin_name}. " + "Enabled in plugins_config.yaml." ) loaded_plugins.append(a_module()) elif plugin_configured and not plugin_enabled: logger.debug( - f"Not loading plugin {plugin_name}. Disabled in plugins_config.yaml." + f"Not loading plugin {plugin_name}. " + "Disabled in plugins_config.yaml." ) elif not plugin_configured: - logger.warn( - f"Not loading plugin {plugin_name}. Key '{plugin_name}' was not found in plugins_config.yaml. " - f"Zipped plugins should use the class name ({plugin_name}) as the key." + logger.warning( + f"Not loading plugin {plugin_name}. " + f"No entry for '{plugin_name}' in plugins_config.yaml. " + "Note: Zipped plugins should use the class name " + f"({plugin_name}) as the key." ) else: if ( module_name := getattr(a_module, "__name__", str(a_module)) ) != "AutoGPTPluginTemplate": logger.debug( - f"Skipping '{module_name}' because it doesn't subclass AutoGPTPluginTemplate." + f"Skipping '{module_name}' because it doesn't subclass " + "AutoGPTPluginTemplate." ) # OpenAI plugins if config.plugins_openai: manifests_specs = fetch_openai_plugins_manifest_and_spec(config) if manifests_specs.keys(): - manifests_specs_clients = initialize_openai_plugins( - manifests_specs, config, debug - ) + manifests_specs_clients = initialize_openai_plugins(manifests_specs, config) for url, openai_plugin_meta in manifests_specs_clients.items(): if not plugins_config.is_enabled(url): - logger.warn( - f"OpenAI Plugin {plugin_module_name} found but not configured" + plugin_name = openai_plugin_meta["manifest"]["name_for_model"] + logger.warning( + f"OpenAI Plugin {plugin_name} found but not configured" ) continue diff --git a/autogpts/autogpt/autogpt/plugins/plugins_config.py b/autogpts/autogpt/autogpt/plugins/plugins_config.py index cc255035a..0494b6e38 100644 --- a/autogpts/autogpt/autogpt/plugins/plugins_config.py +++ b/autogpts/autogpt/autogpt/plugins/plugins_config.py @@ -42,16 +42,17 @@ class PluginsConfig(BaseModel): plugins_denylist, plugins_allowlist, ) - if type(config_data) != dict: + if type(config_data) is not dict: logger.error( - f"Expected plugins config to be a dict, got {type(config_data)}, continuing without plugins" + f"Expected plugins config to be a dict, got {type(config_data)}." + " Continuing without plugins." ) return empty_config return cls(plugins=config_data) except BaseException as e: logger.error( - f"Plugin config is invalid, continuing without plugins. Error: {e}" + f"Plugin config is invalid. Continuing without plugins. Error: {e}" ) return empty_config @@ -63,7 +64,7 @@ class PluginsConfig(BaseModel): plugins_allowlist: list[str], ) -> dict[str, PluginConfig]: if not plugins_config_file.is_file(): - logger.warn("plugins_config.yaml does not exist, creating base config.") + logger.warning("plugins_config.yaml does not exist, creating base config.") cls.create_empty_plugins_config( plugins_config_file, plugins_denylist, @@ -75,13 +76,13 @@ class PluginsConfig(BaseModel): plugins = {} for name, plugin in plugins_config.items(): - if type(plugin) == dict: + if type(plugin) is dict: plugins[name] = PluginConfig( name=name, enabled=plugin.get("enabled", False), config=plugin.get("config", {}), ) - elif type(plugin) == PluginConfig: + elif isinstance(plugin, PluginConfig): plugins[name] = plugin else: raise ValueError(f"Invalid plugin config data type: {type(plugin)}") @@ -93,7 +94,10 @@ class PluginsConfig(BaseModel): plugins_denylist: list[str], plugins_allowlist: list[str], ): - """Create an empty plugins_config.yaml file. Fill it with values from old env variables.""" + """ + Create an empty plugins_config.yaml file. + Fill it with values from old env variables. + """ base_config = {} logger.debug(f"Legacy plugin denylist: {plugins_denylist}") diff --git a/autogpts/autogpt/autogpt/processing/text.py b/autogpts/autogpt/autogpt/processing/text.py index 00351c1f0..5fed8e6b7 100644 --- a/autogpts/autogpt/autogpt/processing/text.py +++ b/autogpts/autogpt/autogpt/processing/text.py @@ -21,8 +21,11 @@ T = TypeVar("T") def batch( sequence: list[T], max_batch_length: int, overlap: int = 0 ) -> Iterator[list[T]]: - """Batch data from iterable into slices of length N. The last batch may be shorter.""" - # batched('ABCDEFG', 3) --> ABC DEF G + """ + Batch data from iterable into slices of length N. The last batch may be shorter. + + Example: `batched('ABCDEFGHIJ', 3)` --> `ABC DEF GHI J` + """ if max_batch_length < 1: raise ValueError("n must be at least one") for i in range(0, len(sequence), max_batch_length - overlap): @@ -60,10 +63,13 @@ async def summarize_text( """Summarize text using the OpenAI API Args: - text (str): The text to summarize - config (Config): The config object - instruction (str): Additional instruction for summarization, e.g. "focus on information related to polar bears", "omit personal information contained in the text" - question (str): Question to answer in the summary + text (str): The text to summarize. + llm_provider: LLM provider to use for summarization. + config (Config): The global application config, containing the FAST_LLM setting. + instruction (str): Additional instruction for summarization, e.g. + "focus on information related to polar bears", or + "omit personal information contained in the text". + question (str): Question to be answered by the summary. Returns: str: The summary of the text @@ -80,9 +86,9 @@ async def summarize_text( if question: instruction = ( - f'include any information that can be used to answer the question "{question}". ' - "Do not directly answer the question itself" - ) + 'Include any information that can be used to answer the question: "%s". ' + "Do not directly answer the question itself." + ) % question summarization_prompt = ChatPrompt(messages=[]) @@ -97,13 +103,12 @@ async def summarize_text( # summarization_prompt.add("user", text) summarization_prompt.messages.append( ChatMessage.user( - "Write a concise summary of the following text" - f"{f'; {instruction}' if instruction is not None else ''}:" + "Write a concise summary of the following text." + f"{f' {instruction}' if instruction is not None else ''}:" "\n\n\n" f'LITERAL TEXT: """{text}"""' "\n\n\n" "CONCISE SUMMARY: The text is best summarized as" - # "Only respond with a concise summary or description of the user message." ) ) @@ -114,7 +119,7 @@ async def summarize_text( temperature=0, max_tokens=500, ) - ).response["content"] + ).response.content logger.debug(f"\n{'-'*16} SUMMARY {'-'*17}\n{summary}\n{'-'*42}\n") return summary.strip(), None @@ -160,14 +165,15 @@ def split_text( tokenizer: ModelTokenizer, with_overlap: bool = True, ) -> Iterator[tuple[str, int]]: - """Split text into chunks of sentences, with each chunk not exceeding the maximum length + """ + Split text into chunks of sentences, with each chunk not exceeding the max length. Args: - text (str): The text to split - for_model (str): The model to chunk for; determines tokenizer and constraints - config (Config): The config object - with_overlap (bool, optional): Whether to allow overlap between chunks - max_chunk_length (int, optional): The maximum length of a chunk + text (str): The text to split. + config (Config): Config object containing the Spacy model setting. + max_chunk_length (int, optional): The maximum length of a chunk. + tokenizer (ModelTokenizer): Tokenizer to use for determining chunk length. + with_overlap (bool, optional): Whether to allow overlap between chunks. Yields: str: The next chunk of text diff --git a/autogpts/autogpt/autogpt/prompts/default_prompts.py b/autogpts/autogpt/autogpt/prompts/default_prompts.py deleted file mode 100644 index 6fa3dede6..000000000 --- a/autogpts/autogpt/autogpt/prompts/default_prompts.py +++ /dev/null @@ -1,29 +0,0 @@ -#########################Setup.py################################# - -DEFAULT_SYSTEM_PROMPT_AICONFIG_AUTOMATIC = """ -Your task is to devise up to 5 highly effective goals and an appropriate role-based name (_GPT) for an autonomous agent, ensuring that the goals are optimally aligned with the successful completion of its assigned task. - -The user will provide the task, you will provide only the output in the exact format specified below with no explanation or conversation. - -Example input: -Help me with marketing my business - -Example output: -Name: CMOGPT -Description: a professional digital marketer AI that assists Solopreneurs in growing their businesses by providing world-class expertise in solving marketing problems for SaaS, content products, agencies, and more. -Goals: -- Engage in effective problem-solving, prioritization, planning, and supporting execution to address your marketing needs as your virtual Chief Marketing Officer. - -- Provide specific, actionable, and concise advice to help you make informed decisions without the use of platitudes or overly wordy explanations. - -- Identify and prioritize quick wins and cost-effective campaigns that maximize results with minimal time and budget investment. - -- Proactively take the lead in guiding you and offering suggestions when faced with unclear information or uncertainty to ensure your marketing strategy remains on track. -""" - -DEFAULT_TASK_PROMPT_AICONFIG_AUTOMATIC = ( - "Task: '{{user_prompt}}'\n" - "Respond only with the output in the exact format specified in the system prompt, with no explanation or conversation.\n" -) - -DEFAULT_USER_DESIRE_PROMPT = "Write a wikipedia style article about the project: https://github.com/significant-gravitas/AutoGPT" # Default prompt diff --git a/autogpts/autogpt/autogpt/prompts/utils.py b/autogpts/autogpt/autogpt/prompts/utils.py index ad5aaa237..f5ab9df9d 100644 --- a/autogpts/autogpt/autogpt/prompts/utils.py +++ b/autogpts/autogpt/autogpt/prompts/utils.py @@ -6,6 +6,6 @@ def format_numbered_list(items: list[Any], start_at: int = 1) -> str: def indent(content: str, indentation: int | str = 4) -> str: - if type(indentation) == int: + if type(indentation) is int: indentation = " " * indentation return indentation + content.replace("\n", f"\n{indentation}") # type: ignore diff --git a/autogpts/autogpt/autogpt/speech/base.py b/autogpts/autogpt/autogpt/speech/base.py index b9bcd040b..fd9fda60f 100644 --- a/autogpts/autogpt/autogpt/speech/base.py +++ b/autogpts/autogpt/autogpt/speech/base.py @@ -31,7 +31,7 @@ class VoiceBase: voice_index (int): The index of the voice to use. """ text = re.sub( - r"\b(?:https?://[-\w_.]+/?\w[-\w_.]*\.(?:[-\w_.]+/?\w[-\w_.]*\.)?[a-z]+(?:/[-\w_.%]+)*\b(?!\.))", + r"\b(?:https?://[-\w_.]+/?\w[-\w_.]*\.(?:[-\w_.]+/?\w[-\w_.]*\.)?[a-z]+(?:/[-\w_.%]+)*\b(?!\.))", # noqa: E501 "", text, ) diff --git a/autogpts/autogpt/autogpt/speech/eleven_labs.py b/autogpts/autogpt/autogpt/speech/eleven_labs.py index c7929222e..897f0fd7d 100644 --- a/autogpts/autogpt/autogpt/speech/eleven_labs.py +++ b/autogpts/autogpt/autogpt/speech/eleven_labs.py @@ -17,8 +17,8 @@ PLACEHOLDERS = {"your-voice-id"} class ElevenLabsConfig(SystemConfiguration): - api_key: str = UserConfigurable() - voice_id: str = UserConfigurable() + api_key: str = UserConfigurable(from_env="ELEVENLABS_API_KEY") + voice_id: str = UserConfigurable(from_env="ELEVENLABS_VOICE_ID") class ElevenLabsSpeech(VoiceBase): @@ -88,6 +88,6 @@ class ElevenLabsSpeech(VoiceBase): os.remove("speech.mpeg") return True else: - logger.warn("Request failed with status code:", response.status_code) + logger.warning("Request failed with status code:", response.status_code) logger.info("Response content:", response.content) return False diff --git a/autogpts/autogpt/autogpt/speech/say.py b/autogpts/autogpt/autogpt/speech/say.py index be4ad5d85..04ab3a4bc 100644 --- a/autogpts/autogpt/autogpt/speech/say.py +++ b/autogpts/autogpt/autogpt/speech/say.py @@ -1,6 +1,7 @@ """ Text to speech module """ from __future__ import annotations +import os import threading from threading import Semaphore from typing import Literal, Optional @@ -20,11 +21,23 @@ _QUEUE_SEMAPHORE = Semaphore( class TTSConfig(SystemConfiguration): speak_mode: bool = False - provider: Literal[ - "elevenlabs", "gtts", "macos", "streamelements" - ] = UserConfigurable(default="gtts") elevenlabs: Optional[ElevenLabsConfig] = None streamelements: Optional[StreamElementsConfig] = None + provider: Literal[ + "elevenlabs", "gtts", "macos", "streamelements" + ] = UserConfigurable( + default="gtts", + from_env=lambda: os.getenv("TEXT_TO_SPEECH_PROVIDER") + or ( + "macos" + if os.getenv("USE_MAC_OS_TTS") + else "elevenlabs" + if os.getenv("ELEVENLABS_API_KEY") + else "streamelements" + if os.getenv("USE_BRIAN_TTS") + else "gtts" + ), + ) # type: ignore class TextToSpeechProvider: @@ -45,7 +58,10 @@ class TextToSpeechProvider: thread.start() def __repr__(self): - return f"{self.__class__.__name__}(provider={self._voice_engine.__class__.__name__})" + return "{class_name}(provider={voice_engine_name})".format( + class_name=self.__class__.__name__, + voice_engine_name=self._voice_engine.__class__.__name__, + ) @staticmethod def _get_voice_engine(config: TTSConfig) -> tuple[VoiceBase, VoiceBase]: diff --git a/autogpts/autogpt/autogpt/speech/stream_elements_speech.py b/autogpts/autogpt/autogpt/speech/stream_elements_speech.py index 99bc43bf0..e12b29b2d 100644 --- a/autogpts/autogpt/autogpt/speech/stream_elements_speech.py +++ b/autogpts/autogpt/autogpt/speech/stream_elements_speech.py @@ -13,7 +13,7 @@ logger = logging.getLogger(__name__) class StreamElementsConfig(SystemConfiguration): - voice: str = UserConfigurable(default="Brian") + voice: str = UserConfigurable(default="Brian", from_env="STREAMELEMENTS_VOICE") class StreamElementsSpeech(VoiceBase): diff --git a/autogpts/autogpt/autogpt/url_utils/validators.py b/autogpts/autogpt/autogpt/url_utils/validators.py index 2593340b8..5f8d2ffc8 100644 --- a/autogpts/autogpt/autogpt/url_utils/validators.py +++ b/autogpts/autogpt/autogpt/url_utils/validators.py @@ -8,12 +8,14 @@ T = TypeVar("T") def validate_url(func: Callable[P, T]) -> Callable[P, T]: - """The method decorator validate_url is used to validate urls for any command that requires - a url as an argument""" + """ + The method decorator validate_url is used to validate urls for any command that + requires a url as an argument. + """ @functools.wraps(func) def wrapper(url: str, *args, **kwargs) -> Any: - """Check if the URL is valid using a basic check, urllib check, and local file check + """Check if the URL is valid and not a local file accessor. Args: url (str): The URL to check @@ -24,6 +26,7 @@ def validate_url(func: Callable[P, T]) -> Callable[P, T]: Raises: ValueError if the url fails any of the validation tests """ + # Most basic check if the URL is valid: if not re.match(r"^https?://", url): raise ValueError("Invalid URL format") @@ -80,29 +83,10 @@ def check_local_file_access(url: str) -> bool: Returns: bool: True if the URL is a local file, False otherwise """ - local_prefixes = [ + # List of local file prefixes + local_file_prefixes = [ "file:///", - "file://localhost/", "file://localhost", - "http://localhost", - "http://localhost/", - "https://localhost", - "https://localhost/", - "http://2130706433", - "http://2130706433/", - "https://2130706433", - "https://2130706433/", - "http://127.0.0.1/", - "http://127.0.0.1", - "https://127.0.0.1/", - "https://127.0.0.1", - "https://0.0.0.0/", - "https://0.0.0.0", - "http://0.0.0.0/", - "http://0.0.0.0", - "http://0000", - "http://0000/", - "https://0000", - "https://0000/", ] - return any(url.startswith(prefix) for prefix in local_prefixes) + + return any(url.startswith(prefix) for prefix in local_file_prefixes) diff --git a/autogpts/autogpt/azure.yaml.template b/autogpts/autogpt/azure.yaml.template index 685b7087a..d9cc2ca8e 100644 --- a/autogpts/autogpt/azure.yaml.template +++ b/autogpts/autogpt/azure.yaml.template @@ -1,7 +1,7 @@ azure_api_type: azure -azure_api_base: your-base-url-for-azure azure_api_version: api-version-for-azure +azure_endpoint: your-azure-openai-endpoint azure_model_map: - fast_llm_deployment_id: gpt35-deployment-id-for-azure - smart_llm_deployment_id: gpt4-deployment-id-for-azure - embedding_model_deployment_id: embedding-deployment-id-for-azure + gpt-3.5-turbo: gpt35-deployment-id-for-azure + gpt-4: gpt4-deployment-id-for-azure + text-embedding-ada-002: embedding-deployment-id-for-azure diff --git a/autogpts/autogpt/data_ingestion.py b/autogpts/autogpt/data_ingestion.py deleted file mode 100644 index 7d596f52c..000000000 --- a/autogpts/autogpt/data_ingestion.py +++ /dev/null @@ -1,98 +0,0 @@ -import argparse -import logging - -from autogpt.commands.file_operations import ingest_file, list_files -from autogpt.config import ConfigBuilder -from autogpt.memory.vector import VectorMemory, get_memory - -config = ConfigBuilder.build_config_from_env() - - -def configure_logging(): - logging.basicConfig( - format="%(asctime)s,%(msecs)d %(name)s %(levelname)s %(message)s", - datefmt="%H:%M:%S", - level=logging.DEBUG, - handlers=[ - logging.FileHandler(filename="log-ingestion.txt", mode="a"), - logging.StreamHandler(), - ], - ) - return logging.getLogger("AutoGPT-Ingestion") - - -def ingest_directory(directory: str, memory: VectorMemory, args): - """ - Ingest all files in a directory by calling the ingest_file function for each file. - - :param directory: The directory containing the files to ingest - :param memory: An object with an add() method to store the chunks in memory - """ - logger = logging.getLogger("AutoGPT-Ingestion") - try: - files = list_files(directory) - for file in files: - ingest_file(file, memory, args.max_length, args.overlap) - except Exception as e: - logger.error(f"Error while ingesting directory '{directory}': {str(e)}") - - -def main() -> None: - logger = configure_logging() - - parser = argparse.ArgumentParser( - description="Ingest a file or a directory with multiple files into memory. " - "Make sure to set your .env before running this script." - ) - group = parser.add_mutually_exclusive_group(required=True) - group.add_argument("--file", type=str, help="The file to ingest.") - group.add_argument( - "--dir", type=str, help="The directory containing the files to ingest." - ) - parser.add_argument( - "--init", - action="store_true", - help="Init the memory and wipe its content (default: False)", - default=False, - ) - parser.add_argument( - "--overlap", - type=int, - help="The overlap size between chunks when ingesting files (default: 200)", - default=200, - ) - parser.add_argument( - "--max_length", - type=int, - help="The max_length of each chunk when ingesting files (default: 4000)", - default=4000, - ) - args = parser.parse_args() - - # Initialize memory - memory = get_memory(config) - if args.init: - memory.clear() - logger.debug("Using memory of type: " + memory.__class__.__name__) - - if args.file: - try: - ingest_file(args.file, memory, args.max_length, args.overlap) - logger.info(f"File '{args.file}' ingested successfully.") - except Exception as e: - logger.error(f"Error while ingesting file '{args.file}': {str(e)}") - elif args.dir: - try: - ingest_directory(args.dir, memory, args) - logger.info(f"Directory '{args.dir}' ingested successfully.") - except Exception as e: - logger.error(f"Error while ingesting directory '{args.dir}': {str(e)}") - else: - logger.warn( - "Please provide either a file path (--file) or a directory name (--dir)" - " inside the auto_gpt_workspace directory as input." - ) - - -if __name__ == "__main__": - main() diff --git a/autogpts/autogpt/docker-compose.yml b/autogpts/autogpt/docker-compose.yml index 945f969b7..281c8f697 100644 --- a/autogpts/autogpt/docker-compose.yml +++ b/autogpts/autogpt/docker-compose.yml @@ -9,8 +9,41 @@ services: build: ./ env_file: - .env + ports: + - "8000:8000" volumes: - ./:/app - ./docker-compose.yml:/app/docker-compose.yml:ro - ./Dockerfile:/app/Dockerfile:ro profiles: ["exclude-from-up"] + + # Only for TESTING purposes. Run with: docker compose run --build --rm autogpt-test + autogpt-test: + build: ./ + env_file: + - .env + environment: + S3_ENDPOINT_URL: http://minio:9000 + AWS_ACCESS_KEY_ID: minio + AWS_SECRET_ACCESS_KEY: minio123 + entrypoint: ["poetry", "run"] + command: ["pytest", "-v"] + volumes: + - ./autogpt:/app/autogpt + - ./tests:/app/tests + depends_on: + - minio + profiles: ["exclude-from-up"] + minio: + image: minio/minio + environment: + MINIO_ACCESS_KEY: minio + MINIO_SECRET_KEY: minio123 + ports: + - 9000:9000 + volumes: + - minio-data:/data + command: server /data + profiles: ["exclude-from-up"] +volumes: + minio-data: diff --git a/autogpts/autogpt/mypy.ini b/autogpts/autogpt/mypy.ini deleted file mode 100644 index 6257f4880..000000000 --- a/autogpts/autogpt/mypy.ini +++ /dev/null @@ -1,14 +0,0 @@ -[mypy] -follow_imports = skip -check_untyped_defs = True -disallow_untyped_calls = True -disallow_untyped_defs = True -files = autogpt/**/*.py,tests/**/*.py - -[mypy-tests.*] 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serve = "autogpt.app.cli:serve" [tool.poetry.dependencies] python = "^3.10" +auto-gpt-plugin-template = {git = "https://github.com/Significant-Gravitas/Auto-GPT-Plugin-Template", rev = "0.1.0"} # autogpt-forge = { path = "../forge" } -autogpt-forge = {git = "https://github.com/Significant-Gravitas/AutoGPT.git", subdirectory = "autogpts/forge"} +autogpt-forge = {git = "https://github.com/Significant-Gravitas/AutoGPT.git", rev = "b238aba", subdirectory = "autogpts/forge"} beautifulsoup4 = "^4.12.2" +boto3 = "^1.33.6" charset-normalizer = "^3.1.0" click = "*" colorama = "^0.4.6" distro = "^1.8.0" docker = "*" -duckduckgo-search = "^3.0.2" +duckduckgo-search = "^4.0.0" en-core-web-sm = {url = "https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.5.0/en_core_web_sm-3.5.0-py3-none-any.whl"} fastapi = "*" ftfy = "^6.1.1" +gitpython = "^3.1.32" google-api-python-client = "*" gTTS = "^2.3.1" hypercorn = "^0.14.4" inflection = "*" jsonschema = "*" -markdown = "*" numpy = "*" -openai = "^0.27.10" +openai = "^1.7.2" orjson = "^3.8.10" Pillow = "*" pinecone-client = "^2.2.1" @@ -50,7 +51,7 @@ playsound = "~1.2.2" prompt_toolkit = "^3.0.38" pydantic = "*" pylatexenc = "*" -PyPDF2 = "*" +pypdf = "^3.1.0" python-docx = "*" python-dotenv = "^1.0.0" pyyaml = "^6.0" @@ -59,6 +60,7 @@ redis = "*" requests = "*" selenium = "^4.11.2" spacy = "^3.0.0" +tenacity = "^8.2.2" tiktoken = "^0.5.0" webdriver-manager = "*" @@ -66,14 +68,18 @@ webdriver-manager = "*" openapi-python-client = "^0.14.0" # Benchmarking -agbenchmark = { path = "../../benchmark", optional = true } +# agbenchmark = { path = "../../benchmark", optional = true } +agbenchmark = {git = "https://github.com/Significant-Gravitas/AutoGPT.git", subdirectory = "benchmark", optional = true} +google-cloud-logging = "^3.8.0" +google-cloud-storage = "^2.13.0" +psycopg2-binary = "^2.9.9" [tool.poetry.extras] benchmark = ["agbenchmark"] [tool.poetry.group.dev.dependencies] -auto-gpt-plugin-template = {git = "https://github.com/Significant-Gravitas/Auto-GPT-Plugin-Template", rev = "0.1.0"} black = "*" +boto3-stubs = {extras = ["s3"], version = "^1.33.6"} flake8 = "*" gitpython = "^3.1.32" isort = "*" @@ -108,7 +114,7 @@ line-length = 88 target-version = ['py310'] include = '\.pyi?$' packages = ["autogpt"] -extend-exclude = '.+/(dist|.venv|venv|build)/.+' +extend-exclude = '.+/(dist|.venv|venv|build|data)/.+' [tool.isort] @@ -126,17 +132,27 @@ sections = [ "FIRSTPARTY", "LOCALFOLDER" ] -skip = ''' - .tox - __pycache__ - *.pyc - .env - venv*/* - .venv/* - reports/* - dist/* - -''' +extend_skip = [ + "agbenchmark_config/temp_folder/", + "data/", +] + + +[tool.mypy] +follow_imports = 'skip' +check_untyped_defs = true +disallow_untyped_calls = true +files = [ + 'autogpt/**/*.py', + 'tests/**/*.py' +] + +[[tool.mypy.overrides]] +module = [ + 'requests.*', + 'yaml.*' +] +ignore_missing_imports = true [tool.pytest.ini_options] diff --git a/autogpts/autogpt/run b/autogpts/autogpt/run index b37c053fa..eebf7fe0f 100755 --- a/autogpts/autogpt/run +++ b/autogpts/autogpt/run @@ -2,7 +2,7 @@ kill $(lsof -t -i :8000) -if [ ! -f .env ]; then +if [ ! -f .env ] && [ -z "$OPENAI_API_KEY" ]; then cp .env.example .env echo "Please add your api keys to the .env file." >&2 # exit 1 diff --git a/autogpts/autogpt/run_continuous.bat b/autogpts/autogpt/run_continuous.bat deleted file mode 100644 index 812aa01c1..000000000 --- a/autogpts/autogpt/run_continuous.bat +++ /dev/null @@ -1,3 +0,0 @@ -@echo off -set argument=--continuous -call run.bat %argument% diff --git a/autogpts/autogpt/run_continuous.sh b/autogpts/autogpt/run_continuous.sh deleted file mode 100755 index 1f4436c88..000000000 --- a/autogpts/autogpt/run_continuous.sh +++ /dev/null @@ -1,3 +0,0 @@ -#!/bin/bash - -./run.sh --continuous $@ diff --git a/autogpts/autogpt/scripts/check_requirements.py b/autogpts/autogpt/scripts/check_requirements.py index 8d7db6d3e..c62520825 100644 --- a/autogpts/autogpt/scripts/check_requirements.py +++ b/autogpts/autogpt/scripts/check_requirements.py @@ -14,12 +14,12 @@ from poetry.factory import Factory def main(): poetry_project = Factory().create_poetry() - # repository = poetry_project.locker.locked_repository() - # dependencies = repository.packages dependency_group = poetry_project.package.dependency_group("main") missing_packages = [] for dep in dependency_group.dependencies: + if dep.is_optional(): + continue # Try to verify that the installed version is suitable with contextlib.suppress(ModuleNotFoundError): installed_version = version(dep.name) # if this fails -> not installed diff --git a/autogpts/autogpt/scripts/install_plugin_deps.py b/autogpts/autogpt/scripts/install_plugin_deps.py index f8b275f37..02cbfc0be 100644 --- a/autogpts/autogpt/scripts/install_plugin_deps.py +++ b/autogpts/autogpt/scripts/install_plugin_deps.py @@ -21,7 +21,7 @@ def install_plugin_dependencies(): """ plugins_dir = Path(os.getenv("PLUGINS_DIR", "plugins")) - logger.debug(f"Checking for dependencies in zipped plugins...") + logger.debug("Checking for dependencies in zipped plugins...") # Install zip-based plugins for plugin_archive in plugins_dir.glob("*.zip"): @@ -49,7 +49,7 @@ def install_plugin_dependencies(): os.remove(extracted) os.rmdir(os.path.join(plugins_dir, basedir)) - logger.debug(f"Checking for dependencies in other plugin folders...") + logger.debug("Checking for dependencies in other plugin folders...") # Install directory-based plugins for requirements_file in glob(f"{plugins_dir}/*/requirements.txt"): diff --git a/autogpts/autogpt/setup b/autogpts/autogpt/setup index 511ef7277..8263dce32 100755 --- a/autogpts/autogpt/setup +++ b/autogpts/autogpt/setup @@ -1,4 +1,8 @@ #!/bin/sh +# Necessary to prevent forge and agbenchmark from breaking each others' install: +# https://github.com/python-poetry/poetry/issues/6958 +POETRY_INSTALLER_PARALLEL=false \ poetry install --no-interaction --extras benchmark + echo "Setup completed successfully." diff --git a/autogpts/autogpt/tests/conftest.py b/autogpts/autogpt/tests/conftest.py index 460c0a665..a73aa7571 100644 --- a/autogpts/autogpt/tests/conftest.py +++ b/autogpts/autogpt/tests/conftest.py @@ -1,4 +1,5 @@ import os +import uuid from pathlib import Path from tempfile import TemporaryDirectory @@ -10,10 +11,13 @@ from autogpt.agents.agent import Agent, AgentConfiguration, AgentSettings from autogpt.app.main import _configure_openai_provider from autogpt.config import AIProfile, Config, ConfigBuilder from autogpt.core.resource.model_providers import ChatModelProvider, OpenAIProvider -from autogpt.file_workspace import FileWorkspace +from autogpt.file_workspace.local import ( + FileWorkspace, + FileWorkspaceConfiguration, + LocalFileWorkspace, +) from autogpt.llm.api_manager import ApiManager from autogpt.logs.config import configure_logging -from autogpt.memory.vector import get_memory from autogpt.models.command_registry import CommandRegistry pytest_plugins = [ @@ -30,7 +34,9 @@ def tmp_project_root(tmp_path: Path) -> Path: @pytest.fixture() def app_data_dir(tmp_project_root: Path) -> Path: - return tmp_project_root / "data" + dir = tmp_project_root / "data" + dir.mkdir(parents=True, exist_ok=True) + return dir @pytest.fixture() @@ -45,14 +51,17 @@ def workspace_root(agent_data_dir: Path) -> Path: @pytest.fixture() def workspace(workspace_root: Path) -> FileWorkspace: - workspace = FileWorkspace(workspace_root, restrict_to_root=True) + workspace = LocalFileWorkspace(FileWorkspaceConfiguration(root=workspace_root)) workspace.initialize() return workspace @pytest.fixture def temp_plugins_config_file(): - """Create a plugins_config.yaml file in a temp directory so that it doesn't mess with existing ones""" + """ + Create a plugins_config.yaml file in a temp directory + so that it doesn't mess with existing ones. + """ config_directory = TemporaryDirectory() config_file = Path(config_directory.name) / "plugins_config.yaml" with open(config_file, "w+") as f: @@ -61,24 +70,25 @@ def temp_plugins_config_file(): yield config_file -@pytest.fixture() +@pytest.fixture(scope="function") def config( temp_plugins_config_file: Path, tmp_project_root: Path, app_data_dir: Path, mocker: MockerFixture, ): - config = ConfigBuilder.build_config_from_env(project_root=tmp_project_root) if not os.environ.get("OPENAI_API_KEY"): os.environ["OPENAI_API_KEY"] = "sk-dummy" + config = ConfigBuilder.build_config_from_env(project_root=tmp_project_root) config.app_data_dir = app_data_dir config.plugins_dir = "tests/unit/data/test_plugins" config.plugins_config_file = temp_plugins_config_file + config.logging.log_dir = Path(__file__).parent / "logs" + config.logging.plain_console_output = True config.noninteractive_mode = True - config.plain_output = True # avoid circular dependency from autogpt.plugins.plugins_config import PluginsConfig @@ -93,11 +103,7 @@ def config( @pytest.fixture(scope="session") def setup_logger(config: Config): - configure_logging( - debug_mode=config.debug_mode, - plain_output=config.plain_output, - log_dir=Path(__file__).parent / "logs", - ) + configure_logging(**config.logging.dict()) @pytest.fixture() @@ -130,6 +136,7 @@ def agent( agent_settings = AgentSettings( name=Agent.default_settings.name, description=Agent.default_settings.description, + agent_id=f"AutoGPT-test-agent-{str(uuid.uuid4())[:8]}", ai_profile=ai_profile, config=AgentConfiguration( fast_llm=config.fast_llm, diff --git a/autogpts/autogpt/tests/integration/memory/_test_json_file_memory.py b/autogpts/autogpt/tests/integration/memory/_test_json_file_memory.py index d8e82c691..b8c98b30e 100644 --- a/autogpts/autogpt/tests/integration/memory/_test_json_file_memory.py +++ b/autogpts/autogpt/tests/integration/memory/_test_json_file_memory.py @@ -68,7 +68,7 @@ def test_json_memory_clear(config: Config, memory_item: MemoryItem): def test_json_memory_get(config: Config, memory_item: MemoryItem, mock_get_embedding): index = JSONFileMemory(config) assert ( - index.get("test", config) == None + index.get("test", config) is None ), "Cannot test get() because initial index is not empty" index.add(memory_item) @@ -97,7 +97,7 @@ def test_json_memory_load_index(config: Config, memory_item: MemoryItem): @pytest.mark.vcr @pytest.mark.requires_openai_api_key -def test_json_memory_get_relevant(config: Config, patched_api_requestor: None) -> None: +def test_json_memory_get_relevant(config: Config, cached_openai_client: None) -> None: index = JSONFileMemory(config) mem1 = MemoryItem.from_text_file("Sample text", "sample.txt", config) mem2 = MemoryItem.from_text_file( diff --git a/autogpts/autogpt/tests/integration/test_execute_code.py b/autogpts/autogpt/tests/integration/test_execute_code.py index cc281a0d6..1c980e025 100644 --- a/autogpts/autogpt/tests/integration/test_execute_code.py +++ b/autogpts/autogpt/tests/integration/test_execute_code.py @@ -66,15 +66,16 @@ def test_execute_python_code(random_code: str, random_string: str, agent: Agent) def test_execute_python_file_invalid(agent: Agent): with pytest.raises(InvalidArgumentError): - sut.execute_python_file("not_python", agent) + sut.execute_python_file(Path("not_python.txt"), agent) def test_execute_python_file_not_found(agent: Agent): with pytest.raises( FileNotFoundError, - match=r"python: can't open file '([a-zA-Z]:)?[/\\\-\w]*notexist.py': \[Errno 2\] No such file or directory", + match=r"python: can't open file '([a-zA-Z]:)?[/\\\-\w]*notexist.py': " + r"\[Errno 2\] No such file or directory", ): - sut.execute_python_file("notexist.py", agent) + sut.execute_python_file(Path("notexist.py"), agent) def test_execute_shell(random_string: str, agent: Agent): diff --git a/autogpts/autogpt/tests/integration/test_image_gen.py b/autogpts/autogpt/tests/integration/test_image_gen.py index 450966486..14b90aec7 100644 --- a/autogpts/autogpt/tests/integration/test_image_gen.py +++ b/autogpts/autogpt/tests/integration/test_image_gen.py @@ -18,7 +18,7 @@ def image_size(request): @pytest.mark.requires_openai_api_key @pytest.mark.vcr -def test_dalle(agent: Agent, workspace, image_size, patched_api_requestor): +def test_dalle(agent: Agent, workspace, image_size, cached_openai_client): """Test DALL-E image generation.""" generate_and_validate( agent, @@ -29,7 +29,8 @@ def test_dalle(agent: Agent, workspace, image_size, patched_api_requestor): @pytest.mark.xfail( - reason="The image is too big to be put in a cassette for a CI pipeline. We're looking into a solution." + reason="The image is too big to be put in a cassette for a CI pipeline. " + "We're looking into a solution." ) @pytest.mark.requires_huggingface_api_key @pytest.mark.parametrize( @@ -69,12 +70,14 @@ def test_sd_webui_negative_prompt(agent: Agent, workspace, image_size): ) # Generate an image with a negative prompt - image_path = lst(gen_image(negative_prompt="horse", filename="negative.jpg")) + image_path = lst( + gen_image(negative_prompt="horse", output_file=Path("negative.jpg")) + ) with Image.open(image_path) as img: neg_image_hash = hashlib.md5(img.tobytes()).hexdigest() # Generate an image without a negative prompt - image_path = lst(gen_image(filename="positive.jpg")) + image_path = lst(gen_image(output_file=Path("positive.jpg"))) with Image.open(image_path) as img: image_hash = hashlib.md5(img.tobytes()).hexdigest() @@ -83,7 +86,7 @@ def test_sd_webui_negative_prompt(agent: Agent, workspace, image_size): def lst(txt): """Extract the file path from the output of `generate_image()`""" - return Path(txt.split(":", maxsplit=1)[1].strip()) + return Path(txt.split(": ", maxsplit=1)[1].strip()) def generate_and_validate( @@ -96,7 +99,8 @@ def generate_and_validate( ): """Generate an image and validate the output.""" agent.legacy_config.image_provider = image_provider - agent.legacy_config.huggingface_image_model = hugging_face_image_model + if hugging_face_image_model: + agent.legacy_config.huggingface_image_model = hugging_face_image_model prompt = "astronaut riding a horse" image_path = lst(generate_image(prompt, agent, image_size, **kwargs)) @@ -108,7 +112,8 @@ def generate_and_validate( @pytest.mark.parametrize( "return_text", [ - '{"error":"Model [model] is currently loading","estimated_time": [delay]}', # Delay + # Delay + '{"error":"Model [model] is currently loading","estimated_time": [delay]}', '{"error":"Model [model] is currently loading"}', # No delay '{"error:}', # Bad JSON "", # Bad Image @@ -139,6 +144,7 @@ def test_huggingface_fail_request_with_delay( mock_post.return_value.text = return_text agent.legacy_config.image_provider = "huggingface" + agent.legacy_config.huggingface_api_token = "mock-api-key" agent.legacy_config.huggingface_image_model = image_model prompt = "astronaut riding a horse" @@ -154,29 +160,6 @@ def test_huggingface_fail_request_with_delay( mock_sleep.assert_not_called() -def test_huggingface_fail_request_with_delay(mocker, agent: Agent): - agent.legacy_config.huggingface_api_token = "1" - - # Mock requests.post - mock_post = mocker.patch("requests.post") - mock_post.return_value.status_code = 500 - mock_post.return_value.ok = False - mock_post.return_value.text = '{"error":"Model CompVis/stable-diffusion-v1-4 is currently loading","estimated_time":0}' - - # Mock time.sleep - mock_sleep = mocker.patch("time.sleep") - - agent.legacy_config.image_provider = "huggingface" - agent.legacy_config.huggingface_image_model = "CompVis/stable-diffusion-v1-4" - - result = generate_image("astronaut riding a horse", agent, 512) - - assert result == "Error creating image." - - # Verify retry was called with delay. - mock_sleep.assert_called_with(0) - - def test_huggingface_fail_request_no_delay(mocker, agent: Agent): agent.legacy_config.huggingface_api_token = "1" @@ -245,7 +228,7 @@ def test_huggingface_fail_missing_api_token(mocker, agent: Agent): agent.legacy_config.huggingface_image_model = "CompVis/stable-diffusion-v1-4" # Mock requests.post to raise ValueError - mock_post = mocker.patch("requests.post", side_effect=ValueError) + mocker.patch("requests.post", side_effect=ValueError) # Verify request raises an error. with pytest.raises(ValueError): diff --git a/autogpts/autogpt/tests/integration/test_web_selenium.py b/autogpts/autogpt/tests/integration/test_web_selenium.py index dfdbb9e0f..1d904b855 100644 --- a/autogpts/autogpt/tests/integration/test_web_selenium.py +++ b/autogpts/autogpt/tests/integration/test_web_selenium.py @@ -6,13 +6,12 @@ from autogpt.commands.web_selenium import BrowsingError, read_webpage @pytest.mark.vcr @pytest.mark.requires_openai_api_key -async def test_browse_website_nonexistent_url( - agent: Agent, patched_api_requestor: None -): +@pytest.mark.asyncio +async def test_browse_website_nonexistent_url(agent: Agent, cached_openai_client: None): url = "https://auto-gpt-thinks-this-website-does-not-exist.com" question = "How to execute a barrel roll" - with pytest.raises(BrowsingError, match=r"NAME_NOT_RESOLVED") as raised: + with pytest.raises(BrowsingError, match="NAME_NOT_RESOLVED") as raised: await read_webpage(url=url, question=question, agent=agent) # Sanity check that the response is not too long diff --git a/autogpts/autogpt/tests/mocks/mock_commands.py b/autogpts/autogpt/tests/mocks/mock_commands.py index 3758c1da2..ab9e961b6 100644 --- a/autogpts/autogpt/tests/mocks/mock_commands.py +++ b/autogpts/autogpt/tests/mocks/mock_commands.py @@ -1,16 +1,29 @@ from autogpt.command_decorator import command +from autogpt.core.utils.json_schema import JSONSchema COMMAND_CATEGORY = "mock" @command( - "function_based", + "function_based_cmd", "Function-based test command", { - "arg1": {"type": "int", "description": "arg 1", "required": True}, - "arg2": {"type": "str", "description": "arg 2", "required": True}, + "arg1": JSONSchema( + type=JSONSchema.Type.INTEGER, + description="arg 1", + required=True, + ), + "arg2": JSONSchema( + type=JSONSchema.Type.STRING, + description="arg 2", + required=True, + ), }, ) -def function_based(arg1: int, arg2: str) -> str: - """A function-based test command that returns a string with the two arguments separated by a dash.""" +def function_based_cmd(arg1: int, arg2: str) -> str: + """A function-based test command. + + Returns: + str: the two arguments separated by a dash. + """ return f"{arg1} - {arg2}" diff --git a/autogpts/autogpt/tests/unit/_test_json_parser.py b/autogpts/autogpt/tests/unit/_test_json_parser.py deleted file mode 100644 index ee871cf48..000000000 --- a/autogpts/autogpt/tests/unit/_test_json_parser.py +++ /dev/null @@ -1,113 +0,0 @@ -import pytest - -from autogpt.json_utils.json_fix_llm import fix_and_parse_json - - -def test_valid_json(): - """Test that a valid JSON string is parsed correctly.""" - json_str = '{"name": "John", "age": 30, "city": "New York"}' - obj = fix_and_parse_json(json_str) - assert obj == {"name": "John", "age": 30, "city": "New York"} - - -def test_invalid_json_minor(): - """Test that an invalid JSON string can be fixed with gpt.""" - json_str = '{"name": "John", "age": 30, "city": "New York",}' - assert fix_and_parse_json(json_str, try_to_fix_with_gpt=False) == { - "name": "John", - "age": 30, - "city": "New York", - } - - -def test_invalid_json_major_with_gpt(): - """Test that an invalid JSON string raises an error when try_to_fix_with_gpt is False.""" - json_str = 'BEGIN: "name": "John" - "age": 30 - "city": "New York" :END' - assert fix_and_parse_json(json_str, try_to_fix_with_gpt=True) == { - "name": "John", - "age": 30, - "city": "New York", - } - - -def test_invalid_json_major_without_gpt(): - """Test that a REALLY invalid JSON string raises an error when try_to_fix_with_gpt is False.""" - json_str = 'BEGIN: "name": "John" - "age": 30 - "city": "New York" :END' - # Assert that this raises an exception: - with pytest.raises(Exception): - fix_and_parse_json(json_str, try_to_fix_with_gpt=False) - - -def test_invalid_json_leading_sentence_with_gpt(): - """Test that a REALLY invalid JSON string raises an error when try_to_fix_with_gpt is False.""" - - json_str = """I suggest we start by browsing the repository to find any issues that we can fix. - - { - "command": { - "name": "browse_website", - "args":{ - "url": "https://github.com/Significant-Gravitas/AutoGPT" - } - }, - "thoughts": - { - "text": "I suggest we start browsing the repository to find any issues that we can fix.", - "reasoning": "Browsing the repository will give us an idea of the current state of the codebase and identify any issues that we can address to improve the repo.", - "plan": "- Look through the repository to find any issues.\n- Investigate any issues to determine what needs to be fixed\n- Identify possible solutions to fix the issues\n- Open Pull Requests with fixes", - "criticism": "I should be careful while browsing so as not to accidentally introduce any new bugs or issues.", - "speak": "I will start browsing the repository to find any issues we can fix." - } - }""" - good_obj = { - "command": { - "name": "browse_website", - "args": {"url": "https://github.com/Significant-Gravitas/AutoGPT"}, - }, - "thoughts": { - "text": "I suggest we start browsing the repository to find any issues that we can fix.", - "reasoning": "Browsing the repository will give us an idea of the current state of the codebase and identify any issues that we can address to improve the repo.", - "plan": "- Look through the repository to find any issues.\n- Investigate any issues to determine what needs to be fixed\n- Identify possible solutions to fix the issues\n- Open Pull Requests with fixes", - "criticism": "I should be careful while browsing so as not to accidentally introduce any new bugs or issues.", - "speak": "I will start browsing the repository to find any issues we can fix.", - }, - } - # Assert that this raises an exception: - assert fix_and_parse_json(json_str, try_to_fix_with_gpt=False) == good_obj - - -def test_invalid_json_leading_sentence_with_gpt(self): - """Test that a REALLY invalid JSON string raises an error when try_to_fix_with_gpt is False.""" - json_str = """I will first need to browse the repository (https://github.com/Significant-Gravitas/AutoGPT) and identify any potential bugs that need fixing. I will use the "browse_website" command for this. - - { - "command": { - "name": "browse_website", - "args":{ - "url": "https://github.com/Significant-Gravitas/AutoGPT" - } - }, - "thoughts": - { - "text": "Browsing the repository to identify potential bugs", - "reasoning": "Before fixing bugs, I need to identify what needs fixing. I will use the 'browse_website' command to analyze the repository.", - "plan": "- Analyze the repository for potential bugs and areas of improvement", - "criticism": "I need to ensure I am thorough and pay attention to detail while browsing the repository.", - "speak": "I am browsing the repository to identify potential bugs." - } - }""" - good_obj = { - "command": { - "name": "browse_website", - "args": {"url": "https://github.com/Significant-Gravitas/AutoGPT"}, - }, - "thoughts": { - "text": "Browsing the repository to identify potential bugs", - "reasoning": "Before fixing bugs, I need to identify what needs fixing. I will use the 'browse_website' command to analyze the repository.", - "plan": "- Analyze the repository for potential bugs and areas of improvement", - "criticism": "I need to ensure I am thorough and pay attention to detail while browsing the repository.", - "speak": "I am browsing the repository to identify potential bugs.", - }, - } - - assert fix_and_parse_json(json_str, try_to_fix_with_gpt=False) == good_obj diff --git a/autogpts/autogpt/tests/unit/models/test_base_open_api_plugin.py b/autogpts/autogpt/tests/unit/models/test_base_open_api_plugin.py index e656f4643..7a8522e7f 100644 --- a/autogpts/autogpt/tests/unit/models/test_base_open_api_plugin.py +++ b/autogpts/autogpt/tests/unit/models/test_base_open_api_plugin.py @@ -73,7 +73,7 @@ def test_dummy_plugin_default_methods(dummy_plugin): assert isinstance(pre_command, tuple) assert len(pre_command) == 2 assert pre_command[0] == "evolve" - assert pre_command[1]["continuously"] == True + assert pre_command[1]["continuously"] is True post_command = dummy_plugin.post_command("evolve", "upgraded successfully!") assert isinstance(post_command, str) assert post_command == "upgraded successfully!" diff --git a/autogpts/autogpt/tests/unit/test_api_manager.py b/autogpts/autogpt/tests/unit/test_api_manager.py index da9b0c3d8..e669756cd 100644 --- a/autogpts/autogpt/tests/unit/test_api_manager.py +++ b/autogpts/autogpt/tests/unit/test_api_manager.py @@ -1,5 +1,3 @@ -from unittest.mock import patch - import pytest from pytest_mock import MockerFixture @@ -77,13 +75,3 @@ class TestApiManager: assert api_manager.get_total_prompt_tokens() == prompt_tokens assert api_manager.get_total_completion_tokens() == 0 assert api_manager.get_total_cost() == (prompt_tokens * 0.0004) / 1000 - - @staticmethod - def test_get_models(): - """Test if getting models works correctly.""" - with patch("openai.Model.list") as mock_list_models: - mock_list_models.return_value = {"data": [{"id": "gpt-3.5-turbo"}]} - result = api_manager.get_models() - - assert result[0]["id"] == "gpt-3.5-turbo" - assert api_manager.models[0]["id"] == "gpt-3.5-turbo" diff --git a/autogpts/autogpt/tests/unit/test_commands.py b/autogpts/autogpt/tests/unit/test_commands.py index 9bff7c12d..a939ec4d2 100644 --- a/autogpts/autogpt/tests/unit/test_commands.py +++ b/autogpts/autogpt/tests/unit/test_commands.py @@ -201,10 +201,11 @@ def test_import_mock_commands_module(): registry.import_command_module(mock_commands_module) - assert "function_based" in registry - assert registry.commands["function_based"].name == "function_based" + assert "function_based_cmd" in registry + assert registry.commands["function_based_cmd"].name == "function_based_cmd" assert ( - registry.commands["function_based"].description == "Function-based test command" + registry.commands["function_based_cmd"].description + == "Function-based test command" ) @@ -230,8 +231,9 @@ def test_import_temp_command_file_module(tmp_path: Path): # Remove the temp directory from sys.path sys.path.remove(str(tmp_path)) - assert "function_based" in registry - assert registry.commands["function_based"].name == "function_based" + assert "function_based_cmd" in registry + assert registry.commands["function_based_cmd"].name == "function_based_cmd" assert ( - registry.commands["function_based"].description == "Function-based test command" + registry.commands["function_based_cmd"].description + == "Function-based test command" ) diff --git a/autogpts/autogpt/tests/unit/test_config.py b/autogpts/autogpt/tests/unit/test_config.py index 8fc852620..522908f1f 100644 --- a/autogpts/autogpt/tests/unit/test_config.py +++ b/autogpts/autogpt/tests/unit/test_config.py @@ -8,21 +8,22 @@ from unittest import mock from unittest.mock import patch import pytest +from openai.pagination import SyncPage +from openai.types import Model +from pydantic import SecretStr from autogpt.app.configurator import GPT_3_MODEL, GPT_4_MODEL, apply_overrides_to_config from autogpt.config import Config, ConfigBuilder -from autogpt.file_workspace import FileWorkspace def test_initial_values(config: Config) -> None: """ Test if the initial values of the config class attributes are set correctly. """ - assert config.debug_mode is False assert config.continuous_mode is False assert config.tts_config.speak_mode is False assert config.fast_llm == "gpt-3.5-turbo-16k" - assert config.smart_llm == "gpt-4-0314" + assert config.smart_llm.startswith("gpt-4") def test_set_continuous_mode(config: Config) -> None: @@ -81,22 +82,10 @@ def test_set_smart_llm(config: Config) -> None: config.smart_llm = smart_llm -def test_set_debug_mode(config: Config) -> None: - """ - Test if the set_debug_mode() method updates the debug_mode attribute. - """ - # Store debug mode to reset it after the test - debug_mode = config.debug_mode - - config.debug_mode = True - assert config.debug_mode is True - - # Reset debug mode - config.debug_mode = debug_mode - - -@patch("openai.Model.list") -def test_smart_and_fast_llms_set_to_gpt4(mock_list_models: Any, config: Config) -> None: +@patch("openai.resources.models.Models.list") +def test_fallback_to_gpt3_if_gpt4_not_available( + mock_list_models: Any, config: Config +) -> None: """ Test if models update to gpt-3.5-turbo if gpt-4 is not available. """ @@ -106,7 +95,10 @@ def test_smart_and_fast_llms_set_to_gpt4(mock_list_models: Any, config: Config) config.fast_llm = "gpt-4" config.smart_llm = "gpt-4" - mock_list_models.return_value = {"data": [{"id": "gpt-3.5-turbo"}]} + mock_list_models.return_value = SyncPage( + data=[Model(id=GPT_3_MODEL, created=0, object="model", owned_by="AutoGPT")], + object="Models", # no idea what this should be, but irrelevant + ) apply_overrides_to_config( config=config, @@ -122,82 +114,96 @@ def test_smart_and_fast_llms_set_to_gpt4(mock_list_models: Any, config: Config) config.smart_llm = smart_llm -def test_missing_azure_config(workspace: FileWorkspace) -> None: - config_file = workspace.get_path("azure_config.yaml") +def test_missing_azure_config(config: Config) -> None: + assert config.openai_credentials is not None + + config_file = config.app_data_dir / "azure_config.yaml" with pytest.raises(FileNotFoundError): - ConfigBuilder.load_azure_config(config_file) + config.openai_credentials.load_azure_config(config_file) config_file.write_text("") - azure_config = ConfigBuilder.load_azure_config(config_file) + with pytest.raises(ValueError): + config.openai_credentials.load_azure_config(config_file) - assert azure_config["openai_api_type"] == "azure" - assert azure_config["openai_api_base"] == "" - assert azure_config["openai_api_version"] == "2023-03-15-preview" - assert azure_config["azure_model_to_deployment_id_map"] == {} + assert config.openai_credentials.api_type != "azure" + assert config.openai_credentials.api_version == "" + assert config.openai_credentials.azure_model_to_deploy_id_map is None -def test_azure_config(config: Config, workspace: FileWorkspace) -> None: - config_file = workspace.get_path("azure_config.yaml") - yaml_content = """ +@pytest.fixture +def config_with_azure(config: Config): + config_file = config.app_data_dir / "azure_config.yaml" + config_file.write_text( + f""" azure_api_type: azure -azure_api_base: https://dummy.openai.azure.com azure_api_version: 2023-06-01-preview +azure_endpoint: https://dummy.openai.azure.com azure_model_map: - fast_llm_deployment_id: FAST-LLM_ID - smart_llm_deployment_id: SMART-LLM_ID - embedding_model_deployment_id: embedding-deployment-id-for-azure + {config.fast_llm}: FAST-LLM_ID + {config.smart_llm}: SMART-LLM_ID + {config.embedding_model}: embedding-deployment-id-for-azure """ - config_file.write_text(yaml_content) - + ) os.environ["USE_AZURE"] = "True" os.environ["AZURE_CONFIG_FILE"] = str(config_file) - config = ConfigBuilder.build_config_from_env(project_root=workspace.root.parent) - - assert config.openai_api_type == "azure" - assert config.openai_api_base == "https://dummy.openai.azure.com" - assert config.openai_api_version == "2023-06-01-preview" - assert config.azure_model_to_deployment_id_map == { - "fast_llm_deployment_id": "FAST-LLM_ID", - "smart_llm_deployment_id": "SMART-LLM_ID", - "embedding_model_deployment_id": "embedding-deployment-id-for-azure", + config_with_azure = ConfigBuilder.build_config_from_env( + project_root=config.project_root + ) + yield config_with_azure + del os.environ["USE_AZURE"] + del os.environ["AZURE_CONFIG_FILE"] + + +def test_azure_config(config_with_azure: Config) -> None: + assert (credentials := config_with_azure.openai_credentials) is not None + assert credentials.api_type == "azure" + assert credentials.api_version == "2023-06-01-preview" + assert credentials.azure_endpoint == SecretStr("https://dummy.openai.azure.com") + assert credentials.azure_model_to_deploy_id_map == { + config_with_azure.fast_llm: "FAST-LLM_ID", + config_with_azure.smart_llm: "SMART-LLM_ID", + config_with_azure.embedding_model: "embedding-deployment-id-for-azure", } - fast_llm = config.fast_llm - smart_llm = config.smart_llm + fast_llm = config_with_azure.fast_llm + smart_llm = config_with_azure.smart_llm assert ( - config.get_azure_credentials(config.fast_llm)["deployment_id"] == "FAST-LLM_ID" + credentials.get_model_access_kwargs(config_with_azure.fast_llm)["model"] + == "FAST-LLM_ID" ) assert ( - config.get_azure_credentials(config.smart_llm)["deployment_id"] + credentials.get_model_access_kwargs(config_with_azure.smart_llm)["model"] == "SMART-LLM_ID" ) # Emulate --gpt4only - config.fast_llm = smart_llm + config_with_azure.fast_llm = smart_llm assert ( - config.get_azure_credentials(config.fast_llm)["deployment_id"] == "SMART-LLM_ID" + credentials.get_model_access_kwargs(config_with_azure.fast_llm)["model"] + == "SMART-LLM_ID" ) assert ( - config.get_azure_credentials(config.smart_llm)["deployment_id"] + credentials.get_model_access_kwargs(config_with_azure.smart_llm)["model"] == "SMART-LLM_ID" ) # Emulate --gpt3only - config.fast_llm = config.smart_llm = fast_llm + config_with_azure.fast_llm = config_with_azure.smart_llm = fast_llm assert ( - config.get_azure_credentials(config.fast_llm)["deployment_id"] == "FAST-LLM_ID" + credentials.get_model_access_kwargs(config_with_azure.fast_llm)["model"] + == "FAST-LLM_ID" ) assert ( - config.get_azure_credentials(config.smart_llm)["deployment_id"] == "FAST-LLM_ID" + credentials.get_model_access_kwargs(config_with_azure.smart_llm)["model"] + == "FAST-LLM_ID" ) - del os.environ["USE_AZURE"] - del os.environ["AZURE_CONFIG_FILE"] - def test_create_config_gpt4only(config: Config) -> None: with mock.patch("autogpt.llm.api_manager.ApiManager.get_models") as mock_get_models: - mock_get_models.return_value = [{"id": GPT_4_MODEL}] + mock_get_models.return_value = [ + Model(id=GPT_4_MODEL, created=0, object="model", owned_by="AutoGPT") + ] apply_overrides_to_config( config=config, gpt4only=True, diff --git a/autogpts/autogpt/tests/unit/test_file_operations.py b/autogpts/autogpt/tests/unit/test_file_operations.py index 6d4c69ace..21ebd0b32 100644 --- a/autogpts/autogpt/tests/unit/test_file_operations.py +++ b/autogpts/autogpt/tests/unit/test_file_operations.py @@ -1,7 +1,3 @@ -""" -This set of unit tests is designed to test the file operations that autoGPT has access to. -""" - import hashlib import os import re @@ -30,7 +26,7 @@ def mock_MemoryItem_from_text( mocker: MockerFixture, mock_embedding: Embedding, config: Config ): mocker.patch.object( - file_ops.MemoryItem, + file_ops.MemoryItemFactory, "from_text", new=lambda content, source_type, config, metadata: MemoryItem( raw_content=content, @@ -67,7 +63,7 @@ def test_file_with_content_path(test_file: TextIOWrapper, file_content, agent: A test_file.write(file_content) test_file.close() file_ops.log_operation( - "write", test_file.name, agent, file_ops.text_checksum(file_content) + "write", Path(test_file.name), agent, file_ops.text_checksum(file_content) ) return Path(test_file.name) @@ -136,42 +132,46 @@ def test_is_duplicate_operation(agent: Agent, mocker: MockerFixture): # Test cases with write operations assert ( file_ops.is_duplicate_operation( - "write", "path/to/file1.txt", agent, "checksum1" + "write", Path("path/to/file1.txt"), agent, "checksum1" ) is True ) assert ( file_ops.is_duplicate_operation( - "write", "path/to/file1.txt", agent, "checksum2" + "write", Path("path/to/file1.txt"), agent, "checksum2" ) is False ) assert ( file_ops.is_duplicate_operation( - "write", "path/to/file3.txt", agent, "checksum3" + "write", Path("path/to/file3.txt"), agent, "checksum3" ) is False ) # Test cases with append operations assert ( file_ops.is_duplicate_operation( - "append", "path/to/file1.txt", agent, "checksum1" + "append", Path("path/to/file1.txt"), agent, "checksum1" ) is False ) # Test cases with delete operations assert ( - file_ops.is_duplicate_operation("delete", "path/to/file1.txt", agent) is False + file_ops.is_duplicate_operation("delete", Path("path/to/file1.txt"), agent) + is False + ) + assert ( + file_ops.is_duplicate_operation("delete", Path("path/to/file3.txt"), agent) + is True ) - assert file_ops.is_duplicate_operation("delete", "path/to/file3.txt", agent) is True # Test logging a file operation def test_log_operation(agent: Agent): - file_ops.log_operation("log_test", "path/to/test", agent=agent) + file_ops.log_operation("log_test", Path("path/to/test"), agent=agent) with open(agent.file_manager.file_ops_log_path, "r", encoding="utf-8") as f: content = f.read() - assert f"log_test: path/to/test\n" in content + assert "log_test: path/to/test\n" in content def test_text_checksum(file_content: str): @@ -182,10 +182,12 @@ def test_text_checksum(file_content: str): def test_log_operation_with_checksum(agent: Agent): - file_ops.log_operation("log_test", "path/to/test", agent=agent, checksum="ABCDEF") + file_ops.log_operation( + "log_test", Path("path/to/test"), agent=agent, checksum="ABCDEF" + ) with open(agent.file_manager.file_ops_log_path, "r", encoding="utf-8") as f: content = f.read() - assert f"log_test: path/to/test #ABCDEF\n" in content + assert "log_test: path/to/test #ABCDEF\n" in content def test_read_file( diff --git a/autogpts/autogpt/tests/unit/test_gcs_file_workspace.py b/autogpts/autogpt/tests/unit/test_gcs_file_workspace.py new file mode 100644 index 000000000..bfc87e0a4 --- /dev/null +++ b/autogpts/autogpt/tests/unit/test_gcs_file_workspace.py @@ -0,0 +1,131 @@ +import os +import uuid +from pathlib import Path + +import pytest +import pytest_asyncio +from google.auth.exceptions import GoogleAuthError +from google.cloud import storage +from google.cloud.exceptions import NotFound + +from autogpt.file_workspace.gcs import GCSFileWorkspace, GCSFileWorkspaceConfiguration + +try: + storage.Client() +except GoogleAuthError: + pytest.skip("Google Cloud Authentication not configured", allow_module_level=True) + + +@pytest.fixture(scope="module") +def gcs_bucket_name() -> str: + return f"test-bucket-{str(uuid.uuid4())[:8]}" + + +@pytest.fixture(scope="module") +def gcs_workspace_uninitialized(gcs_bucket_name: str) -> GCSFileWorkspace: + os.environ["WORKSPACE_STORAGE_BUCKET"] = gcs_bucket_name + ws_config = GCSFileWorkspaceConfiguration.from_env() + ws_config.root = Path("/workspaces/AutoGPT-some-unique-task-id") + workspace = GCSFileWorkspace(ws_config) + yield workspace # type: ignore + del os.environ["WORKSPACE_STORAGE_BUCKET"] + + +def test_initialize( + gcs_bucket_name: str, gcs_workspace_uninitialized: GCSFileWorkspace +): + gcs = gcs_workspace_uninitialized._gcs + + # test that the bucket doesn't exist yet + with pytest.raises(NotFound): + gcs.get_bucket(gcs_bucket_name) + + gcs_workspace_uninitialized.initialize() + + # test that the bucket has been created + bucket = gcs.get_bucket(gcs_bucket_name) + + # clean up + bucket.delete(force=True) + + +@pytest.fixture(scope="module") +def gcs_workspace(gcs_workspace_uninitialized: GCSFileWorkspace) -> GCSFileWorkspace: + (gcs_workspace := gcs_workspace_uninitialized).initialize() + yield gcs_workspace # type: ignore + + # Empty & delete the test bucket + gcs_workspace._bucket.delete(force=True) + + +def test_workspace_bucket_name( + gcs_workspace: GCSFileWorkspace, + gcs_bucket_name: str, +): + assert gcs_workspace._bucket.name == gcs_bucket_name + + +NESTED_DIR = "existing/test/dir" +TEST_FILES: list[tuple[str | Path, str]] = [ + ("existing_test_file_1", "test content 1"), + ("existing_test_file_2.txt", "test content 2"), + (Path("existing_test_file_3"), "test content 3"), + (Path(f"{NESTED_DIR}/test/file/4"), "test content 4"), +] + + +@pytest_asyncio.fixture +async def gcs_workspace_with_files(gcs_workspace: GCSFileWorkspace) -> GCSFileWorkspace: + for file_name, file_content in TEST_FILES: + gcs_workspace._bucket.blob( + str(gcs_workspace.get_path(file_name)) + ).upload_from_string(file_content) + yield gcs_workspace # type: ignore + + +@pytest.mark.asyncio +async def test_read_file(gcs_workspace_with_files: GCSFileWorkspace): + for file_name, file_content in TEST_FILES: + content = gcs_workspace_with_files.read_file(file_name) + assert content == file_content + + with pytest.raises(NotFound): + gcs_workspace_with_files.read_file("non_existent_file") + + +def test_list_files(gcs_workspace_with_files: GCSFileWorkspace): + # List at root level + assert (files := gcs_workspace_with_files.list()) == gcs_workspace_with_files.list() + assert len(files) > 0 + assert set(files) == set(Path(file_name) for file_name, _ in TEST_FILES) + + # List at nested path + assert ( + nested_files := gcs_workspace_with_files.list(NESTED_DIR) + ) == gcs_workspace_with_files.list(NESTED_DIR) + assert len(nested_files) > 0 + assert set(nested_files) == set( + p.relative_to(NESTED_DIR) + for file_name, _ in TEST_FILES + if (p := Path(file_name)).is_relative_to(NESTED_DIR) + ) + + +@pytest.mark.asyncio +async def test_write_read_file(gcs_workspace: GCSFileWorkspace): + await gcs_workspace.write_file("test_file", "test_content") + assert gcs_workspace.read_file("test_file") == "test_content" + + +@pytest.mark.asyncio +async def test_overwrite_file(gcs_workspace_with_files: GCSFileWorkspace): + for file_name, _ in TEST_FILES: + await gcs_workspace_with_files.write_file(file_name, "new content") + assert gcs_workspace_with_files.read_file(file_name) == "new content" + + +def test_delete_file(gcs_workspace_with_files: GCSFileWorkspace): + for file_to_delete, _ in TEST_FILES: + gcs_workspace_with_files.delete_file(file_to_delete) + with pytest.raises(NotFound): + gcs_workspace_with_files.read_file(file_to_delete) diff --git a/autogpts/autogpt/tests/unit/test_git_commands.py b/autogpts/autogpt/tests/unit/test_git_commands.py index 48fa92d7f..42bcd7b99 100644 --- a/autogpts/autogpt/tests/unit/test_git_commands.py +++ b/autogpts/autogpt/tests/unit/test_git_commands.py @@ -26,7 +26,7 @@ def test_clone_auto_gpt_repository(workspace, mock_clone_from, agent: Agent): assert clone_result == expected_output mock_clone_from.assert_called_once_with( - url=f"{scheme}{agent.legacy_config.github_username}:{agent.legacy_config.github_api_key}@{repo}", + url=f"{scheme}{agent.legacy_config.github_username}:{agent.legacy_config.github_api_key}@{repo}", # noqa: E501 to_path=clone_path, ) diff --git a/autogpts/autogpt/tests/unit/test_workspace.py b/autogpts/autogpt/tests/unit/test_local_file_workspace.py index 58cad4597..8f57d43b0 100644 --- a/autogpts/autogpt/tests/unit/test_workspace.py +++ b/autogpts/autogpt/tests/unit/test_local_file_workspace.py @@ -1,9 +1,8 @@ -import itertools from pathlib import Path import pytest -from autogpt.file_workspace import FileWorkspace +from autogpt.file_workspace.local import FileWorkspaceConfiguration, LocalFileWorkspace _WORKSPACE_ROOT = Path("home/users/monty/auto_gpt_workspace") @@ -31,17 +30,11 @@ _INACCESSIBLE_PATHS = ( Path("test_folder/../../not_auto_gpt_workspace/test_file.txt"), ] + [ - # Contains null bytes - Path(template.format(null_byte=null_byte)) - for template, null_byte in itertools.product( - [ - "{null_byte}", - "{null_byte}test_file.txt", - "test_folder/{null_byte}", - "test_folder/{null_byte}test_file.txt", - ], - FileWorkspace.NULL_BYTES, - ) + # Contains null byte + Path("\0"), + Path("\0test_file.txt"), + Path("test_folder/\0"), + Path("test_folder/\0test_file.txt"), ] + [ # Absolute paths @@ -68,7 +61,7 @@ def inaccessible_path(request): def test_sanitize_path_accessible(accessible_path, workspace_root): - full_path = FileWorkspace._sanitize_path( + full_path = LocalFileWorkspace._sanitize_path( accessible_path, root=workspace_root, restrict_to_root=True, @@ -79,7 +72,7 @@ def test_sanitize_path_accessible(accessible_path, workspace_root): def test_sanitize_path_inaccessible(inaccessible_path, workspace_root): with pytest.raises(ValueError): - FileWorkspace._sanitize_path( + LocalFileWorkspace._sanitize_path( inaccessible_path, root=workspace_root, restrict_to_root=True, @@ -87,13 +80,13 @@ def test_sanitize_path_inaccessible(inaccessible_path, workspace_root): def test_get_path_accessible(accessible_path, workspace_root): - workspace = FileWorkspace(workspace_root, True) + workspace = LocalFileWorkspace(FileWorkspaceConfiguration(root=workspace_root)) full_path = workspace.get_path(accessible_path) assert full_path.is_absolute() assert full_path.is_relative_to(workspace_root) def test_get_path_inaccessible(inaccessible_path, workspace_root): - workspace = FileWorkspace(workspace_root, True) + workspace = LocalFileWorkspace(FileWorkspaceConfiguration(root=workspace_root)) with pytest.raises(ValueError): workspace.get_path(inaccessible_path) diff --git a/autogpts/autogpt/tests/unit/test_logs.py b/autogpts/autogpt/tests/unit/test_logs.py index da0a48711..1ded61f31 100644 --- a/autogpts/autogpt/tests/unit/test_logs.py +++ b/autogpts/autogpt/tests/unit/test_logs.py @@ -7,12 +7,20 @@ from autogpt.logs.utils import remove_color_codes "raw_text, clean_text", [ ( - "COMMAND = \x1b[36mbrowse_website\x1b[0m ARGUMENTS = \x1b[36m{'url': 'https://www.google.com', 'question': 'What is the capital of France?'}\x1b[0m", - "COMMAND = browse_website ARGUMENTS = {'url': 'https://www.google.com', 'question': 'What is the capital of France?'}", + "COMMAND = \x1b[36mbrowse_website\x1b[0m " + "ARGUMENTS = \x1b[36m{'url': 'https://www.google.com'," + " 'question': 'What is the capital of France?'}\x1b[0m", + "COMMAND = browse_website " + "ARGUMENTS = {'url': 'https://www.google.com'," + " 'question': 'What is the capital of France?'}", ), ( - "{'Schaue dir meine Projekte auf github () an, als auch meine Webseiten': 'https://github.com/Significant-Gravitas/AutoGPT, https://discord.gg/autogpt und https://twitter.com/Auto_GPT'}", - "{'Schaue dir meine Projekte auf github () an, als auch meine Webseiten': 'https://github.com/Significant-Gravitas/AutoGPT, https://discord.gg/autogpt und https://twitter.com/Auto_GPT'}", + "{'Schaue dir meine Projekte auf github () an, als auch meine Webseiten': " + "'https://github.com/Significant-Gravitas/AutoGPT," + " https://discord.gg/autogpt und https://twitter.com/Auto_GPT'}", + "{'Schaue dir meine Projekte auf github () an, als auch meine Webseiten': " + "'https://github.com/Significant-Gravitas/AutoGPT," + " https://discord.gg/autogpt und https://twitter.com/Auto_GPT'}", ), ("", ""), ("hello", "hello"), diff --git a/autogpts/autogpt/tests/unit/test_plugins.py b/autogpts/autogpt/tests/unit/test_plugins.py index 981715ac3..d7f57c91b 100644 --- a/autogpts/autogpt/tests/unit/test_plugins.py +++ b/autogpts/autogpt/tests/unit/test_plugins.py @@ -21,7 +21,7 @@ def test_scan_plugins_openai(config: Config): ) # Test that the function returns the correct number of plugins - result = scan_plugins(config, debug=True) + result = scan_plugins(config) assert len(result) == 1 @@ -34,7 +34,7 @@ def test_scan_plugins_generic(config: Config): plugins_config.plugins["AutoGPTPVicuna"] = PluginConfig( name="AutoGPTPVicuna", enabled=True ) - result = scan_plugins(config, debug=True) + result = scan_plugins(config) plugin_class_names = [plugin.__class__.__name__ for plugin in result] assert len(result) == 2 @@ -51,7 +51,7 @@ def test_scan_plugins_not_enabled(config: Config): plugins_config.plugins["auto_gpt_vicuna"] = PluginConfig( name="auto_gptp_vicuna", enabled=False ) - result = scan_plugins(config, debug=True) + result = scan_plugins(config) plugin_class_names = [plugin.__class__.__name__ for plugin in result] assert len(result) == 1 @@ -65,7 +65,10 @@ def test_inspect_zip_for_modules(): def test_create_base_config(config: Config): - """Test the backwards-compatibility shim to convert old plugin allow/deny list to a config file""" + """ + Test the backwards-compatibility shim to convert old plugin allow/deny list + to a config file. + """ config.plugins_allowlist = ["a", "b"] config.plugins_denylist = ["c", "d"] @@ -96,7 +99,9 @@ def test_create_base_config(config: Config): def test_load_config(config: Config): - """Test that the plugin config is loaded correctly from the plugins_config.yaml file""" + """ + Test that the plugin config is loaded correctly from the plugins_config.yaml file. + """ # Create a test config and write it to disk test_config = { "a": {"enabled": True, "config": {"api_key": "1234"}}, diff --git a/autogpts/autogpt/tests/unit/test_retry_provider_openai.py b/autogpts/autogpt/tests/unit/test_retry_provider_openai.py deleted file mode 100644 index e076a3973..000000000 --- a/autogpts/autogpt/tests/unit/test_retry_provider_openai.py +++ /dev/null @@ -1,143 +0,0 @@ -import logging - -import pytest -from openai.error import APIError, RateLimitError, ServiceUnavailableError - -from autogpt.llm.providers import openai -from autogpt.logs.config import USER_FRIENDLY_OUTPUT_LOGGER - - -@pytest.fixture(params=[RateLimitError, ServiceUnavailableError, APIError]) -def error(request): - if request.param == APIError: - return request.param("Error", http_status=502) - else: - return request.param("Error") - - -def error_factory(error_instance, error_count, retry_count, warn_user=True): - """Creates errors""" - - class RaisesError: - def __init__(self): - self.count = 0 - - @openai.retry_api( - max_retries=retry_count, backoff_base=0.001, warn_user=warn_user - ) - def __call__(self): - self.count += 1 - if self.count <= error_count: - raise error_instance - return self.count - - return RaisesError() - - -def test_retry_open_api_no_error(caplog: pytest.LogCaptureFixture): - """Tests the retry functionality with no errors expected""" - - @openai.retry_api() - def f(): - return 1 - - result = f() - assert result == 1 - - output = caplog.text - assert output == "" - assert output == "" - - -@pytest.mark.parametrize( - "error_count, retry_count, failure", - [(2, 10, False), (2, 2, False), (10, 2, True), (3, 2, True), (1, 0, True)], - ids=["passing", "passing_edge", "failing", "failing_edge", "failing_no_retries"], -) -def test_retry_open_api_passing( - caplog: pytest.LogCaptureFixture, - error: Exception, - error_count: int, - retry_count: int, - failure: bool, -): - """Tests the retry with simulated errors [RateLimitError, ServiceUnavailableError, APIError], but should ulimately pass""" - - # Add capture handler to non-propagating logger - logging.getLogger(USER_FRIENDLY_OUTPUT_LOGGER).addHandler(caplog.handler) - - call_count = min(error_count, retry_count) + 1 - - raises = error_factory(error, error_count, retry_count) - if failure: - with pytest.raises(type(error)): - raises() - else: - result = raises() - assert result == call_count - - assert raises.count == call_count - - output = caplog.text - - if error_count and retry_count: - if type(error) == RateLimitError: - assert "Reached rate limit" in output - assert "Please double check" in output - if type(error) == ServiceUnavailableError: - assert "The OpenAI API engine is currently overloaded" in output - assert "Please double check" in output - else: - assert output == "" - - -def test_retry_open_api_rate_limit_no_warn(caplog: pytest.LogCaptureFixture): - """Tests the retry logic with a rate limit error""" - error_count = 2 - retry_count = 10 - - raises = error_factory(RateLimitError, error_count, retry_count, warn_user=False) - result = raises() - call_count = min(error_count, retry_count) + 1 - assert result == call_count - assert raises.count == call_count - - output = caplog.text - - assert "Reached rate limit" in output - assert "Please double check" not in output - - -def test_retry_open_api_service_unavairable_no_warn(caplog: pytest.LogCaptureFixture): - """Tests the retry logic with a service unavairable error""" - error_count = 2 - retry_count = 10 - - raises = error_factory( - ServiceUnavailableError, error_count, retry_count, warn_user=False - ) - result = raises() - call_count = min(error_count, retry_count) + 1 - assert result == call_count - assert raises.count == call_count - - output = caplog.text - - assert "The OpenAI API engine is currently overloaded" in output - assert "Please double check" not in output - - -def test_retry_openapi_other_api_error(caplog: pytest.LogCaptureFixture): - """Tests the Retry logic with a non rate limit error such as HTTP500""" - error_count = 2 - retry_count = 10 - - raises = error_factory(APIError("Error", http_status=500), error_count, retry_count) - - with pytest.raises(APIError): - raises() - call_count = 1 - assert raises.count == call_count - - output = caplog.text - assert output == "" diff --git a/autogpts/autogpt/tests/unit/test_s3_file_workspace.py b/autogpts/autogpt/tests/unit/test_s3_file_workspace.py new file mode 100644 index 000000000..980d1e3b8 --- /dev/null +++ b/autogpts/autogpt/tests/unit/test_s3_file_workspace.py @@ -0,0 +1,123 @@ +import os +import uuid +from pathlib import Path + +import pytest +import pytest_asyncio +from botocore.exceptions import ClientError + +from autogpt.file_workspace.s3 import S3FileWorkspace, S3FileWorkspaceConfiguration + +if not os.getenv("S3_ENDPOINT_URL") and not os.getenv("AWS_ACCESS_KEY_ID"): + pytest.skip("S3 environment variables are not set", allow_module_level=True) + + +@pytest.fixture +def s3_bucket_name() -> str: + return f"test-bucket-{str(uuid.uuid4())[:8]}" + + +@pytest.fixture +def s3_workspace_uninitialized(s3_bucket_name: str) -> S3FileWorkspace: + os.environ["WORKSPACE_STORAGE_BUCKET"] = s3_bucket_name + ws_config = S3FileWorkspaceConfiguration.from_env() + ws_config.root = Path("/workspaces/AutoGPT-some-unique-task-id") + workspace = S3FileWorkspace(ws_config) + yield workspace # type: ignore + del os.environ["WORKSPACE_STORAGE_BUCKET"] + + +def test_initialize(s3_bucket_name: str, s3_workspace_uninitialized: S3FileWorkspace): + s3 = s3_workspace_uninitialized._s3 + + # test that the bucket doesn't exist yet + with pytest.raises(ClientError): + s3.meta.client.head_bucket(Bucket=s3_bucket_name) + + s3_workspace_uninitialized.initialize() + + # test that the bucket has been created + s3.meta.client.head_bucket(Bucket=s3_bucket_name) + + +def test_workspace_bucket_name( + s3_workspace: S3FileWorkspace, + s3_bucket_name: str, +): + assert s3_workspace._bucket.name == s3_bucket_name + + +@pytest.fixture +def s3_workspace(s3_workspace_uninitialized: S3FileWorkspace) -> S3FileWorkspace: + (s3_workspace := s3_workspace_uninitialized).initialize() + yield s3_workspace # type: ignore + + # Empty & delete the test bucket + s3_workspace._bucket.objects.all().delete() + s3_workspace._bucket.delete() + + +NESTED_DIR = "existing/test/dir" +TEST_FILES: list[tuple[str | Path, str]] = [ + ("existing_test_file_1", "test content 1"), + ("existing_test_file_2.txt", "test content 2"), + (Path("existing_test_file_3"), "test content 3"), + (Path(f"{NESTED_DIR}/test/file/4"), "test content 4"), +] + + +@pytest_asyncio.fixture +async def s3_workspace_with_files(s3_workspace: S3FileWorkspace) -> S3FileWorkspace: + for file_name, file_content in TEST_FILES: + s3_workspace._bucket.Object(str(s3_workspace.get_path(file_name))).put( + Body=file_content + ) + yield s3_workspace # type: ignore + + +@pytest.mark.asyncio +async def test_read_file(s3_workspace_with_files: S3FileWorkspace): + for file_name, file_content in TEST_FILES: + content = s3_workspace_with_files.read_file(file_name) + assert content == file_content + + with pytest.raises(ClientError): + s3_workspace_with_files.read_file("non_existent_file") + + +def test_list_files(s3_workspace_with_files: S3FileWorkspace): + # List at root level + assert (files := s3_workspace_with_files.list()) == s3_workspace_with_files.list() + assert len(files) > 0 + assert set(files) == set(Path(file_name) for file_name, _ in TEST_FILES) + + # List at nested path + assert ( + nested_files := s3_workspace_with_files.list(NESTED_DIR) + ) == s3_workspace_with_files.list(NESTED_DIR) + assert len(nested_files) > 0 + assert set(nested_files) == set( + p.relative_to(NESTED_DIR) + for file_name, _ in TEST_FILES + if (p := Path(file_name)).is_relative_to(NESTED_DIR) + ) + + +@pytest.mark.asyncio +async def test_write_read_file(s3_workspace: S3FileWorkspace): + await s3_workspace.write_file("test_file", "test_content") + assert s3_workspace.read_file("test_file") == "test_content" + + +@pytest.mark.asyncio +async def test_overwrite_file(s3_workspace_with_files: S3FileWorkspace): + for file_name, _ in TEST_FILES: + await s3_workspace_with_files.write_file(file_name, "new content") + assert s3_workspace_with_files.read_file(file_name) == "new content" + + +def test_delete_file(s3_workspace_with_files: S3FileWorkspace): + for file_to_delete, _ in TEST_FILES: + s3_workspace_with_files.delete_file(file_to_delete) + with pytest.raises(ClientError): + s3_workspace_with_files.read_file(file_to_delete) diff --git a/autogpts/autogpt/tests/unit/test_spinner.py b/autogpts/autogpt/tests/unit/test_spinner.py index 8f894b79d..9f2cbac65 100644 --- a/autogpts/autogpt/tests/unit/test_spinner.py +++ b/autogpts/autogpt/tests/unit/test_spinner.py @@ -1,29 +1,7 @@ -# Generated by CodiumAI import time from autogpt.app.spinner import Spinner -""" -Code Analysis - -Main functionalities: -The Spinner class provides a simple way to display a spinning animation while a process is running. It can be used to indicate that a process is ongoing and to provide visual feedback to the user. The class can be used as a context manager, which means that it can be used with the 'with' statement to automatically start and stop the spinner animation. - -Methods: -- __init__(self, message: str = "Loading...", delay: float = 0.1) -> None: Initializes the Spinner class with a message to display and a delay between each spinner update. -- spin(self) -> None: Spins the spinner animation while the process is running. -- __enter__(self): Starts the spinner animation when used as a context manager. -- __exit__(self, exc_type, exc_value, exc_traceback) -> None: Stops the spinner animation when used as a context manager. -- update_message(self, new_message, delay=0.1): Updates the message displayed by the spinner animation. - -Fields: -- spinner: An itertools.cycle object that contains the characters used for the spinner animation. -- delay: The delay between each spinner update. -- message: The message to display. -- running: A boolean value that indicates whether the spinner animation is running. -- spinner_thread: A threading.Thread object that runs the spin method in a separate thread. -""" - ALMOST_DONE_MESSAGE = "Almost done..." PLEASE_WAIT = "Please wait..." diff --git a/autogpts/autogpt/tests/unit/test_text_file_parsers.py b/autogpts/autogpt/tests/unit/test_text_file_parsers.py index ae2ad3ce5..c13241580 100644 --- a/autogpts/autogpt/tests/unit/test_text_file_parsers.py +++ b/autogpts/autogpt/tests/unit/test_text_file_parsers.py @@ -1,14 +1,19 @@ import json import logging +import os.path import tempfile from pathlib import Path from xml.etree import ElementTree import docx +import pytest import yaml from bs4 import BeautifulSoup -from autogpt.commands.file_operations_utils import is_file_binary_fn, read_textual_file +from autogpt.commands.file_operations_utils import ( + decode_textual_file, + is_file_binary_fn, +) logger = logging.getLogger(__name__) @@ -39,7 +44,8 @@ def mock_pdf_file(): # Write the page object f.write(b"2 0 obj\n") f.write( - b"<< /Type /Page /Parent 1 0 R /Resources << /Font << /F1 3 0 R >> >> /MediaBox [0 0 612 792] /Contents 4 0 R >>\n" + b"<< /Type /Page /Parent 1 0 R /Resources << /Font << /F1 3 0 R >> >> " + b"/MediaBox [0 0 612 792] /Contents 4 0 R >>\n" ) f.write(b"endobj\n") # Write the font object @@ -103,7 +109,10 @@ def mock_yaml_file(): def mock_html_file(): html = BeautifulSoup( - f"<html><head><title>This is a test</title></head><body><p>{plain_text_str}</p></body></html>", + "<html>" + "<head><title>This is a test</title></head>" + f"<body><p>{plain_text_str}</p></body>" + "</html>", "html.parser", ) with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".html") as f: @@ -119,7 +128,12 @@ def mock_md_file(): def mock_latex_file(): with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".tex") as f: - latex_str = rf"\documentclass{{article}}\begin{{document}}{plain_text_str}\end{{document}}" + latex_str = ( + r"\documentclass{article}" + r"\begin{document}" + f"{plain_text_str}" + r"\end{document}" + ) f.write(latex_str) return f.name @@ -139,15 +153,18 @@ respective_file_creation_functions = { binary_files_extensions = [".pdf", ".docx"] -def test_parsers(): - for ( - file_extension, - c_file_creator, - ) in respective_file_creation_functions.items(): - created_file_path = Path(c_file_creator()) - loaded_text = read_textual_file(created_file_path, logger) +@pytest.mark.parametrize( + "file_extension, c_file_creator", + respective_file_creation_functions.items(), +) +def test_parsers(file_extension, c_file_creator): + created_file_path = Path(c_file_creator()) + with open(created_file_path, "rb") as file: + loaded_text = decode_textual_file(file, os.path.splitext(file.name)[1], logger) assert plain_text_str in loaded_text should_be_binary = file_extension in binary_files_extensions - assert should_be_binary == is_file_binary_fn(created_file_path) + assert should_be_binary == is_file_binary_fn(file) + + created_file_path.unlink() # cleanup diff --git a/autogpts/autogpt/tests/unit/test_url_validation.py b/autogpts/autogpt/tests/unit/test_url_validation.py index 5d6e8124e..cfecc48dd 100644 --- a/autogpts/autogpt/tests/unit/test_url_validation.py +++ b/autogpts/autogpt/tests/unit/test_url_validation.py @@ -3,33 +3,6 @@ from pytest import raises from autogpt.url_utils.validators import validate_url -""" -Code Analysis - -Objective: -The objective of the 'validate_url' function is to validate URLs for any command that requires a URL as an argument. It checks if the URL is valid using a basic check, urllib check, and local file check. If the URL fails any of the validation tests, it raises a ValueError. - -Inputs: -- func: A callable function that takes in any number of arguments and returns any type of output. - -Flow: -- The 'validate_url' function takes in a callable function as an argument. -- It defines a wrapper function that takes in a URL and any number of arguments and keyword arguments. -- The wrapper function first checks if the URL starts with "http://" or "https://". If not, it raises a ValueError with the message "Invalid URL format". -- It then checks if the URL is valid using the 'is_valid_url' function. If not, it raises a ValueError with the message "Missing Scheme or Network location". -- It then checks if the URL is a local file using the 'check_local_file_access' function. If it is, it raises a ValueError with the message "Access to local files is restricted". -- If the URL passes all the validation tests, it sanitizes the URL using the 'sanitize_url' function and calls the original function with the sanitized URL and any other arguments and keyword arguments. -- The wrapper function returns the result of the original function. - -Outputs: -- The 'validate_url' function returns the wrapper function that takes in a URL and any number of arguments and keyword arguments and returns the result of the original function. - -Additional aspects: -- The 'validate_url' function uses the 'functools.wraps' decorator to preserve the original function's metadata, such as its name, docstring, and annotations. -- The 'validate_url' function uses the 'urlparse' function from the 'urllib.parse' module to parse the URL and extract its components. -- The 'validate_url' function uses the 'urljoin' function from the 'requests.compat' module to join the sanitized URL components back into a URL string. -""" - @validate_url def dummy_method(url): @@ -64,103 +37,121 @@ def test_url_validation_fails_invalid_url(url, expected_error): local_file = ( - ("http://localhost"), - ("https://localhost/"), - ("http://2130706433"), - ("https://2130706433"), - ("http://127.0.0.1/"), + ("file://localhost"), + ("file://localhost/home/reinier/secrets.txt"), + ("file:///home/reinier/secrets.txt"), + ("file:///C:/Users/Reinier/secrets.txt"), ) @pytest.mark.parametrize("url", local_file) def test_url_validation_fails_local_path(url): - with raises(ValueError, match="Access to local files is restricted"): + with raises(ValueError): dummy_method(url) -class TestValidateUrl: - # Tests that the function successfully validates a valid URL with http:// or https:// prefix. - def test_happy_path_valid_url(self): - """Test that the function successfully validates a valid URL with http:// or https:// prefix""" +def test_happy_path_valid_url(): + """ + Test that the function successfully validates a valid URL with `http://` or + `https://` prefix. + """ + + @validate_url + def test_func(url): + return url + + assert test_func("https://www.google.com") == "https://www.google.com" + assert test_func("http://www.google.com") == "http://www.google.com" + - @validate_url - def test_func(url): - return url +def test_general_behavior_additional_path_parameters_query_string(): + """ + Test that the function successfully validates a valid URL with additional path, + parameters, and query string. + """ - assert test_func("https://www.google.com") == "https://www.google.com" - assert test_func("http://www.google.com") == "http://www.google.com" + @validate_url + def test_func(url): + return url - # Tests that the function successfully validates a valid URL with additional path, parameters, and query string. - def test_general_behavior_additional_path_parameters_query_string(self): - """Test that the function successfully validates a valid URL with additional path, parameters, and query string""" + assert ( + test_func("https://www.google.com/search?q=python") + == "https://www.google.com/search?q=python" + ) - @validate_url - def test_func(url): - return url - assert ( - test_func("https://www.google.com/search?q=python") - == "https://www.google.com/search?q=python" - ) +def test_edge_case_missing_scheme_or_network_location(): + """ + Test that the function raises a ValueError if the URL is missing scheme or + network location. + """ - # Tests that the function raises a ValueError if the URL is missing scheme or network location. - def test_edge_case_missing_scheme_or_network_location(self): - """Test that the function raises a ValueError if the URL is missing scheme or network location""" + @validate_url + def test_func(url): + return url - @validate_url - def test_func(url): - return url + with pytest.raises(ValueError): + test_func("www.google.com") - with pytest.raises(ValueError): - test_func("www.google.com") - # Tests that the function raises a ValueError if the URL has local file access. - def test_edge_case_local_file_access(self): - """Test that the function raises a ValueError if the URL has local file access""" +def test_edge_case_local_file_access(): + """Test that the function raises a ValueError if the URL has local file access""" - @validate_url - def test_func(url): - return url + @validate_url + def test_func(url): + return url - with pytest.raises(ValueError): - test_func("file:///etc/passwd") + with pytest.raises(ValueError): + test_func("file:///etc/passwd") - # Tests that the function sanitizes the URL by removing any unnecessary components. - def test_general_behavior_sanitizes_url(self): - """Test that the function sanitizes the URL by removing any unnecessary components""" - @validate_url - def test_func(url): - return url +def test_general_behavior_sanitizes_url(): + """Test that the function sanitizes the URL by removing unnecessary components""" - assert ( - test_func("https://www.google.com/search?q=python#top") - == "https://www.google.com/search?q=python" - ) + @validate_url + def test_func(url): + return url - # Tests that the function raises a ValueError if the URL has an invalid format (e.g. missing slashes). - def test_general_behavior_invalid_url_format(self): - """Test that the function raises a ValueError if the URL has an invalid format (e.g. missing slashes)""" + assert ( + test_func("https://www.google.com/search?q=python#top") + == "https://www.google.com/search?q=python" + ) - @validate_url - def test_func(url): - return url - with pytest.raises(ValueError): - test_func("https:www.google.com") +def test_general_behavior_invalid_url_format(): + """ + Test that the function raises a ValueError if the URL has an invalid format + (e.g. missing slashes) + """ - # Tests that the function can handle URLs that contain unusual but valid characters. - def test_url_with_special_chars(self): - url = "https://example.com/path%20with%20spaces" - assert dummy_method(url) == url + @validate_url + def test_func(url): + return url - # Tests that the function raises a ValueError if the URL is over 2000 characters. - def test_extremely_long_url(self): - url = "http://example.com/" + "a" * 2000 - with raises(ValueError, match="URL is too long"): - dummy_method(url) + with pytest.raises(ValueError): + test_func("https:www.google.com") - # Tests that the function can handle internationalized URLs, which contain non-ASCII characters. - def test_internationalized_url(self): - url = "http://例子.测试" - assert dummy_method(url) == url + +def test_url_with_special_chars(): + """ + Tests that the function can handle URLs that contain unusual but valid characters. + """ + url = "https://example.com/path%20with%20spaces" + assert dummy_method(url) == url + + +def test_extremely_long_url(): + """ + Tests that the function raises a ValueError if the URL is over 2000 characters. + """ + url = "http://example.com/" + "a" * 2000 + with raises(ValueError, match="URL is too long"): + dummy_method(url) + + +def test_internationalized_url(): + """ + Tests that the function can handle internationalized URLs with non-ASCII characters. + """ + url = "http://例子.测试" + assert dummy_method(url) == url diff --git a/autogpts/autogpt/tests/unit/test_utils.py b/autogpts/autogpt/tests/unit/test_utils.py index 2cea8dce9..afe2497dc 100644 --- a/autogpts/autogpt/tests/unit/test_utils.py +++ b/autogpts/autogpt/tests/unit/test_utils.py @@ -3,6 +3,7 @@ from unittest.mock import patch import pytest import requests +from git import InvalidGitRepositoryError from autogpt.app.utils import ( get_bulletin_from_web, @@ -18,11 +19,15 @@ from tests.utils import skip_in_ci def valid_json_response() -> dict: return { "thoughts": { - "text": "My task is complete. I will use the 'task_complete' command to shut down.", - "reasoning": "I will use the 'task_complete' command because it allows me to shut down and signal that my task is complete.", - "plan": "I will use the 'task_complete' command with the reason 'Task complete: retrieved Tesla's revenue in 2022.' to shut down.", - "criticism": "I need to ensure that I have completed all necessary tasks before shutting down.", - "speak": "", + "text": "My task is complete. I will use the 'task_complete' command " + "to shut down.", + "reasoning": "I will use the 'task_complete' command because it allows me " + "to shut down and signal that my task is complete.", + "plan": "I will use the 'task_complete' command with the reason " + "'Task complete: retrieved Tesla's revenue in 2022.' to shut down.", + "criticism": "I need to ensure that I have completed all necessary tasks " + "before shutting down.", + "speak": "All done!", }, "command": { "name": "task_complete", @@ -35,10 +40,14 @@ def valid_json_response() -> dict: def invalid_json_response() -> dict: return { "thoughts": { - "text": "My task is complete. I will use the 'task_complete' command to shut down.", - "reasoning": "I will use the 'task_complete' command because it allows me to shut down and signal that my task is complete.", - "plan": "I will use the 'task_complete' command with the reason 'Task complete: retrieved Tesla's revenue in 2022.' to shut down.", - "criticism": "I need to ensure that I have completed all necessary tasks before shutting down.", + "text": "My task is complete. I will use the 'task_complete' command " + "to shut down.", + "reasoning": "I will use the 'task_complete' command because it allows me " + "to shut down and signal that my task is complete.", + "plan": "I will use the 'task_complete' command with the reason " + "'Task complete: retrieved Tesla's revenue in 2022.' to shut down.", + "criticism": "I need to ensure that I have completed all necessary tasks " + "before shutting down.", "speak": "", }, "command": {"name": "", "args": {}}, @@ -51,27 +60,32 @@ def test_validate_yaml_file_valid(): result, message = validate_yaml_file("valid_test_file.yaml") os.remove("valid_test_file.yaml") - assert result == True + assert result is True assert "Successfully validated" in message def test_validate_yaml_file_not_found(): result, message = validate_yaml_file("non_existent_file.yaml") - assert result == False + assert result is False assert "wasn't found" in message def test_validate_yaml_file_invalid(): with open("invalid_test_file.yaml", "w") as f: f.write( - "settings:\n first_setting: value\n second_setting: value\n nested_setting: value\n third_setting: value\nunindented_setting: value" + "settings:\n" + " first_setting: value\n" + " second_setting: value\n" + " nested_setting: value\n" + " third_setting: value\n" + "unindented_setting: value" ) result, message = validate_yaml_file("invalid_test_file.yaml") os.remove("invalid_test_file.yaml") print(result) print(message) - assert result == False + assert result is False assert "There was an issue while trying to read" in message @@ -85,7 +99,7 @@ def test_get_bulletin_from_web_success(mock_get): assert expected_content in bulletin mock_get.assert_called_with( - "https://raw.githubusercontent.com/Significant-Gravitas/AutoGPT/master/autogpts/autogpt/BULLETIN.md" + "https://raw.githubusercontent.com/Significant-Gravitas/AutoGPT/master/autogpts/autogpt/BULLETIN.md" # noqa: E501 ) @@ -121,7 +135,7 @@ def test_get_latest_bulletin_with_file(): with patch("autogpt.app.utils.get_bulletin_from_web", return_value=""): bulletin, is_new = get_latest_bulletin() assert expected_content in bulletin - assert is_new == False + assert is_new is False os.remove("data/CURRENT_BULLETIN.md") @@ -152,7 +166,7 @@ def test_get_latest_bulletin_new_bulletin_same_as_old_bulletin(): ): bulletin, is_new = get_latest_bulletin() assert expected_content in bulletin - assert is_new == False + assert is_new is False os.remove("data/CURRENT_BULLETIN.md") @@ -160,8 +174,6 @@ def test_get_latest_bulletin_new_bulletin_same_as_old_bulletin(): @skip_in_ci def test_get_current_git_branch(): branch_name = get_current_git_branch() - - # Assuming that the branch name will be non-empty if the function is working correctly. assert branch_name != "" @@ -175,7 +187,7 @@ def test_get_current_git_branch_success(mock_repo): @patch("autogpt.app.utils.Repo") def test_get_current_git_branch_failure(mock_repo): - mock_repo.side_effect = Exception() + mock_repo.side_effect = InvalidGitRepositoryError() branch_name = get_current_git_branch() assert branch_name == "" @@ -193,3 +205,19 @@ def test_extract_json_from_response_wrapped_in_code_block(valid_json_response: d assert ( extract_dict_from_response(emulated_response_from_openai) == valid_json_response ) + + +def test_extract_json_from_response_wrapped_in_code_block_with_language( + valid_json_response: dict, +): + emulated_response_from_openai = "```json" + str(valid_json_response) + "```" + assert ( + extract_dict_from_response(emulated_response_from_openai) == valid_json_response + ) + + +def test_extract_json_from_response_json_contained_in_string(valid_json_response: dict): + emulated_response_from_openai = "sentence1" + str(valid_json_response) + "sentence2" + assert ( + extract_dict_from_response(emulated_response_from_openai) == valid_json_response + ) diff --git a/autogpts/autogpt/tests/unit/test_web_search.py b/autogpts/autogpt/tests/unit/test_web_search.py index a8ccb0ce6..c4aba67f1 100644 --- a/autogpts/autogpt/tests/unit/test_web_search.py +++ b/autogpts/autogpt/tests/unit/test_web_search.py @@ -24,28 +24,28 @@ def test_safe_google_results_invalid_input(): @pytest.mark.parametrize( - "query, num_results, expected_output, return_value", + "query, num_results, expected_output_parts, return_value", [ ( "test", 1, - '[\n {\n "title": "Result 1",\n "url": "https://example.com/result1"\n }\n]', + ("Result 1", "https://example.com/result1"), [{"title": "Result 1", "href": "https://example.com/result1"}], ), - ("", 1, "[]", []), - ("no results", 1, "[]", []), + ("", 1, (), []), + ("no results", 1, (), []), ], ) def test_google_search( - query, num_results, expected_output, return_value, mocker, agent: Agent + query, num_results, expected_output_parts, return_value, mocker, agent: Agent ): mock_ddg = mocker.Mock() mock_ddg.return_value = return_value mocker.patch("autogpt.commands.web_search.DDGS.text", mock_ddg) actual_output = web_search(query, agent=agent, num_results=num_results) - expected_output = safe_google_results(expected_output) - assert actual_output == expected_output + for o in expected_output_parts: + assert o in actual_output @pytest.fixture diff --git a/autogpts/autogpt/tests/vcr/__init__.py b/autogpts/autogpt/tests/vcr/__init__.py index 4d45aafc9..faef46a68 100644 --- a/autogpts/autogpt/tests/vcr/__init__.py +++ b/autogpts/autogpt/tests/vcr/__init__.py @@ -2,8 +2,11 @@ import logging import os from hashlib import sha256 -import openai.api_requestor import pytest +from openai import OpenAI +from openai._models import FinalRequestOptions +from openai._types import Omit +from openai._utils import is_given from pytest_mock import MockerFixture from .vcr_filter import ( @@ -21,6 +24,7 @@ BASE_VCR_CONFIG = { "Authorization", "AGENT-MODE", "AGENT-TYPE", + "Cookie", "OpenAI-Organization", "X-OpenAI-Client-User-Agent", "User-Agent", @@ -51,30 +55,26 @@ def vcr_cassette_dir(request): return os.path.join("tests/vcr_cassettes", test_name) -def patch_api_base(requestor: openai.api_requestor.APIRequestor): - new_api_base = f"{PROXY}/v1" - requestor.api_base = new_api_base - return requestor - - @pytest.fixture -def patched_api_requestor(mocker: MockerFixture): - init_requestor = openai.api_requestor.APIRequestor.__init__ - prepare_request = openai.api_requestor.APIRequestor._prepare_request_raw +def cached_openai_client(mocker: MockerFixture) -> OpenAI: + client = OpenAI() + _prepare_options = client._prepare_options - def patched_init_requestor(requestor, *args, **kwargs): - init_requestor(requestor, *args, **kwargs) - patch_api_base(requestor) + def _patched_prepare_options(self, options: FinalRequestOptions): + _prepare_options(options) - def patched_prepare_request(self, *args, **kwargs): - url, headers, data = prepare_request(self, *args, **kwargs) + headers: dict[str, str | Omit] = ( + {**options.headers} if is_given(options.headers) else {} + ) + options.headers = headers + data: dict = options.json_data if PROXY: - headers["AGENT-MODE"] = os.environ.get("AGENT_MODE") - headers["AGENT-TYPE"] = os.environ.get("AGENT_TYPE") + headers["AGENT-MODE"] = os.environ.get("AGENT_MODE", Omit()) + headers["AGENT-TYPE"] = os.environ.get("AGENT_TYPE", Omit()) - logging.getLogger("patched_api_requestor").debug( - f"Outgoing API request: {headers}\n{data.decode() if data else None}" + logging.getLogger("cached_openai_client").debug( + f"Outgoing API request: {headers}\n{data if data else None}" ) # Add hash header for cheap & fast matching on cassette playback @@ -82,16 +82,12 @@ def patched_api_requestor(mocker: MockerFixture): freeze_request_body(data), usedforsecurity=False ).hexdigest() - return url, headers, data - if PROXY: - mocker.patch.object( - openai.api_requestor.APIRequestor, - "__init__", - new=patched_init_requestor, - ) + client.base_url = f"{PROXY}/v1" mocker.patch.object( - openai.api_requestor.APIRequestor, - "_prepare_request_raw", - new=patched_prepare_request, + client, + "_prepare_options", + new=_patched_prepare_options, ) + + return client diff --git a/autogpts/autogpt/tests/vcr/vcr_filter.py b/autogpts/autogpt/tests/vcr/vcr_filter.py index b1eb6461e..77b65d207 100644 --- a/autogpts/autogpt/tests/vcr/vcr_filter.py +++ b/autogpts/autogpt/tests/vcr/vcr_filter.py @@ -4,6 +4,7 @@ import os import re from io import BytesIO from typing import Any, Dict, List +from urllib.parse import urlparse, urlunparse from vcr.request import Request @@ -43,14 +44,9 @@ def replace_message_content(content: str, replacements: List[Dict[str, str]]) -> return content -def freeze_request_body(json_body: str | bytes) -> bytes: +def freeze_request_body(body: dict) -> bytes: """Remove any dynamic items from the request body""" - try: - body = json.loads(json_body) - except ValueError: - return json_body if type(json_body) == bytes else json_body.encode() - if "messages" not in body: return json.dumps(body, sort_keys=True).encode() @@ -73,9 +69,11 @@ def freeze_request(request: Request) -> Request: with contextlib.suppress(ValueError): request.body = freeze_request_body( - request.body.getvalue() - if isinstance(request.body, BytesIO) - else request.body + json.loads( + request.body.getvalue() + if isinstance(request.body, BytesIO) + else request.body + ) ) return request @@ -98,9 +96,6 @@ def before_record_request(request: Request) -> Request | None: return filtered_request_without_dynamic_data -from urllib.parse import urlparse, urlunparse - - def replace_request_hostname( request: Request, original_url: str, new_hostname: str ) -> Request: diff --git a/autogpts/autogpt/tests/vcr_cassettes b/autogpts/autogpt/tests/vcr_cassettes -Subproject 9996f1d104a1e4f33c1e10aa664d01ea78db2a0 +Subproject 03bf1eb089c19217a08ec97e814b6a3b65b4aff diff --git a/autogpts/evo.ninja/setup b/autogpts/evo.ninja/setup new file mode 100755 index 000000000..3d1c2f708 --- /dev/null +++ b/autogpts/evo.ninja/setup @@ -0,0 +1,17 @@ +#!/bin/bash + +# Ensure all commands are run within this script's directory +SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )" +cd "$SCRIPT_DIR" + +# Clone the repo and checkout the release branch +REPO="https://github.com/polywrap/evo.ninja" +BRANCH="release/autogpt" + +echo "Cloning evo.ninja..." +git init +git remote add origin $REPO +git pull +git checkout $BRANCH + +echo "Setup successfully." diff --git a/autogpts/forge/.gitignore b/autogpts/forge/.gitignore index c9a11fcef..afac6b07b 100644 --- a/autogpts/forge/.gitignore +++ b/autogpts/forge/.gitignore @@ -1,7 +1,6 @@ ## Original ignores autogpt/keys.py autogpt/*.json -**/auto_gpt_workspace/* *.mpeg .env azure.yaml diff --git a/autogpts/forge/advanced_commands/README.md b/autogpts/forge/advanced_commands/README.md deleted file mode 100644 index 8a48c7199..000000000 --- a/autogpts/forge/advanced_commands/README.md +++ /dev/null @@ -1,2 +0,0 @@ -Advanced commands to develop on the forge and the benchmark. -Stability not guaranteed. diff --git a/autogpts/forge/advanced_commands/run_benchmark_dev b/autogpts/forge/advanced_commands/run_benchmark_dev deleted file mode 100644 index ed4cbf0cf..000000000 --- a/autogpts/forge/advanced_commands/run_benchmark_dev +++ /dev/null @@ -1,9 +0,0 @@ -#!/bin/bash - -# Kill processes using port 8080 if any. -if lsof -t -i :8080; then - kill $(lsof -t -i :8080) -fi -SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" - -uvicorn agbenchmark.app:app --host localhost --port 8080 --reload --log-level info --reload-dir "$SCRIPT_DIR/../../../benchmark/agbenchmark" diff --git a/autogpts/forge/forge/__main__.py b/autogpts/forge/forge/__main__.py index 011eae057..c251fbdf3 100644 --- a/autogpts/forge/forge/__main__.py +++ b/autogpts/forge/forge/__main__.py @@ -41,5 +41,9 @@ if __name__ == "__main__": forge.sdk.forge_log.setup_logger() uvicorn.run( - "forge.app:app", host="localhost", port=port, log_level="error", reload=True + "forge.app:app", + host="localhost", + port=int(port), + log_level="error", + reload=True, ) diff --git a/autogpts/forge/forge/actions/__init__.py b/autogpts/forge/forge/actions/__init__.py new file mode 100644 index 000000000..36b4d1a16 --- /dev/null +++ b/autogpts/forge/forge/actions/__init__.py @@ -0,0 +1 @@ +from .registry import Action, ActionParameter, ActionRegister, action diff --git a/autogpts/forge/forge/sdk/abilities/file_system/files.py b/autogpts/forge/forge/actions/file_system/files.py index a91597da4..ca7abde29 100644 --- a/autogpts/forge/forge/sdk/abilities/file_system/files.py +++ b/autogpts/forge/forge/actions/file_system/files.py @@ -1,8 +1,9 @@ from typing import List -from ..registry import ability +from ..registry import action -@ability( + +@action( name="list_files", description="List files in a directory", parameters=[ @@ -22,7 +23,7 @@ async def list_files(agent, task_id: str, path: str) -> List[str]: return agent.workspace.list(task_id=task_id, path=str(path)) -@ability( +@action( name="write_file", description="Write data to a file", parameters=[ @@ -57,7 +58,7 @@ async def write_file(agent, task_id: str, file_path: str, data: bytes): ) -@ability( +@action( name="read_file", description="Read data from a file", parameters=[ diff --git a/autogpts/forge/forge/sdk/abilities/finish.py b/autogpts/forge/forge/actions/finish.py index 7524bd8b9..db1b2804a 100644 --- a/autogpts/forge/forge/sdk/abilities/finish.py +++ b/autogpts/forge/forge/actions/finish.py @@ -1,10 +1,11 @@ -from ..forge_log import ForgeLogger -from .registry import ability +from sdk.forge_log import ForgeLogger + +from .registry import action logger = ForgeLogger(__name__) -@ability( +@action( name="finish", description="Use this to shut down once you have accomplished all of your goals," " or when there are insurmountable problems that make it impossible" diff --git a/autogpts/forge/forge/sdk/abilities/registry.py b/autogpts/forge/forge/actions/registry.py index c4b853ec2..552d873f3 100644 --- a/autogpts/forge/forge/sdk/abilities/registry.py +++ b/autogpts/forge/forge/actions/registry.py @@ -7,9 +7,9 @@ from typing import Any, Callable, List import pydantic -class AbilityParameter(pydantic.BaseModel): +class ActionParameter(pydantic.BaseModel): """ - This class represents a parameter for an ability. + This class represents a parameter for an action. Attributes: name (str): The name of the parameter. @@ -24,22 +24,22 @@ class AbilityParameter(pydantic.BaseModel): required: bool -class Ability(pydantic.BaseModel): +class Action(pydantic.BaseModel): """ - This class represents an ability in the system. + This class represents an action in the system. Attributes: - name (str): The name of the ability. - description (str): A brief description of what the ability does. - method (Callable): The method that implements the ability. - parameters (List[AbilityParameter]): A list of parameters that the ability requires. - output_type (str): The type of the output that the ability returns. + name (str): The name of the action. + description (str): A brief description of what the action does. + method (Callable): The method that implements the action. + parameters (List[ActionParameter]): A list of parameters that the action requires. + output_type (str): The type of the output that the action returns. """ name: str description: str method: Callable - parameters: List[AbilityParameter] + parameters: List[ActionParameter] output_type: str category: str | None = None @@ -71,22 +71,22 @@ class Ability(pydantic.BaseModel): return func_summary -def ability( - name: str, description: str, parameters: List[AbilityParameter], output_type: str +def action( + name: str, description: str, parameters: List[ActionParameter], output_type: str ): def decorator(func): func_params = inspect.signature(func).parameters param_names = set( - [AbilityParameter.parse_obj(param).name for param in parameters] + [ActionParameter.parse_obj(param).name for param in parameters] ) param_names.add("agent") param_names.add("task_id") func_param_names = set(func_params.keys()) if param_names != func_param_names: raise ValueError( - f"Mismatch in parameter names. Ability Annotation includes {param_names}, but function actually takes {func_param_names} in function {func.__name__} signature" + f"Mismatch in parameter names. Action Annotation includes {param_names}, but function actually takes {func_param_names} in function {func.__name__} signature" ) - func.ability = Ability( + func.action = Action( name=name, description=description, parameters=parameters, @@ -98,88 +98,88 @@ def ability( return decorator -class AbilityRegister: +class ActionRegister: def __init__(self, agent) -> None: self.abilities = {} self.register_abilities() self.agent = agent def register_abilities(self) -> None: - for ability_path in glob.glob( + for action_path in glob.glob( os.path.join(os.path.dirname(__file__), "**/*.py"), recursive=True ): - if not os.path.basename(ability_path) in [ + if not os.path.basename(action_path) in [ "__init__.py", "registry.py", ]: - ability = os.path.relpath( - ability_path, os.path.dirname(__file__) + action = os.path.relpath( + action_path, os.path.dirname(__file__) ).replace("/", ".") try: module = importlib.import_module( - f".{ability[:-3]}", package="forge.sdk.abilities" + f".{action[:-3]}", package="forge.sdk.abilities" ) for attr in dir(module): func = getattr(module, attr) - if hasattr(func, "ability"): - ab = func.ability + if hasattr(func, "action"): + ab = func.action ab.category = ( - ability.split(".")[0].lower().replace("_", " ") - if len(ability.split(".")) > 1 + action.split(".")[0].lower().replace("_", " ") + if len(action.split(".")) > 1 else "general" ) - self.abilities[func.ability.name] = func.ability + self.abilities[func.action.name] = func.action except Exception as e: print(f"Error occurred while registering abilities: {str(e)}") - def list_abilities(self) -> List[Ability]: + def list_abilities(self) -> List[Action]: return self.abilities def list_abilities_for_prompt(self) -> List[str]: - return [str(ability) for ability in self.abilities.values()] + return [str(action) for action in self.abilities.values()] def abilities_description(self) -> str: abilities_by_category = {} - for ability in self.abilities.values(): - if ability.category not in abilities_by_category: - abilities_by_category[ability.category] = [] - abilities_by_category[ability.category].append(str(ability)) + for action in self.abilities.values(): + if action.category not in abilities_by_category: + abilities_by_category[action.category] = [] + abilities_by_category[action.category].append(str(action)) abilities_description = "" for category, abilities in abilities_by_category.items(): if abilities_description != "": abilities_description += "\n" abilities_description += f"{category}:" - for ability in abilities: - abilities_description += f" {ability}" + for action in abilities: + abilities_description += f" {action}" return abilities_description - async def run_ability( - self, task_id: str, ability_name: str, *args: Any, **kwds: Any + async def run_action( + self, task_id: str, action_name: str, *args: Any, **kwds: Any ) -> Any: """ - This method runs a specified ability with the provided arguments and keyword arguments. + This method runs a specified action with the provided arguments and keyword arguments. - The agent is passed as the first argument to the ability. This allows the ability to access and manipulate + The agent is passed as the first argument to the action. This allows the action to access and manipulate the agent's state as needed. Args: - task_id (str): The ID of the task that the ability is being run for. - ability_name (str): The name of the ability to run. + task_id (str): The ID of the task that the action is being run for. + action_name (str): The name of the action to run. *args: Variable length argument list. **kwds: Arbitrary keyword arguments. Returns: - Any: The result of the ability execution. + Any: The result of the action execution. Raises: - Exception: If there is an error in running the ability. + Exception: If there is an error in running the action. """ try: - ability = self.abilities[ability_name] - return await ability(self.agent, task_id, *args, **kwds) + action = self.abilities[action_name] + return await action(self.agent, task_id, *args, **kwds) except Exception: raise @@ -188,6 +188,6 @@ if __name__ == "__main__": import sys sys.path.append("/Users/swifty/dev/forge/forge") - register = AbilityRegister(agent=None) + register = ActionRegister(agent=None) print(register.abilities_description()) - print(register.run_ability("abc", "list_files", "/Users/swifty/dev/forge/forge")) + print(register.run_action("abc", "list_files", "/Users/swifty/dev/forge/forge")) diff --git a/autogpts/forge/forge/sdk/abilities/web/web_search.py b/autogpts/forge/forge/actions/web/web_search.py index 70a53f7d5..2bcc0a32d 100644 --- a/autogpts/forge/forge/sdk/abilities/web/web_search.py +++ b/autogpts/forge/forge/actions/web/web_search.py @@ -1,4 +1,3 @@ - from __future__ import annotations import json @@ -7,12 +6,12 @@ from itertools import islice from duckduckgo_search import DDGS -from ..registry import ability +from ..registry import action DUCKDUCKGO_MAX_ATTEMPTS = 3 -@ability( +@action( name="web_search", description="Searches the web", parameters=[ diff --git a/autogpts/forge/forge/sdk/abilities/web/web_selenium.py b/autogpts/forge/forge/actions/web/web_selenium.py index 3d93d9468..9e3c7494b 100644 --- a/autogpts/forge/forge/sdk/abilities/web/web_selenium.py +++ b/autogpts/forge/forge/actions/web/web_selenium.py @@ -5,13 +5,16 @@ from __future__ import annotations COMMAND_CATEGORY = "web_browse" COMMAND_CATEGORY_TITLE = "Web Browsing" +import functools import logging import re from pathlib import Path from sys import platform -from typing import TYPE_CHECKING, Optional, Type, List, Tuple +from typing import TYPE_CHECKING, Any, Callable, List, Optional, Tuple, Type +from urllib.parse import urljoin, urlparse from bs4 import BeautifulSoup +from requests.compat import urljoin from selenium.common.exceptions import WebDriverException from selenium.webdriver.chrome.options import Options as ChromeOptions from selenium.webdriver.chrome.service import Service as ChromeDriverService @@ -33,19 +36,9 @@ from webdriver_manager.chrome import ChromeDriverManager from webdriver_manager.firefox import GeckoDriverManager from webdriver_manager.microsoft import EdgeChromiumDriverManager as EdgeDriverManager +from forge.sdk.errors import CommandExecutionError -from ..registry import ability -from forge.sdk.errors import * -import functools -import re -from typing import Any, Callable -from urllib.parse import urljoin, urlparse - -from requests.compat import urljoin - - -from bs4 import BeautifulSoup -from requests.compat import urljoin +from ..registry import action def extract_hyperlinks(soup: BeautifulSoup, base_url: str) -> list[tuple[str, str]]: @@ -76,7 +69,6 @@ def format_hyperlinks(hyperlinks: list[tuple[str, str]]) -> list[str]: return [f"{link_text} ({link_url})" for link_text, link_url in hyperlinks] - def validate_url(func: Callable[..., Any]) -> Any: """The method decorator validate_url is used to validate urls for any command that requires a url as an argument""" @@ -178,8 +170,6 @@ def check_local_file_access(url: str) -> bool: return any(url.startswith(prefix) for prefix in local_prefixes) - - logger = logging.getLogger(__name__) FILE_DIR = Path(__file__).parent.parent @@ -191,7 +181,7 @@ class BrowsingError(CommandExecutionError): """An error occurred while trying to browse the page""" -@ability( +@action( name="read_webpage", description="Read a webpage, and extract specific information from it if a question is specified. If you are looking to extract specific information from the webpage, you should specify a question.", parameters=[ @@ -201,17 +191,19 @@ class BrowsingError(CommandExecutionError): "type": "string", "required": True, }, - { + { "name": "question", "description": "A question that you want to answer using the content of the webpage.", "type": "string", "required": False, - } + }, ], output_type="string", ) @validate_url -async def read_webpage(agent, task_id: str, url: str, question: str = "") -> Tuple(str, List[str]): +async def read_webpage( + agent, task_id: str, url: str, question: str = "" +) -> Tuple(str, List[str]): """Browse a website and return the answer and links to the user Args: @@ -372,4 +364,3 @@ def close_browser(driver: WebDriver) -> None: None """ driver.quit() - diff --git a/autogpts/forge/forge/agent.py b/autogpts/forge/forge/agent.py index f96a6a91d..7757c6680 100644 --- a/autogpts/forge/forge/agent.py +++ b/autogpts/forge/forge/agent.py @@ -1,3 +1,4 @@ +from forge.actions import ActionRegister from forge.sdk import ( Agent, AgentDB, @@ -6,13 +7,8 @@ from forge.sdk import ( StepRequestBody, Task, TaskRequestBody, - Workspace, - PromptEngine, - chat_completion_request, - ChromaMemStore + Workspace, ) -import json -import pprint LOG = ForgeLogger(__name__) @@ -78,6 +74,7 @@ class ForgeAgent(Agent): Feel free to create subclasses of the database and workspace to implement your own storage """ super().__init__(database, workspace) + self.abilities = ActionRegister(self) async def create_task(self, task_request: TaskRequestBody) -> Task: """ @@ -139,9 +136,11 @@ class ForgeAgent(Agent): step.output = "Washington D.C" - LOG.info(f"\t✅ Final Step completed: {step.step_id}. \n" + - f"Output should be placeholder text Washington D.C. You'll need to \n" + - f"modify execute_step to include LLM behavior. Follow the tutorial " + - f"if confused. ") + LOG.info( + f"\t✅ Final Step completed: {step.step_id}. \n" + + f"Output should be placeholder text Washington D.C. You'll need to \n" + + f"modify execute_step to include LLM behavior. Follow the tutorial " + + f"if confused. " + ) return step diff --git a/autogpts/forge/forge/app.py b/autogpts/forge/forge/app.py index b14856358..e04edd756 100644 --- a/autogpts/forge/forge/app.py +++ b/autogpts/forge/forge/app.py @@ -2,6 +2,7 @@ import os from forge.agent import ForgeAgent from forge.sdk import LocalWorkspace + from .db import ForgeDatabase database_name = os.getenv("DATABASE_STRING") diff --git a/autogpts/forge/forge/db.py b/autogpts/forge/forge/db.py index 10e78dc5a..cff096379 100644 --- a/autogpts/forge/forge/db.py +++ b/autogpts/forge/forge/db.py @@ -1,16 +1,14 @@ -from .sdk import AgentDB, ForgeLogger, NotFoundError, Base -from sqlalchemy.exc import SQLAlchemyError - import datetime -from sqlalchemy import ( - Column, - DateTime, - String, -) import uuid +from sqlalchemy import Column, DateTime, String +from sqlalchemy.exc import SQLAlchemyError + +from .sdk import AgentDB, Base, ForgeLogger, NotFoundError + LOG = ForgeLogger(__name__) + class ChatModel(Base): __tablename__ = "chat" msg_id = Column(String, primary_key=True, index=True) @@ -22,6 +20,7 @@ class ChatModel(Base): DateTime, default=datetime.datetime.utcnow, onupdate=datetime.datetime.utcnow ) + class ActionModel(Base): __tablename__ = "action" action_id = Column(String, primary_key=True, index=True) @@ -35,10 +34,9 @@ class ActionModel(Base): class ForgeDatabase(AgentDB): - async def add_chat_history(self, task_id, messages): for message in messages: - await self.add_chat_message(task_id, message['role'], message['content']) + await self.add_chat_message(task_id, message["role"], message["content"]) async def add_chat_message(self, task_id, role, content): if self.debug_enabled: @@ -55,7 +53,9 @@ class ForgeDatabase(AgentDB): session.commit() session.refresh(mew_msg) if self.debug_enabled: - LOG.debug(f"Created new Chat message with task_id: {mew_msg.msg_id}") + LOG.debug( + f"Created new Chat message with task_id: {mew_msg.msg_id}" + ) return mew_msg except SQLAlchemyError as e: LOG.error(f"SQLAlchemy error while creating task: {e}") @@ -65,7 +65,7 @@ class ForgeDatabase(AgentDB): except Exception as e: LOG.error(f"Unexpected error while creating task: {e}") raise - + async def get_chat_history(self, task_id): if self.debug_enabled: LOG.debug(f"Getting chat history with task_id: {task_id}") @@ -80,9 +80,7 @@ class ForgeDatabase(AgentDB): return [{"role": m.role, "content": m.content} for m in messages] else: - LOG.error( - f"Chat history not found with task_id: {task_id}" - ) + LOG.error(f"Chat history not found with task_id: {task_id}") raise NotFoundError("Chat history not found") except SQLAlchemyError as e: LOG.error(f"SQLAlchemy error while getting chat history: {e}") @@ -92,7 +90,7 @@ class ForgeDatabase(AgentDB): except Exception as e: LOG.error(f"Unexpected error while getting chat history: {e}") raise - + async def create_action(self, task_id, name, args): try: with self.Session() as session: @@ -106,7 +104,9 @@ class ForgeDatabase(AgentDB): session.commit() session.refresh(new_action) if self.debug_enabled: - LOG.debug(f"Created new Action with task_id: {new_action.action_id}") + LOG.debug( + f"Created new Action with task_id: {new_action.action_id}" + ) return new_action except SQLAlchemyError as e: LOG.error(f"SQLAlchemy error while creating action: {e}") @@ -131,9 +131,7 @@ class ForgeDatabase(AgentDB): return [{"name": a.name, "args": a.args} for a in actions] else: - LOG.error( - f"Action history not found with task_id: {task_id}" - ) + LOG.error(f"Action history not found with task_id: {task_id}") raise NotFoundError("Action history not found") except SQLAlchemyError as e: LOG.error(f"SQLAlchemy error while getting action history: {e}") diff --git a/autogpts/forge/forge/sdk/llm.py b/autogpts/forge/forge/llm.py index 9be2afb4d..4fe850052 100644 --- a/autogpts/forge/forge/sdk/llm.py +++ b/autogpts/forge/forge/llm.py @@ -1,18 +1,18 @@ -import typing +from pathlib import Path -import openai +from litellm import AuthenticationError, InvalidRequestError, ModelResponse, acompletion +from openai import OpenAI +from openai.types import CreateEmbeddingResponse +from openai.types.audio import Transcription from tenacity import retry, stop_after_attempt, wait_random_exponential -from .forge_log import ForgeLogger -from litellm import completion, acompletion, AuthenticationError, InvalidRequestError +from .sdk.forge_log import ForgeLogger LOG = ForgeLogger(__name__) @retry(wait=wait_random_exponential(min=1, max=40), stop=stop_after_attempt(3)) -async def chat_completion_request( - model, messages, **kwargs -) -> typing.Union[typing.Dict[str, typing.Any], Exception]: +async def chat_completion_request(model, messages, **kwargs) -> ModelResponse: """Generate a response to a list of messages using OpenAI's API""" try: kwargs["model"] = model @@ -22,8 +22,10 @@ async def chat_completion_request( return resp except AuthenticationError as e: LOG.exception("Authentication Error") + raise except InvalidRequestError as e: LOG.exception("Invalid Request Error") + raise except Exception as e: LOG.error("Unable to generate ChatCompletion response") LOG.error(f"Exception: {e}") @@ -33,12 +35,12 @@ async def chat_completion_request( @retry(wait=wait_random_exponential(min=1, max=40), stop=stop_after_attempt(3)) async def create_embedding_request( messages, model="text-embedding-ada-002" -) -> typing.Union[typing.Dict[str, typing.Any], Exception]: +) -> CreateEmbeddingResponse: """Generate an embedding for a list of messages using OpenAI's API""" try: - return await openai.Embedding.acreate( + return OpenAI().embeddings.create( input=[f"{m['role']}: {m['content']}" for m in messages], - engine=model, + model=model, ) except Exception as e: LOG.error("Unable to generate ChatCompletion response") @@ -47,12 +49,12 @@ async def create_embedding_request( @retry(wait=wait_random_exponential(min=1, max=40), stop=stop_after_attempt(3)) -async def transcribe_audio( - audio_file: str, -) -> typing.Union[typing.Dict[str, typing.Any], Exception]: +async def transcribe_audio(audio_file: Path) -> Transcription: """Transcribe an audio file using OpenAI's API""" try: - return await openai.Audio.transcribe(model="whisper-1", file=audio_file) + return OpenAI().audio.transcriptions.create( + model="whisper-1", file=audio_file.open(mode="rb") + ) except Exception as e: LOG.error("Unable to generate ChatCompletion response") LOG.error(f"Exception: {e}") diff --git a/autogpts/forge/forge/sdk/memory/__init__.py b/autogpts/forge/forge/memory/__init__.py index ad8ced929..b0182da70 100644 --- a/autogpts/forge/forge/sdk/memory/__init__.py +++ b/autogpts/forge/forge/memory/__init__.py @@ -1,2 +1,2 @@ -from .memstore import MemStore from .chroma_memstore import ChromaMemStore +from .memstore import MemStore diff --git a/autogpts/forge/forge/sdk/memory/chroma_memstore.py b/autogpts/forge/forge/memory/chroma_memstore.py index 8dd4971d2..7764f1ab9 100644 --- a/autogpts/forge/forge/sdk/memory/chroma_memstore.py +++ b/autogpts/forge/forge/memory/chroma_memstore.py @@ -1,8 +1,9 @@ -from .memstore import MemStore +import hashlib import chromadb from chromadb.config import Settings -import hashlib + +from .memstore import MemStore class ChromaMemStore: diff --git a/autogpts/forge/forge/sdk/memory/memstore.py b/autogpts/forge/forge/memory/memstore.py index 7ab9aae50..7ab9aae50 100644 --- a/autogpts/forge/forge/sdk/memory/memstore.py +++ b/autogpts/forge/forge/memory/memstore.py diff --git a/autogpts/forge/forge/sdk/memory/memstore_test.py b/autogpts/forge/forge/memory/memstore_test.py index 3eb24309b..3eb24309b 100644 --- a/autogpts/forge/forge/sdk/memory/memstore_test.py +++ b/autogpts/forge/forge/memory/memstore_test.py diff --git a/autogpts/forge/forge/sdk/__init__.py b/autogpts/forge/forge/sdk/__init__.py index b3471b6d6..9ee9f428a 100644 --- a/autogpts/forge/forge/sdk/__init__.py +++ b/autogpts/forge/forge/sdk/__init__.py @@ -2,12 +2,12 @@ The Forge SDK. This is the core of the Forge. It contains the agent protocol, which is the core of the Forge. """ +from ..llm import chat_completion_request, create_embedding_request, transcribe_audio from .agent import Agent from .db import AgentDB, Base +from .errors import * from .forge_log import ForgeLogger -from .llm import chat_completion_request, create_embedding_request, transcribe_audio -from .prompting import PromptEngine -from .schema import ( +from .model import ( Artifact, ArtifactUpload, Pagination, @@ -21,7 +21,5 @@ from .schema import ( TaskRequestBody, TaskStepsListResponse, ) +from .prompting import PromptEngine from .workspace import LocalWorkspace, Workspace -from .errors import * -from .memory.chroma_memstore import ChromaMemStore -from .memory.memstore import MemStore
\ No newline at end of file diff --git a/autogpts/forge/forge/sdk/abilities/__init__.py b/autogpts/forge/forge/sdk/abilities/__init__.py deleted file mode 100644 index e69de29bb..000000000 --- a/autogpts/forge/forge/sdk/abilities/__init__.py +++ /dev/null diff --git a/autogpts/forge/forge/sdk/agent.py b/autogpts/forge/forge/sdk/agent.py index d230e81b0..125167938 100644 --- a/autogpts/forge/forge/sdk/agent.py +++ b/autogpts/forge/forge/sdk/agent.py @@ -9,13 +9,21 @@ from fastapi.middleware.cors import CORSMiddleware from fastapi.responses import RedirectResponse, StreamingResponse from fastapi.staticfiles import StaticFiles -from .abilities.registry import AbilityRegister from .db import AgentDB from .errors import NotFoundError from .forge_log import ForgeLogger from .middlewares import AgentMiddleware +from .model import ( + Artifact, + Step, + StepRequestBody, + Task, + TaskArtifactsListResponse, + TaskListResponse, + TaskRequestBody, + TaskStepsListResponse, +) from .routes.agent_protocol import base_router -from .schema import * from .workspace import Workspace LOG = ForgeLogger(__name__) @@ -25,7 +33,6 @@ class Agent: def __init__(self, database: AgentDB, workspace: Workspace): self.db = database self.workspace = workspace - self.abilities = AbilityRegister(self) def get_agent_app(self, router: APIRouter = base_router): """ diff --git a/autogpts/forge/forge/sdk/agent_test.py b/autogpts/forge/forge/sdk/agent_test.py index 85d2d66ee..d2d23abbe 100644 --- a/autogpts/forge/forge/sdk/agent_test.py +++ b/autogpts/forge/forge/sdk/agent_test.py @@ -2,7 +2,7 @@ import pytest from .agent import Agent from .db import AgentDB -from .schema import StepRequestBody, Task, TaskListResponse, TaskRequestBody +from .model import StepRequestBody, Task, TaskListResponse, TaskRequestBody from .workspace import LocalWorkspace diff --git a/autogpts/forge/forge/sdk/db.py b/autogpts/forge/forge/sdk/db.py index 0b35139b9..ce4d22f6f 100644 --- a/autogpts/forge/forge/sdk/db.py +++ b/autogpts/forge/forge/sdk/db.py @@ -7,7 +7,7 @@ IT IS NOT ADVISED TO USE THIS IN PRODUCTION! import datetime import math import uuid -from typing import Any, Dict, List, Optional, Tuple +from typing import Any, Dict, List, Literal, Optional, Tuple from sqlalchemy import ( JSON, @@ -23,7 +23,7 @@ from sqlalchemy.orm import DeclarativeBase, joinedload, relationship, sessionmak from .errors import NotFoundError from .forge_log import ForgeLogger -from .schema import Artifact, Pagination, Status, Step, StepRequestBody, Task +from .model import Artifact, Pagination, Status, Step, StepRequestBody, Task LOG = ForgeLogger(__name__) @@ -259,7 +259,7 @@ class AgentDB: LOG.error(f"Unexpected error while creating step: {e}") raise - async def get_task(self, task_id: int) -> Task: + async def get_task(self, task_id: str) -> Task: """Get a task by its id""" if self.debug_enabled: LOG.debug(f"Getting task with task_id: {task_id}") @@ -311,6 +311,29 @@ class AgentDB: LOG.error(f"Unexpected error while getting step: {e}") raise + async def get_artifact(self, artifact_id: str) -> Artifact: + if self.debug_enabled: + LOG.debug(f"Getting artifact with and artifact_id: {artifact_id}") + try: + with self.Session() as session: + if ( + artifact_model := session.query(ArtifactModel) + .filter_by(artifact_id=artifact_id) + .first() + ): + return convert_to_artifact(artifact_model) + else: + LOG.error(f"Artifact not found with and artifact_id: {artifact_id}") + raise NotFoundError("Artifact not found") + except SQLAlchemyError as e: + LOG.error(f"SQLAlchemy error while getting artifact: {e}") + raise + except NotFoundError as e: + raise + except Exception as e: + LOG.error(f"Unexpected error while getting artifact: {e}") + raise + async def update_step( self, task_id: str, @@ -353,28 +376,32 @@ class AgentDB: LOG.error(f"Unexpected error while getting step: {e}") raise - async def get_artifact(self, artifact_id: str) -> Artifact: - if self.debug_enabled: - LOG.debug(f"Getting artifact with and artifact_id: {artifact_id}") - try: - with self.Session() as session: - if ( - artifact_model := session.query(ArtifactModel) - .filter_by(artifact_id=artifact_id) - .first() - ): - return convert_to_artifact(artifact_model) - else: - LOG.error(f"Artifact not found with and artifact_id: {artifact_id}") - raise NotFoundError("Artifact not found") - except SQLAlchemyError as e: - LOG.error(f"SQLAlchemy error while getting artifact: {e}") - raise - except NotFoundError as e: - raise - except Exception as e: - LOG.error(f"Unexpected error while getting artifact: {e}") - raise + async def update_artifact( + self, + artifact_id: str, + *, + file_name: str = "", + relative_path: str = "", + agent_created: Optional[Literal[True]] = None, + ) -> Artifact: + LOG.debug(f"Updating artifact with artifact_id: {artifact_id}") + with self.Session() as session: + if ( + artifact := session.query(ArtifactModel) + .filter_by(artifact_id=artifact_id) + .first() + ): + if file_name: + artifact.file_name = file_name + if relative_path: + artifact.relative_path = relative_path + if agent_created: + artifact.agent_created = agent_created + session.commit() + return await self.get_artifact(artifact_id) + else: + LOG.error(f"Artifact not found with artifact_id: {artifact_id}") + raise NotFoundError("Artifact not found") async def list_tasks( self, page: int = 1, per_page: int = 10 diff --git a/autogpts/forge/forge/sdk/db_test.py b/autogpts/forge/forge/sdk/db_test.py index 5346eb3ba..14330435e 100644 --- a/autogpts/forge/forge/sdk/db_test.py +++ b/autogpts/forge/forge/sdk/db_test.py @@ -14,7 +14,13 @@ from forge.sdk.db import ( convert_to_task, ) from forge.sdk.errors import NotFoundError as DataNotFoundError -from forge.sdk.schema import * +from forge.sdk.model import ( + Artifact, + Status, + Step, + StepRequestBody, + Task, +) @pytest.mark.asyncio diff --git a/autogpts/forge/forge/sdk/schema.py b/autogpts/forge/forge/sdk/model.py index 1dc2e25e0..6a55b5a24 100644 --- a/autogpts/forge/forge/sdk/schema.py +++ b/autogpts/forge/forge/sdk/model.py @@ -73,7 +73,7 @@ class TaskRequestBody(BaseModel): description="Input prompt for the task.", example="Write the words you receive to the file 'output.txt'.", ) - additional_input: Optional[dict] = {} + additional_input: Optional[dict] = None class Task(TaskRequestBody): @@ -113,7 +113,7 @@ class StepRequestBody(BaseModel): description="Input prompt for the step.", example="Washington", ) - additional_input: Optional[dict] = {} + additional_input: Optional[dict] = None class Status(Enum): @@ -156,7 +156,7 @@ class Step(StepRequestBody): description="Output of the task step.", example="I am going to use the write_to_file command and write Washington to a file called output.txt <write_to_file('output.txt', 'Washington')", ) - additional_output: Optional[StepOutput] = Field(default_factory=dict) + additional_output: Optional[dict] = None artifacts: Optional[List[Artifact]] = Field( [], description="A list of artifacts that the step has produced." ) diff --git a/autogpts/forge/forge/sdk/routes/agent_protocol.py b/autogpts/forge/forge/sdk/routes/agent_protocol.py index ad5f41fca..8a46fde0b 100644 --- a/autogpts/forge/forge/sdk/routes/agent_protocol.py +++ b/autogpts/forge/forge/sdk/routes/agent_protocol.py @@ -30,7 +30,7 @@ from fastapi.responses import FileResponse from forge.sdk.errors import * from forge.sdk.forge_log import ForgeLogger -from forge.sdk.schema import * +from forge.sdk.model import * base_router = APIRouter() diff --git a/autogpts/forge/forge/sdk/workspace.py b/autogpts/forge/forge/sdk/workspace.py index 87fe34901..ff7c52427 100644 --- a/autogpts/forge/forge/sdk/workspace.py +++ b/autogpts/forge/forge/sdk/workspace.py @@ -3,6 +3,8 @@ import os import typing from pathlib import Path +from google.cloud import storage + class Workspace(abc.ABC): @abc.abstractclassmethod @@ -81,3 +83,51 @@ class LocalWorkspace(Workspace): if not base.exists() or not base.is_dir(): return [] return [str(p.relative_to(self.base_path / task_id)) for p in base.iterdir()] + + +class GCSWorkspace(Workspace): + def __init__(self, bucket_name: str, base_path: str = ""): + self.bucket_name = bucket_name + self.base_path = Path(base_path).resolve() if base_path else "" + self.storage_client = storage.Client() + self.bucket = self.storage_client.get_bucket(self.bucket_name) + + def _resolve_path(self, task_id: str, path: str) -> Path: + path = str(path) + path = path if not path.startswith("/") else path[1:] + abs_path = (self.base_path / task_id / path).resolve() + if not str(abs_path).startswith(str(self.base_path)): + print("Error") + raise ValueError(f"Directory traversal is not allowed! - {abs_path}") + return abs_path + + def read(self, task_id: str, path: str) -> bytes: + blob = self.bucket.blob(self._resolve_path(task_id, path)) + if not blob.exists(): + raise FileNotFoundError() + return blob.download_as_bytes() + + def write(self, task_id: str, path: str, data: bytes) -> None: + blob = self.bucket.blob(self._resolve_path(task_id, path)) + blob.upload_from_string(data) + + def delete(self, task_id: str, path: str, directory=False, recursive=False): + if directory and not recursive: + raise ValueError("recursive must be True when deleting a directory") + blob = self.bucket.blob(self._resolve_path(task_id, path)) + if not blob.exists(): + return + if directory: + for b in list(self.bucket.list_blobs(prefix=blob.name)): + b.delete() + else: + blob.delete() + + def exists(self, task_id: str, path: str) -> bool: + blob = self.bucket.blob(self._resolve_path(task_id, path)) + return blob.exists() + + def list(self, task_id: str, path: str) -> typing.List[str]: + prefix = os.path.join(task_id, self.base_path, path).replace("\\", "/") + "/" + blobs = list(self.bucket.list_blobs(prefix=prefix)) + return [str(Path(b.name).relative_to(prefix[:-1])) for b in blobs] diff --git a/autogpts/forge/integrations/README.md b/autogpts/forge/integrations/README.md deleted file mode 100644 index 1e442449d..000000000 --- a/autogpts/forge/integrations/README.md +++ /dev/null @@ -1,5 +0,0 @@ -You developed a tool that could help people build agents? - -Fork this repository, integrate your tool to the forge and send us the link of your fork in the autogpt discord: https://discord.gg/autogpt (ping maintainers) - -PS: make sure the way you integrate your tool allows for easy rebases from upstream. diff --git a/autogpts/forge/poetry.lock b/autogpts/forge/poetry.lock index 622949574..1978f42f2 100644 --- a/autogpts/forge/poetry.lock +++ b/autogpts/forge/poetry.lock @@ -10,15 +10,16 @@ files = [] develop = false [package.dependencies] +agent-protocol-client = "^1.1.0" click = "^8.1.3" +click-default-group = "^1.2.4" colorama = "^0.4.6" fastapi = "^0.99.0" gitpython = "^3.1.32" -helicone = "^1.0.9" httpx = "^0.24.0" matplotlib = "^3.7.2" networkx = "^3.1" -openai = "^0.27.8" 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"^0.23.2" -litellm = "^0.1.821" -duckduckgo-search = "^3.8.0" +litellm = "^1.17.9" +duckduckgo-search = "^4.0.0" selenium = "^4.13.0" bs4 = "^0.0.1" -agbenchmark = { path = "../../benchmark", optional = true } +# agbenchmark = { path = "../../benchmark", optional = true } +agbenchmark = {git = "https://github.com/Significant-Gravitas/AutoGPT.git", subdirectory = "benchmark", optional = true} webdriver-manager = "^4.0.1" +google-cloud-storage = "^2.13.0" [tool.poetry.extras] benchmark = ["agbenchmark"] diff --git a/autogpts/forge/tutorials/001_getting_started.md b/autogpts/forge/tutorials/001_getting_started.md index 4fb899951..a971451e7 100644 --- a/autogpts/forge/tutorials/001_getting_started.md +++ b/autogpts/forge/tutorials/001_getting_started.md @@ -57,17 +57,6 @@ Create your agent template using the command:  -### Entering the Arena -The Arena is a collection of all AutoGPT agents. It serves as a competitive environment where all agents are assessed to find the best generalist agent. Entering the Arena is a required step for participating in AutoGPT hackathons. It allows your agent to be part of a diverse and dynamic ecosystem, where it is periodically assessed by the benchmark to be scored on the official leaderboard. - -Officially enter the Arena by executing the command: - -```bash -./run arena enter YOUR_AGENT_NAME -``` - - - ## Section 4: Running Your Agent Begin by starting your agent using the command: diff --git a/autogpts/forge/tutorials/003_crafting_agent_logic.md b/autogpts/forge/tutorials/003_crafting_agent_logic.md index 4a5066fa9..9be40ad06 100644 --- a/autogpts/forge/tutorials/003_crafting_agent_logic.md +++ b/autogpts/forge/tutorials/003_crafting_agent_logic.md @@ -242,7 +242,7 @@ try: } # Get the LLM's response and interpret it chat_response = await chat_completion_request(**chat_completion_kwargs) - answer = json.loads(chat_response["choices"][0]["message"]["content"]) + answer = json.loads(chat_response.choices[0].message.content) # Log the answer for reference LOG.info(pprint.pformat(answer)) @@ -264,16 +264,16 @@ Extracting clear messages from LLM outputs can be complex. Our method is simple Abilities are the gears and levers that enable the agent to interact with tasks at hand. Let's unpack the mechanisms behind these abilities and how you can harness, and even extend, them. -In the SDK, there's a `abilities` folder containing `registry.py`, `finish.py`, and a `file_system` subfolder. You can also add your own abilities here. `registry.py` is the main file for abilities. It contains the `@ability` decorator and the `AbilityRegister` class. This class actively tracks abilities and outlines their function. The base Agent class includes a default ability register available via `self.abilities`. It looks like this: +In the Forge folder, there's a `actions` folder containing `registry.py`, `finish.py`, and a `file_system` subfolder. You can also add your own abilities here. `registry.py` is the main file for abilities. It contains the `@action` decorator and the `ActionRegister` class. This class actively tracks abilities and outlines their function. The base Agent class includes a default Action register available via `self.abilities`. It looks like this: ```python -self.abilities = AbilityRegister(self) +self.abilities = ActionRegister(self) ``` -The `AbilityRegister` has two key methods. `list_abilities_for_prompt` prepares abilities for prompts. `run_ability` makes the ability work. An ability is a function with the `@ability` decorator. It must have specific parameters, including the agent and `task_id`. +The `ActionRegister` has two key methods. `list_abilities_for_prompt` prepares abilities for prompts. `run_action` makes the ability work. An ability is a function with the `@action` decorator. It must have specific parameters, including the agent and `task_id`. ```python -@ability( +@action( name="write_file", description="Write data to a file", parameters=[ @@ -296,14 +296,14 @@ async def write_file(agent, task_id: str, file_path: str, data: bytes) -> None: pass ``` -The `@ability` decorator defines the ability's details, like its identity (name), functionality (description), and operational parameters. +The `@action` decorator defines the ability's details, like its identity (name), functionality (description), and operational parameters. ## Example of a Custom Ability: Webpage Fetcher ```python import requests -@ability( +@action( name="fetch_webpage", description="Retrieve the content of a webpage", parameters=[ @@ -339,7 +339,7 @@ With the ability details, we use it. We call the `run_ability` function: ```python # Run the ability and get the output # We don't actually use the output in this example -output = await self.abilities.run_ability( +output = await self.abilities.run_action( task_id, ability["name"], **ability["args"] ) ``` @@ -403,7 +403,7 @@ async def execute_step(self, task_id: str, step_request: StepRequestBody) -> Ste } # Make the chat completion request and parse the response chat_response = await chat_completion_request(**chat_completion_kwargs) - answer = json.loads(chat_response["choices"][0]["message"]["content"]) + answer = json.loads(chat_response.choices[0].message.content) # Log the answer for debugging purposes LOG.info(pprint.pformat(answer)) @@ -420,7 +420,7 @@ async def execute_step(self, task_id: str, step_request: StepRequestBody) -> Ste # Run the ability and get the output # We don't actually use the output in this example - output = await self.abilities.run_ability( + output = await self.abilities.run_action( task_id, ability["name"], **ability["args"] ) diff --git a/benchmark/agbenchmark/__main__.py b/benchmark/agbenchmark/__main__.py index 76ca7529a..9fff53523 100644 --- a/benchmark/agbenchmark/__main__.py +++ b/benchmark/agbenchmark/__main__.py @@ -1,5 +1,4 @@ -import glob -import json +import logging import os import sys from datetime import datetime, timezone @@ -7,205 +6,100 @@ from pathlib import Path from typing import Any, Optional import click -import pytest -import toml +from click_default_group import DefaultGroup from dotenv import load_dotenv -from helicone.lock import HeliconeLockManager -from agbenchmark.app import app -from agbenchmark.reports.ReportManager import SingletonReportManager -from agbenchmark.utils.data_types import AgentBenchmarkConfig +from agbenchmark.config import AgentBenchmarkConfig +from agbenchmark.utils.logging import configure_logging load_dotenv() +# try: +# if os.getenv("HELICONE_API_KEY"): +# import helicone # noqa + +# helicone_enabled = True +# else: +# helicone_enabled = False +# except ImportError: +# helicone_enabled = False + + +class InvalidInvocationError(ValueError): + pass + + +logger = logging.getLogger(__name__) + BENCHMARK_START_TIME_DT = datetime.now(timezone.utc) BENCHMARK_START_TIME = BENCHMARK_START_TIME_DT.strftime("%Y-%m-%dT%H:%M:%S+00:00") -TEMP_FOLDER_ABS_PATH = Path.cwd() / "agbenchmark_config" / "temp_folder" -CHALLENGES_ALREADY_BEATEN = ( - Path.cwd() / "agbenchmark_config" / "challenges_already_beaten.json" -) -UPDATES_JSON_PATH = Path.cwd() / "agbenchmark_config" / "updates.json" -if os.environ.get("HELICONE_API_KEY"): - HeliconeLockManager.write_custom_property( - "benchmark_start_time", BENCHMARK_START_TIME - ) +# if helicone_enabled: +# from helicone.lock import HeliconeLockManager -with open( - Path(__file__).resolve().parent / "challenges" / "optional_categories.json" -) as f: - OPTIONAL_CATEGORIES = json.load(f)["optional_categories"] - - -def get_unique_categories() -> set[str]: - """Find all data.json files in the directory relative to this file and its subdirectories, - read the "category" field from each file, and return a set of unique categories.""" - categories = set() - - # Get the directory of this file - this_dir = os.path.dirname(os.path.abspath(__file__)) - - glob_path = os.path.join(this_dir, "./challenges/**/data.json") - # Use it as the base for the glob pattern - for data_file in glob.glob(glob_path, recursive=True): - with open(data_file, "r") as f: - try: - data = json.load(f) - categories.update(data.get("category", [])) - except json.JSONDecodeError: - print(f"Error: {data_file} is not a valid JSON file.") - continue - except IOError: - print(f"IOError: file could not be read: {data_file}") - continue - - return categories - - -def run_benchmark( - maintain: bool = False, - improve: bool = False, - explore: bool = False, - mock: bool = False, - no_dep: bool = False, - nc: bool = False, - keep_answers: bool = False, - category: Optional[tuple[str]] = None, - skip_category: Optional[tuple[str]] = None, - test: Optional[str] = None, - cutoff: Optional[int] = None, - server: bool = False, -) -> int: - """Start the benchmark tests. If a category flag is provided, run the categories with that mark.""" - # Check if configuration file exists and is not empty - - initialize_updates_file() - SingletonReportManager() - agent_benchmark_config_path = str(Path.cwd() / "agbenchmark_config" / "config.json") - try: - with open(agent_benchmark_config_path, "r") as f: - agent_benchmark_config = AgentBenchmarkConfig(**json.load(f)) - agent_benchmark_config.agent_benchmark_config_path = ( - agent_benchmark_config_path - ) - except json.JSONDecodeError: - print("Error: benchmark_config.json is not a valid JSON file.") - return 1 +# HeliconeLockManager.write_custom_property( +# "benchmark_start_time", BENCHMARK_START_TIME +# ) - if maintain and improve and explore: - print( - "Error: You can't use --maintain, --improve or --explore at the same time. Please choose one." - ) - return 1 - if test and (category or skip_category or maintain or improve or explore): - print( - "Error: If you're running a specific test make sure no other options are selected. Please just pass the --test." - ) - return 1 - - assert agent_benchmark_config.host, "Error: host needs to be added to the config." +@click.group(cls=DefaultGroup, default_if_no_args=True) +@click.option("--debug", is_flag=True, help="Enable debug output") +def cli( + debug: bool, +) -> Any: + configure_logging(logging.DEBUG if debug else logging.INFO) - print("Current configuration:") - for key, value in vars(agent_benchmark_config).items(): - print(f"{key}: {value}") - pytest_args = ["-vs"] - if keep_answers: - pytest_args.append("--keep-answers") +@cli.command(hidden=True) +def start(): + raise DeprecationWarning( + "`agbenchmark start` is deprecated. Use `agbenchmark run` instead." + ) - if test: - print("Running specific test:", test) - else: - # Categories that are used in the challenges - categories = get_unique_categories() - if category: - invalid_categories = set(category) - categories - assert ( - not invalid_categories - ), f"Invalid categories: {invalid_categories}. Valid categories are: {categories}" - - if category: - categories_to_run = set(category) - if skip_category: - categories_to_run = categories_to_run.difference(set(skip_category)) - assert categories_to_run, "Error: You can't skip all categories" - pytest_args.extend(["-m", " or ".join(categories_to_run), "--category"]) - print("Running tests of category:", categories_to_run) - elif skip_category: - categories_to_run = categories - set(skip_category) - assert categories_to_run, "Error: You can't skip all categories" - pytest_args.extend(["-m", " or ".join(categories_to_run), "--category"]) - print("Running tests of category:", categories_to_run) - else: - print("Running all categories") - - if maintain: - print("Running only regression tests") - pytest_args.append("--maintain") - elif improve: - print("Running only non-regression tests") - pytest_args.append("--improve") - elif explore: - print("Only attempt challenges that have never been beaten") - pytest_args.append("--explore") - - if mock: - pytest_args.append("--mock") - os.environ[ - "IS_MOCK" - ] = "True" # ugly hack to make the mock work when calling from API - - if no_dep: - pytest_args.append("--no_dep") - - if nc and cutoff: - print( - "Error: You can't use both --nc and --cutoff at the same time. Please choose one." - ) - return 1 - if nc: - pytest_args.append("--nc") - if cutoff: - pytest_args.append("--cutoff") - print(f"Setting cuttoff override to {cutoff} seconds.") - current_dir = Path(__file__).resolve().parent - print(f"Current directory: {current_dir}") - pytest_args.extend((str(current_dir), "--cache-clear")) - exit_code = pytest.main(pytest_args) - SingletonReportManager().clear_instance() - - -@click.group(invoke_without_command=True) -@click.option("--backend", is_flag=True, help="If it's being run from the cli") -@click.option("-c", "--category", multiple=True, help="Specific category to run") +@cli.command(default=True) +@click.option( + "-N", "--attempts", default=1, help="Number of times to run each challenge." +) +@click.option( + "-c", + "--category", + multiple=True, + help="(+) Select a category to run.", +) @click.option( "-s", "--skip-category", multiple=True, - help="Skips preventing the tests from this category from running", + help="(+) Exclude a category from running.", ) -@click.option("--test", multiple=True, help="Specific test to run") -@click.option("--maintain", is_flag=True, help="Runs only regression tests") -@click.option("--improve", is_flag=True, help="Run only non-regression tests") +@click.option("--test", multiple=True, help="(+) Select a test to run.") +@click.option("--maintain", is_flag=True, help="Run only regression tests.") +@click.option("--improve", is_flag=True, help="Run only non-regression tests.") @click.option( "--explore", is_flag=True, - help="Only attempt challenges that have never been beaten", + help="Run only challenges that have never been beaten.", ) -@click.option("--mock", is_flag=True, help="Run with mock") @click.option( - "--no_dep", + "--no-dep", is_flag=True, - help="Run without dependencies", + help="Run all (selected) challenges, regardless of dependency success/failure.", ) -@click.option("--nc", is_flag=True, help="Run without cutoff") +@click.option("--cutoff", type=int, help="Override the challenge time limit (seconds).") +@click.option("--nc", is_flag=True, help="Disable the challenge time limit.") +@click.option("--mock", is_flag=True, help="Run with mock") @click.option("--keep-answers", is_flag=True, help="Keep answers") -@click.option("--cutoff", help="Set or override tests cutoff (seconds)") -@click.argument("value", type=str, required=False) -def cli( +@click.option( + "--backend", + is_flag=True, + help="Write log output to a file instead of the terminal.", +) +# @click.argument( +# "agent_path", type=click.Path(exists=True, file_okay=False), required=False +# ) +def run( maintain: bool, improve: bool, explore: bool, @@ -213,18 +107,38 @@ def cli( no_dep: bool, nc: bool, keep_answers: bool, - category: Optional[list[str]] = None, - skip_category: Optional[list[str]] = None, - test: Optional[str] = None, + test: tuple[str], + category: tuple[str], + skip_category: tuple[str], + attempts: int, cutoff: Optional[int] = None, backend: Optional[bool] = False, - value: Optional[str] = None, -) -> Any: - # Redirect stdout if backend is True - if value == "start": - raise ("`agbenchmark start` is removed. Run `agbenchmark` instead.") - if value == "serve": - return serve() + # agent_path: Optional[Path] = None, +) -> None: + """ + Run the benchmark on the agent in the current directory. + + Options marked with (+) can be specified multiple times, to select multiple items. + """ + from agbenchmark.main import run_benchmark, validate_args + + agbenchmark_config = AgentBenchmarkConfig.load() + logger.debug(f"agbenchmark_config: {agbenchmark_config.agbenchmark_config_dir}") + try: + validate_args( + maintain=maintain, + improve=improve, + explore=explore, + tests=test, + categories=category, + skip_categories=skip_category, + no_cutoff=nc, + cutoff=cutoff, + ) + except InvalidInvocationError as e: + logger.error("Error: " + "\n".join(e.args)) + sys.exit(1) + original_stdout = sys.stdout # Save the original standard output exit_code = None @@ -232,16 +146,18 @@ def cli( with open("backend/backend_stdout.txt", "w") as f: sys.stdout = f exit_code = run_benchmark( + config=agbenchmark_config, maintain=maintain, improve=improve, explore=explore, mock=mock, no_dep=no_dep, - nc=nc, + no_cutoff=nc, keep_answers=keep_answers, - category=category, - skip_category=skip_category, - test=test, + tests=test, + categories=category, + skip_categories=skip_category, + attempts_per_challenge=attempts, cutoff=cutoff, ) @@ -249,16 +165,18 @@ def cli( else: exit_code = run_benchmark( + config=agbenchmark_config, maintain=maintain, improve=improve, explore=explore, mock=mock, no_dep=no_dep, - nc=nc, + no_cutoff=nc, keep_answers=keep_answers, - category=category, - skip_category=skip_category, - test=test, + tests=test, + categories=category, + skip_categories=skip_category, + attempts_per_challenge=attempts, cutoff=cutoff, ) @@ -266,33 +184,44 @@ def cli( @cli.command() -def version(): - """Print the version of the benchmark tool.""" - current_directory = Path(__file__).resolve().parent - version = toml.load(current_directory / ".." / "pyproject.toml")["tool"]["poetry"][ - "version" - ] - print(f"Benchmark Tool Version {version}") +@click.option("--port", type=int, help="Port to run the API on.") +def serve(port: Optional[int] = None): + """Serve the benchmark frontend and API on port 8080.""" + import uvicorn + from agbenchmark.app import setup_fastapi_app -def serve(): - import uvicorn + config = AgentBenchmarkConfig.load() + app = setup_fastapi_app(config) # Run the FastAPI application using uvicorn - uvicorn.run(app, host="0.0.0.0", port=8080) + port = port or int(os.getenv("PORT", 8080)) + uvicorn.run(app, host="0.0.0.0", port=port) -def initialize_updates_file(): - if os.path.exists(UPDATES_JSON_PATH): - # If the file already exists, overwrite it with an empty list - with open(UPDATES_JSON_PATH, "w") as file: - json.dump([], file, indent=2) - print("Initialized updates.json by overwriting with an empty array") - else: - # If the file doesn't exist, create it and write an empty list - with open(UPDATES_JSON_PATH, "w") as file: - json.dump([], file, indent=2) - print("Created updates.json and initialized it with an empty array") +@cli.command() +def config(): + """Displays info regarding the present AGBenchmark config.""" + try: + config = AgentBenchmarkConfig.load() + except FileNotFoundError as e: + click.echo(e, err=True) + return 1 + + k_col_width = max(len(k) for k in config.dict().keys()) + for k, v in config.dict().items(): + click.echo(f"{k: <{k_col_width}} = {v}") + + +@cli.command() +def version(): + """Print version info for the AGBenchmark application.""" + import toml + + package_root = Path(__file__).resolve().parent.parent + pyproject = toml.load(package_root / "pyproject.toml") + version = pyproject["tool"]["poetry"]["version"] + click.echo(f"AGBenchmark version {version}") if __name__ == "__main__": diff --git a/benchmark/agbenchmark/agent_api_interface.py b/benchmark/agbenchmark/agent_api_interface.py index 18ff4520e..6eadcc537 100644 --- a/benchmark/agbenchmark/agent_api_interface.py +++ b/benchmark/agbenchmark/agent_api_interface.py @@ -1,33 +1,33 @@ -import json import logging import os -import pathlib import time -from typing import Any, Dict, Optional +from pathlib import Path +from typing import AsyncIterator, Optional -from agbenchmark.__main__ import TEMP_FOLDER_ABS_PATH, UPDATES_JSON_PATH -from agbenchmark.agent_interface import get_list_of_file_paths -from agbenchmark.agent_protocol_client import ( +from agent_protocol_client import ( AgentApi, ApiClient, Configuration, + Step, TaskRequestBody, ) -from agbenchmark.agent_protocol_client.models.step import Step -from agbenchmark.utils.data_types import ChallengeData -LOG = logging.getLogger(__name__) +from agbenchmark.agent_interface import get_list_of_file_paths +from agbenchmark.config import AgentBenchmarkConfig +logger = logging.getLogger(__name__) -async def run_api_agent( - task: ChallengeData, config: Dict[str, Any], artifacts_location: str, timeout: int -) -> None: - host_value = None - configuration = Configuration(host=config["AgentBenchmarkConfig"].host + "/ap/v1") +async def run_api_agent( + task: str, + config: AgentBenchmarkConfig, + timeout: int, + artifacts_location: Optional[Path] = None, +) -> AsyncIterator[Step]: + configuration = Configuration(host=config.host) async with ApiClient(configuration) as api_client: api_instance = AgentApi(api_client) - task_request_body = TaskRequestBody(input=task.task) + task_request_body = TaskRequestBody(input=task) start_time = time.time() response = await api_instance.create_agent_task( @@ -35,54 +35,52 @@ async def run_api_agent( ) task_id = response.task_id - await upload_artifacts( - api_instance, artifacts_location, task_id, "artifacts_in" - ) - - i = 1 - steps_remaining = True - while steps_remaining: - # Read the existing JSON data from the file + if artifacts_location: + await upload_artifacts( + api_instance, artifacts_location, task_id, "artifacts_in" + ) + while True: step = await api_instance.execute_agent_task_step(task_id=task_id) - await append_updates_file(step) - - print(f"[{task.name}] - step {step.name} ({i}. request)") - i += 1 + yield step if time.time() - start_time > timeout: raise TimeoutError("Time limit exceeded") if not step or step.is_last: - steps_remaining = False - # if we're calling a mock agent, we "cheat" and give the correct artifacts to pass the tests - if os.getenv("IS_MOCK"): - await upload_artifacts( - api_instance, artifacts_location, task_id, "artifacts_out" - ) + break + + if artifacts_location: + # In "mock" mode, we cheat by giving the correct artifacts to pass the test + if os.getenv("IS_MOCK"): + await upload_artifacts( + api_instance, artifacts_location, task_id, "artifacts_out" + ) - await copy_agent_artifacts_into_temp_folder(api_instance, task_id) + await download_agent_artifacts_into_folder( + api_instance, task_id, config.temp_folder + ) -async def copy_agent_artifacts_into_temp_folder(api_instance, task_id): +async def download_agent_artifacts_into_folder( + api_instance: AgentApi, task_id: str, folder: Path +): artifacts = await api_instance.list_agent_task_artifacts(task_id=task_id) + for artifact in artifacts.artifacts: # current absolute path of the directory of the file - directory_location = pathlib.Path(TEMP_FOLDER_ABS_PATH) if artifact.relative_path: - path = ( + path: str = ( artifact.relative_path if not artifact.relative_path.startswith("/") else artifact.relative_path[1:] ) - directory_location = pathlib.Path( - os.path.dirname(directory_location / path) - ) - LOG.info(f"Creating directory {directory_location}") + folder = (folder / path).parent - directory_location.mkdir(parents=True, exist_ok=True) + if not folder.exists(): + folder.mkdir(parents=True) - file_path = directory_location / artifact.file_name - LOG.info(f"Writing file {file_path}") + file_path = folder / artifact.file_name + logger.debug(f"Downloading agent artifact {artifact.file_name} to {folder}") with open(file_path, "wb") as f: content = await api_instance.download_agent_task_artifact( task_id=task_id, artifact_id=artifact.artifact_id @@ -91,35 +89,16 @@ async def copy_agent_artifacts_into_temp_folder(api_instance, task_id): f.write(content) -async def append_updates_file(step: Step): - with open(UPDATES_JSON_PATH, "r") as file: - existing_data = json.load(file) - # Append the new update to the existing array - new_update = create_update_json(step) - - existing_data.append(new_update) - # Write the updated array back to the file - with open(UPDATES_JSON_PATH, "w") as file: - file.write(json.dumps(existing_data, indent=2)) - - async def upload_artifacts( - api_instance: ApiClient, artifacts_location: str, task_id: str, type: str + api_instance: AgentApi, artifacts_location: Path, task_id: str, type: str ) -> None: for file_path in get_list_of_file_paths(artifacts_location, type): relative_path: Optional[str] = "/".join( - file_path.split(f"{type}/", 1)[-1].split("/")[:-1] + str(file_path).split(f"{type}/", 1)[-1].split("/")[:-1] ) if not relative_path: relative_path = None await api_instance.upload_agent_task_artifacts( - task_id=task_id, file=file_path, relative_path=relative_path + task_id=task_id, file=str(file_path), relative_path=relative_path ) - - -def create_update_json(step: Step): - now = int(time.time()) - content = {"content": step.to_dict(), "timestamp": now} - - return content diff --git a/benchmark/agbenchmark/agent_interface.py b/benchmark/agbenchmark/agent_interface.py index 269e8f8ff..52bd2093c 100644 --- a/benchmark/agbenchmark/agent_interface.py +++ b/benchmark/agbenchmark/agent_interface.py @@ -1,45 +1,27 @@ import os import shutil -import sys -from typing import List +from pathlib import Path from dotenv import load_dotenv -from agbenchmark.execute_sub_process import execute_subprocess - load_dotenv() -helicone_graphql_logs = os.getenv("HELICONE_GRAPHQL_LOGS") -HELICONE_GRAPHQL_LOGS = ( - helicone_graphql_logs.lower() == "true" if helicone_graphql_logs else False -) - - -def run_agent(task: str, timeout: int) -> None: - print(f"Running agbenchmark/benchmarks.py with timeout {timeout}") - - command = [sys.executable, "-m", "agbenchmark_config.benchmarks", str(task)] - - execute_subprocess(command, timeout) +HELICONE_GRAPHQL_LOGS = os.getenv("HELICONE_GRAPHQL_LOGS", "").lower() == "true" def get_list_of_file_paths( - challenge_dir_path: str, artifact_folder_name: str -) -> List[str]: - # this file is at agbenchmark\agent_interface.py - source_dir = os.path.join( - challenge_dir_path, - artifact_folder_name, - ) - if not os.path.exists(source_dir): + challenge_dir_path: str | Path, artifact_folder_name: str +) -> list[Path]: + source_dir = Path(challenge_dir_path) / artifact_folder_name + if not source_dir.exists(): return [] - return [os.path.join(source_dir, file_name) for file_name in os.listdir(source_dir)] + return list(source_dir.iterdir()) -def copy_artifacts_into_temp_folder( - workspace: str | dict[str, str], artifact_folder_name: str, challenge_dir_path: str +def copy_challenge_artifacts_into_workspace( + challenge_dir_path: str | Path, artifact_folder_name: str, workspace: str | Path ) -> None: file_paths = get_list_of_file_paths(challenge_dir_path, artifact_folder_name) for file_path in file_paths: - if os.path.isfile(file_path): + if file_path.is_file(): shutil.copy(file_path, workspace) diff --git a/benchmark/agbenchmark/agent_protocol_client/__init__.py b/benchmark/agbenchmark/agent_protocol_client/__init__.py deleted file mode 100644 index c393f2f83..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/__init__.py +++ /dev/null @@ -1,42 +0,0 @@ -# coding: utf-8 - -# flake8: noqa - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -__version__ = "1.0.0" - -# import apis into sdk package -from agbenchmark.agent_protocol_client.api.agent_api import AgentApi -from agbenchmark.agent_protocol_client.api_client import ApiClient - -# import ApiClient -from agbenchmark.agent_protocol_client.api_response import ApiResponse -from agbenchmark.agent_protocol_client.configuration import Configuration -from agbenchmark.agent_protocol_client.exceptions import ( - ApiAttributeError, - ApiException, - ApiKeyError, - ApiTypeError, - ApiValueError, - OpenApiException, -) - -# import models into sdk package -from agbenchmark.agent_protocol_client.models.artifact import Artifact -from agbenchmark.agent_protocol_client.models.step import Step -from agbenchmark.agent_protocol_client.models.step_all_of import StepAllOf -from agbenchmark.agent_protocol_client.models.step_request_body import StepRequestBody -from agbenchmark.agent_protocol_client.models.task import Task -from agbenchmark.agent_protocol_client.models.task_all_of import TaskAllOf -from agbenchmark.agent_protocol_client.models.task_request_body import TaskRequestBody diff --git a/benchmark/agbenchmark/agent_protocol_client/api/__init__.py b/benchmark/agbenchmark/agent_protocol_client/api/__init__.py deleted file mode 100644 index 3b2e21069..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/api/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -# flake8: noqa - -# import apis into api package -from agbenchmark.agent_protocol_client.api.agent_api import AgentApi diff --git a/benchmark/agbenchmark/agent_protocol_client/api/agent_api.py b/benchmark/agbenchmark/agent_protocol_client/api/agent_api.py deleted file mode 100644 index 2597c880f..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/api/agent_api.py +++ /dev/null @@ -1,1647 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -import re # noqa: F401 -from typing import Any, Awaitable, List, Optional, Union, overload - -from pydantic import Field, StrictBytes, StrictStr, validate_arguments -from typing_extensions import Annotated - -from agbenchmark.agent_protocol_client.api_client import ApiClient -from agbenchmark.agent_protocol_client.api_response import ApiResponse -from agbenchmark.agent_protocol_client.exceptions import ( # noqa: F401 - ApiTypeError, - ApiValueError, -) -from agbenchmark.agent_protocol_client.models.artifact import Artifact -from agbenchmark.agent_protocol_client.models.step import Step -from agbenchmark.agent_protocol_client.models.step_request_body import StepRequestBody -from agbenchmark.agent_protocol_client.models.task import Task -from agbenchmark.agent_protocol_client.models.task_request_body import TaskRequestBody - - -class AgentApi(object): - """NOTE: This class is auto generated by OpenAPI Generator - Ref: https://openapi-generator.tech - - Do not edit the class manually. - """ - - def __init__(self, api_client=None): - if api_client is None: - api_client = ApiClient.get_default() - self.api_client = api_client - - @overload - async def create_agent_task( - self, task_request_body: Optional[TaskRequestBody] = None, **kwargs - ) -> Task: # noqa: E501 - ... - - @overload - def create_agent_task( - self, - task_request_body: Optional[TaskRequestBody] = None, - async_req: Optional[bool] = True, - **kwargs, - ) -> Task: # noqa: E501 - ... - - @validate_arguments - def create_agent_task( - self, - task_request_body: Optional[TaskRequestBody] = None, - async_req: Optional[bool] = None, - **kwargs, - ) -> Union[Task, Awaitable[Task]]: # noqa: E501 - """Creates a task for the agent. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.create_agent_task(task_request_body, async_req=True) - >>> result = thread.get() - - :param task_request_body: - :type task_request_body: TaskRequestBody - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: Task - """ - kwargs["_return_http_data_only"] = True - if "_preload_content" in kwargs: - raise ValueError( - "Error! Please call the create_agent_task_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data" - ) - if async_req is not None: - kwargs["async_req"] = async_req - return self.create_agent_task_with_http_info( - task_request_body, **kwargs - ) # noqa: E501 - - @validate_arguments - def create_agent_task_with_http_info( - self, task_request_body: Optional[TaskRequestBody] = None, **kwargs - ) -> ApiResponse: # noqa: E501 - """Creates a task for the agent. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.create_agent_task_with_http_info(task_request_body, async_req=True) - >>> result = thread.get() - - :param task_request_body: - :type task_request_body: TaskRequestBody - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :type _preload_content: bool, optional - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :type _return_http_data_only: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_auth: dict, optional - :type _content_type: string, optional: force content-type for the request - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: tuple(Task, status_code(int), headers(HTTPHeaderDict)) - """ - - _params = locals() - - _all_params = ["task_request_body"] - _all_params.extend( - [ - "async_req", - "_return_http_data_only", - "_preload_content", - "_request_timeout", - "_request_auth", - "_content_type", - "_headers", - ] - ) - - # validate the arguments - for _key, _val in _params["kwargs"].items(): - if _key not in _all_params: - raise ApiTypeError( - "Got an unexpected keyword argument '%s'" - " to method create_agent_task" % _key - ) - _params[_key] = _val - del _params["kwargs"] - - _collection_formats = {} - - # process the path parameters - _path_params = {} - - # process the query parameters - _query_params = [] - # process the header parameters - _header_params = dict(_params.get("_headers", {})) - # process the form parameters - _form_params = [] - _files = {} - # process the body parameter - _body_params = None - if _params["task_request_body"] is not None: - _body_params = _params["task_request_body"] - - # set the HTTP header `Accept` - _header_params["Accept"] = self.api_client.select_header_accept( - ["application/json"] - ) # noqa: E501 - - # set the HTTP header `Content-Type` - _content_types_list = _params.get( - "_content_type", - self.api_client.select_header_content_type(["application/json"]), - ) - if _content_types_list: - _header_params["Content-Type"] = _content_types_list - - # authentication setting - _auth_settings = [] # noqa: E501 - - _response_types_map = { - "200": "Task", - } - - return self.api_client.call_api( - "/agent/tasks", - "POST", - _path_params, - _query_params, - _header_params, - body=_body_params, - post_params=_form_params, - files=_files, - response_types_map=_response_types_map, - auth_settings=_auth_settings, - async_req=_params.get("async_req"), - _return_http_data_only=_params.get("_return_http_data_only"), # noqa: E501 - _preload_content=_params.get("_preload_content", True), - _request_timeout=_params.get("_request_timeout"), - collection_formats=_collection_formats, - _request_auth=_params.get("_request_auth"), - ) - - @overload - async def download_agent_task_artifact( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - artifact_id: Annotated[StrictStr, Field(..., description="ID of the artifact")], - **kwargs, - ) -> bytearray: # noqa: E501 - ... - - @overload - def download_agent_task_artifact( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - artifact_id: Annotated[StrictStr, Field(..., description="ID of the artifact")], - async_req: Optional[bool] = True, - **kwargs, - ) -> bytearray: # noqa: E501 - ... - - @validate_arguments - def download_agent_task_artifact( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - artifact_id: Annotated[StrictStr, Field(..., description="ID of the artifact")], - async_req: Optional[bool] = None, - **kwargs, - ) -> Union[bytearray, Awaitable[bytearray]]: # noqa: E501 - """Download a specified artifact. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.download_agent_task_artifact(task_id, artifact_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param artifact_id: ID of the artifact (required) - :type artifact_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: bytearray - """ - kwargs["_return_http_data_only"] = True - if "_preload_content" in kwargs: - raise ValueError( - "Error! Please call the download_agent_task_artifact_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data" - ) - if async_req is not None: - kwargs["async_req"] = async_req - return self.download_agent_task_artifact_with_http_info( - task_id, artifact_id, **kwargs - ) # noqa: E501 - - @validate_arguments - def download_agent_task_artifact_with_http_info( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - artifact_id: Annotated[StrictStr, Field(..., description="ID of the artifact")], - **kwargs, - ) -> ApiResponse: # noqa: E501 - """Download a specified artifact. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.download_agent_task_artifact_with_http_info(task_id, artifact_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param artifact_id: ID of the artifact (required) - :type artifact_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :type _preload_content: bool, optional - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :type _return_http_data_only: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_auth: dict, optional - :type _content_type: string, optional: force content-type for the request - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: tuple(bytearray, status_code(int), headers(HTTPHeaderDict)) - """ - - _params = locals() - - _all_params = ["task_id", "artifact_id"] - _all_params.extend( - [ - "async_req", - "_return_http_data_only", - "_preload_content", - "_request_timeout", - "_request_auth", - "_content_type", - "_headers", - ] - ) - - # validate the arguments - for _key, _val in _params["kwargs"].items(): - if _key not in _all_params: - raise ApiTypeError( - "Got an unexpected keyword argument '%s'" - " to method download_agent_task_artifact" % _key - ) - _params[_key] = _val - del _params["kwargs"] - - _collection_formats = {} - - # process the path parameters - _path_params = {} - if _params["task_id"]: - _path_params["task_id"] = _params["task_id"] - - if _params["artifact_id"]: - _path_params["artifact_id"] = _params["artifact_id"] - - # process the query parameters - _query_params = [] - # process the header parameters - _header_params = dict(_params.get("_headers", {})) - # process the form parameters - _form_params = [] - _files = {} - # process the body parameter - _body_params = None - # set the HTTP header `Accept` - _header_params["Accept"] = self.api_client.select_header_accept( - ["application/octet-stream"] - ) # noqa: E501 - - # authentication setting - _auth_settings = [] # noqa: E501 - - _response_types_map = { - "200": "bytearray", - } - - return self.api_client.call_api( - "/agent/tasks/{task_id}/artifacts/{artifact_id}", - "GET", - _path_params, - _query_params, - _header_params, - body=_body_params, - post_params=_form_params, - files=_files, - response_types_map=_response_types_map, - auth_settings=_auth_settings, - async_req=_params.get("async_req"), - _return_http_data_only=_params.get("_return_http_data_only"), # noqa: E501 - _preload_content=_params.get("_preload_content", True), - _request_timeout=_params.get("_request_timeout"), - collection_formats=_collection_formats, - _request_auth=_params.get("_request_auth"), - ) - - @overload - async def execute_agent_task_step( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - step_request_body: Optional[StepRequestBody] = None, - **kwargs, - ) -> Step: # noqa: E501 - ... - - @overload - def execute_agent_task_step( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - step_request_body: Optional[StepRequestBody] = None, - async_req: Optional[bool] = True, - **kwargs, - ) -> Step: # noqa: E501 - ... - - @validate_arguments - def execute_agent_task_step( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - step_request_body: Optional[StepRequestBody] = None, - async_req: Optional[bool] = None, - **kwargs, - ) -> Union[Step, Awaitable[Step]]: # noqa: E501 - """Execute a step in the specified agent task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.execute_agent_task_step(task_id, step_request_body, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param step_request_body: - :type step_request_body: StepRequestBody - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: Step - """ - kwargs["_return_http_data_only"] = True - if "_preload_content" in kwargs: - raise ValueError( - "Error! Please call the execute_agent_task_step_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data" - ) - if async_req is not None: - kwargs["async_req"] = async_req - return self.execute_agent_task_step_with_http_info( - task_id, step_request_body, **kwargs - ) # noqa: E501 - - @validate_arguments - def execute_agent_task_step_with_http_info( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - step_request_body: Optional[StepRequestBody] = None, - **kwargs, - ) -> ApiResponse: # noqa: E501 - """Execute a step in the specified agent task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.execute_agent_task_step_with_http_info(task_id, step_request_body, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param step_request_body: - :type step_request_body: StepRequestBody - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :type _preload_content: bool, optional - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :type _return_http_data_only: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_auth: dict, optional - :type _content_type: string, optional: force content-type for the request - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: tuple(Step, status_code(int), headers(HTTPHeaderDict)) - """ - - _params = locals() - - _all_params = ["task_id", "step_request_body"] - _all_params.extend( - [ - "async_req", - "_return_http_data_only", - "_preload_content", - "_request_timeout", - "_request_auth", - "_content_type", - "_headers", - ] - ) - - # validate the arguments - for _key, _val in _params["kwargs"].items(): - if _key not in _all_params: - raise ApiTypeError( - "Got an unexpected keyword argument '%s'" - " to method execute_agent_task_step" % _key - ) - _params[_key] = _val - del _params["kwargs"] - - _collection_formats = {} - - # process the path parameters - _path_params = {} - if _params["task_id"]: - _path_params["task_id"] = _params["task_id"] - - # process the query parameters - _query_params = [] - # process the header parameters - _header_params = dict(_params.get("_headers", {})) - # process the form parameters - _form_params = [] - _files = {} - # process the body parameter - _body_params = None - if _params["step_request_body"] is not None: - _body_params = _params["step_request_body"] - - # set the HTTP header `Accept` - _header_params["Accept"] = self.api_client.select_header_accept( - ["application/json"] - ) # noqa: E501 - - # set the HTTP header `Content-Type` - _content_types_list = _params.get( - "_content_type", - self.api_client.select_header_content_type(["application/json"]), - ) - if _content_types_list: - _header_params["Content-Type"] = _content_types_list - - # authentication setting - _auth_settings = [] # noqa: E501 - - _response_types_map = { - "200": "Step", - } - - return self.api_client.call_api( - "/agent/tasks/{task_id}/steps", - "POST", - _path_params, - _query_params, - _header_params, - body=_body_params, - post_params=_form_params, - files=_files, - response_types_map=_response_types_map, - auth_settings=_auth_settings, - async_req=_params.get("async_req"), - _return_http_data_only=_params.get("_return_http_data_only"), # noqa: E501 - _preload_content=_params.get("_preload_content", True), - _request_timeout=_params.get("_request_timeout"), - collection_formats=_collection_formats, - _request_auth=_params.get("_request_auth"), - ) - - @overload - async def get_agent_task( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - **kwargs, - ) -> Task: # noqa: E501 - ... - - @overload - def get_agent_task( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - async_req: Optional[bool] = True, - **kwargs, - ) -> Task: # noqa: E501 - ... - - @validate_arguments - def get_agent_task( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - async_req: Optional[bool] = None, - **kwargs, - ) -> Union[Task, Awaitable[Task]]: # noqa: E501 - """Get details about a specified agent task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.get_agent_task(task_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: Task - """ - kwargs["_return_http_data_only"] = True - if "_preload_content" in kwargs: - raise ValueError( - "Error! Please call the get_agent_task_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data" - ) - if async_req is not None: - kwargs["async_req"] = async_req - return self.get_agent_task_with_http_info(task_id, **kwargs) # noqa: E501 - - @validate_arguments - def get_agent_task_with_http_info( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - **kwargs, - ) -> ApiResponse: # noqa: E501 - """Get details about a specified agent task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.get_agent_task_with_http_info(task_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :type _preload_content: bool, optional - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :type _return_http_data_only: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_auth: dict, optional - :type _content_type: string, optional: force content-type for the request - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: tuple(Task, status_code(int), headers(HTTPHeaderDict)) - """ - - _params = locals() - - _all_params = ["task_id"] - _all_params.extend( - [ - "async_req", - "_return_http_data_only", - "_preload_content", - "_request_timeout", - "_request_auth", - "_content_type", - "_headers", - ] - ) - - # validate the arguments - for _key, _val in _params["kwargs"].items(): - if _key not in _all_params: - raise ApiTypeError( - "Got an unexpected keyword argument '%s'" - " to method get_agent_task" % _key - ) - _params[_key] = _val - del _params["kwargs"] - - _collection_formats = {} - - # process the path parameters - _path_params = {} - if _params["task_id"]: - _path_params["task_id"] = _params["task_id"] - - # process the query parameters - _query_params = [] - # process the header parameters - _header_params = dict(_params.get("_headers", {})) - # process the form parameters - _form_params = [] - _files = {} - # process the body parameter - _body_params = None - # set the HTTP header `Accept` - _header_params["Accept"] = self.api_client.select_header_accept( - ["application/json"] - ) # noqa: E501 - - # authentication setting - _auth_settings = [] # noqa: E501 - - _response_types_map = { - "200": "Task", - } - - return self.api_client.call_api( - "/agent/tasks/{task_id}", - "GET", - _path_params, - _query_params, - _header_params, - body=_body_params, - post_params=_form_params, - files=_files, - response_types_map=_response_types_map, - auth_settings=_auth_settings, - async_req=_params.get("async_req"), - _return_http_data_only=_params.get("_return_http_data_only"), # noqa: E501 - _preload_content=_params.get("_preload_content", True), - _request_timeout=_params.get("_request_timeout"), - collection_formats=_collection_formats, - _request_auth=_params.get("_request_auth"), - ) - - @overload - async def get_agent_task_step( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - step_id: Annotated[StrictStr, Field(..., description="ID of the step")], - **kwargs, - ) -> Step: # noqa: E501 - ... - - @overload - def get_agent_task_step( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - step_id: Annotated[StrictStr, Field(..., description="ID of the step")], - async_req: Optional[bool] = True, - **kwargs, - ) -> Step: # noqa: E501 - ... - - @validate_arguments - def get_agent_task_step( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - step_id: Annotated[StrictStr, Field(..., description="ID of the step")], - async_req: Optional[bool] = None, - **kwargs, - ) -> Union[Step, Awaitable[Step]]: # noqa: E501 - """Get details about a specified task step. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.get_agent_task_step(task_id, step_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param step_id: ID of the step (required) - :type step_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: Step - """ - kwargs["_return_http_data_only"] = True - if "_preload_content" in kwargs: - raise ValueError( - "Error! Please call the get_agent_task_step_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data" - ) - if async_req is not None: - kwargs["async_req"] = async_req - return self.get_agent_task_step_with_http_info( - task_id, step_id, **kwargs - ) # noqa: E501 - - @validate_arguments - def get_agent_task_step_with_http_info( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - step_id: Annotated[StrictStr, Field(..., description="ID of the step")], - **kwargs, - ) -> ApiResponse: # noqa: E501 - """Get details about a specified task step. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.get_agent_task_step_with_http_info(task_id, step_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param step_id: ID of the step (required) - :type step_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :type _preload_content: bool, optional - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :type _return_http_data_only: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_auth: dict, optional - :type _content_type: string, optional: force content-type for the request - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: tuple(Step, status_code(int), headers(HTTPHeaderDict)) - """ - - _params = locals() - - _all_params = ["task_id", "step_id"] - _all_params.extend( - [ - "async_req", - "_return_http_data_only", - "_preload_content", - "_request_timeout", - "_request_auth", - "_content_type", - "_headers", - ] - ) - - # validate the arguments - for _key, _val in _params["kwargs"].items(): - if _key not in _all_params: - raise ApiTypeError( - "Got an unexpected keyword argument '%s'" - " to method get_agent_task_step" % _key - ) - _params[_key] = _val - del _params["kwargs"] - - _collection_formats = {} - - # process the path parameters - _path_params = {} - if _params["task_id"]: - _path_params["task_id"] = _params["task_id"] - - if _params["step_id"]: - _path_params["step_id"] = _params["step_id"] - - # process the query parameters - _query_params = [] - # process the header parameters - _header_params = dict(_params.get("_headers", {})) - # process the form parameters - _form_params = [] - _files = {} - # process the body parameter - _body_params = None - # set the HTTP header `Accept` - _header_params["Accept"] = self.api_client.select_header_accept( - ["application/json"] - ) # noqa: E501 - - # authentication setting - _auth_settings = [] # noqa: E501 - - _response_types_map = { - "200": "Step", - } - - return self.api_client.call_api( - "/agent/tasks/{task_id}/steps/{step_id}", - "GET", - _path_params, - _query_params, - _header_params, - body=_body_params, - post_params=_form_params, - files=_files, - response_types_map=_response_types_map, - auth_settings=_auth_settings, - async_req=_params.get("async_req"), - _return_http_data_only=_params.get("_return_http_data_only"), # noqa: E501 - _preload_content=_params.get("_preload_content", True), - _request_timeout=_params.get("_request_timeout"), - collection_formats=_collection_formats, - _request_auth=_params.get("_request_auth"), - ) - - @overload - async def list_agent_task_artifacts( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - **kwargs, - ) -> Any: # noqa: E501 - ... - - @overload - def list_agent_task_artifacts( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - async_req: Optional[bool] = True, - **kwargs, - ) -> Any: # noqa: E501 - ... - - @validate_arguments - def list_agent_task_artifacts( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - async_req: Optional[bool] = None, - **kwargs, - ) -> Union[Any, Awaitable[Any]]: # noqa: E501 - """List all artifacts that have been created for the given task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.list_agent_task_artifacts(task_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: List[Artifact] - """ - kwargs["_return_http_data_only"] = True - if "_preload_content" in kwargs: - raise ValueError( - "Error! Please call the list_agent_task_artifacts_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data" - ) - if async_req is not None: - kwargs["async_req"] = async_req - return self.list_agent_task_artifacts_with_http_info( - task_id, **kwargs - ) # noqa: E501 - - @validate_arguments - def list_agent_task_artifacts_with_http_info( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - **kwargs, - ) -> ApiResponse: # noqa: E501 - """List all artifacts that have been created for the given task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.list_agent_task_artifacts_with_http_info(task_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :type _preload_content: bool, optional - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :type _return_http_data_only: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_auth: dict, optional - :type _content_type: string, optional: force content-type for the request - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: tuple(List[Artifact], status_code(int), headers(HTTPHeaderDict)) - """ - - _params = locals() - - _all_params = ["task_id"] - _all_params.extend( - [ - "async_req", - "_return_http_data_only", - "_preload_content", - "_request_timeout", - "_request_auth", - "_content_type", - "_headers", - ] - ) - - # validate the arguments - for _key, _val in _params["kwargs"].items(): - if _key not in _all_params: - raise ApiTypeError( - "Got an unexpected keyword argument '%s'" - " to method list_agent_task_artifacts" % _key - ) - _params[_key] = _val - del _params["kwargs"] - - _collection_formats = {} - - # process the path parameters - _path_params = {} - if _params["task_id"]: - _path_params["task_id"] = _params["task_id"] - - # process the query parameters - _query_params = [] - # process the header parameters - _header_params = dict(_params.get("_headers", {})) - # process the form parameters - _form_params = [] - _files = {} - # process the body parameter - _body_params = None - # set the HTTP header `Accept` - _header_params["Accept"] = self.api_client.select_header_accept( - ["application/json"] - ) # noqa: E501 - - # authentication setting - _auth_settings = [] # noqa: E501 - - _response_types_map = { - "200": "Artifacts", - } - - return self.api_client.call_api( - "/agent/tasks/{task_id}/artifacts", - "GET", - _path_params, - _query_params, - _header_params, - body=_body_params, - post_params=_form_params, - files=_files, - response_types_map=_response_types_map, - auth_settings=_auth_settings, - async_req=_params.get("async_req"), - _return_http_data_only=_params.get("_return_http_data_only"), # noqa: E501 - _preload_content=_params.get("_preload_content", True), - _request_timeout=_params.get("_request_timeout"), - collection_formats=_collection_formats, - _request_auth=_params.get("_request_auth"), - ) - - @overload - async def list_agent_task_steps( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - **kwargs, - ) -> List[str]: # noqa: E501 - ... - - @overload - def list_agent_task_steps( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - async_req: Optional[bool] = True, - **kwargs, - ) -> List[str]: # noqa: E501 - ... - - @validate_arguments - def list_agent_task_steps( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - async_req: Optional[bool] = None, - **kwargs, - ) -> Union[List[str], Awaitable[List[str]]]: # noqa: E501 - """List all steps for the specified task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.list_agent_task_steps(task_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: List[str] - """ - kwargs["_return_http_data_only"] = True - if "_preload_content" in kwargs: - raise ValueError( - "Error! Please call the list_agent_task_steps_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data" - ) - if async_req is not None: - kwargs["async_req"] = async_req - return self.list_agent_task_steps_with_http_info( - task_id, **kwargs - ) # noqa: E501 - - @validate_arguments - def list_agent_task_steps_with_http_info( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - **kwargs, - ) -> ApiResponse: # noqa: E501 - """List all steps for the specified task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.list_agent_task_steps_with_http_info(task_id, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :type _preload_content: bool, optional - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :type _return_http_data_only: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_auth: dict, optional - :type _content_type: string, optional: force content-type for the request - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: tuple(List[str], status_code(int), headers(HTTPHeaderDict)) - """ - - _params = locals() - - _all_params = ["task_id"] - _all_params.extend( - [ - "async_req", - "_return_http_data_only", - "_preload_content", - "_request_timeout", - "_request_auth", - "_content_type", - "_headers", - ] - ) - - # validate the arguments - for _key, _val in _params["kwargs"].items(): - if _key not in _all_params: - raise ApiTypeError( - "Got an unexpected keyword argument '%s'" - " to method list_agent_task_steps" % _key - ) - _params[_key] = _val - del _params["kwargs"] - - _collection_formats = {} - - # process the path parameters - _path_params = {} - if _params["task_id"]: - _path_params["task_id"] = _params["task_id"] - - # process the query parameters - _query_params = [] - # process the header parameters - _header_params = dict(_params.get("_headers", {})) - # process the form parameters - _form_params = [] - _files = {} - # process the body parameter - _body_params = None - # set the HTTP header `Accept` - _header_params["Accept"] = self.api_client.select_header_accept( - ["application/json"] - ) # noqa: E501 - - # authentication setting - _auth_settings = [] # noqa: E501 - - _response_types_map = { - "200": "List[str]", - } - - return self.api_client.call_api( - "/agent/tasks/{task_id}/steps", - "GET", - _path_params, - _query_params, - _header_params, - body=_body_params, - post_params=_form_params, - files=_files, - response_types_map=_response_types_map, - auth_settings=_auth_settings, - async_req=_params.get("async_req"), - _return_http_data_only=_params.get("_return_http_data_only"), # noqa: E501 - _preload_content=_params.get("_preload_content", True), - _request_timeout=_params.get("_request_timeout"), - collection_formats=_collection_formats, - _request_auth=_params.get("_request_auth"), - ) - - @overload - async def list_agent_tasks_ids(self, **kwargs) -> List[str]: # noqa: E501 - ... - - @overload - def list_agent_tasks_ids( - self, async_req: Optional[bool] = True, **kwargs - ) -> List[str]: # noqa: E501 - ... - - @validate_arguments - def list_agent_tasks_ids( - self, async_req: Optional[bool] = None, **kwargs - ) -> Union[List[str], Awaitable[List[str]]]: # noqa: E501 - """List all tasks that have been created for the agent. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.list_agent_tasks_ids(async_req=True) - >>> result = thread.get() - - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: List[str] - """ - kwargs["_return_http_data_only"] = True - if "_preload_content" in kwargs: - raise ValueError( - "Error! Please call the list_agent_tasks_ids_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data" - ) - if async_req is not None: - kwargs["async_req"] = async_req - return self.list_agent_tasks_ids_with_http_info(**kwargs) # noqa: E501 - - @validate_arguments - def list_agent_tasks_ids_with_http_info( - self, **kwargs - ) -> ApiResponse: # noqa: E501 - """List all tasks that have been created for the agent. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.list_agent_tasks_ids_with_http_info(async_req=True) - >>> result = thread.get() - - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :type _preload_content: bool, optional - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :type _return_http_data_only: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_auth: dict, optional - :type _content_type: string, optional: force content-type for the request - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: tuple(List[str], status_code(int), headers(HTTPHeaderDict)) - """ - - _params = locals() - - _all_params = [] - _all_params.extend( - [ - "async_req", - "_return_http_data_only", - "_preload_content", - "_request_timeout", - "_request_auth", - "_content_type", - "_headers", - ] - ) - - # validate the arguments - for _key, _val in _params["kwargs"].items(): - if _key not in _all_params: - raise ApiTypeError( - "Got an unexpected keyword argument '%s'" - " to method list_agent_tasks_ids" % _key - ) - _params[_key] = _val - del _params["kwargs"] - - _collection_formats = {} - - # process the path parameters - _path_params = {} - - # process the query parameters - _query_params = [] - # process the header parameters - _header_params = dict(_params.get("_headers", {})) - # process the form parameters - _form_params = [] - _files = {} - # process the body parameter - _body_params = None - # set the HTTP header `Accept` - _header_params["Accept"] = self.api_client.select_header_accept( - ["application/json"] - ) # noqa: E501 - - # authentication setting - _auth_settings = [] # noqa: E501 - - _response_types_map = { - "200": "List[str]", - } - - return self.api_client.call_api( - "/agent/tasks", - "GET", - _path_params, - _query_params, - _header_params, - body=_body_params, - post_params=_form_params, - files=_files, - response_types_map=_response_types_map, - auth_settings=_auth_settings, - async_req=_params.get("async_req"), - _return_http_data_only=_params.get("_return_http_data_only"), # noqa: E501 - _preload_content=_params.get("_preload_content", True), - _request_timeout=_params.get("_request_timeout"), - collection_formats=_collection_formats, - _request_auth=_params.get("_request_auth"), - ) - - @overload - async def upload_agent_task_artifacts( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - file: Annotated[ - Union[StrictBytes, StrictStr], Field(..., description="File to upload.") - ], - relative_path: Annotated[ - Optional[StrictStr], - Field( - description="Relative path of the artifact in the agent's workspace." - ), - ] = None, - **kwargs, - ) -> Artifact: # noqa: E501 - ... - - @overload - def upload_agent_task_artifacts( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - file: Annotated[ - Union[StrictBytes, StrictStr], Field(..., description="File to upload.") - ], - relative_path: Annotated[ - Optional[StrictStr], - Field( - description="Relative path of the artifact in the agent's workspace." - ), - ] = None, - async_req: Optional[bool] = True, - **kwargs, - ) -> Artifact: # noqa: E501 - ... - - @validate_arguments - def upload_agent_task_artifacts( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - file: Annotated[ - Union[StrictBytes, StrictStr], Field(..., description="File to upload.") - ], - relative_path: Annotated[ - Optional[StrictStr], - Field( - description="Relative path of the artifact in the agent's workspace." - ), - ] = None, - async_req: Optional[bool] = None, - **kwargs, - ) -> Union[Artifact, Awaitable[Artifact]]: # noqa: E501 - """Upload an artifact for the specified task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.upload_agent_task_artifacts(task_id, file, relative_path, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param file: File to upload. (required) - :type file: bytearray - :param relative_path: Relative path of the artifact in the agent's workspace. - :type relative_path: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: Artifact - """ - kwargs["_return_http_data_only"] = True - if "_preload_content" in kwargs: - raise ValueError( - "Error! Please call the upload_agent_task_artifacts_with_http_info method with `_preload_content` instead and obtain raw data from ApiResponse.raw_data" - ) - if async_req is not None: - kwargs["async_req"] = async_req - return self.upload_agent_task_artifacts_with_http_info( - task_id, file, relative_path, **kwargs - ) # noqa: E501 - - @validate_arguments - def upload_agent_task_artifacts_with_http_info( - self, - task_id: Annotated[StrictStr, Field(..., description="ID of the task")], - file: Annotated[ - Union[StrictBytes, StrictStr], Field(..., description="File to upload.") - ], - relative_path: Annotated[ - Optional[StrictStr], - Field( - description="Relative path of the artifact in the agent's workspace." - ), - ] = None, - **kwargs, - ) -> ApiResponse: # noqa: E501 - """Upload an artifact for the specified task. # noqa: E501 - - This method makes a synchronous HTTP request by default. To make an - asynchronous HTTP request, please pass async_req=True - - >>> thread = api.upload_agent_task_artifacts_with_http_info(task_id, file, relative_path, async_req=True) - >>> result = thread.get() - - :param task_id: ID of the task (required) - :type task_id: str - :param file: File to upload. (required) - :type file: bytearray - :param relative_path: Relative path of the artifact in the agent's workspace. - :type relative_path: str - :param async_req: Whether to execute the request asynchronously. - :type async_req: bool, optional - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :type _preload_content: bool, optional - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :type _return_http_data_only: bool, optional - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_auth: dict, optional - :type _content_type: string, optional: force content-type for the request - :return: Returns the result object. - If the method is called asynchronously, - returns the request thread. - :rtype: tuple(Artifact, status_code(int), headers(HTTPHeaderDict)) - """ - - _params = locals() - - _all_params = ["task_id", "file", "relative_path"] - _all_params.extend( - [ - "async_req", - "_return_http_data_only", - "_preload_content", - "_request_timeout", - "_request_auth", - "_content_type", - "_headers", - ] - ) - - # validate the arguments - for _key, _val in _params["kwargs"].items(): - if _key not in _all_params: - raise ApiTypeError( - "Got an unexpected keyword argument '%s'" - " to method upload_agent_task_artifacts" % _key - ) - _params[_key] = _val - del _params["kwargs"] - - _collection_formats = {} - - # process the path parameters - _path_params = {} - if _params["task_id"]: - _path_params["task_id"] = _params["task_id"] - - # process the query parameters - _query_params = [] - # process the header parameters - _header_params = dict(_params.get("_headers", {})) - # process the form parameters - _form_params = [] - _files = {} - if _params["file"]: - _files["file"] = _params["file"] - - if _params["relative_path"]: - _form_params.append(("relative_path", _params["relative_path"])) - - # process the body parameter - _body_params = None - # set the HTTP header `Accept` - _header_params["Accept"] = self.api_client.select_header_accept( - ["application/json"] - ) # noqa: E501 - - # set the HTTP header `Content-Type` - _content_types_list = _params.get( - "_content_type", - self.api_client.select_header_content_type(["multipart/form-data"]), - ) - if _content_types_list: - _header_params["Content-Type"] = _content_types_list - - # authentication setting - _auth_settings = [] # noqa: E501 - - _response_types_map = { - "200": "Artifact", - } - - return self.api_client.call_api( - "/agent/tasks/{task_id}/artifacts", - "POST", - _path_params, - _query_params, - _header_params, - body=_body_params, - post_params=_form_params, - files=_files, - response_types_map=_response_types_map, - auth_settings=_auth_settings, - async_req=_params.get("async_req"), - _return_http_data_only=_params.get("_return_http_data_only"), # noqa: E501 - _preload_content=_params.get("_preload_content", True), - _request_timeout=_params.get("_request_timeout"), - collection_formats=_collection_formats, - _request_auth=_params.get("_request_auth"), - ) diff --git a/benchmark/agbenchmark/agent_protocol_client/api_client.py b/benchmark/agbenchmark/agent_protocol_client/api_client.py deleted file mode 100644 index ce178a96b..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/api_client.py +++ /dev/null @@ -1,838 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -import atexit -import datetime -import json -import mimetypes -import os -import re -import tempfile -from multiprocessing.pool import ThreadPool -from urllib.parse import quote - -from dateutil.parser import parse - -import agbenchmark.agent_protocol_client.models -from agbenchmark.agent_protocol_client import rest -from agbenchmark.agent_protocol_client.api_response import ApiResponse -from agbenchmark.agent_protocol_client.configuration import Configuration -from agbenchmark.agent_protocol_client.exceptions import ApiException, ApiValueError - - -class ApiClient(object): - """Generic API client for OpenAPI client library builds. - - OpenAPI generic API client. This client handles the client- - server communication, and is invariant across implementations. Specifics of - the methods and models for each application are generated from the OpenAPI - templates. - - :param configuration: .Configuration object for this client - :param header_name: a header to pass when making calls to the API. - :param header_value: a header value to pass when making calls to - the API. - :param cookie: a cookie to include in the header when making calls - to the API - :param pool_threads: The number of threads to use for async requests - to the API. More threads means more concurrent API requests. - """ - - PRIMITIVE_TYPES = (float, bool, bytes, str, int) - NATIVE_TYPES_MAPPING = { - "int": int, - "long": int, # TODO remove as only py3 is supported? - "float": float, - "str": str, - "bool": bool, - "date": datetime.date, - "datetime": datetime.datetime, - "object": object, - } - _pool = None - - def __init__( - self, - configuration=None, - header_name=None, - header_value=None, - cookie=None, - pool_threads=1, - ): - # use default configuration if none is provided - if configuration is None: - configuration = Configuration.get_default() - self.configuration = configuration - self.pool_threads = pool_threads - - self.rest_client = rest.RESTClientObject(configuration) - self.default_headers = {} - if header_name is not None: - self.default_headers[header_name] = header_value - self.cookie = cookie - # Set default User-Agent. - self.user_agent = "OpenAPI-Generator/1.0.0/python" - self.client_side_validation = configuration.client_side_validation - - async def __aenter__(self): - return self - - async def __aexit__(self, exc_type, exc_value, traceback): - await self.close() - - async def close(self): - await self.rest_client.close() - if self._pool: - self._pool.close() - self._pool.join() - self._pool = None - if hasattr(atexit, "unregister"): - atexit.unregister(self.close) - - @property - def pool(self): - """Create thread pool on first request - avoids instantiating unused threadpool for blocking clients. - """ - if self._pool is None: - atexit.register(self.close) - self._pool = ThreadPool(self.pool_threads) - return self._pool - - @property - def user_agent(self): - """User agent for this API client""" - return self.default_headers["User-Agent"] - - @user_agent.setter - def user_agent(self, value): - self.default_headers["User-Agent"] = value - - def set_default_header(self, header_name, header_value): - self.default_headers[header_name] = header_value - - _default = None - - @classmethod - def get_default(cls): - """Return new instance of ApiClient. - - This method returns newly created, based on default constructor, - object of ApiClient class or returns a copy of default - ApiClient. - - :return: The ApiClient object. - """ - if cls._default is None: - cls._default = ApiClient() - return cls._default - - @classmethod - def set_default(cls, default): - """Set default instance of ApiClient. - - It stores default ApiClient. - - :param default: object of ApiClient. - """ - cls._default = default - - async def __call_api( - self, - resource_path, - method, - path_params=None, - query_params=None, - header_params=None, - body=None, - post_params=None, - files=None, - response_types_map=None, - auth_settings=None, - _return_http_data_only=None, - collection_formats=None, - _preload_content=True, - _request_timeout=None, - _host=None, - _request_auth=None, - ): - config = self.configuration - - # header parameters - header_params = header_params or {} - header_params.update(self.default_headers) - if self.cookie: - header_params["Cookie"] = self.cookie - if header_params: - header_params = self.sanitize_for_serialization(header_params) - header_params = dict( - self.parameters_to_tuples(header_params, collection_formats) - ) - - # path parameters - if path_params: - path_params = self.sanitize_for_serialization(path_params) - path_params = self.parameters_to_tuples(path_params, collection_formats) - for k, v in path_params: - # specified safe chars, encode everything - resource_path = resource_path.replace( - "{%s}" % k, quote(str(v), safe=config.safe_chars_for_path_param) - ) - - # post parameters - if post_params or files: - post_params = post_params if post_params else [] - post_params = self.sanitize_for_serialization(post_params) - post_params = self.parameters_to_tuples(post_params, collection_formats) - post_params.extend(self.files_parameters(files)) - - # auth setting - self.update_params_for_auth( - header_params, - query_params, - auth_settings, - resource_path, - method, - body, - request_auth=_request_auth, - ) - - # body - if body: - body = self.sanitize_for_serialization(body) - - # request url - if _host is None: - url = self.configuration.host + resource_path - else: - # use server/host defined in path or operation instead - url = _host + resource_path - - # query parameters - if query_params: - query_params = self.sanitize_for_serialization(query_params) - url_query = self.parameters_to_url_query(query_params, collection_formats) - url += "?" + url_query - - try: - # perform request and return response - response_data = await self.request( - method, - url, - query_params=query_params, - headers=header_params, - post_params=post_params, - body=body, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - ) - except ApiException as e: - if e.body: - e.body = e.body.decode("utf-8") - raise e - - self.last_response = response_data - - return_data = None # assuming derialization is not needed - # data needs deserialization or returns HTTP data (deserialized) only - if _preload_content or _return_http_data_only: - response_type = response_types_map.get(str(response_data.status), None) - - if response_type == "bytearray": - response_data.data = response_data.data - else: - match = None - content_type = response_data.getheader("content-type") - if content_type is not None: - match = re.search(r"charset=([a-zA-Z\-\d]+)[\s;]?", content_type) - encoding = match.group(1) if match else "utf-8" - response_data.data = response_data.data.decode(encoding) - - # deserialize response data - if response_type == "bytearray": - return_data = response_data.data - elif response_type: - return_data = self.deserialize(response_data, response_type) - else: - return_data = None - - if _return_http_data_only: - return return_data - else: - return ApiResponse( - status_code=response_data.status, - data=return_data, - headers=response_data.getheaders(), - raw_data=response_data.data, - ) - - def sanitize_for_serialization(self, obj): - """Builds a JSON POST object. - - If obj is None, return None. - If obj is str, int, long, float, bool, return directly. - If obj is datetime.datetime, datetime.date - convert to string in iso8601 format. - If obj is list, sanitize each element in the list. - If obj is dict, return the dict. - If obj is OpenAPI model, return the properties dict. - - :param obj: The data to serialize. - :return: The serialized form of data. - """ - if obj is None: - return None - elif isinstance(obj, self.PRIMITIVE_TYPES): - return obj - elif isinstance(obj, list): - return [self.sanitize_for_serialization(sub_obj) for sub_obj in obj] - elif isinstance(obj, tuple): - return tuple(self.sanitize_for_serialization(sub_obj) for sub_obj in obj) - elif isinstance(obj, (datetime.datetime, datetime.date)): - return obj.isoformat() - - if isinstance(obj, dict): - obj_dict = obj - else: - # Convert model obj to dict except - # attributes `openapi_types`, `attribute_map` - # and attributes which value is not None. - # Convert attribute name to json key in - # model definition for request. - obj_dict = obj.to_dict() - - return { - key: self.sanitize_for_serialization(val) for key, val in obj_dict.items() - } - - def deserialize(self, response, response_type): - """Deserializes response into an object. - - :param response: RESTResponse object to be deserialized. - :param response_type: class literal for - deserialized object, or string of class name. - - :return: deserialized object. - """ - # handle file downloading - # save response body into a tmp file and return the instance - if response_type == "file": - return self.__deserialize_file(response) - - # fetch data from response object - try: - data = json.loads(response.data) - except ValueError: - data = response.data - - return self.__deserialize(data, response_type) - - def __deserialize(self, data, klass): - """Deserializes dict, list, str into an object. - - :param data: dict, list or str. - :param klass: class literal, or string of class name. - - :return: object. - """ - if data is None: - return None - - if type(klass) == str: - if klass.startswith("List["): - sub_kls = re.match(r"List\[(.*)]", klass).group(1) - return [self.__deserialize(sub_data, sub_kls) for sub_data in data] - - if klass.startswith("Dict["): - sub_kls = re.match(r"Dict\[([^,]*), (.*)]", klass).group(2) - return {k: self.__deserialize(v, sub_kls) for k, v in data.items()} - - # convert str to class - if klass in self.NATIVE_TYPES_MAPPING: - klass = self.NATIVE_TYPES_MAPPING[klass] - else: - klass = getattr(agbenchmark.agent_protocol_client.models, klass) - - if klass in self.PRIMITIVE_TYPES: - return self.__deserialize_primitive(data, klass) - elif klass == object: - return self.__deserialize_object(data) - elif klass == datetime.date: - return self.__deserialize_date(data) - elif klass == datetime.datetime: - return self.__deserialize_datetime(data) - else: - return self.__deserialize_model(data, klass) - - def call_api( - self, - resource_path, - method, - path_params=None, - query_params=None, - header_params=None, - body=None, - post_params=None, - files=None, - response_types_map=None, - auth_settings=None, - async_req=None, - _return_http_data_only=None, - collection_formats=None, - _preload_content=True, - _request_timeout=None, - _host=None, - _request_auth=None, - ): - """Makes the HTTP request (synchronous) and returns deserialized data. - - To make an async_req request, set the async_req parameter. - - :param resource_path: Path to method endpoint. - :param method: Method to call. - :param path_params: Path parameters in the url. - :param query_params: Query parameters in the url. - :param header_params: Header parameters to be - placed in the request header. - :param body: Request body. - :param post_params dict: Request post form parameters, - for `application/x-www-form-urlencoded`, `multipart/form-data`. - :param auth_settings list: Auth Settings names for the request. - :param response: Response data type. - :param files dict: key -> filename, value -> filepath, - for `multipart/form-data`. - :param async_req bool: execute request asynchronously - :param _return_http_data_only: response data instead of ApiResponse - object with status code, headers, etc - :param _preload_content: if False, the ApiResponse.data will - be set to none and raw_data will store the - HTTP response body without reading/decoding. - Default is True. - :param collection_formats: dict of collection formats for path, query, - header, and post parameters. - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - :param _request_auth: set to override the auth_settings for an a single - request; this effectively ignores the authentication - in the spec for a single request. - :type _request_token: dict, optional - :return: - If async_req parameter is True, - the request will be called asynchronously. - The method will return the request thread. - If parameter async_req is False or missing, - then the method will return the response directly. - """ - if not async_req: - return self.__call_api( - resource_path, - method, - path_params, - query_params, - header_params, - body, - post_params, - files, - response_types_map, - auth_settings, - _return_http_data_only, - collection_formats, - _preload_content, - _request_timeout, - _host, - _request_auth, - ) - - return self.pool.apply_async( - self.__call_api, - ( - resource_path, - method, - path_params, - query_params, - header_params, - body, - post_params, - files, - response_types_map, - auth_settings, - _return_http_data_only, - collection_formats, - _preload_content, - _request_timeout, - _host, - _request_auth, - ), - ) - - def request( - self, - method, - url, - query_params=None, - headers=None, - post_params=None, - body=None, - _preload_content=True, - _request_timeout=None, - ): - """Makes the HTTP request using RESTClient.""" - if method == "GET": - return self.rest_client.get_request( - url, - query_params=query_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - headers=headers, - ) - elif method == "HEAD": - return self.rest_client.head_request( - url, - query_params=query_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - headers=headers, - ) - elif method == "OPTIONS": - return self.rest_client.options_request( - url, - query_params=query_params, - headers=headers, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - ) - elif method == "POST": - return self.rest_client.post_request( - url, - query_params=query_params, - headers=headers, - post_params=post_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - body=body, - ) - elif method == "PUT": - return self.rest_client.put_request( - url, - query_params=query_params, - headers=headers, - post_params=post_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - body=body, - ) - elif method == "PATCH": - return self.rest_client.patch_request( - url, - query_params=query_params, - headers=headers, - post_params=post_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - body=body, - ) - elif method == "DELETE": - return self.rest_client.delete_request( - url, - query_params=query_params, - headers=headers, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - body=body, - ) - else: - raise ApiValueError( - "http method must be `GET`, `HEAD`, `OPTIONS`," - " `POST`, `PATCH`, `PUT` or `DELETE`." - ) - - def parameters_to_tuples(self, params, collection_formats): - """Get parameters as list of tuples, formatting collections. - - :param params: Parameters as dict or list of two-tuples - :param dict collection_formats: Parameter collection formats - :return: Parameters as list of tuples, collections formatted - """ - new_params = [] - if collection_formats is None: - collection_formats = {} - for k, v in ( - params.items() if isinstance(params, dict) else params - ): # noqa: E501 - if k in collection_formats: - collection_format = collection_formats[k] - if collection_format == "multi": - new_params.extend((k, value) for value in v) - else: - if collection_format == "ssv": - delimiter = " " - elif collection_format == "tsv": - delimiter = "\t" - elif collection_format == "pipes": - delimiter = "|" - else: # csv is the default - delimiter = "," - new_params.append((k, delimiter.join(str(value) for value in v))) - else: - new_params.append((k, v)) - return new_params - - def parameters_to_url_query(self, params, collection_formats): - """Get parameters as list of tuples, formatting collections. - - :param params: Parameters as dict or list of two-tuples - :param dict collection_formats: Parameter collection formats - :return: URL query string (e.g. a=Hello%20World&b=123) - """ - new_params = [] - if collection_formats is None: - collection_formats = {} - for k, v in ( - params.items() if isinstance(params, dict) else params - ): # noqa: E501 - if isinstance(v, (int, float)): - v = str(v) - if isinstance(v, bool): - v = str(v).lower() - if isinstance(v, dict): - v = json.dumps(v) - - if k in collection_formats: - collection_format = collection_formats[k] - if collection_format == "multi": - new_params.extend((k, value) for value in v) - else: - if collection_format == "ssv": - delimiter = " " - elif collection_format == "tsv": - delimiter = "\t" - elif collection_format == "pipes": - delimiter = "|" - else: # csv is the default - delimiter = "," - new_params.append( - (k, delimiter.join(quote(str(value)) for value in v)) - ) - else: - new_params.append((k, quote(str(v)))) - - return "&".join(["=".join(item) for item in new_params]) - - def files_parameters(self, files=None): - """Builds form parameters. - - :param files: File parameters. - :return: Form parameters with files. - """ - params = [] - - if files: - for k, v in files.items(): - if not v: - continue - file_names = v if type(v) is list else [v] - for n in file_names: - with open(n, "rb") as f: - filename = os.path.basename(f.name) - filedata = f.read() - mimetype = ( - mimetypes.guess_type(filename)[0] - or "application/octet-stream" - ) - params.append(tuple([k, tuple([filename, filedata, mimetype])])) - - return params - - def select_header_accept(self, accepts): - """Returns `Accept` based on an array of accepts provided. - - :param accepts: List of headers. - :return: Accept (e.g. application/json). - """ - if not accepts: - return - - for accept in accepts: - if re.search("json", accept, re.IGNORECASE): - return accept - - return accepts[0] - - def select_header_content_type(self, content_types): - """Returns `Content-Type` based on an array of content_types provided. - - :param content_types: List of content-types. - :return: Content-Type (e.g. application/json). - """ - if not content_types: - return None - - for content_type in content_types: - if re.search("json", content_type, re.IGNORECASE): - return content_type - - return content_types[0] - - def update_params_for_auth( - self, - headers, - queries, - auth_settings, - resource_path, - method, - body, - request_auth=None, - ): - """Updates header and query params based on authentication setting. - - :param headers: Header parameters dict to be updated. - :param queries: Query parameters tuple list to be updated. - :param auth_settings: Authentication setting identifiers list. - :resource_path: A string representation of the HTTP request resource path. - :method: A string representation of the HTTP request method. - :body: A object representing the body of the HTTP request. - The object type is the return value of sanitize_for_serialization(). - :param request_auth: if set, the provided settings will - override the token in the configuration. - """ - if not auth_settings: - return - - if request_auth: - self._apply_auth_params( - headers, queries, resource_path, method, body, request_auth - ) - return - - for auth in auth_settings: - auth_setting = self.configuration.auth_settings().get(auth) - if auth_setting: - self._apply_auth_params( - headers, queries, resource_path, method, body, auth_setting - ) - - def _apply_auth_params( - self, headers, queries, resource_path, method, body, auth_setting - ): - """Updates the request parameters based on a single auth_setting - - :param headers: Header parameters dict to be updated. - :param queries: Query parameters tuple list to be updated. - :resource_path: A string representation of the HTTP request resource path. - :method: A string representation of the HTTP request method. - :body: A object representing the body of the HTTP request. - The object type is the return value of sanitize_for_serialization(). - :param auth_setting: auth settings for the endpoint - """ - if auth_setting["in"] == "cookie": - headers["Cookie"] = auth_setting["value"] - elif auth_setting["in"] == "header": - if auth_setting["type"] != "http-signature": - headers[auth_setting["key"]] = auth_setting["value"] - elif auth_setting["in"] == "query": - queries.append((auth_setting["key"], auth_setting["value"])) - else: - raise ApiValueError("Authentication token must be in `query` or `header`") - - def __deserialize_file(self, response): - """Deserializes body to file - - Saves response body into a file in a temporary folder, - using the filename from the `Content-Disposition` header if provided. - - :param response: RESTResponse. - :return: file path. - """ - fd, path = tempfile.mkstemp(dir=self.configuration.temp_folder_path) - os.close(fd) - os.remove(path) - - content_disposition = response.getheader("Content-Disposition") - if content_disposition: - filename = re.search( - r'filename=[\'"]?([^\'"\s]+)[\'"]?', content_disposition - ).group(1) - path = os.path.join(os.path.dirname(path), filename) - - with open(path, "wb") as f: - f.write(response.data) - - return path - - def __deserialize_primitive(self, data, klass): - """Deserializes string to primitive type. - - :param data: str. - :param klass: class literal. - - :return: int, long, float, str, bool. - """ - try: - return klass(data) - except UnicodeEncodeError: - return str(data) - except TypeError: - return data - - def __deserialize_object(self, value): - """Return an original value. - - :return: object. - """ - return value - - def __deserialize_date(self, string): - """Deserializes string to date. - - :param string: str. - :return: date. - """ - try: - return parse(string).date() - except ImportError: - return string - except ValueError: - raise rest.ApiException( - status=0, reason="Failed to parse `{0}` as date object".format(string) - ) - - def __deserialize_datetime(self, string): - """Deserializes string to datetime. - - The string should be in iso8601 datetime format. - - :param string: str. - :return: datetime. - """ - try: - return parse(string) - except ImportError: - return string - except ValueError: - raise rest.ApiException( - status=0, - reason=("Failed to parse `{0}` as datetime object".format(string)), - ) - - def __deserialize_model(self, data, klass): - """Deserializes list or dict to model. - - :param data: dict, list. - :param klass: class literal. - :return: model object. - """ - - return klass.from_dict(data) diff --git a/benchmark/agbenchmark/agent_protocol_client/api_response.py b/benchmark/agbenchmark/agent_protocol_client/api_response.py deleted file mode 100644 index d1fdefc1e..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/api_response.py +++ /dev/null @@ -1,28 +0,0 @@ -"""API response object.""" - -from __future__ import annotations - -from typing import Any, Dict, Optional - -from pydantic import Field, StrictInt, StrictStr - - -class ApiResponse: - """ - API response object - """ - - status_code: Optional[StrictInt] = Field(None, description="HTTP status code") - headers: Optional[Dict[StrictStr, StrictStr]] = Field( - None, description="HTTP headers" - ) - data: Optional[Any] = Field( - None, description="Deserialized data given the data type" - ) - raw_data: Optional[Any] = Field(None, description="Raw data (HTTP response body)") - - def __init__(self, status_code=None, headers=None, data=None, raw_data=None): - self.status_code = status_code - self.headers = headers - self.data = data - self.raw_data = raw_data diff --git a/benchmark/agbenchmark/agent_protocol_client/configuration.py b/benchmark/agbenchmark/agent_protocol_client/configuration.py deleted file mode 100644 index 8bbcec716..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/configuration.py +++ /dev/null @@ -1,447 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -import copy -import http.client as httplib -import logging -import sys - -import urllib3 - -JSON_SCHEMA_VALIDATION_KEYWORDS = { - "multipleOf", - "maximum", - "exclusiveMaximum", - "minimum", - "exclusiveMinimum", - "maxLength", - "minLength", - "pattern", - "maxItems", - "minItems", -} - - -class Configuration(object): - """This class contains various settings of the API client. - - :param host: Base url. - :param api_key: Dict to store API key(s). - Each entry in the dict specifies an API key. - The dict key is the name of the security scheme in the OAS specification. - The dict value is the API key secret. - :param api_key_prefix: Dict to store API prefix (e.g. Bearer). - The dict key is the name of the security scheme in the OAS specification. - The dict value is an API key prefix when generating the auth data. - :param username: Username for HTTP basic authentication. - :param password: Password for HTTP basic authentication. - :param access_token: Access token. - :param server_index: Index to servers configuration. - :param server_variables: Mapping with string values to replace variables in - templated server configuration. The validation of enums is performed for - variables with defined enum values before. - :param server_operation_index: Mapping from operation ID to an index to server - configuration. - :param server_operation_variables: Mapping from operation ID to a mapping with - string values to replace variables in templated server configuration. - The validation of enums is performed for variables with defined enum values before. - :param ssl_ca_cert: str - the path to a file of concatenated CA certificates - in PEM format. - - """ - - _default = None - - def __init__( - self, - host=None, - api_key=None, - api_key_prefix=None, - username=None, - password=None, - access_token=None, - server_index=None, - server_variables=None, - server_operation_index=None, - server_operation_variables=None, - ssl_ca_cert=None, - ): - """Constructor""" - self._base_path = "http://localhost" if host is None else host - """Default Base url - """ - self.server_index = 0 if server_index is None and host is None else server_index - self.server_operation_index = server_operation_index or {} - """Default server index - """ - self.server_variables = server_variables or {} - self.server_operation_variables = server_operation_variables or {} - """Default server variables - """ - self.temp_folder_path = None - """Temp file folder for downloading files - """ - # Authentication Settings - self.api_key = {} - if api_key: - self.api_key = api_key - """dict to store API key(s) - """ - self.api_key_prefix = {} - if api_key_prefix: - self.api_key_prefix = api_key_prefix - """dict to store API prefix (e.g. Bearer) - """ - self.refresh_api_key_hook = None - """function hook to refresh API key if expired - """ - self.username = username - """Username for HTTP basic authentication - """ - self.password = password - """Password for HTTP basic authentication - """ - self.access_token = access_token - """Access token - """ - self.logger = {} - """Logging Settings - """ - self.logger["package_logger"] = logging.getLogger("agent_protocol_client") - self.logger["urllib3_logger"] = logging.getLogger("urllib3") - self.logger_format = "%(asctime)s %(levelname)s %(message)s" - """Log format - """ - self.logger_stream_handler = None - """Log stream handler - """ - self.logger_file_handler = None - """Log file handler - """ - self.logger_file = None - """Debug file location - """ - self.debug = False - """Debug switch - """ - - self.verify_ssl = True - """SSL/TLS verification - Set this to false to skip verifying SSL certificate when calling API - from https server. - """ - self.ssl_ca_cert = ssl_ca_cert - """Set this to customize the certificate file to verify the peer. - """ - self.cert_file = None - """client certificate file - """ - self.key_file = None - """client key file - """ - self.assert_hostname = None - """Set this to True/False to enable/disable SSL hostname verification. - """ - self.tls_server_name = None - """SSL/TLS Server Name Indication (SNI) - Set this to the SNI value expected by the server. - """ - - self.connection_pool_maxsize = 100 - """This value is passed to the aiohttp to limit simultaneous connections. - Default values is 100, None means no-limit. - """ - - self.proxy = None - """Proxy URL - """ - self.proxy_headers = None - """Proxy headers - """ - self.safe_chars_for_path_param = "" - """Safe chars for path_param - """ - self.retries = None - """Adding retries to override urllib3 default value 3 - """ - # Enable client side validation - self.client_side_validation = True - - self.socket_options = None - """Options to pass down to the underlying urllib3 socket - """ - - self.datetime_format = "%Y-%m-%dT%H:%M:%S.%f%z" - """datetime format - """ - - self.date_format = "%Y-%m-%d" - """date format - """ - - def __deepcopy__(self, memo): - cls = self.__class__ - result = cls.__new__(cls) - memo[id(self)] = result - for k, v in self.__dict__.items(): - if k not in ("logger", "logger_file_handler"): - setattr(result, k, copy.deepcopy(v, memo)) - # shallow copy of loggers - result.logger = copy.copy(self.logger) - # use setters to configure loggers - result.logger_file = self.logger_file - result.debug = self.debug - return result - - def __setattr__(self, name, value): - object.__setattr__(self, name, value) - - @classmethod - def set_default(cls, default): - """Set default instance of configuration. - - It stores default configuration, which can be - returned by get_default_copy method. - - :param default: object of Configuration - """ - cls._default = default - - @classmethod - def get_default_copy(cls): - """Deprecated. Please use `get_default` instead. - - Deprecated. Please use `get_default` instead. - - :return: The configuration object. - """ - return cls.get_default() - - @classmethod - def get_default(cls): - """Return the default configuration. - - This method returns newly created, based on default constructor, - object of Configuration class or returns a copy of default - configuration. - - :return: The configuration object. - """ - if cls._default is None: - cls._default = Configuration() - return cls._default - - @property - def logger_file(self): - """The logger file. - - If the logger_file is None, then add stream handler and remove file - handler. Otherwise, add file handler and remove stream handler. - - :param value: The logger_file path. - :type: str - """ - return self.__logger_file - - @logger_file.setter - def logger_file(self, value): - """The logger file. - - If the logger_file is None, then add stream handler and remove file - handler. Otherwise, add file handler and remove stream handler. - - :param value: The logger_file path. - :type: str - """ - self.__logger_file = value - if self.__logger_file: - # If set logging file, - # then add file handler and remove stream handler. - self.logger_file_handler = logging.FileHandler(self.__logger_file) - self.logger_file_handler.setFormatter(self.logger_formatter) - for _, logger in self.logger.items(): - logger.addHandler(self.logger_file_handler) - - @property - def debug(self): - """Debug status - - :param value: The debug status, True or False. - :type: bool - """ - return self.__debug - - @debug.setter - def debug(self, value): - """Debug status - - :param value: The debug status, True or False. - :type: bool - """ - self.__debug = value - if self.__debug: - # if debug status is True, turn on debug logging - for _, logger in self.logger.items(): - logger.setLevel(logging.DEBUG) - # turn on httplib debug - httplib.HTTPConnection.debuglevel = 1 - else: - # if debug status is False, turn off debug logging, - # setting log level to default `logging.WARNING` - for _, logger in self.logger.items(): - logger.setLevel(logging.WARNING) - # turn off httplib debug - httplib.HTTPConnection.debuglevel = 0 - - @property - def logger_format(self): - """The logger format. - - The logger_formatter will be updated when sets logger_format. - - :param value: The format string. - :type: str - """ - return self.__logger_format - - @logger_format.setter - def logger_format(self, value): - """The logger format. - - The logger_formatter will be updated when sets logger_format. - - :param value: The format string. - :type: str - """ - self.__logger_format = value - self.logger_formatter = logging.Formatter(self.__logger_format) - - def get_api_key_with_prefix(self, identifier, alias=None): - """Gets API key (with prefix if set). - - :param identifier: The identifier of apiKey. - :param alias: The alternative identifier of apiKey. - :return: The token for api key authentication. - """ - if self.refresh_api_key_hook is not None: - self.refresh_api_key_hook(self) - key = self.api_key.get( - identifier, self.api_key.get(alias) if alias is not None else None - ) - if key: - prefix = self.api_key_prefix.get(identifier) - if prefix: - return "%s %s" % (prefix, key) - else: - return key - - def get_basic_auth_token(self): - """Gets HTTP basic authentication header (string). - - :return: The token for basic HTTP authentication. - """ - username = "" - if self.username is not None: - username = self.username - password = "" - if self.password is not None: - password = self.password - return urllib3.util.make_headers(basic_auth=username + ":" + password).get( - "authorization" - ) - - def auth_settings(self): - """Gets Auth Settings dict for api client. - - :return: The Auth Settings information dict. - """ - auth = {} - return auth - - def to_debug_report(self): - """Gets the essential information for debugging. - - :return: The report for debugging. - """ - return ( - "Python SDK Debug Report:\n" - "OS: {env}\n" - "Python Version: {pyversion}\n" - "Version of the API: v0.2\n" - "SDK Package Version: 1.0.0".format(env=sys.platform, pyversion=sys.version) - ) - - def get_host_settings(self): - """Gets an array of host settings - - :return: An array of host settings - """ - return [ - { - "url": "", - "description": "No description provided", - } - ] - - def get_host_from_settings(self, index, variables=None, servers=None): - """Gets host URL based on the index and variables - :param index: array index of the host settings - :param variables: hash of variable and the corresponding value - :param servers: an array of host settings or None - :return: URL based on host settings - """ - if index is None: - return self._base_path - - variables = {} if variables is None else variables - servers = self.get_host_settings() if servers is None else servers - - try: - server = servers[index] - except IndexError: - raise ValueError( - "Invalid index {0} when selecting the host settings. " - "Must be less than {1}".format(index, len(servers)) - ) - - url = server["url"] - - # go through variables and replace placeholders - for variable_name, variable in server.get("variables", {}).items(): - used_value = variables.get(variable_name, variable["default_value"]) - - if "enum_values" in variable and used_value not in variable["enum_values"]: - raise ValueError( - "The variable `{0}` in the host URL has invalid value " - "{1}. Must be {2}.".format( - variable_name, variables[variable_name], variable["enum_values"] - ) - ) - - url = url.replace("{" + variable_name + "}", used_value) - - return url - - @property - def host(self): - """Return generated host.""" - return self.get_host_from_settings( - self.server_index, variables=self.server_variables - ) - - @host.setter - def host(self, value): - """Fix base path.""" - self._base_path = value - self.server_index = None diff --git a/benchmark/agbenchmark/agent_protocol_client/docs/AgentApi.md b/benchmark/agbenchmark/agent_protocol_client/docs/AgentApi.md deleted file mode 100644 index 7f0be780c..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/docs/AgentApi.md +++ /dev/null @@ -1,615 +0,0 @@ -# agbenchmark.agent_protocol_client.AgentApi - -All URIs are relative to _http://localhost_ - -| Method | HTTP request | Description | -| ---------------------------------------------------------------------------- | ------------------------------------------------------ | ------------------------------------------------------------- | -| [**create_agent_task**](AgentApi.md#create_agent_task) | **POST** /agent/tasks | Creates a task for the agent. | -| [**download_agent_task_artifact**](AgentApi.md#download_agent_task_artifact) | **GET** /agent/tasks/{task_id}/artifacts/{artifact_id} | Download a specified artifact. | -| [**execute_agent_task_step**](AgentApi.md#execute_agent_task_step) | **POST** /agent/tasks/{task_id}/steps | Execute a step in the specified agent task. | -| [**get_agent_task**](AgentApi.md#get_agent_task) | **GET** /agent/tasks/{task_id} | Get details about a specified agent task. | -| [**get_agent_task_step**](AgentApi.md#get_agent_task_step) | **GET** /agent/tasks/{task_id}/steps/{step_id} | Get details about a specified task step. | -| [**list_agent_task_artifacts**](AgentApi.md#list_agent_task_artifacts) | **GET** /agent/tasks/{task_id}/artifacts | List all artifacts that have been created for the given task. | -| [**list_agent_task_steps**](AgentApi.md#list_agent_task_steps) | **GET** /agent/tasks/{task_id}/steps | List all steps for the specified task. | -| [**list_agent_tasks_ids**](AgentApi.md#list_agent_tasks_ids) | **GET** /agent/tasks | List all tasks that have been created for the agent. | -| [**upload_agent_task_artifacts**](AgentApi.md#upload_agent_task_artifacts) | **POST** /agent/tasks/{task_id}/artifacts | Upload an artifact for the specified task. | - -# **create_agent_task** - -> Task create_agent_task(task_request_body=task_request_body) - -Creates a task for the agent. - -### Example - -```python -import time -import os -import agent_protocol_client -from agbenchmark.agent_protocol_client.models.task import Task -from agbenchmark.agent_protocol_client.models.task_request_body import TaskRequestBody -from agbenchmark.agent_protocol_client.rest import ApiException -from pprint import pprint - -# Defining the host is optional and defaults to http://localhost -# See configuration.py for a list of all supported configuration parameters. -configuration = agbenchmark.agent_protocol_client.Configuration( - host = "http://localhost" -) - - -# Enter a context with an instance of the API client -async with agbenchmark.agent_protocol_client.ApiClient(configuration) as api_client: - # Create an instance of the API class - api_instance = agbenchmark.agent_protocol_client.AgentApi(api_client) - task_request_body = agbenchmark.agent_protocol_client.TaskRequestBody() # TaskRequestBody | (optional) - - try: - # Creates a task for the agent. - api_response = await api_instance.create_agent_task(task_request_body=task_request_body) - print("The response of AgentApi->create_agent_task:\n") - pprint(api_response) - except Exception as e: - print("Exception when calling AgentApi->create_agent_task: %s\n" % e) -``` - -### Parameters - -| Name | Type | Description | Notes | -| --------------------- | ----------------------------------------- | ----------- | ---------- | -| **task_request_body** | [**TaskRequestBody**](TaskRequestBody.md) | | [optional] | - -### Return type - -[**Task**](Task.md) - -### Authorization - -No authorization required - -### HTTP request headers - -- **Content-Type**: application/json -- **Accept**: application/json - -### HTTP response details - -| Status code | Description | Response headers | -| ----------- | ------------------------------------------ | ---------------- | -| **200** | A new agent task was successfully created. | - | -| **0** | Internal Server Error | - | - -[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md) - -# **download_agent_task_artifact** - -> bytearray download_agent_task_artifact(task_id, artifact_id) - -Download a specified artifact. - -### Example - -```python -import time -import os -import agent_protocol_client -from agbenchmark.agent_protocol_client.rest import ApiException -from pprint import pprint - -# Defining the host is optional and defaults to http://localhost -# See configuration.py for a list of all supported configuration parameters. -configuration = agbenchmark.agent_protocol_client.Configuration( - host = "http://localhost" -) - - -# Enter a context with an instance of the API client -async with agbenchmark.agent_protocol_client.ApiClient(configuration) as api_client: - # Create an instance of the API class - api_instance = agbenchmark.agent_protocol_client.AgentApi(api_client) - task_id = 'task_id_example' # str | ID of the task - artifact_id = 'artifact_id_example' # str | ID of the artifact - - try: - # Download a specified artifact. - api_response = await api_instance.download_agent_task_artifact(task_id, artifact_id) - print("The response of AgentApi->download_agent_task_artifact:\n") - pprint(api_response) - except Exception as e: - print("Exception when calling AgentApi->download_agent_task_artifact: %s\n" % e) -``` - -### Parameters - -| Name | Type | Description | Notes | -| --------------- | ------- | ------------------ | ----- | -| **task_id** | **str** | ID of the task | -| **artifact_id** | **str** | ID of the artifact | - -### Return type - -**bytearray** - -### Authorization - -No authorization required - -### HTTP request headers - -- **Content-Type**: Not defined -- **Accept**: application/octet-stream - -### HTTP response details - -| Status code | Description | Response headers | -| ----------- | ------------------------------------- | ---------------- | -| **200** | Returned the content of the artifact. | - | -| **0** | Internal Server Error | - | - -[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md) - -# **execute_agent_task_step** - -> Step execute_agent_task_step(task_id, step_request_body=step_request_body) - -Execute a step in the specified agent task. - -### Example - -```python -import time -import os -import agent_protocol_client -from agbenchmark.agent_protocol_client.models.step import Step -from agbenchmark.agent_protocol_client.models.step_request_body import StepRequestBody -from agbenchmark.agent_protocol_client.rest import ApiException -from pprint import pprint - -# Defining the host is optional and defaults to http://localhost -# See configuration.py for a list of all supported configuration parameters. -configuration = agbenchmark.agent_protocol_client.Configuration( - host = "http://localhost" -) - - -# Enter a context with an instance of the API client -async with agbenchmark.agent_protocol_client.ApiClient(configuration) as api_client: - # Create an instance of the API class - api_instance = agbenchmark.agent_protocol_client.AgentApi(api_client) - task_id = 'task_id_example' # str | ID of the task - step_request_body = agbenchmark.agent_protocol_client.StepRequestBody() # StepRequestBody | (optional) - - try: - # Execute a step in the specified agent task. - api_response = await api_instance.execute_agent_task_step(task_id, step_request_body=step_request_body) - print("The response of AgentApi->execute_agent_task_step:\n") - pprint(api_response) - except Exception as e: - print("Exception when calling AgentApi->execute_agent_task_step: %s\n" % e) -``` - -### Parameters - -| Name | Type | Description | Notes | -| --------------------- | ----------------------------------------- | -------------- | ---------- | -| **task_id** | **str** | ID of the task | -| **step_request_body** | [**StepRequestBody**](StepRequestBody.md) | | [optional] | - -### Return type - -[**Step**](Step.md) - -### Authorization - -No authorization required - -### HTTP request headers - -- **Content-Type**: application/json -- **Accept**: application/json - -### HTTP response details - -| Status code | Description | Response headers | -| ----------- | --------------------------------- | ---------------- | -| **200** | Executed step for the agent task. | - | -| **0** | Internal Server Error | - | - -[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md) - -# **get_agent_task** - -> Task get_agent_task(task_id) - -Get details about a specified agent task. - -### Example - -```python -import time -import os -import agent_protocol_client -from agbenchmark.agent_protocol_client.models.task import Task -from agbenchmark.agent_protocol_client.rest import ApiException -from pprint import pprint - -# Defining the host is optional and defaults to http://localhost -# See configuration.py for a list of all supported configuration parameters. -configuration = agbenchmark.agent_protocol_client.Configuration( - host = "http://localhost" -) - - -# Enter a context with an instance of the API client -async with agbenchmark.agent_protocol_client.ApiClient(configuration) as api_client: - # Create an instance of the API class - api_instance = agbenchmark.agent_protocol_client.AgentApi(api_client) - task_id = 'task_id_example' # str | ID of the task - - try: - # Get details about a specified agent task. - api_response = await api_instance.get_agent_task(task_id) - print("The response of AgentApi->get_agent_task:\n") - pprint(api_response) - except Exception as e: - print("Exception when calling AgentApi->get_agent_task: %s\n" % e) -``` - -### Parameters - -| Name | Type | Description | Notes | -| ----------- | ------- | -------------- | ----- | -| **task_id** | **str** | ID of the task | - -### Return type - -[**Task**](Task.md) - -### Authorization - -No authorization required - -### HTTP request headers - -- **Content-Type**: Not defined -- **Accept**: application/json - -### HTTP response details - -| Status code | Description | Response headers | -| ----------- | ------------------------------------- | ---------------- | -| **200** | Returned details about an agent task. | - | -| **0** | Internal Server Error | - | - -[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md) - -# **get_agent_task_step** - -> Step get_agent_task_step(task_id, step_id) - -Get details about a specified task step. - -### Example - -```python -import time -import os -import agent_protocol_client -from agbenchmark.agent_protocol_client.models.step import Step -from agbenchmark.agent_protocol_client.rest import ApiException -from pprint import pprint - -# Defining the host is optional and defaults to http://localhost -# See configuration.py for a list of all supported configuration parameters. -configuration = agbenchmark.agent_protocol_client.Configuration( - host = "http://localhost" -) - - -# Enter a context with an instance of the API client -async with agbenchmark.agent_protocol_client.ApiClient(configuration) as api_client: - # Create an instance of the API class - api_instance = agbenchmark.agent_protocol_client.AgentApi(api_client) - task_id = 'task_id_example' # str | ID of the task - step_id = 'step_id_example' # str | ID of the step - - try: - # Get details about a specified task step. - api_response = await api_instance.get_agent_task_step(task_id, step_id) - print("The response of AgentApi->get_agent_task_step:\n") - pprint(api_response) - except Exception as e: - print("Exception when calling AgentApi->get_agent_task_step: %s\n" % e) -``` - -### Parameters - -| Name | Type | Description | Notes | -| ----------- | ------- | -------------- | ----- | -| **task_id** | **str** | ID of the task | -| **step_id** | **str** | ID of the step | - -### Return type - -[**Step**](Step.md) - -### Authorization - -No authorization required - -### HTTP request headers - -- **Content-Type**: Not defined -- **Accept**: application/json - -### HTTP response details - -| Status code | Description | Response headers | -| ----------- | ------------------------------------------ | ---------------- | -| **200** | Returned details about an agent task step. | - | -| **0** | Internal Server Error | - | - -[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md) - -# **list_agent_task_artifacts** - -> List[Artifact] list_agent_task_artifacts(task_id) - -List all artifacts that have been created for the given task. - -### Example - -```python -import time -import os -import agent_protocol_client -from agbenchmark.agent_protocol_client.models.artifact import Artifact -from agbenchmark.agent_protocol_client.rest import ApiException -from pprint import pprint - -# Defining the host is optional and defaults to http://localhost -# See configuration.py for a list of all supported configuration parameters. -configuration = agbenchmark.agent_protocol_client.Configuration( - host = "http://localhost" -) - - -# Enter a context with an instance of the API client -async with agbenchmark.agent_protocol_client.ApiClient(configuration) as api_client: - # Create an instance of the API class - api_instance = agbenchmark.agent_protocol_client.AgentApi(api_client) - task_id = 'task_id_example' # str | ID of the task - - try: - # List all artifacts that have been created for the given task. - api_response = await api_instance.list_agent_task_artifacts(task_id) - print("The response of AgentApi->list_agent_task_artifacts:\n") - pprint(api_response) - except Exception as e: - print("Exception when calling AgentApi->list_agent_task_artifacts: %s\n" % e) -``` - -### Parameters - -| Name | Type | Description | Notes | -| ----------- | ------- | -------------- | ----- | -| **task_id** | **str** | ID of the task | - -### Return type - -[**List[Artifact]**](Artifact.md) - -### Authorization - -No authorization required - -### HTTP request headers - -- **Content-Type**: Not defined -- **Accept**: application/json - -### HTTP response details - -| Status code | Description | Response headers | -| ----------- | ------------------------------------- | ---------------- | -| **200** | Returned the content of the artifact. | - | -| **0** | Internal Server Error | - | - -[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md) - -# **list_agent_task_steps** - -> List[str] list_agent_task_steps(task_id) - -List all steps for the specified task. - -### Example - -```python -import time -import os -import agent_protocol_client -from agbenchmark.agent_protocol_client.rest import ApiException -from pprint import pprint - -# Defining the host is optional and defaults to http://localhost -# See configuration.py for a list of all supported configuration parameters. -configuration = agbenchmark.agent_protocol_client.Configuration( - host = "http://localhost" -) - - -# Enter a context with an instance of the API client -async with agbenchmark.agent_protocol_client.ApiClient(configuration) as api_client: - # Create an instance of the API class - api_instance = agbenchmark.agent_protocol_client.AgentApi(api_client) - task_id = 'task_id_example' # str | ID of the task - - try: - # List all steps for the specified task. - api_response = await api_instance.list_agent_task_steps(task_id) - print("The response of AgentApi->list_agent_task_steps:\n") - pprint(api_response) - except Exception as e: - print("Exception when calling AgentApi->list_agent_task_steps: %s\n" % e) -``` - -### Parameters - -| Name | Type | Description | Notes | -| ----------- | ------- | -------------- | ----- | -| **task_id** | **str** | ID of the task | - -### Return type - -**List[str]** - -### Authorization - -No authorization required - -### HTTP request headers - -- **Content-Type**: Not defined -- **Accept**: application/json - -### HTTP response details - -| Status code | Description | Response headers | -| ----------- | ------------------------------------------------------------- | ---------------- | -| **200** | Returned list of agent's step IDs for the specified task. | - | -| **0** | Internal Server Error | - | - -[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md) - -# **list_agent_tasks_ids** - -> List[str] list_agent_tasks_ids() - -List all tasks that have been created for the agent. - -### Example - -```python -import time -import os -import agent_protocol_client -from agbenchmark.agent_protocol_client.rest import ApiException -from pprint import pprint - -# Defining the host is optional and defaults to http://localhost -# See configuration.py for a list of all supported configuration parameters. -configuration = agbenchmark.agent_protocol_client.Configuration( - host = "http://localhost" -) - - -# Enter a context with an instance of the API client -async with agbenchmark.agent_protocol_client.ApiClient(configuration) as api_client: - # Create an instance of the API class - api_instance = agbenchmark.agent_protocol_client.AgentApi(api_client) - - try: - # List all tasks that have been created for the agent. - api_response = await api_instance.list_agent_tasks_ids() - print("The response of AgentApi->list_agent_tasks_ids:\n") - pprint(api_response) - except Exception as e: - print("Exception when calling AgentApi->list_agent_tasks_ids: %s\n" % e) -``` - -### Parameters - -This endpoint does not need any parameter. - -### Return type - -**List[str]** - -### Authorization - -No authorization required - -### HTTP request headers - -- **Content-Type**: Not defined -- **Accept**: application/json - -### HTTP response details - -| Status code | Description | Response headers | -| ----------- | -------------------------------------- | ---------------- | -| **200** | Returned list of agent's task IDs. | - | -| **0** | Internal Server Error | - | - -[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md) - -# **upload_agent_task_artifacts** - -> Artifact upload_agent_task_artifacts(task_id, file, relative_path=relative_path) - -Upload an artifact for the specified task. - -### Example - -```python -import time -import os -import agent_protocol_client -from agbenchmark.agent_protocol_client.models.artifact import Artifact -from agbenchmark.agent_protocol_client.rest import ApiException -from pprint import pprint - -# Defining the host is optional and defaults to http://localhost -# See configuration.py for a list of all supported configuration parameters. -configuration = agbenchmark.agent_protocol_client.Configuration( - host = "http://localhost" -) - - -# Enter a context with an instance of the API client -async with agbenchmark.agent_protocol_client.ApiClient(configuration) as api_client: - # Create an instance of the API class - api_instance = agbenchmark.agent_protocol_client.AgentApi(api_client) - task_id = 'task_id_example' # str | ID of the task - file = None # bytearray | File to upload. - relative_path = 'relative_path_example' # str | Relative path of the artifact in the agent's workspace. (optional) - - try: - # Upload an artifact for the specified task. - api_response = await api_instance.upload_agent_task_artifacts(task_id, file, relative_path=relative_path) - print("The response of AgentApi->upload_agent_task_artifacts:\n") - pprint(api_response) - except Exception as e: - print("Exception when calling AgentApi->upload_agent_task_artifacts: %s\n" % e) -``` - -### Parameters - -| Name | Type | Description | Notes | -| ----------------- | ------------- | ----------------------------------------------------------- | ---------- | -| **task_id** | **str** | ID of the task | -| **file** | **bytearray** | File to upload. | -| **relative_path** | **str** | Relative path of the artifact in the agent's workspace. | [optional] | - -### Return type - -[**Artifact**](Artifact.md) - -### Authorization - -No authorization required - -### HTTP request headers - -- **Content-Type**: multipart/form-data -- **Accept**: application/json - -### HTTP response details - -| Status code | Description | Response headers | -| ----------- | ------------------------------------- | ---------------- | -| **200** | Returned the content of the artifact. | - | -| **0** | Internal Server Error | - | - -[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md) diff --git a/benchmark/agbenchmark/agent_protocol_client/exceptions.py b/benchmark/agbenchmark/agent_protocol_client/exceptions.py deleted file mode 100644 index bd26eac3c..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/exceptions.py +++ /dev/null @@ -1,154 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -class OpenApiException(Exception): - """The base exception class for all OpenAPIExceptions""" - - -class ApiTypeError(OpenApiException, TypeError): - def __init__(self, msg, path_to_item=None, valid_classes=None, key_type=None): - """Raises an exception for TypeErrors - - Args: - msg (str): the exception message - - Keyword Args: - path_to_item (list): a list of keys an indices to get to the - current_item - None if unset - valid_classes (tuple): the primitive classes that current item - should be an instance of - None if unset - key_type (bool): False if our value is a value in a dict - True if it is a key in a dict - False if our item is an item in a list - None if unset - """ - self.path_to_item = path_to_item - self.valid_classes = valid_classes - self.key_type = key_type - full_msg = msg - if path_to_item: - full_msg = "{0} at {1}".format(msg, render_path(path_to_item)) - super(ApiTypeError, self).__init__(full_msg) - - -class ApiValueError(OpenApiException, ValueError): - def __init__(self, msg, path_to_item=None): - """ - Args: - msg (str): the exception message - - Keyword Args: - path_to_item (list) the path to the exception in the - received_data dict. None if unset - """ - - self.path_to_item = path_to_item - full_msg = msg - if path_to_item: - full_msg = "{0} at {1}".format(msg, render_path(path_to_item)) - super(ApiValueError, self).__init__(full_msg) - - -class ApiAttributeError(OpenApiException, AttributeError): - def __init__(self, msg, path_to_item=None): - """ - Raised when an attribute reference or assignment fails. - - Args: - msg (str): the exception message - - Keyword Args: - path_to_item (None/list) the path to the exception in the - received_data dict - """ - self.path_to_item = path_to_item - full_msg = msg - if path_to_item: - full_msg = "{0} at {1}".format(msg, render_path(path_to_item)) - super(ApiAttributeError, self).__init__(full_msg) - - -class ApiKeyError(OpenApiException, KeyError): - def __init__(self, msg, path_to_item=None): - """ - Args: - msg (str): the exception message - - Keyword Args: - path_to_item (None/list) the path to the exception in the - received_data dict - """ - self.path_to_item = path_to_item - full_msg = msg - if path_to_item: - full_msg = "{0} at {1}".format(msg, render_path(path_to_item)) - super(ApiKeyError, self).__init__(full_msg) - - -class ApiException(OpenApiException): - def __init__(self, status=None, reason=None, http_resp=None): - if http_resp: - self.status = http_resp.status - self.reason = http_resp.reason - self.body = http_resp.data - self.headers = http_resp.getheaders() - else: - self.status = status - self.reason = reason - self.body = None - self.headers = None - - def __str__(self): - """Custom error messages for exception""" - error_message = "({0})\n" "Reason: {1}\n".format(self.status, self.reason) - if self.headers: - error_message += "HTTP response headers: {0}\n".format(self.headers) - - if self.body: - error_message += "HTTP response body: {0}\n".format(self.body) - - return error_message - - -class NotFoundException(ApiException): - def __init__(self, status=None, reason=None, http_resp=None): - super(NotFoundException, self).__init__(status, reason, http_resp) - - -class UnauthorizedException(ApiException): - def __init__(self, status=None, reason=None, http_resp=None): - super(UnauthorizedException, self).__init__(status, reason, http_resp) - - -class ForbiddenException(ApiException): - def __init__(self, status=None, reason=None, http_resp=None): - super(ForbiddenException, self).__init__(status, reason, http_resp) - - -class ServiceException(ApiException): - def __init__(self, status=None, reason=None, http_resp=None): - super(ServiceException, self).__init__(status, reason, http_resp) - - -def render_path(path_to_item): - """Returns a string representation of a path""" - result = "" - for pth in path_to_item: - if isinstance(pth, int): - result += "[{0}]".format(pth) - else: - result += "['{0}']".format(pth) - return result diff --git a/benchmark/agbenchmark/agent_protocol_client/models/__init__.py b/benchmark/agbenchmark/agent_protocol_client/models/__init__.py deleted file mode 100644 index c7bd82dcd..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/__init__.py +++ /dev/null @@ -1,25 +0,0 @@ -# coding: utf-8 - -# flake8: noqa -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -# import models into model package -from agbenchmark.agent_protocol_client.models.artifact import Artifact -from agbenchmark.agent_protocol_client.models.artifacts import Artifacts -from agbenchmark.agent_protocol_client.models.pagination import Pagination -from agbenchmark.agent_protocol_client.models.step import Step -from agbenchmark.agent_protocol_client.models.step_all_of import StepAllOf -from agbenchmark.agent_protocol_client.models.step_request_body import StepRequestBody -from agbenchmark.agent_protocol_client.models.task import Task -from agbenchmark.agent_protocol_client.models.task_all_of import TaskAllOf -from agbenchmark.agent_protocol_client.models.task_request_body import TaskRequestBody diff --git a/benchmark/agbenchmark/agent_protocol_client/models/artifact.py b/benchmark/agbenchmark/agent_protocol_client/models/artifact.py deleted file mode 100644 index d2e7c101b..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/artifact.py +++ /dev/null @@ -1,72 +0,0 @@ -# coding: utf-8 - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 -from typing import Optional - -from pydantic import BaseModel, Field, StrictStr - - -class Artifact(BaseModel): - """ - Artifact that the task has produced. - """ - - artifact_id: StrictStr = Field(..., description="ID of the artifact.") - file_name: StrictStr = Field(..., description="Filename of the artifact.") - relative_path: Optional[StrictStr] = Field( - None, description="Relative path of the artifact in the agent's workspace." - ) - __properties = ["artifact_id", "file_name", "relative_path"] - created_at: StrictStr = Field(..., description="Creation date of the artifact.") - # modified_at: StrictStr = Field(..., description="Modification date of the artifact.") - agent_created: bool = Field(..., description="True if created by the agent") - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> Artifact: - """Create an instance of Artifact from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> Artifact: - """Create an instance of Artifact from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return Artifact.parse_obj(obj) - - _obj = Artifact.parse_obj( - { - "artifact_id": obj.get("artifact_id"), - "file_name": obj.get("file_name"), - "relative_path": obj.get("relative_path"), - "created_at": obj.get("created_at"), - "modified_at": obj.get("modified_at"), - "agent_created": obj.get("agent_created"), - } - ) - return _obj diff --git a/benchmark/agbenchmark/agent_protocol_client/models/artifacts.py b/benchmark/agbenchmark/agent_protocol_client/models/artifacts.py deleted file mode 100644 index 1d61a0558..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/artifacts.py +++ /dev/null @@ -1,77 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 - -from pydantic import BaseModel - -from agbenchmark.agent_protocol_client.models.artifact import Artifact -from agbenchmark.agent_protocol_client.models.pagination import Pagination - - -class Artifacts(BaseModel): - """ - Artifacts that the task has produced. - """ - - artifacts: list[Artifact] - pagination: Pagination - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> Artifacts: - """Create an instance of Artifacts from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> Artifacts: - """Create an instance of Artifacts from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return Artifacts.parse_obj(obj) - - _obj = Artifacts.parse_obj( - { - "artifacts": obj.get("artifacts"), - "pagination": obj.get("pagination"), - } - ) - return _obj - - -Artifacts.update_forward_refs() diff --git a/benchmark/agbenchmark/agent_protocol_client/models/pagination.py b/benchmark/agbenchmark/agent_protocol_client/models/pagination.py deleted file mode 100644 index 433de1f28..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/pagination.py +++ /dev/null @@ -1,75 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 - -from pydantic import BaseModel - - -class Pagination(BaseModel): - """ - Pagination that the task has produced. - """ - - total_items: int - total_pages: int - current_page: int - page_size: int - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> Pagination: - """Create an instance of Pagination from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> Pagination: - """Create an instance of Pagination from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return Pagination.parse_obj(obj) - - _obj = Pagination.parse_obj( - { - "total_items": obj.get("total_items"), - "total_pages": obj.get("total_pages"), - "current_page": obj.get("current_page"), - "page_size": obj.get("page_size"), - } - ) - return _obj diff --git a/benchmark/agbenchmark/agent_protocol_client/models/step.py b/benchmark/agbenchmark/agent_protocol_client/models/step.py deleted file mode 100644 index befef1abc..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/step.py +++ /dev/null @@ -1,146 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 -from typing import Any, Optional - -from pydantic import BaseModel, Field, StrictBool, StrictStr, conlist, validator - -from agbenchmark.agent_protocol_client.models.artifact import Artifact - - -class Step(BaseModel): - """ - Step - """ - - input: Optional[StrictStr] = Field(None, description="Input prompt for the step.") - additional_input: Optional[Any] = Field( - None, description="Input parameters for the task step. Any value is allowed." - ) - task_id: StrictStr = Field( - ..., description="The ID of the task this step belongs to." - ) - step_id: StrictStr = Field(..., description="The ID of the task step.") - name: Optional[StrictStr] = Field(None, description="The name of the task step.") - status: StrictStr = Field(..., description="The status of the task step.") - output: Optional[StrictStr] = Field(None, description="Output of the task step.") - additional_output: Optional[Any] = Field( - None, - description="Output that the task step has produced. Any value is allowed.", - ) - artifacts: conlist(Artifact) = Field( - ..., description="A list of artifacts that the step has produced." - ) - is_last: Optional[StrictBool] = Field( - False, description="Whether this is the last step in the task." - ) - __properties = [ - "input", - "additional_input", - "task_id", - "step_id", - "name", - "status", - "output", - "additional_output", - "artifacts", - "is_last", - ] - - @validator("status") - def status_validate_enum(cls, value): - """Validates the enum""" - if value not in ("created", "completed"): - raise ValueError("must be one of enum values ('created', 'completed')") - return value - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> Step: - """Create an instance of Step from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - # override the default output from pydantic by calling `to_dict()` of each item in artifacts (list) - _items = [] - if self.artifacts: - for _item in self.artifacts: - if _item: - _items.append(_item.to_dict()) - _dict["artifacts"] = _items - # set to None if additional_input (nullable) is None - # and __fields_set__ contains the field - if self.additional_input is None and "additional_input" in self.__fields_set__: - _dict["additional_input"] = None - - # set to None if additional_output (nullable) is None - # and __fields_set__ contains the field - if ( - self.additional_output is None - and "additional_output" in self.__fields_set__ - ): - _dict["additional_output"] = None - - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> Step: - """Create an instance of Step from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return Step.parse_obj(obj) - - _obj = Step.parse_obj( - { - "input": obj.get("input"), - "additional_input": obj.get("additional_input"), - "task_id": obj.get("task_id"), - "step_id": obj.get("step_id"), - "name": obj.get("name"), - "status": obj.get("status"), - "output": obj.get("output"), - "additional_output": obj.get("additional_output"), - "artifacts": [ - Artifact.from_dict(_item) for _item in obj.get("artifacts") - ] - if obj.get("artifacts") is not None - else None, - "is_last": obj.get("is_last") - if obj.get("is_last") is not None - else False, - } - ) - return _obj diff --git a/benchmark/agbenchmark/agent_protocol_client/models/step_all_of.py b/benchmark/agbenchmark/agent_protocol_client/models/step_all_of.py deleted file mode 100644 index 8770f3b31..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/step_all_of.py +++ /dev/null @@ -1,133 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 -from typing import Any, Optional - -from pydantic import BaseModel, Field, StrictBool, StrictStr, conlist, validator - -from agbenchmark.agent_protocol_client.models.artifact import Artifact - - -class StepAllOf(BaseModel): - """ - StepAllOf - """ - - task_id: StrictStr = Field( - ..., description="The ID of the task this step belongs to." - ) - step_id: StrictStr = Field(..., description="The ID of the task step.") - name: Optional[StrictStr] = Field(None, description="The name of the task step.") - status: StrictStr = Field(..., description="The status of the task step.") - output: Optional[StrictStr] = Field(None, description="Output of the task step.") - additional_output: Optional[Any] = Field( - None, - description="Output that the task step has produced. Any value is allowed.", - ) - artifacts: conlist(Artifact) = Field( - ..., description="A list of artifacts that the step has produced." - ) - is_last: Optional[StrictBool] = Field( - False, description="Whether this is the last step in the task." - ) - __properties = [ - "task_id", - "step_id", - "name", - "status", - "output", - "additional_output", - "artifacts", - "is_last", - ] - - @validator("status") - def status_validate_enum(cls, value): - """Validates the enum""" - if value not in ("created", "completed"): - raise ValueError("must be one of enum values ('created', 'completed')") - return value - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> StepAllOf: - """Create an instance of StepAllOf from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - # override the default output from pydantic by calling `to_dict()` of each item in artifacts (list) - _items = [] - if self.artifacts: - for _item in self.artifacts: - if _item: - _items.append(_item.to_dict()) - _dict["artifacts"] = _items - # set to None if additional_output (nullable) is None - # and __fields_set__ contains the field - if ( - self.additional_output is None - and "additional_output" in self.__fields_set__ - ): - _dict["additional_output"] = None - - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> StepAllOf: - """Create an instance of StepAllOf from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return StepAllOf.parse_obj(obj) - - _obj = StepAllOf.parse_obj( - { - "task_id": obj.get("task_id"), - "step_id": obj.get("step_id"), - "name": obj.get("name"), - "status": obj.get("status"), - "output": obj.get("output"), - "additional_output": obj.get("additional_output"), - "artifacts": [ - Artifact.from_dict(_item) for _item in obj.get("artifacts") - ] - if obj.get("artifacts") is not None - else None, - "is_last": obj.get("is_last") - if obj.get("is_last") is not None - else False, - } - ) - return _obj diff --git a/benchmark/agbenchmark/agent_protocol_client/models/step_request_body.py b/benchmark/agbenchmark/agent_protocol_client/models/step_request_body.py deleted file mode 100644 index 47d642cfb..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/step_request_body.py +++ /dev/null @@ -1,77 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 -from typing import Any, Optional - -from pydantic import BaseModel, Field, StrictStr - - -class StepRequestBody(BaseModel): - """ - Body of the task request. - """ - - input: Optional[StrictStr] = Field(None, description="Input prompt for the step.") - additional_input: Optional[Any] = Field( - None, description="Input parameters for the task step. Any value is allowed." - ) - __properties = ["input", "additional_input"] - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> StepRequestBody: - """Create an instance of StepRequestBody from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - # set to None if additional_input (nullable) is None - # and __fields_set__ contains the field - if self.additional_input is None and "additional_input" in self.__fields_set__: - _dict["additional_input"] = None - - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> StepRequestBody: - """Create an instance of StepRequestBody from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return StepRequestBody.parse_obj(obj) - - _obj = StepRequestBody.parse_obj( - {"input": obj.get("input"), "additional_input": obj.get("additional_input")} - ) - return _obj diff --git a/benchmark/agbenchmark/agent_protocol_client/models/step_result.py b/benchmark/agbenchmark/agent_protocol_client/models/step_result.py deleted file mode 100644 index 99bf8f820..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/step_result.py +++ /dev/null @@ -1,89 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v1 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 -from typing import Any, Optional - -from pydantic import BaseModel, Field, StrictBool, conlist - - -class StepResult(BaseModel): - """ - Result of the task step. - """ - - output: Optional[Any] = Field( - None, - description="Output that the task step has produced. Any value is allowed.", - ) - artifacts: conlist(Any) = Field( - ..., description="A list of artifacts that the step has produced." - ) - is_last: Optional[StrictBool] = Field( - False, description="Whether this is the last step in the task." - ) - __properties = ["output", "artifacts", "is_last"] - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> StepResult: - """Create an instance of StepResult from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - # set to None if output (nullable) is None - # and __fields_set__ contains the field - if self.output is None and "output" in self.__fields_set__: - _dict["output"] = None - - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> StepResult: - """Create an instance of StepResult from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return StepResult.parse_obj(obj) - - _obj = StepResult.parse_obj( - { - "output": obj.get("output"), - "artifacts": obj.get("artifacts"), - "is_last": obj.get("is_last") - if obj.get("is_last") is not None - else False, - } - ) - return _obj diff --git a/benchmark/agbenchmark/agent_protocol_client/models/task.py b/benchmark/agbenchmark/agent_protocol_client/models/task.py deleted file mode 100644 index 90329f25f..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/task.py +++ /dev/null @@ -1,99 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 -from typing import Any, Optional - -from pydantic import BaseModel, Field, StrictStr, conlist - -from agbenchmark.agent_protocol_client.models.artifact import Artifact - - -class Task(BaseModel): - """ - Task - """ - - input: Optional[StrictStr] = Field(None, description="Input prompt for the task.") - additional_input: Optional[Any] = Field( - None, description="Input parameters for the task. Any value is allowed." - ) - task_id: StrictStr = Field(..., description="The ID of the task.") - artifacts: conlist(Artifact) = Field( - ..., description="A list of artifacts that the task has produced." - ) - __properties = ["input", "additional_input", "task_id", "artifacts"] - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> Task: - """Create an instance of Task from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - # override the default output from pydantic by calling `to_dict()` of each item in artifacts (list) - _items = [] - if self.artifacts: - for _item in self.artifacts: - if _item: - _items.append(_item.to_dict()) - _dict["artifacts"] = _items - # set to None if additional_input (nullable) is None - # and __fields_set__ contains the field - if self.additional_input is None and "additional_input" in self.__fields_set__: - _dict["additional_input"] = None - - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> Task: - """Create an instance of Task from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return Task.parse_obj(obj) - - _obj = Task.parse_obj( - { - "input": obj.get("input"), - "additional_input": obj.get("additional_input"), - "task_id": obj.get("task_id"), - "artifacts": [ - Artifact.from_dict(_item) for _item in obj.get("artifacts") - ] - if obj.get("artifacts") is not None - else None, - } - ) - return _obj diff --git a/benchmark/agbenchmark/agent_protocol_client/models/task_all_of.py b/benchmark/agbenchmark/agent_protocol_client/models/task_all_of.py deleted file mode 100644 index 710377de6..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/task_all_of.py +++ /dev/null @@ -1,87 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 - -from pydantic import BaseModel, Field, StrictStr, conlist - -from agbenchmark.agent_protocol_client.models.artifact import Artifact - - -class TaskAllOf(BaseModel): - """ - Definition of an agent task. - """ - - task_id: StrictStr = Field(..., description="The ID of the task.") - artifacts: conlist(Artifact) = Field( - ..., description="A list of artifacts that the task has produced." - ) - __properties = ["task_id", "artifacts"] - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> TaskAllOf: - """Create an instance of TaskAllOf from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - # override the default output from pydantic by calling `to_dict()` of each item in artifacts (list) - _items = [] - if self.artifacts: - for _item in self.artifacts: - if _item: - _items.append(_item.to_dict()) - _dict["artifacts"] = _items - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> TaskAllOf: - """Create an instance of TaskAllOf from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return TaskAllOf.parse_obj(obj) - - _obj = TaskAllOf.parse_obj( - { - "task_id": obj.get("task_id"), - "artifacts": [ - Artifact.from_dict(_item) for _item in obj.get("artifacts") - ] - if obj.get("artifacts") is not None - else None, - } - ) - return _obj diff --git a/benchmark/agbenchmark/agent_protocol_client/models/task_request_body.py b/benchmark/agbenchmark/agent_protocol_client/models/task_request_body.py deleted file mode 100644 index 40a5d4ecb..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/models/task_request_body.py +++ /dev/null @@ -1,77 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -from __future__ import annotations - -import json -import pprint -import re # noqa: F401 -from typing import Any, Optional - -from pydantic import BaseModel, Field, StrictStr - - -class TaskRequestBody(BaseModel): - """ - Body of the task request. - """ - - input: Optional[StrictStr] = Field(None, description="Input prompt for the task.") - additional_input: Optional[Any] = Field( - None, description="Input parameters for the task. Any value is allowed." - ) - __properties = ["input", "additional_input"] - - class Config: - """Pydantic configuration""" - - allow_population_by_field_name = True - validate_assignment = True - - def to_str(self) -> str: - """Returns the string representation of the model using alias""" - return pprint.pformat(self.dict(by_alias=True)) - - def to_json(self) -> str: - """Returns the JSON representation of the model using alias""" - return json.dumps(self.to_dict()) - - @classmethod - def from_json(cls, json_str: str) -> TaskRequestBody: - """Create an instance of TaskRequestBody from a JSON string""" - return cls.from_dict(json.loads(json_str)) - - def to_dict(self): - """Returns the dictionary representation of the model using alias""" - _dict = self.dict(by_alias=True, exclude={}, exclude_none=True) - # set to None if additional_input (nullable) is None - # and __fields_set__ contains the field - if self.additional_input is None and "additional_input" in self.__fields_set__: - _dict["additional_input"] = None - - return _dict - - @classmethod - def from_dict(cls, obj: dict) -> TaskRequestBody: - """Create an instance of TaskRequestBody from a dict""" - if obj is None: - return None - - if not isinstance(obj, dict): - return TaskRequestBody.parse_obj(obj) - - _obj = TaskRequestBody.parse_obj( - {"input": obj.get("input"), "additional_input": obj.get("additional_input")} - ) - return _obj diff --git a/benchmark/agbenchmark/agent_protocol_client/rest.py b/benchmark/agbenchmark/agent_protocol_client/rest.py deleted file mode 100644 index f8767d083..000000000 --- a/benchmark/agbenchmark/agent_protocol_client/rest.py +++ /dev/null @@ -1,314 +0,0 @@ -# coding: utf-8 - -""" - Agent Communication Protocol - - Specification of the API protocol for communication with an agent. # noqa: E501 - - The version of the OpenAPI document: v0.2 - Generated by OpenAPI Generator (https://openapi-generator.tech) - - Do not edit the class manually. -""" - - -import asyncio -import io -import json -import logging -import re -import ssl -from urllib.parse import urlencode - -import aiohttp - -from agbenchmark.agent_protocol_client.exceptions import ApiException, ApiValueError - -logger = logging.getLogger(__name__) - - -class RESTResponse(io.IOBase): - def __init__(self, resp, data): - self.aiohttp_response = resp - self.status = resp.status - self.reason = resp.reason - self.data = data - - def getheaders(self): - """Returns a CIMultiDictProxy of the response headers.""" - return self.aiohttp_response.headers - - def getheader(self, name, default=None): - """Returns a given response header.""" - return self.aiohttp_response.headers.get(name, default) - - -class RESTClientObject(object): - def __init__(self, configuration, pools_size=4, maxsize=None): - # maxsize is number of requests to host that are allowed in parallel - if maxsize is None: - maxsize = configuration.connection_pool_maxsize - - ssl_context = ssl.create_default_context(cafile=configuration.ssl_ca_cert) - if configuration.cert_file: - ssl_context.load_cert_chain( - configuration.cert_file, keyfile=configuration.key_file - ) - - if not configuration.verify_ssl: - ssl_context.check_hostname = False - ssl_context.verify_mode = ssl.CERT_NONE - - connector = aiohttp.TCPConnector(limit=maxsize, ssl=ssl_context) - - self.proxy = configuration.proxy - self.proxy_headers = configuration.proxy_headers - - # https pool manager - self.pool_manager = aiohttp.ClientSession(connector=connector, trust_env=True) - - async def close(self): - await self.pool_manager.close() - - async def request( - self, - method, - url, - query_params=None, - headers=None, - body=None, - post_params=None, - _preload_content=True, - _request_timeout=None, - ): - """Execute request - - :param method: http request method - :param url: http request url - :param query_params: query parameters in the url - :param headers: http request headers - :param body: request json body, for `application/json` - :param post_params: request post parameters, - `application/x-www-form-urlencoded` - and `multipart/form-data` - :param _preload_content: this is a non-applicable field for - the AiohttpClient. - :param _request_timeout: timeout setting for this request. If one - number provided, it will be total request - timeout. It can also be a pair (tuple) of - (connection, read) timeouts. - """ - method = method.upper() - assert method in ["GET", "HEAD", "DELETE", "POST", "PUT", "PATCH", "OPTIONS"] - - if post_params and body: - raise ApiValueError( - "body parameter cannot be used with post_params parameter." - ) - - post_params = post_params or {} - headers = headers or {} - # url already contains the URL query string - # so reset query_params to empty dict - query_params = {} - timeout = _request_timeout or 5 * 60 - - if "Content-Type" not in headers: - headers["Content-Type"] = "application/json" - - args = {"method": method, "url": url, "timeout": timeout, "headers": headers} - - if self.proxy: - args["proxy"] = self.proxy - if self.proxy_headers: - args["proxy_headers"] = self.proxy_headers - - if query_params: - args["url"] += "?" + urlencode(query_params) - - # For `POST`, `PUT`, `PATCH`, `OPTIONS`, `DELETE` - if method in ["POST", "PUT", "PATCH", "OPTIONS", "DELETE"]: - if re.search("json", headers["Content-Type"], re.IGNORECASE): - if body is not None: - body = json.dumps(body) - args["data"] = body - elif ( - headers["Content-Type"] == "application/x-www-form-urlencoded" - ): # noqa: E501 - args["data"] = aiohttp.FormData(post_params) - elif headers["Content-Type"] == "multipart/form-data": - # must del headers['Content-Type'], or the correct - # Content-Type which generated by aiohttp - del headers["Content-Type"] - data = aiohttp.FormData() - for param in post_params: - k, v = param - if isinstance(v, tuple) and len(v) == 3: - data.add_field(k, value=v[1], filename=v[0], content_type=v[2]) - else: - data.add_field(k, v) - args["data"] = data - - # Pass a `bytes` parameter directly in the body to support - # other content types than Json when `body` argument is provided - # in serialized form - elif isinstance(body, bytes): - args["data"] = body - else: - # Cannot generate the request from given parameters - msg = """Cannot prepare a request message for provided - arguments. Please check that your arguments match - declared content type.""" - raise ApiException(status=0, reason=msg) - - await asyncio.sleep(0.001) - - r = await self.pool_manager.request(**args) - if _preload_content: - data = await r.read() - r = RESTResponse(r, data) - - # log response body - logger.debug("response body: %s", r.data) - - if not 200 <= r.status <= 299: - raise ApiException(http_resp=r) - - return r - - async def get_request( - self, - url, - headers=None, - query_params=None, - _preload_content=True, - _request_timeout=None, - ): - return await self.request( - "GET", - url, - headers=headers, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - query_params=query_params, - ) - - async def head_request( - self, - url, - headers=None, - query_params=None, - _preload_content=True, - _request_timeout=None, - ): - return await self.request( - "HEAD", - url, - headers=headers, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - query_params=query_params, - ) - - async def options_request( - self, - url, - headers=None, - query_params=None, - post_params=None, - body=None, - _preload_content=True, - _request_timeout=None, - ): - return await self.request( - "OPTIONS", - url, - headers=headers, - query_params=query_params, - post_params=post_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - body=body, - ) - - async def delete_request( - self, - url, - headers=None, - query_params=None, - body=None, - _preload_content=True, - _request_timeout=None, - ): - return await self.request( - "DELETE", - url, - headers=headers, - query_params=query_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - body=body, - ) - - async def post_request( - self, - url, - headers=None, - query_params=None, - post_params=None, - body=None, - _preload_content=True, - _request_timeout=None, - ): - return await self.request( - "POST", - url, - headers=headers, - query_params=query_params, - post_params=post_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - body=body, - ) - - async def put_request( - self, - url, - headers=None, - query_params=None, - post_params=None, - body=None, - _preload_content=True, - _request_timeout=None, - ): - return await self.request( - "PUT", - url, - headers=headers, - query_params=query_params, - post_params=post_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - body=body, - ) - - async def patch_request( - self, - url, - headers=None, - query_params=None, - post_params=None, - body=None, - _preload_content=True, - _request_timeout=None, - ): - return await self.request( - "PATCH", - url, - headers=headers, - query_params=query_params, - post_params=post_params, - _preload_content=_preload_content, - _request_timeout=_request_timeout, - body=body, - ) diff --git a/benchmark/agbenchmark/app.py b/benchmark/agbenchmark/app.py index ad14cb692..40fee14b6 100644 --- a/benchmark/agbenchmark/app.py +++ b/benchmark/agbenchmark/app.py @@ -1,78 +1,81 @@ import datetime +import glob +import json +import logging +import sys +import time import uuid -from collections import defaultdict, deque +from collections import deque +from multiprocessing import Process from pathlib import Path +from typing import Optional import httpx - -from agbenchmark.agent_protocol_client import ( - AgentApi, - ApiClient, - ApiException, - Configuration, +import psutil +from agent_protocol_client import AgentApi, ApiClient, ApiException, Configuration +from agent_protocol_client.models import Task, TaskRequestBody +from fastapi import APIRouter, FastAPI, HTTPException, Request, Response +from fastapi.middleware.cors import CORSMiddleware +from pydantic import BaseModel, Extra, ValidationError + +from agbenchmark.challenges import ChallengeInfo +from agbenchmark.config import AgentBenchmarkConfig +from agbenchmark.reports.processing.report_types_v2 import ( + BenchmarkRun, + Metrics, + RepositoryInfo, + RunDetails, + TaskInfo, ) -from agbenchmark.reports.processing.report_types_v2 import BenchmarkRun from agbenchmark.schema import TaskEvalRequestBody from agbenchmark.utils.utils import write_pretty_json -configuration = Configuration(host="http://localhost:8000" + "/ap/v1") - -import json -import os -import sys -from typing import Any, Optional - -import psutil -from fastapi import APIRouter, FastAPI -from fastapi import ( - HTTPException as FastAPIHTTPException, # Import HTTPException from FastAPI -) -from fastapi import Request, Response -from fastapi.middleware.cors import CORSMiddleware - -from agbenchmark.execute_sub_process import execute_subprocess -from agbenchmark.schema import Task, TaskRequestBody - -sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) -from fastapi import FastAPI -from pydantic import BaseModel, Extra - -router = APIRouter() -import glob - -# Change the current working directory to the benchmark path -# home_path = find_absolute_benchmark_path() -# os.chdir(home_path) +sys.path.append(str(Path(__file__).parent.parent)) -general_command = ["poetry", "run", "agbenchmark", "start", "--backend"] +logger = logging.getLogger(__name__) -import psutil - -challenges_path = os.path.join(os.path.dirname(__file__), "challenges") - -json_files = deque( +CHALLENGES: dict[str, ChallengeInfo] = {} +challenges_path = Path(__file__).parent / "challenges" +challenge_spec_files = deque( glob.glob( f"{challenges_path}/**/data.json", recursive=True, ) ) -CHALLENGES = {} -task_informations = defaultdict(dict) +logger.debug("Loading challenges...") +while challenge_spec_files: + challenge_spec_file = Path(challenge_spec_files.popleft()) + challenge_relpath = challenge_spec_file.relative_to(challenges_path.parent) + if challenge_relpath.is_relative_to("challenges/deprecated"): + continue + + logger.debug(f"Loading {challenge_relpath}...") + try: + challenge_info = ChallengeInfo.parse_file(challenge_spec_file) + except ValidationError as e: + if logging.getLogger().level == logging.DEBUG: + logger.warning(f"Spec file {challenge_relpath} failed to load:\n{e}") + logger.debug(f"Invalid challenge spec: {challenge_spec_file.read_text()}") + continue + challenge_info.spec_file = challenge_spec_file -while json_files: - json_file = json_files.popleft() + if not challenge_info.eval_id: + challenge_info.eval_id = str(uuid.uuid4()) + # this will sort all the keys of the JSON systematically + # so that the order is always the same + write_pretty_json(challenge_info.dict(), challenge_spec_file) - with open(json_file, "r") as file: - data = json.load(file) + CHALLENGES[challenge_info.eval_id] = challenge_info - if "eval_id" not in data: - data["eval_id"] = str(uuid.uuid4()) - # this will sort all the keys of the JSON systematically so that the order is always the same - write_pretty_json(data, json_file) - # ok - CHALLENGES[data["eval_id"]] = data - CHALLENGES[data["eval_id"]]["path"] = json_file + +class BenchmarkTaskInfo(BaseModel): + task_id: str + start_time: datetime.datetime + challenge_info: ChallengeInfo + + +task_informations: dict[str, BenchmarkTaskInfo] = {} def find_agbenchmark_without_uvicorn(): @@ -93,10 +96,10 @@ def find_agbenchmark_without_uvicorn(): ): try: # Convert the process.info dictionary values to strings and concatenate them - full_info = " ".join([str(v) for k, v in process.info.items()]) + full_info = " ".join([str(v) for k, v in process.as_dict().items()]) if "agbenchmark" in full_info and "uvicorn" not in full_info: - pids.append(process.info["pid"]) + pids.append(process.pid) except (psutil.NoSuchProcess, psutil.AccessDenied, psutil.ZombieProcess): pass return pids @@ -114,24 +117,12 @@ class CreateReportRequest(BaseModel): updates_list = [] -updates_list = [] - -import json - origins = [ "http://localhost:8000", "http://localhost:8080", "http://127.0.0.1:5000", "http://localhost:5000", ] -app = FastAPI() -app.add_middleware( - CORSMiddleware, - allow_origins=origins, - allow_credentials=True, - allow_methods=["*"], - allow_headers=["*"], -) def stream_output(pipe): @@ -139,275 +130,205 @@ def stream_output(pipe): print(line, end="") -@router.post("/reports") -def run_single_test(body: CreateReportRequest) -> Any: - pids = find_agbenchmark_without_uvicorn() - print(f"pids already running with agbenchmark: {pids}") - print(body.dict()) - # it's a hack because other parts of the code are using sys.argv - print(os.getcwd()) - command_options = ["agbenchmark"] - # if body.category: - # sys.argv.append(f"--category={body.category}") - command_options.append(f"--test={body.test}") - if body.mock: - command_options.append("--mock") - - execute_subprocess(command_options, 200) - import json - from pathlib import Path - - print("finished running") - # List all folders in the current working directory - path_reports = Path.cwd() / "agbenchmark_config" / "reports" - folders = [folder for folder in path_reports.iterdir() if folder.is_dir()] - - # Sort the folders based on their names - sorted_folders = sorted(folders, key=lambda x: x.name) - - # Get the last folder - last_folder = sorted_folders[-1] if sorted_folders else None - - # Read report.json from this folder - if last_folder: - report_path = last_folder / "report.json" - print(report_path) - if report_path.exists(): - with report_path.open() as file: - data = json.load(file) - print(data) - else: - print(f"'report.json' does not exist in '{last_folder}'") - else: - print("No folders found.") - - return Response( - content=json.dumps(data), - status_code=200, - media_type="application/json", - ) - - -import json -from typing import Any +def setup_fastapi_app(agbenchmark_config: AgentBenchmarkConfig) -> FastAPI: + from agbenchmark.agent_api_interface import upload_artifacts + from agbenchmark.challenges import get_challenge_from_source_uri + from agbenchmark.main import run_benchmark -from fastapi import FastAPI, Request, Response + configuration = Configuration( + host=agbenchmark_config.host or "http://localhost:8000" + ) + app = FastAPI() + app.add_middleware( + CORSMiddleware, + allow_origins=origins, + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], + ) + router = APIRouter() + @router.post("/reports") + def run_single_test(body: CreateReportRequest) -> dict: + pids = find_agbenchmark_without_uvicorn() + logger.info(f"pids already running with agbenchmark: {pids}") -@router.get("/updates") -def get_updates(request: Request) -> Any: - from agbenchmark.__main__ import UPDATES_JSON_PATH + logger.debug(f"Request to /reports: {body.dict()}") - try: - # Read data from the "update.json" file (provide the correct file path) - with open(UPDATES_JSON_PATH, "r") as file: - data = json.load(file) - - # Get the last_update_time from the query parameter - query_param = request.query_params.get("last_update_time") - - if query_param is None: - # Handle the case when last_update_time is not provided - print("ERROR: last_update_time parameter is missing") - return Response( - content=json.dumps({"error": "last_update_time parameter is missing"}), - status_code=400, - media_type="application/json", - headers={"Content-Type": "application/json"}, + # Start the benchmark in a separate thread + benchmark_process = Process( + target=lambda: run_benchmark( + config=agbenchmark_config, + tests=(body.test,), + mock=body.mock or False, ) - - # Convert query_param to a Unix timestamp (assuming it's in seconds as a string) - query_timestamp = int(query_param) - - # Filter the data based on the timestamp (keep timestamps before query_timestamp) - filtered_data = [item for item in data if item["timestamp"] > query_timestamp] - - # Extract only the "content" field from each item - filtered_data = [item["content"] for item in filtered_data] - - # Convert the filtered data to JSON - filtered_json = json.dumps(filtered_data, indent=2) - - print("INFO: Returning filtered data to the client") - return Response( - content=filtered_json, - status_code=200, - media_type="application/json", - headers={"Content-Type": "application/json"}, - ) - except FileNotFoundError: - print("ERROR: File not found: updates.json") - return Response( - content=json.dumps({"error": "File not found"}), - status_code=404, - media_type="application/json", - headers={"Content-Type": "application/json"}, ) - - -@router.post("/agent/tasks", tags=["agent"], response_model=Task) -async def create_agent_task(task_eval_request: TaskEvalRequestBody) -> Task: - """ - Creates a new task using the provided TaskRequestBody and returns a Task. - - Args: - request (Request): FastAPI request object. - task (TaskRequestBody): The task request containing input and additional input data. - - Returns: - Task: A new task with task_id, input, additional_input, and empty lists for artifacts and steps. - - Example: - Request (TaskRequestBody defined in schema.py): - { - "input": "Write the words you receive to the file 'output.txt'.", - "additional_input": "python/code" - } - - Response (Task defined in schema.py): - { - "task_id": "50da533e-3904-4401-8a07-c49adf88b5eb", - "input": "Write the word 'Washington' to a .txt file", - "additional_input": "python/code", - "artifacts": [], - } - """ - from agbenchmark.agent_api_interface import upload_artifacts - - try: - async with ApiClient(configuration) as api_client: - api_instance = AgentApi(api_client) - task_input = CHALLENGES[task_eval_request.eval_id]["task"] - - task_request_body = TaskRequestBody(input=task_input) - task_response = await api_instance.create_agent_task( - task_request_body=task_request_body - ) - task_informations[task_response.task_id][ - "benchmark_start_time" - ] = datetime.datetime.now(datetime.timezone.utc).strftime( - "%Y-%m-%dT%H:%M:%S+00:00" + benchmark_process.start() + + # Wait for the benchmark to finish, with a timeout of 200 seconds + timeout = 200 + start_time = time.time() + while benchmark_process.is_alive(): + if time.time() - start_time > timeout: + logger.warning(f"Benchmark run timed out after {timeout} seconds") + benchmark_process.terminate() + break + time.sleep(1) + else: + logger.debug(f"Benchmark finished running in {time.time() - start_time} s") + + # List all folders in the current working directory + path_reports = agbenchmark_config.reports_folder + folders = [folder for folder in path_reports.iterdir() if folder.is_dir()] + + # Sort the folders based on their names + sorted_folders = sorted(folders, key=lambda x: x.name) + + # Get the last folder + latest_folder = sorted_folders[-1] if sorted_folders else None + + # Read report.json from this folder + if latest_folder: + report_path = latest_folder / "report.json" + logger.debug(f"Getting latest report from {report_path}") + if report_path.exists(): + with report_path.open() as file: + data = json.load(file) + logger.debug(f"Report data: {data}") + else: + logger.error( + "Could not get result after running benchmark: " + f"'report.json' does not exist in '{latest_folder}'" + ) + else: + logger.error( + "Could not get result after running benchmark: no reports found" ) - task_informations[task_response.task_id][ - "eval_id" - ] = task_eval_request.eval_id - await upload_artifacts( - api_instance, - str(Path(CHALLENGES[task_eval_request.eval_id]["path"]).parent), - task_response.task_id, - "artifacts_in", + + return data + + @router.post("/agent/tasks", tags=["agent"]) + async def create_agent_task(task_eval_request: TaskEvalRequestBody) -> Task: + """ + Creates a new task using the provided TaskEvalRequestBody and returns a Task. + + Args: + task_eval_request: `TaskRequestBody` including an eval_id. + + Returns: + Task: A new task with task_id, input, additional_input, + and empty lists for artifacts and steps. + + Example: + Request (TaskEvalRequestBody defined in schema.py): + { + ..., + "eval_id": "50da533e-3904-4401-8a07-c49adf88b5eb" + } + + Response (Task defined in `agent_protocol_client.models`): + { + "task_id": "50da533e-3904-4401-8a07-c49adf88b5eb", + "input": "Write the word 'Washington' to a .txt file", + "artifacts": [] + } + """ + try: + challenge_info = CHALLENGES[task_eval_request.eval_id] + async with ApiClient(configuration) as api_client: + api_instance = AgentApi(api_client) + task_input = challenge_info.task + + task_request_body = TaskRequestBody(input=task_input) + task_response = await api_instance.create_agent_task( + task_request_body=task_request_body + ) + task_info = BenchmarkTaskInfo( + task_id=task_response.task_id, + start_time=datetime.datetime.now(datetime.timezone.utc), + challenge_info=challenge_info, + ) + task_informations[task_info.task_id] = task_info + + if input_artifacts_dir := challenge_info.task_artifacts_dir: + await upload_artifacts( + api_instance, + input_artifacts_dir, + task_response.task_id, + "artifacts_in", + ) + return task_response + except ApiException as e: + logger.error(f"Error whilst trying to create a task:\n{e}") + logger.error( + "The above error was caused while processing request: " + f"{task_eval_request}" ) - return Response( - content=task_response.json(), - status_code=200, - media_type="application/json", + raise HTTPException(500) + + @router.post("/agent/tasks/{task_id}/steps") + async def proxy(request: Request, task_id: str): + timeout = httpx.Timeout(300.0, read=300.0) # 5 minutes + async with httpx.AsyncClient(timeout=timeout) as client: + # Construct the new URL + new_url = f"{configuration.host}/ap/v1/agent/tasks/{task_id}/steps" + + # Forward the request + response = await client.post( + new_url, + data=await request.body(), + headers=dict(request.headers), ) - except ApiException as e: - print(f"Error whilst trying to create a task: {task_eval_request}") - return Response( - content=json.dumps({"error": "Internal server error"}), - status_code=500, - media_type="application/json", - ) - -@router.post("/agent/tasks/{task_id}/steps") -async def proxy(request: Request, task_id: str): - timeout = httpx.Timeout(300.0, read=300.0) # 5 minutes - async with httpx.AsyncClient(timeout=timeout) as client: - # Construct the new URL - new_url = f"http://localhost:8000/ap/v1/agent/tasks/{task_id}/steps" - - # Forward the request - response = await client.post( - new_url, - data=await request.body(), - headers=dict(request.headers), - ) + # Return the response from the forwarded request + return Response(content=response.content, status_code=response.status_code) - # Return the response from the forwarded request - return Response(content=response.content, status_code=response.status_code) - - -@router.post("/agent/tasks/{task_id}/evaluations") -async def create_evaluation(task_id: str) -> deque: - from agbenchmark.__main__ import TEMP_FOLDER_ABS_PATH - from agbenchmark.agent_api_interface import copy_agent_artifacts_into_temp_folder - from agbenchmark.agent_interface import copy_artifacts_into_temp_folder - from agbenchmark.generate_test import create_challenge + @router.post("/agent/tasks/{task_id}/evaluations") + async def create_evaluation(task_id: str) -> BenchmarkRun: + task_info = task_informations[task_id] + challenge = get_challenge_from_source_uri(task_info.challenge_info.source_uri) + try: + async with ApiClient(configuration) as api_client: + api_instance = AgentApi(api_client) + eval_results = await challenge.evaluate_task_state( + api_instance, task_id + ) + + eval_info = BenchmarkRun( + repository_info=RepositoryInfo(), + run_details=RunDetails( + command=f"agbenchmark --test={challenge.info.name}", + benchmark_start_time=( + task_info.start_time.strftime("%Y-%m-%dT%H:%M:%S+00:00") + ), + test_name=challenge.info.name, + ), + task_info=TaskInfo( + data_path=challenge.info.source_uri, + is_regression=None, + category=[c.value for c in challenge.info.category], + task=challenge.info.task, + answer=challenge.info.reference_answer or "", + description=challenge.info.description or "", + ), + metrics=Metrics( + success=all(e.passed for e in eval_results), + success_percentage=( + 100 * sum(e.score for e in eval_results) / len(eval_results) + if eval_results # avoid division by 0 + else 0 + ), + attempted=True, + ), + config={}, + ) - try: - async with ApiClient(configuration) as api_client: - api_instance = AgentApi(api_client) - await copy_agent_artifacts_into_temp_folder(api_instance, task_id) - # add custom python - data = CHALLENGES[task_informations[task_id]["eval_id"]] - - artifact_path = str(Path(data["path"]).parent) - copy_artifacts_into_temp_folder( - TEMP_FOLDER_ABS_PATH, "custom_python", artifact_path - ) - json_file = CHALLENGES[task_informations[task_id]["eval_id"]]["path"] - json_files = deque() - - _, challenge_class = create_challenge(data, json_file, json_files) - challenge_instance = challenge_class() - scores = challenge_instance.get_scores(config={}) - test_name = "Test" + data["name"] - is_score_100 = 1 in scores["values"] - - info_details = { - "repository_info": { - "repo_url": None, - "team_name": None, - "benchmark_git_commit_sha": None, - "agent_git_commit_sha": None, - }, - "run_details": { - "run_id": None, - "command": "agbenchmark" + " --test=" + test_name, - "completion_time": None, - "benchmark_start_time": task_informations[task_id][ - "benchmark_start_time" - ], - "test_name": data["name"], - }, - "task_info": { - "data_path": data["path"].split("benchmark/", 1)[-1], - "is_regression": None, - "category": data["category"], - "task": data["task"], - "answer": data["ground"]["answer"], - "description": data["info"]["description"], - }, - "metrics": { - "difficulty": None, - "success": is_score_100, - "attempted": True, - "success_percentage": None, - "cost": None, - "run_time": None, - }, - "reached_cutoff": None, - "config": {}, - } - - BenchmarkRun.parse_obj(info_details) - - print(json.dumps(info_details, indent=4)) - return Response( - content=json.dumps(info_details), - status_code=200, - media_type="application/json", - ) - except ApiException as e: - print(f"Error whilst trying to evaluate the task: {task_id}") - return Response( - content=json.dumps({"error": "Internal server error"}), - status_code=500, - media_type="application/json", - ) - # path = Path(json_file).resolve() + logger.debug(f"Returning evaluation data:\n{eval_info.json(indent=4)}") + return eval_info + except ApiException as e: + logger.error(f"Error {e} whilst trying to evaluate task: {task_id}") + raise HTTPException(500) + app.include_router(router, prefix="/ap/v1") -app.include_router(router, prefix="/ap/v1") + return app diff --git a/benchmark/agbenchmark/challenges/__init__.py b/benchmark/agbenchmark/challenges/__init__.py index e69de29bb..68105d854 100644 --- a/benchmark/agbenchmark/challenges/__init__.py +++ b/benchmark/agbenchmark/challenges/__init__.py @@ -0,0 +1,56 @@ +import glob +import json +import logging +from pathlib import Path + +from .base import BaseChallenge, ChallengeInfo +from .builtin import OPTIONAL_CATEGORIES + +logger = logging.getLogger(__name__) + + +def get_challenge_from_source_uri(source_uri: str) -> type[BaseChallenge]: + from .builtin import BuiltinChallenge + from .webarena import WebArenaChallenge + + provider_prefix = source_uri.split("/", 1)[0] + + if provider_prefix == BuiltinChallenge.SOURCE_URI_PREFIX: + return BuiltinChallenge.from_source_uri(source_uri) + + if provider_prefix == WebArenaChallenge.SOURCE_URI_PREFIX: + return WebArenaChallenge.from_source_uri(source_uri) + + raise ValueError(f"Cannot resolve source_uri '{source_uri}'") + + +def get_unique_categories() -> set[str]: + """ + Reads all challenge spec files and returns a set of all their categories. + """ + categories = set() + + challenges_dir = Path(__file__).parent + glob_path = f"{challenges_dir}/**/data.json" + + for data_file in glob.glob(glob_path, recursive=True): + with open(data_file, "r") as f: + try: + challenge_data = json.load(f) + categories.update(challenge_data.get("category", [])) + except json.JSONDecodeError: + logger.error(f"Error: {data_file} is not a valid JSON file.") + continue + except IOError: + logger.error(f"IOError: file could not be read: {data_file}") + continue + + return categories + + +__all__ = [ + "BaseChallenge", + "ChallengeInfo", + "get_unique_categories", + "OPTIONAL_CATEGORIES", +] diff --git a/benchmark/agbenchmark/challenges/base.py b/benchmark/agbenchmark/challenges/base.py new file mode 100644 index 000000000..64ead3a9d --- /dev/null +++ b/benchmark/agbenchmark/challenges/base.py @@ -0,0 +1,104 @@ +import logging +from abc import ABC, abstractmethod +from pathlib import Path +from typing import AsyncIterator, ClassVar, Optional + +import pytest +from agent_protocol_client import AgentApi, Step +from colorama import Fore, Style +from pydantic import BaseModel, Field + +from agbenchmark.config import AgentBenchmarkConfig +from agbenchmark.utils.data_types import Category, DifficultyLevel, EvalResult + +logger = logging.getLogger(__name__) + + +class ChallengeInfo(BaseModel): + eval_id: str = "" + name: str + task: str + task_artifacts_dir: Optional[Path] = None + category: list[Category] + difficulty: Optional[DifficultyLevel] = None + description: Optional[str] = None + dependencies: list[str] = Field(default_factory=list) + reference_answer: Optional[str] + + source_uri: str + """Internal reference indicating the source of the challenge specification""" + + +class BaseChallenge(ABC): + """ + The base class and shared interface for all specific challenge implementations. + """ + + info: ClassVar[ChallengeInfo] + + @classmethod + @abstractmethod + def from_source_uri(cls, source_uri: str) -> type["BaseChallenge"]: + """ + Construct an individual challenge subclass from a suitable `source_uri` (as in + `ChallengeInfo.source_uri`). + """ + ... + + @abstractmethod + def test_method( + self, + config: AgentBenchmarkConfig, + request: pytest.FixtureRequest, + i_attempt: int, + ) -> None: + """ + Test method for use by Pytest-based benchmark sessions. Should return normally + if the challenge passes, and raise a (preferably descriptive) error otherwise. + """ + ... + + @classmethod + async def run_challenge( + cls, config: AgentBenchmarkConfig, timeout: int + ) -> AsyncIterator[Step]: + """ + Runs the challenge on the subject agent with the specified timeout. + Also prints basic challenge and status info to STDOUT. + + Params: + config: The subject agent's benchmark config. + timeout: Timeout (seconds) after which to stop the run if not finished. + + Yields: + Step: The steps generated by the agent for the challenge task. + """ + # avoid circular import + from agbenchmark.agent_api_interface import run_api_agent + + print() + print( + f"{Fore.MAGENTA + Style.BRIGHT}{'='*24} " + f"Starting {cls.info.name} challenge" + f" {'='*24}{Style.RESET_ALL}" + ) + print(f"{Fore.CYAN}Timeout:{Fore.RESET} {timeout} seconds") + print(f"{Fore.CYAN}Task:{Fore.RESET} {cls.info.task}") + + print() + logger.debug(f"Starting {cls.info.name} challenge run") + i = 0 + async for step in run_api_agent( + cls.info.task, config, timeout, cls.info.task_artifacts_dir + ): + i += 1 + print(f"[{cls.info.name}] - step {step.name} ({i}. request)") + yield step + logger.debug(f"Finished {cls.info.name} challenge run") + + @classmethod + @abstractmethod + async def evaluate_task_state( + cls, agent: AgentApi, task_id: str + ) -> list[EvalResult]: + ... diff --git a/benchmark/agbenchmark/challenges/builtin.py b/benchmark/agbenchmark/challenges/builtin.py new file mode 100644 index 000000000..590696688 --- /dev/null +++ b/benchmark/agbenchmark/challenges/builtin.py @@ -0,0 +1,425 @@ +from collections import deque +import glob +import json +import logging +import os +import subprocess +import sys +import tempfile +from pathlib import Path +from typing import Any, ClassVar, Iterator, Literal, Optional + +import pytest +from agent_protocol_client import AgentApi, ApiClient, Configuration as ClientConfig +from colorama import Fore, Style +from openai import _load_client as get_openai_client +from pydantic import BaseModel, constr, Field, validator + +from agbenchmark.agent_api_interface import download_agent_artifacts_into_folder +from agbenchmark.agent_interface import copy_challenge_artifacts_into_workspace +from agbenchmark.config import AgentBenchmarkConfig +from agbenchmark.utils.data_types import Category, DifficultyLevel, EvalResult +from agbenchmark.utils.prompts import ( + END_PROMPT, + FEW_SHOT_EXAMPLES, + PROMPT_MAP, + SCORING_MAP, +) + +from .base import BaseChallenge, ChallengeInfo + +logger = logging.getLogger(__name__) + +with open(Path(__file__).parent / "optional_categories.json") as f: + OPTIONAL_CATEGORIES: list[str] = json.load(f)["optional_categories"] + + +class BuiltinChallengeSpec(BaseModel): + eval_id: str = "" + name: str + task: str + category: list[Category] + dependencies: list[str] + cutoff: int + + class Info(BaseModel): + difficulty: DifficultyLevel + description: constr(regex=r"^Tests if the agent can.*") + side_effects: list[str] = Field(default_factory=list) + + info: Info + + class Ground(BaseModel): + answer: str + should_contain: Optional[list[str]] = None + should_not_contain: Optional[list[str]] = None + files: list[str] + case_sensitive: Optional[bool] = True + + class Eval(BaseModel): + type: str + scoring: Optional[Literal["percentage", "scale", "binary"]] + template: Optional[Literal["rubric", "reference", "question", "custom"]] + examples: Optional[str] + + @validator("scoring", "template", always=True) + def validate_eval_fields(cls, v, values, field): + if "type" in values and values["type"] == "llm": + if v is None: + raise ValueError( + f"{field.name} must be provided when eval type is 'llm'" + ) + else: + if v is not None: + raise ValueError( + f"{field.name} should only exist when eval type is 'llm'" + ) + return v + + eval: Eval + + ground: Ground + + metadata: Optional[dict[str, Any]] = None + spec_file: Path | None = Field(None, exclude=True) + + +class BuiltinChallenge(BaseChallenge): + """ + Base class for AGBenchmark's built-in challenges (challenges/**/*.json). + + All of the logic is present in this class. Individual challenges are created as + subclasses of `BuiltinChallenge` with challenge-specific values assigned to the + ClassVars `_spec` etc. + + Dynamically constructing subclasses rather than class instances for the individual + challenges makes them suitable for collection by Pytest, which will run their + `test_method` like any regular test item. + """ + + _spec: ClassVar[BuiltinChallengeSpec] + CHALLENGE_LOCATION: ClassVar[str] + ARTIFACTS_LOCATION: ClassVar[str] + + SOURCE_URI_PREFIX = "__BUILTIN__" + + @classmethod + def from_challenge_spec( + cls, spec: BuiltinChallengeSpec + ) -> type["BuiltinChallenge"]: + if not spec.spec_file: + raise ValueError("spec.spec_file not defined") + + challenge_info = ChallengeInfo( + eval_id=spec.eval_id, + name=spec.name, + task=spec.task, + task_artifacts_dir=spec.spec_file.parent, + category=spec.category, + difficulty=spec.info.difficulty, + description=spec.info.description, + dependencies=spec.dependencies, + reference_answer=spec.ground.answer, + source_uri=( + f"__BUILTIN__/{spec.spec_file.relative_to(Path(__file__).parent)}" + ), + ) + + challenge_class_name = f"Test{challenge_info.name}" + logger.debug(f"Creating {challenge_class_name} from spec: {spec.spec_file}") + return type( + challenge_class_name, + (BuiltinChallenge,), + { + "info": challenge_info, + "_spec": spec, + "CHALLENGE_LOCATION": str(spec.spec_file), + "ARTIFACTS_LOCATION": str(spec.spec_file.resolve().parent), + }, + ) + + @classmethod + def from_challenge_spec_file(cls, spec_file: Path) -> type["BuiltinChallenge"]: + challenge_spec = BuiltinChallengeSpec.parse_file(spec_file) + challenge_spec.spec_file = spec_file + return cls.from_challenge_spec(challenge_spec) + + @classmethod + def from_source_uri(cls, source_uri: str) -> type["BuiltinChallenge"]: + if not source_uri.startswith(cls.SOURCE_URI_PREFIX): + raise ValueError(f"Invalid source_uri for BuiltinChallenge: {source_uri}") + + path = source_uri.split("/", 1)[1] + spec_file = Path(__file__).parent / path + return cls.from_challenge_spec_file(spec_file) + + @pytest.mark.asyncio + async def test_method( + self, + config: AgentBenchmarkConfig, + request: pytest.FixtureRequest, + i_attempt: int, + ) -> None: + if os.environ.get("HELICONE_API_KEY"): + from helicone.lock import HeliconeLockManager + + HeliconeLockManager.write_custom_property("challenge", self.info.name) + + timeout = self._spec.cutoff or 60 + + if request.config.getoption("--nc"): + timeout = 100000 + elif cutoff := request.config.getoption("--cutoff"): + timeout = int(cutoff) # type: ignore + + task_id = "" + timed_out = None + try: + async for step in self.run_challenge(config, timeout): + if not task_id: + task_id = step.task_id + if request.config.getoption("--mock"): + # Run only one step in mock mode + break + timed_out = False + except TimeoutError: + timed_out = True + request.node.user_properties.append(("timed_out", timed_out)) + + agent_client_config = ClientConfig(host=config.host) + async with ApiClient(agent_client_config) as api_client: + api_instance = AgentApi(api_client) + eval_results = await self.evaluate_task_state(api_instance, task_id) + + if not eval_results: + if timed_out: + raise TimeoutError("Timed out, no results to evaluate") + else: + raise ValueError("No results to evaluate") + + request.node.user_properties.append( + ( + "answers", + [r.result for r in eval_results] + if request.config.getoption("--keep-answers") + else None, + ) + ) + request.node.user_properties.append(("scores", [r.score for r in eval_results])) + + # FIXME: this allows partial failure + assert any(r.passed for r in eval_results), ( + f"No passed evals: {eval_results}" + if not timed_out + else f"Timed out; no passed evals: {eval_results}" + ) + + @classmethod + async def evaluate_task_state( + cls, agent: AgentApi, task_id: str + ) -> list[EvalResult]: + with tempfile.TemporaryDirectory() as workspace: + workspace = Path(workspace) + await download_agent_artifacts_into_folder(agent, task_id, workspace) + if cls.info.task_artifacts_dir: + copy_challenge_artifacts_into_workspace( + cls.info.task_artifacts_dir, "custom_python", workspace + ) + + return list(cls.evaluate_workspace_content(workspace)) + + @classmethod + def evaluate_workspace_content(cls, workspace: Path) -> Iterator[EvalResult]: + if cls._spec.task == "" and os.getenv("IS_MOCK"): + yield EvalResult( + result="This is a mock answer", + result_source="step_output", + score=1.0, + passed=True, + ) + return + + result_ground = cls._spec.ground + outputs_for_eval = cls.get_outputs_for_eval(workspace, result_ground) + + if result_ground.should_contain or result_ground.should_not_contain: + for source, content in outputs_for_eval: + score = cls.score_result(content, result_ground) + if score is not None: + print(f"{Fore.GREEN}Your score is:{Style.RESET_ALL}", score) + yield EvalResult( + result=content, + result_source=str(source), + score=score, + passed=score > 0.9, # FIXME: arbitrary threshold + ) + + if result_ground.eval.type == "llm": + combined_results = "\n".join(output[1] for output in outputs_for_eval) + llm_eval = cls.score_result_with_llm(combined_results, result_ground) + print(f"{Fore.GREEN}Your score is:{Style.RESET_ALL}", llm_eval) + if result_ground.eval.scoring == "percentage": + score = llm_eval / 100 + elif result_ground.eval.scoring == "scale": + score = llm_eval / 10 + else: + score = llm_eval + + yield EvalResult( + result=combined_results, + result_source=", ".join(str(res[0]) for res in outputs_for_eval), + score=score, + passed=score > 0.9, # FIXME: arbitrary threshold + ) + + @staticmethod + def get_outputs_for_eval( + workspace: str | Path | dict[str, str], ground: BuiltinChallengeSpec.Ground + ) -> Iterator[tuple[str | Path, str]]: + if isinstance(workspace, dict): + workspace = workspace["output"] + + script_dir = workspace + + for file_pattern in ground.files: + # Check if it is a file extension + if file_pattern.startswith("."): + # Find all files with the given extension in the workspace + matching_files = glob.glob(os.path.join(script_dir, "*" + file_pattern)) + else: + # Otherwise, it is a specific file + matching_files = [os.path.join(script_dir, file_pattern)] + + for file_path in matching_files: + if ground.eval.type == "python": + result = subprocess.run( + [sys.executable, file_path], + cwd=os.path.abspath(workspace), + capture_output=True, + text=True, + ) + if "error" in result.stderr or result.returncode != 0: + print(result.stderr) + assert False, result.stderr + yield ( + Path(file_path).relative_to(workspace), + f"Output: {result.stdout}\n", + ) + else: + with open(file_path, "r") as f: + yield Path(file_path).relative_to(workspace), f.read() + else: + if ground.eval.type == "pytest": + result = subprocess.run( + [sys.executable, "-m", "pytest"], + cwd=os.path.abspath(workspace), + capture_output=True, + text=True, + ) + if "error" in result.stderr or result.returncode != 0: + print(result.stderr) + assert False, result.stderr + yield "pytest", f"Output: {result.stdout}\n" + + @staticmethod + def score_result(content: str, ground: BuiltinChallengeSpec.Ground) -> float | None: + print(f"{Fore.BLUE}Scoring content:{Style.RESET_ALL}", content) + if ground.should_contain: + for should_contain_word in ground.should_contain: + if not ground.case_sensitive: + should_contain_word = should_contain_word.lower() + content = content.lower() + print_content = ( + f"{Fore.BLUE}Word that should exist{Style.RESET_ALL}" + f" - {should_contain_word}:" + ) + if should_contain_word not in content: + print(print_content, "False") + return 0.0 + else: + print(print_content, "True") + return 1.0 + + if ground.should_not_contain: + for should_not_contain_word in ground.should_not_contain: + if not ground.case_sensitive: + should_not_contain_word = should_not_contain_word.lower() + content = content.lower() + print_content = ( + f"{Fore.BLUE}Word that should not exist{Style.RESET_ALL}" + f" - {should_not_contain_word}:" + ) + if should_not_contain_word in content: + print(print_content, "False") + return 0.0 + else: + print(print_content, "True") + return 1.0 + + @classmethod + def score_result_with_llm( + cls, content: str, ground: BuiltinChallengeSpec.Ground + ) -> float: + if os.getenv("IS_MOCK"): + return 1.0 + + # the validation for this is done in the Eval BaseModel + scoring = SCORING_MAP[ground.eval.scoring] # type: ignore + prompt = PROMPT_MAP[ground.eval.template].format( # type: ignore + task=cls._spec.task, scoring=scoring, answer=ground.answer, response=content + ) + + if ground.eval.examples: + prompt += FEW_SHOT_EXAMPLES.format(examples=ground.eval.examples) + + prompt += END_PROMPT + + answer = get_openai_client().chat.completions.create( + model="gpt-4", + messages=[ + {"role": "system", "content": prompt}, + ], + ) + + return float(answer.choices[0].message.content) # type: ignore + + +def load_builtin_challenges() -> Iterator[type[BuiltinChallenge]]: + logger.info("Loading built-in challenges...") + + challenges_path = os.path.dirname(__file__) + logger.debug(f"Looking for challenge spec files in {challenges_path}...") + + json_files = deque( + glob.glob( + f"{challenges_path}/**/data.json", + recursive=True, + ) + ) + + logger.debug(f"Found {len(json_files)} built-in challenges.") + + loaded, ignored = 0, 0 + while json_files: + # Take and remove the first element from json_files + json_file = json_files.popleft() + if _challenge_should_be_ignored(json_file): + ignored += 1 + continue + + challenge = BuiltinChallenge.from_challenge_spec_file(Path(json_file)) + logger.debug(f"Generated test for {challenge.info.name}") + yield challenge + + loaded += 1 + + logger.info( + f"Loading built-in challenges complete: loaded {loaded}, ignored {ignored}." + ) + + +def _challenge_should_be_ignored(json_file_path: str): + return ( + "challenges/deprecated" in json_file_path + or "challenges/library" in json_file_path + ) diff --git a/benchmark/agbenchmark/challenges/webarena.py b/benchmark/agbenchmark/challenges/webarena.py new file mode 100644 index 000000000..24f569327 --- /dev/null +++ b/benchmark/agbenchmark/challenges/webarena.py @@ -0,0 +1,478 @@ +import logging +import os +from abc import ABC, abstractmethod +from typing import ClassVar, Iterator, Literal + +import pytest +import requests +from agent_protocol_client import AgentApi, Step +from pydantic import BaseModel, validator, ValidationError + +from agbenchmark.config import AgentBenchmarkConfig +from agbenchmark.utils.data_types import Category, EvalResult + +from .base import BaseChallenge, ChallengeInfo + +logger = logging.getLogger(__name__) + + +EvalType = Literal["string_match", "url_match", "program_html"] +WebArenaSite = Literal[ + "gitlab", "map", "reddit", "shopping", "shopping_admin", "wikipedia" +] +ReferenceAnswerType = Literal["exact_match", "fuzzy_match", "must_include"] + + +class WebArenaSiteInfo(BaseModel): + base_url: str + available: bool = True + additional_info: str = "" + unavailable_reason: str = "" + + +_git_user, _git_password = os.getenv("WEBARENA_GIT_CREDENTIALS", ":").split(":") + +site_info_map: dict[WebArenaSite, WebArenaSiteInfo] = { + "gitlab": WebArenaSiteInfo( + base_url="http://git.junglegym.ai", + available=bool(_git_user and _git_password), + additional_info=( + f"To log in, use the username '{_git_user}' and password '{_git_password}'." + ), + unavailable_reason=( + "WEBARENA_GIT_CREDENTIALS not set (correctly): " + f"'{os.getenv('WEBARENA_GIT_CREDENTIALS', '')}', " + "should be USERNAME:PASSWORD." + ), + ), + "map": WebArenaSiteInfo( + base_url="http://ec2-3-131-244-37.us-east-2.compute.amazonaws.com:3000/" + ), + "reddit": WebArenaSiteInfo(base_url="http://forum.junglegym.ai"), + "shopping": WebArenaSiteInfo(base_url="http://shop.junglegym.ai"), + "shopping_admin": WebArenaSiteInfo( + base_url="http://cms.junglegym.ai/admin", + additional_info="To log in, use the username 'admin' and password 'admin1234'.", + ), + "wikipedia": WebArenaSiteInfo(base_url="http://wiki.junglegym.ai"), +} + + +def get_site_url(site: WebArenaSite) -> str: + if site not in site_info_map: + raise ValueError(f"JungleGym site '{site}' unknown, cannot resolve URL") + return site_info_map[site].base_url + + +def resolve_uri(uri: str) -> str: + """ + Resolves URIs with mock hosts, like `__WIKI__/wiki/Octopus`, with the corresponding + JungleGym site mirror host. + """ + segments = uri.split("__") + if len(segments) > 2 and (site := segments[1]).lower() in site_info_map: + return uri.replace(f"__{site}__", get_site_url(site.lower())) # type: ignore + return uri + + +class Eval(ABC): + @abstractmethod + def evaluate(self, string: str) -> bool: + ... + + @property + @abstractmethod + def description(self) -> str: + ... + + +class StringEval(BaseModel, Eval): + type: ReferenceAnswerType + + +class ExactStringMatchEval(StringEval): + type: Literal["exact_match"] = "exact_match" + reference_answer: str + + @property + def description(self) -> str: + return f"Answer must be '{self.reference_answer}'" + + def evaluate(self, string: str) -> bool: + return string == self.reference_answer + + +class FuzzyStringMatchEval(StringEval): + type: Literal["fuzzy_match"] = "fuzzy_match" + reference_answer: str + + @property + def description(self) -> str: + return f"Answer must contain something like '{self.reference_answer}'" + + def evaluate(self, string: str) -> bool: + # TODO: use LLM for matching (or something else that's flexible/robust) + return self.reference_answer.lower() in string.lower() + + +class MustIncludeStringEval(StringEval): + type: Literal["must_include"] = "must_include" + reference_answer: str + + @property + def description(self) -> str: + return f"Answer must include '{self.reference_answer}'" + + def evaluate(self, string: str) -> bool: + return self.reference_answer.lower() in string.lower() + + +class UrlMatchEval(BaseModel, Eval): + url: str + """Example: `"__WIKI__/wiki/Octopus"`""" + + @property + def description(self) -> str: + return f"Agent must navigate to '{self.url}'" + + def evaluate(self, url: str) -> bool: + return url == resolve_uri(self.url) + + +class ProgramHtmlEval(BaseModel): + url: str + locator: str + """JavaScript code that returns the value to check""" + required_contents: str + + @property + def description(self) -> str: + return ( + f"On the webpage {self.url}, " + f"`{self.locator}` should contain '{self.required_contents}'" + ) + + def evaluate(self, selenium_instance) -> bool: + result = selenium_instance.execute_script( + self.locator or "return document.body.innerHTML;" + ) + return self.required_contents in result + + +_Eval = StringEval | UrlMatchEval | ProgramHtmlEval + + +class WebArenaChallengeSpec(BaseModel): + task_id: int + sites: list[WebArenaSite] + """The sites needed to complete the task""" + start_url: str + """The full URL at which to start""" + start_url_junglegym: str + """The JungleGym site (base URL) at which to start""" + require_login: bool + require_reset: bool + storage_state: str | None + + intent: str + intent_template: str + intent_template_id: int + instantiation_dict: dict[str, str | list[str]] + + class EvalSet(BaseModel): + class StringMatchEvalSet(BaseModel): + exact_match: str | None + fuzzy_match: list[str] | None + must_include: list[str] | None + + reference_answers: StringMatchEvalSet | None + """For string_match eval, a set of criteria to judge the final answer""" + reference_answer_raw_annotation: str | None + string_note: str | None + annotation_note: str | None + + reference_url: str | None + """For url_match eval, the last URL that should be visited""" + url_note: str | None + + program_html: list[ProgramHtmlEval] + """For program_html eval, a list of criteria to judge the site state by""" + + eval_types: list[EvalType] + + @validator("eval_types") + def check_eval_parameters(cls, v: list[EvalType], values): + if "string_match" in v and not values.get("reference_answers"): + raise ValueError("'string_match' eval_type requires reference_answers") + if "url_match" in v and not values.get("reference_url"): + raise ValueError("'url_match' eval_type requires reference_url") + if "program_html" in v and not values.get("program_html"): + raise ValueError( + "'program_html' eval_type requires at least one program_html eval" + ) + return v + + @property + def evaluators(self) -> list[_Eval]: + evaluators: list[_Eval] = [] + if self.reference_answers: + if self.reference_answers.exact_match: + evaluators.append( + ExactStringMatchEval( + reference_answer=self.reference_answers.exact_match + ) + ) + if self.reference_answers.fuzzy_match: + evaluators.extend( + FuzzyStringMatchEval(reference_answer=a) + for a in self.reference_answers.fuzzy_match + ) + if self.reference_answers.must_include: + evaluators.extend( + MustIncludeStringEval(reference_answer=a) + for a in self.reference_answers.must_include + ) + if self.reference_url: + evaluators.append(UrlMatchEval(url=self.reference_url)) + evaluators.extend(self.program_html) + return evaluators + + eval: EvalSet + """Evaluation criteria by which to judge the agent's performance""" + + @property + def assignment_for_agent(self): + sites = [get_site_url(s) for s in self.sites] + nav_constraint = ( + f"You are ONLY allowed to access URLs in {' and '.join(sites)}." + ) + + return ( + f"First of all, go to {self.start_url}. " + f"{self.intent.rstrip('.')}.\n" + f"{nav_constraint}" + ) + + +class WebArenaChallenge(BaseChallenge): + _spec: ClassVar[WebArenaChallengeSpec] + + SOURCE_URI_PREFIX = "__JUNGLEGYM__/webarena/tasks/" + SOURCE_URI_TEMPLATE = f"{SOURCE_URI_PREFIX}{{task_id}}" + + @classmethod + def from_source_uri(cls, source_uri: str) -> type["WebArenaChallenge"]: + if not source_uri.startswith(cls.SOURCE_URI_PREFIX): + raise ValueError(f"Invalid source_uri for WebArenaChallenge: {source_uri}") + + source_url = source_uri.replace( + cls.SOURCE_URI_PREFIX, + "https://api.junglegym.ai/get_webarena_by_task_id?task_id=", + ) + results = requests.get(source_url).json()["data"] + if not results: + raise ValueError(f"Could not fetch challenge {source_uri}") + return cls.from_challenge_spec(WebArenaChallengeSpec.parse_obj(results[0])) + + @classmethod + def from_challenge_spec( + cls, spec: WebArenaChallengeSpec + ) -> type["WebArenaChallenge"]: + challenge_info = ChallengeInfo( + eval_id=f"junglegym-webarena-{spec.task_id}", + name=f"WebArenaTask_{spec.task_id}", + task=spec.assignment_for_agent, + category=[ + Category.GENERALIST, + Category.WEB, + ], # TODO: make categories more specific + reference_answer=spec.eval.reference_answer_raw_annotation, + source_uri=cls.SOURCE_URI_TEMPLATE.format(task_id=spec.task_id), + ) + return type( + f"Test{challenge_info.name}", + (WebArenaChallenge,), + { + "info": challenge_info, + "_spec": spec, + }, + ) + + @classmethod + def evaluate_answer(cls, answer: str) -> list[tuple[_Eval, EvalResult]]: + results: list[tuple[_Eval, EvalResult]] = [] + for evaluator in cls._spec.eval.evaluators: + if isinstance(evaluator, StringEval): # string_match + results.append( + ( + evaluator, + EvalResult( + result=answer, + result_source="step_output", + score=evaluator.evaluate(answer), + passed=evaluator.evaluate(answer), + ), + ) + ) + return results + + @classmethod + def evaluate_step_result(cls, step: Step) -> list[tuple[_Eval, EvalResult]]: + assert step.output + eval_results = cls.evaluate_answer(step.output) + for eval in cls._spec.eval.evaluators: + if isinstance(eval, UrlMatchEval): + passed = resolve_uri(eval.url) in step.output # HACK: url_match bodge + eval_results.append( + ( + eval, + EvalResult( + result=step.output, + result_source="step_output", + score=1.0 if passed else 0.0, + passed=passed, + ), + ) + ) + # TODO: add support for program_html evals + return eval_results + + @classmethod + async def evaluate_task_state( + cls, agent: AgentApi, task_id: str + ) -> list[EvalResult]: + steps: list[Step] = (await agent.list_agent_task_steps(task_id)).steps + + eval_results_per_step = [cls.evaluate_step_result(step) for step in steps] + # Get the column aggregate (highest scored EvalResult for each Eval) + # from the matrix of EvalResults per step. + return [ + max(step_results_for_eval, key=lambda r: r[1].score)[1] + for step_results_for_eval in zip(*eval_results_per_step) + ] + + @pytest.mark.asyncio + async def test_method( + self, + config: AgentBenchmarkConfig, + request: pytest.FixtureRequest, + i_attempt: int, + ) -> None: + if os.environ.get("HELICONE_API_KEY"): + from helicone.lock import HeliconeLockManager + + HeliconeLockManager.write_custom_property("challenge", self.info.name) + + timeout = 120 + if request.config.getoption("--nc"): + timeout = 100000 + elif cutoff := request.config.getoption("--cutoff"): + timeout = int(cutoff) + + timed_out = None + eval_results_per_step: list[list[tuple[_Eval, EvalResult]]] = [] + try: + async for step in self.run_challenge(config, timeout): + if not step.output: + logger.warn(f"Step has no output: {step}") + continue + step_eval_results = self.evaluate_step_result(step) + logger.debug(f"Intermediary results: {step_eval_results}") + eval_results_per_step.append(step_eval_results) + if step.is_last: + request.node.user_properties.append( + ( + "answers", + step.output + if request.config.getoption("--keep-answers") + else None, + ) + ) + timed_out = False + except TimeoutError: + timed_out = True + request.node.user_properties.append(("timed_out", timed_out)) + + # Get the column aggregate (highest score for each Eval) + # from the matrix of EvalResults per step. + evals_results = [ + max(step_results_for_eval, key=lambda r: r[1].score) + for step_results_for_eval in zip(*eval_results_per_step) + ] + + if not evals_results: + if timed_out: + raise TimeoutError("Timed out, no results to evaluate") + else: + raise ValueError("No results to evaluate") + + request.node.user_properties.append( + ("scores", [r[1].score for r in evals_results]) + ) + + # FIXME: arbitrary threshold + assert all(r[1].score > 0.9 for r in evals_results), ( + "Scores insufficient:\n\n" + if not timed_out + else "Timed out; scores insufficient:\n\n" + ) + "\n".join(f"{repr(r[0])}\n -> {repr(r[1])}" for r in evals_results) + + +def load_webarena_challenges() -> Iterator[type[WebArenaChallenge]]: + logger.info("Loading WebArena challenges...") + + for site, info in site_info_map.items(): + if not info.available: + logger.warning( + f"JungleGym site '{site}' is not available: {info.unavailable_reason} " + "Skipping all challenges which use this site." + ) + + # response = requests.get("https://api.junglegym.ai/get_full_webarena_dataset") + # challenge_dicts = response.json()["data"] + + # Until the full WebArena challenge set is supported, use a hand-picked selection + import json + from pathlib import Path + + challenge_dicts = json.loads( + (Path(__file__).parent / "webarena_selection.json").read_bytes() + ) + + logger.debug( + "Fetched WebArena dataset. " + f"Constructing {len(challenge_dicts)} WebArenaChallenges..." + ) + loaded = 0 + failed = 0 + skipped = 0 + for entry in challenge_dicts: + try: + challenge_spec = WebArenaChallengeSpec.parse_obj(entry) + for site in challenge_spec.sites: + site_info = site_info_map.get(site) + if site_info is None: + logger.warning( + f"WebArena task {challenge_spec.task_id} requires unknown site " + f"'{site}'; skipping..." + ) + break + if not site_info.available: + logger.debug( + f"WebArena task {challenge_spec.task_id} requires unavailable " + f"site '{site}'; skipping..." + ) + break + else: + yield WebArenaChallenge.from_challenge_spec(challenge_spec) + loaded += 1 + continue + skipped += 1 + except ValidationError as e: + failed += 1 + logger.warning(f"Error validating WebArena challenge entry: {entry}") + logger.warning(f"Error details: {e}") + logger.info( + "Loading WebArena challenges complete: " + f"loaded {loaded}, skipped {skipped}. {failed} challenge failed to load." + ) diff --git a/benchmark/agbenchmark/challenges/webarena_selection.json b/benchmark/agbenchmark/challenges/webarena_selection.json new file mode 100644 index 000000000..e35a27d37 --- /dev/null +++ b/benchmark/agbenchmark/challenges/webarena_selection.json @@ -0,0 +1,523 @@ +[ + { + "sites": [ + "shopping_admin" + ], + "task_id": 0, + "require_login": true, + "storage_state": "./.auth/shopping_admin_state.json", + "start_url": "http://cms.junglegym.ai/admin", + "geolocation": "NaN", + "intent_template": "What is the top-{{n}} best-selling product in {{year}}", + "instantiation_dict": { + "n": 1, + "year": 2022 + }, + "intent": "What is the top-1 best-selling product in 2022", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "exact_match": "Quest Lumaflex™ Band" + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "Quest Lumaflex™ Band" + }, + "intent_template_id": 279, + "string_note": null, + "start_url_junglegym": "http://cms.junglegym.ai/admin" + }, + { + "sites": [ + "shopping_admin" + ], + "task_id": 4, + "require_login": true, + "storage_state": "./.auth/shopping_admin_state.json", + "start_url": "http://cms.junglegym.ai/admin", + "geolocation": "NaN", + "intent_template": "What are the top-{{n}} best-selling product in {{period}}", + "instantiation_dict": { + "n": 3, + "period": "Jan 2023" + }, + "intent": "What are the top-3 best-selling product in Jan 2023", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "Impulse Duffle", + "Overnight Duffle", + "Hawkeye Yoga Short-32-Blue" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "Impulse Duffle, Overnight Duffle, Hawkeye Yoga Short-32-Blue" + }, + "intent_template_id": 279, + "string_note": null, + "start_url_junglegym": "http://cms.junglegym.ai/admin" + }, + { + "sites": [ + "shopping_admin" + ], + "task_id": 6, + "require_login": true, + "storage_state": "./.auth/shopping_admin_state.json", + "start_url": "http://cms.junglegym.ai/admin", + "geolocation": "NaN", + "intent_template": "What are the top-{{n}} best-selling product in {{year}}", + "instantiation_dict": { + "n": 5, + "year": 2023 + }, + "intent": "What are the top-5 best-selling product in 2023", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "Sprite Yoga Strap 6 foot", + "Overnight Duffle", + "Ida Workout Parachute Pant-29-Purple", + "Hawkeye Yoga Short-32-Blue", + "Sprite Stasis Ball 65 cm" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "Sprite Yoga Strap 6 foot, Overnight Duffle, Ida Workout Parachute Pant-29-Purple, Hawkeye Yoga Short-32-Blue, Sprite Stasis Ball 65 cm" + }, + "intent_template_id": 279, + "string_note": null, + "start_url_junglegym": "http://cms.junglegym.ai/admin" + }, + { + "sites": [ + "shopping_admin" + ], + "task_id": 11, + "require_login": true, + "storage_state": "./.auth/shopping_admin_state.json", + "start_url": "http://cms.junglegym.ai/admin", + "geolocation": "NaN", + "intent_template": "Tell me the the number of reviews that our store received by far that mention term \"{{term}}\"", + "instantiation_dict": { + "term": "disappointed" + }, + "intent": "Tell me the the number of reviews that our store received by far that mention term \"disappointed\"", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "6" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "6" + }, + "intent_template_id": 288, + "string_note": null, + "start_url_junglegym": "http://cms.junglegym.ai/admin" + }, + { + "sites": [ + "shopping" + ], + "task_id": 21, + "require_login": true, + "storage_state": "./.auth/shopping_state.json", + "start_url": "http://shop.junglegym.ai/6s-wireless-headphones-over-ear-noise-canceling-hi-fi-bass-foldable-stereo-wireless-kid-headsets-earbuds-with-built-in-mic-micro-sd-tf-fm-for-iphone-samsung-ipad-pc-black-gold.html", + "geolocation": "NaN", + "intent_template": "List out reviewers, if exist, who mention about {{description}}", + "instantiation_dict": { + "description": "ear cups being small" + }, + "intent": "List out reviewers, if exist, who mention about ear cups being small", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "Joseph Brzezinski", + "Catso", + "Dibbins", + "Anglebert Dinkherhump", + "Michelle Davis" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "Joseph Brzezinski, Catso, Dibbins, Anglebert Dinkherhump, Michelle Davis" + }, + "intent_template_id": 222, + "string_note": null, + "start_url_junglegym": "http://shop.junglegym.ai" + }, + { + "sites": [ + "reddit" + ], + "task_id": 27, + "require_login": true, + "storage_state": "./.auth/reddit_state.json", + "start_url": "http://forum.junglegym.ai", + "geolocation": "NaN", + "intent_template": "Tell me the count of comments that have received more downvotes than upvotes for the user who made the latest post on the {{forum}} forum.", + "instantiation_dict": { + "forum": "Showerthoughts" + }, + "intent": "Tell me the count of comments that have received more downvotes than upvotes for the user who made the latest post on the Showerthoughts forum.", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "0" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "0" + }, + "intent_template_id": 33, + "string_note": null, + "start_url_junglegym": "http://forum.junglegym.ai" + }, + { + "sites": [ + "shopping_admin" + ], + "task_id": 43, + "require_login": true, + "storage_state": "./.auth/shopping_admin_state.json", + "start_url": "http://cms.junglegym.ai/admin", + "geolocation": "NaN", + "intent_template": "List the top {{n}} search terms in my store", + "instantiation_dict": { + "n": "3" + }, + "intent": "List the top 3 search terms in my store", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "hollister", + "Joust Bag", + "Antonia Race Tank" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "hollister, Joust Bag, Antonia Race Tank" + }, + "intent_template_id": 285, + "string_note": null, + "start_url_junglegym": "http://cms.junglegym.ai/admin" + }, + { + "sites": [ + "shopping_admin" + ], + "task_id": 77, + "require_login": true, + "storage_state": "./.auth/shopping_admin_state.json", + "start_url": "http://cms.junglegym.ai/admin", + "geolocation": "NaN", + "intent_template": "What is the total count of {{status}} reviews amongst all the reviews?", + "instantiation_dict": { + "status": "Pending" + }, + "intent": "What is the total count of Pending reviews amongst all the reviews?", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "5" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "5" + }, + "intent_template_id": 277, + "string_note": null, + "start_url_junglegym": "http://cms.junglegym.ai/admin" + }, + { + "sites": [ + "shopping_admin" + ], + "task_id": 95, + "require_login": true, + "storage_state": "./.auth/shopping_admin_state.json", + "start_url": "http://cms.junglegym.ai/admin", + "geolocation": "NaN", + "intent_template": "Telll me the grand total of invoice {{id}}.", + "instantiation_dict": { + "id": "000000002" + }, + "intent": "Telll me the grand total of invoice 000000002.", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "39.64" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "$39.64" + }, + "intent_template_id": 274, + "string_note": null, + "start_url_junglegym": "http://cms.junglegym.ai/admin" + }, + { + "sites": [ + "shopping_admin" + ], + "task_id": 107, + "require_login": true, + "storage_state": "./.auth/shopping_admin_state.json", + "start_url": "http://cms.junglegym.ai/admin", + "geolocation": "NaN", + "intent_template": "Presents the monthly count of successful orders {{period}} in MM:COUNT format", + "instantiation_dict": { + "period": "from May to December 2022" + }, + "intent": "Presents the monthly count of successful orders from May to December 2022 in MM:COUNT format", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "fuzzy_match": [ + "May: 8 orders", + "June: 13 orders", + "July: 9 orders", + "August: 8 orders", + "Sepetember: 10 orders", + "October: 4 orders", + "November: 5 orders", + "December: 10 orders" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "May: 8 orders June: 13 orders July: 9 orders August: 8 orders Sepetember: 10 orders Octorbor: 4 orders November: 5 orders December: 10 orders " + }, + "intent_template_id": 270, + "string_note": null, + "start_url_junglegym": "http://cms.junglegym.ai/admin" + }, + { + "sites": [ + "shopping_admin" + ], + "task_id": 112, + "require_login": true, + "storage_state": "./.auth/shopping_admin_state.json", + "start_url": "http://cms.junglegym.ai/admin", + "geolocation": "NaN", + "intent_template": "Show me the customers who have expressed dissatisfaction with {{product}}?", + "instantiation_dict": { + "product": "Circe fleece" + }, + "intent": "Show me the customers who have expressed dissatisfaction with Circe fleece?", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "exact_match": "Hannah Lim" + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "Hannah Lim" + }, + "intent_template_id": 245, + "string_note": null, + "start_url_junglegym": "http://cms.junglegym.ai/admin" + }, + { + "sites": [ + "shopping" + ], + "task_id": 124, + "require_login": true, + "storage_state": "./.auth/shopping_state.json", + "start_url": "http://shop.junglegym.ai", + "geolocation": "NaN", + "intent_template": "What is the price range of {{product}} in the One Stop Market?", + "instantiation_dict": { + "product": "wireless earphone" + }, + "intent": "What is the price range of wireless earphone in the One Stop Market?", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "0.14", + "745.00" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "$0.14 - $745.00" + }, + "intent_template_id": 159, + "string_note": null, + "start_url_junglegym": "http://shop.junglegym.ai" + }, + { + "sites": [ + "gitlab" + ], + "task_id": 134, + "require_login": true, + "storage_state": "./.auth/gitlab_state.json", + "start_url": "http://git.junglegym.ai", + "geolocation": "NaN", + "intent_template": "How many commits did {{user}} make to {{repo}} on {{date}}?", + "instantiation_dict": { + "user": "kilian", + "repo": "a11yproject", + "date": "3/1/2023" + }, + "intent": "How many commits did kilian make to a11yproject on 3/1/2023?", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "0" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "0" + }, + "intent_template_id": 322, + "string_note": null, + "start_url_junglegym": "http://git.junglegym.ai" + }, + { + "sites": [ + "gitlab" + ], + "task_id": 136, + "require_login": true, + "storage_state": "./.auth/gitlab_state.json", + "start_url": "http://git.junglegym.ai", + "geolocation": "NaN", + "intent_template": "How many commits did {{user}} make to {{repo}} on {{date}}?", + "instantiation_dict": { + "user": "Steven Woodson", + "repo": "a11y-webring.club", + "date": "2/6/2023" + }, + "intent": "How many commits did Steven Woodson make to a11y-webring.club on 2/6/2023?", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "5" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "5" + }, + "intent_template_id": 322, + "string_note": null, + "start_url_junglegym": "http://git.junglegym.ai" + }, + { + "sites": [ + "shopping" + ], + "task_id": 163, + "require_login": true, + "storage_state": "./.auth/shopping_state.json", + "start_url": "http://shop.junglegym.ai/ostent-16gb-memory-card-stick-storage-for-sony-ps-vita-psv1000-2000-pch-z081-z161-z321-z641.html", + "geolocation": "NaN", + "intent_template": "What are the main criticisms of this product? Please extract the relevant sentences.", + "instantiation_dict": {}, + "intent": "What are the main criticisms of this product? Please extract the relevant sentences.", + "require_reset": false, + "eval": { + "eval_types": [ + "string_match" + ], + "reference_answers": { + "must_include": [ + "I ordered the 16gb but I only got 14 gigs even though I formatted the card", + "The memory card is kind of slow on games and downloads", + "No original packaging It's used and the previous owners data has not been erased", + "The product is a legit sony hardware that have been owned by someone else before", + "The media could not be loaded", + "I could not format the card so I wasn’t able to use it for my VITA" + ] + }, + "reference_url": "", + "program_html": [], + "string_note": "", + "reference_answer_raw_annotation": "I ordered the 16gb but I only got 14 gigs even though I formatted the card. The memory card is kind of slow on games and downloads. No original packaging It's used and the previous owners data has not been erased. The product is a legit sony hardware that have been owned by someone else before The media could not be loaded. I could not format the card so I wasn’t able to use it for my VITA" + }, + "intent_template_id": 136, + "string_note": null, + "start_url_junglegym": "http://shop.junglegym.ai" + } +] diff --git a/benchmark/agbenchmark/config.py b/benchmark/agbenchmark/config.py new file mode 100644 index 000000000..7605b86b5 --- /dev/null +++ b/benchmark/agbenchmark/config.py @@ -0,0 +1,119 @@ +import json +import sys +from datetime import datetime +from pathlib import Path +from typing import Optional + +from pydantic import BaseSettings, Field + + +def _calculate_info_test_path(base_path: Path, benchmark_start_time: datetime) -> Path: + """ + Calculates the path to the directory where the test report will be saved. + """ + # Ensure the reports path exists + base_path.mkdir(parents=True, exist_ok=True) + + # Get current UTC date-time stamp + date_stamp = benchmark_start_time.strftime("%Y%m%dT%H%M%S") + + # Default run name + run_name = "full_run" + + # Map command-line arguments to their respective labels + arg_labels = { + "--test": None, + "--category": None, + "--maintain": "maintain", + "--improve": "improve", + "--explore": "explore", + } + + # Identify the relevant command-line argument + for arg, label in arg_labels.items(): + if arg in sys.argv: + test_arg = sys.argv[sys.argv.index(arg) + 1] if label is None else None + run_name = arg.strip("--") + if test_arg: + run_name = f"{run_name}_{test_arg}" + break + + # Create the full new directory path with ISO standard UTC date-time stamp + report_path = base_path / f"{date_stamp}_{run_name}" + + # Ensure the new directory is created + # FIXME: this is not a desirable side-effect of loading the config + report_path.mkdir(exist_ok=True) + + return report_path + + +class AgentBenchmarkConfig(BaseSettings, extra="allow"): + """ + Configuration model and loader for the AGBenchmark. + + Projects that want to use AGBenchmark should contain an agbenchmark_config folder + with a config.json file that - at minimum - specifies the `host` at which the + subject application exposes an Agent Protocol compliant API. + """ + + agbenchmark_config_dir: Path = Field(..., exclude=True) + """Path to the agbenchmark_config folder of the subject agent application.""" + + categories: list[str] | None = None + """Categories to benchmark the agent for. If omitted, all categories are assumed.""" + + host: str + """Host (scheme://address:port) of the subject agent application.""" + + @classmethod + def load(cls, config_dir: Optional[Path] = None) -> "AgentBenchmarkConfig": + config_dir = config_dir or cls.find_config_folder() + with (config_dir / "config.json").open("r") as f: + return cls( + agbenchmark_config_dir=config_dir, + **json.load(f), + ) + + @staticmethod + def find_config_folder(for_dir: Path = Path.cwd()) -> Path: + """ + Find the closest ancestor folder containing an agbenchmark_config folder, + and returns the path of that agbenchmark_config folder. + """ + current_directory = for_dir + while current_directory != Path("/"): + if (path := current_directory / "agbenchmark_config").exists(): + if (path / "config.json").is_file(): + return path + current_directory = current_directory.parent + raise FileNotFoundError( + "No 'agbenchmark_config' directory found in the path hierarchy." + ) + + @property + def config_file(self) -> Path: + return self.agbenchmark_config_dir / "config.json" + + @property + def reports_folder(self) -> Path: + return self.agbenchmark_config_dir / "reports" + + def get_report_dir(self, benchmark_start_time: datetime) -> Path: + return _calculate_info_test_path(self.reports_folder, benchmark_start_time) + + @property + def regression_tests_file(self) -> Path: + return self.reports_folder / "regression_tests.json" + + @property + def success_rate_file(self) -> Path: + return self.reports_folder / "success_rate.json" + + @property + def challenges_already_beaten_file(self) -> Path: + return self.agbenchmark_config_dir / "challenges_already_beaten.json" + + @property + def temp_folder(self) -> Path: + return self.agbenchmark_config_dir / "temp_folder" diff --git a/benchmark/agbenchmark/conftest.py b/benchmark/agbenchmark/conftest.py index 33b0809ac..7e417a603 100644 --- a/benchmark/agbenchmark/conftest.py +++ b/benchmark/agbenchmark/conftest.py @@ -1,282 +1,189 @@ import contextlib import json +import logging import os import shutil -import sys import threading import time -from pathlib import Path # noqa -from typing import Any, Generator +from pathlib import Path +from typing import Generator import pytest -from agbenchmark.__main__ import TEMP_FOLDER_ABS_PATH +from agbenchmark.challenges import OPTIONAL_CATEGORIES, BaseChallenge +from agbenchmark.config import AgentBenchmarkConfig +from agbenchmark.reports.processing.report_types import Test +from agbenchmark.reports.ReportManager import RegressionTestsTracker from agbenchmark.reports.reports import ( - finalize_reports, - generate_single_call_report, + add_test_result_to_report, + make_empty_test_report, session_finish, ) -from agbenchmark.utils.data_types import AgentBenchmarkConfig +from agbenchmark.utils.data_types import Category GLOBAL_TIMEOUT = ( 1500 # The tests will stop after 25 minutes so we can send the reports. ) +agbenchmark_config = AgentBenchmarkConfig.load() +logger = logging.getLogger(__name__) + pytest_plugins = ["agbenchmark.utils.dependencies"] collect_ignore = ["challenges"] -suite_reports: dict[str, list] = {} - - -def load_config_from_request(request: Any) -> AgentBenchmarkConfig: - """ - This function loads the configuration for the agent benchmark from a given request. - - Args: - request (Any): The request object from which the agent benchmark configuration is to be loaded. - - Returns: - AgentBenchmarkConfig: The loaded agent benchmark configuration. - - Raises: - json.JSONDecodeError: If the benchmark configuration file is not a valid JSON file. - """ - agent_benchmark_config_path = Path.cwd() / "agbenchmark_config" / "config.json" - try: - with open(agent_benchmark_config_path, "r") as f: - agent_benchmark_config = AgentBenchmarkConfig(**json.load(f)) - agent_benchmark_config.agent_benchmark_config_path = ( - agent_benchmark_config_path - ) - return agent_benchmark_config - except json.JSONDecodeError: - print("Error: benchmark_config.json is not a valid JSON file.") - raise @pytest.fixture(scope="module") -def config(request: Any) -> Any: - """ - This pytest fixture is responsible for loading the agent benchmark configuration from a given request. - This fixture is scoped to the module level, meaning it's invoked once per test module. - - Args: - request (Any): The request object from which the agent benchmark configuration is to be loaded. - - Returns: - Any: The loaded configuration dictionary. - - Raises: - json.JSONDecodeError: If the benchmark configuration file is not a valid JSON file. - """ - config = {} - agent_benchmark_config_path = Path.cwd() / "agbenchmark_config" / "config.json" - try: - with open(agent_benchmark_config_path, "r") as f: - agent_benchmark_config = AgentBenchmarkConfig(**json.load(f)) - agent_benchmark_config.agent_benchmark_config_path = ( - agent_benchmark_config_path - ) - except json.JSONDecodeError: - print("Error: benchmark_config.json is not a valid JSON file.") - raise - - config["AgentBenchmarkConfig"] = agent_benchmark_config - - return config +def config() -> AgentBenchmarkConfig: + return agbenchmark_config @pytest.fixture(autouse=True) -def temp_folder() -> Generator[str, None, None]: +def temp_folder() -> Generator[Path, None, None]: """ - This pytest fixture is responsible for setting up and tearing down the temporary folder for each test. + Pytest fixture that sets up and tears down the temporary folder for each test. It is automatically used in every test due to the 'autouse=True' parameter. - It is used in order to let agbenchmark store files so they can then be evaluated. """ # create output directory if it doesn't exist - if not os.path.exists(TEMP_FOLDER_ABS_PATH): - os.makedirs(TEMP_FOLDER_ABS_PATH, exist_ok=True) + if not os.path.exists(agbenchmark_config.temp_folder): + os.makedirs(agbenchmark_config.temp_folder, exist_ok=True) - yield + yield agbenchmark_config.temp_folder # teardown after test function completes if not os.getenv("KEEP_TEMP_FOLDER_FILES"): - for filename in os.listdir(TEMP_FOLDER_ABS_PATH): - file_path = os.path.join(TEMP_FOLDER_ABS_PATH, filename) + for filename in os.listdir(agbenchmark_config.temp_folder): + file_path = os.path.join(agbenchmark_config.temp_folder, filename) try: if os.path.isfile(file_path) or os.path.islink(file_path): os.unlink(file_path) elif os.path.isdir(file_path): shutil.rmtree(file_path) except Exception as e: - print(f"Failed to delete {file_path}. Reason: {e}") + logger.warning(f"Failed to delete {file_path}. Reason: {e}") -def pytest_addoption(parser: Any) -> None: +def pytest_addoption(parser: pytest.Parser) -> None: """ - This function is a pytest hook that is called to add command-line options. - It is used to add custom command-line options that are specific to the agent benchmark tests. - These options can be used to control the behavior of the tests. - The "--mock" option is used to run the tests in mock mode. - The "--host" option is used to specify the host for the tests. - The "--category" option is used to run only tests of a specific category. - The "--nc" option is used to run the tests without caching. - The "--cutoff" option is used to specify a cutoff time for the tests. - The "--improve" option is used to run only the tests that are marked for improvement. - The "--maintain" option is used to run only the tests that are marked for maintenance. - The "--explore" option is used to run the tests in exploration mode. - The "--test" option is used to run a specific test. - The "--no_dep" option is used to run the tests without dependencies. - The "--keep_answers" option is used to keep the answers of the tests. + Pytest hook that adds command-line options to the `pytest` command. + The added options are specific to agbenchmark and control its behavior: + * `--mock` is used to run the tests in mock mode. + * `--host` is used to specify the host for the tests. + * `--category` is used to run only tests of a specific category. + * `--nc` is used to run the tests without caching. + * `--cutoff` is used to specify a cutoff time for the tests. + * `--improve` is used to run only the tests that are marked for improvement. + * `--maintain` is used to run only the tests that are marked for maintenance. + * `--explore` is used to run the tests in exploration mode. + * `--test` is used to run a specific test. + * `--no-dep` is used to run the tests without dependencies. + * `--keep-answers` is used to keep the answers of the tests. Args: - parser (Any): The parser object to which the command-line options are added. + parser: The Pytest CLI parser to which the command-line options are added. """ - parser.addoption("--no_dep", action="store_true", default=False) - parser.addoption("--mock", action="store_true", default=False) - parser.addoption("--host", action="store_true", default=None) - parser.addoption("--nc", action="store_true", default=False) - parser.addoption("--cutoff", action="store_true", default=False) - parser.addoption("--category", action="store_true", default=False) - parser.addoption("--test", action="store_true", default=None) - parser.addoption("--improve", action="store_true", default=False) - parser.addoption("--maintain", action="store_true", default=False) - parser.addoption("--explore", action="store_true", default=False) - parser.addoption("--keep-answers", action="store_true", default=False) + parser.addoption("-N", "--attempts", action="store") + parser.addoption("--no-dep", action="store_true") + parser.addoption("--mock", action="store_true") + parser.addoption("--host", default=None) + parser.addoption("--nc", action="store_true") + parser.addoption("--cutoff", action="store") + parser.addoption("--category", action="append") + parser.addoption("--test", action="append") + parser.addoption("--improve", action="store_true") + parser.addoption("--maintain", action="store_true") + parser.addoption("--explore", action="store_true") + parser.addoption("--keep-answers", action="store_true") + + +def pytest_configure(config: pytest.Config) -> None: + # Register category markers to prevent "unknown marker" warnings + for category in Category: + config.addinivalue_line("markers", f"{category.value}: {category}") @pytest.fixture(autouse=True) -def check_regression(request: Any) -> None: +def check_regression(request: pytest.FixtureRequest) -> None: """ - This pytest fixture is responsible for checking if a test is a regression test. - It is automatically used in every test due to the 'autouse=True' parameter. - The test name and the agent benchmark configuration are retrieved from the request object. - The regression reports are loaded from the path specified in the agent benchmark configuration. - If the "--improve" option is used and the test name exists in the regression tests, the test is skipped. - If the "--maintain" option is used and the test name does not exist in the regression tests, the test is also skipped. + Fixture that checks for every test if it should be treated as a regression test, + and whether to skip it based on that. + + The test name is retrieved from the `request` object. Regression reports are loaded + from the path specified in the benchmark configuration. + + Effect: + * If the `--improve` option is used and the current test is considered a regression + test, it is skipped. + * If the `--maintain` option is used and the current test is not considered a + regression test, it is also skipped. Args: - request (Any): The request object from which the test name and the agent benchmark configuration are retrieved. + request: The request object from which the test name and the benchmark + configuration are retrieved. """ - test_name = request.node.parent.name - agent_benchmark_config = load_config_from_request(request) - with contextlib.suppress(Exception): - test = agent_benchmark_config.get_regression_reports_path() - print(f"Found a test {test}") - data = json.loads(test) - print(f"Got its data {data}") - challenge_location = getattr(request.node.parent.cls, "CHALLENGE_LOCATION", "") + with contextlib.suppress(FileNotFoundError): + rt_tracker = RegressionTestsTracker(agbenchmark_config.regression_tests_file) + test_name = request.node.parent.name + challenge_location = getattr(request.node.parent.cls, "CHALLENGE_LOCATION", "") skip_string = f"Skipping {test_name} at {challenge_location}" # Check if the test name exists in the regression tests - if request.config.getoption("--improve") and data.get(test_name, None): + is_regression_test = rt_tracker.has_regression_test(test_name) + if request.config.getoption("--improve") and is_regression_test: pytest.skip(f"{skip_string} because it's a regression test") - elif request.config.getoption("--maintain") and not data.get(test_name, None): + elif request.config.getoption("--maintain") and not is_regression_test: pytest.skip(f"{skip_string} because it's not a regression test") -# this is to get the challenge_data from every test -@pytest.fixture(autouse=True) -def challenge_data(request: Any) -> None: - """ - This pytest fixture is responsible for providing the challenge data for each test. - It is automatically used in every test due to the 'autouse=True' parameter. - The challenge data is retrieved from the request object's parameters. - This fixture is essential for the pytest system as it provides the necessary data for each test. - - Args: - request (Any): The request object from which the challenge data is retrieved. - - Returns: - None: The challenge data is directly passed to the test function and does not need to be returned. - """ - print(f"REQUEST DATA HERE {request}") - return request.param - - @pytest.fixture(autouse=True, scope="session") -def mock(request: Any) -> None: +def mock(request: pytest.FixtureRequest) -> bool: """ - This pytest fixture is responsible for retrieving the value of the "--mock" command-line option. - It is automatically used in every test session due to the 'autouse=True' parameter and 'session' scope. - The "--mock" option is used to run the tests in mock mode. - This fixture is essential for the pytest system as it provides the necessary command-line option value for each test session. + Pytest fixture that retrieves the value of the `--mock` command-line option. + The `--mock` option is used to run the tests in mock mode. Args: - request (Any): The request object from which the "--mock" option value is retrieved. + request: The `pytest.FixtureRequest` from which the `--mock` option value + is retrieved. Returns: - None: The "--mock" option value is directly passed to the test session and does not need to be returned. + bool: Whether `--mock` is set for this session. """ return request.config.getoption("--mock") -@pytest.fixture(autouse=True, scope="function") -def timer(request: Any) -> Any: - """ - This pytest fixture is responsible for timing the execution of each test. - It is automatically used in every test due to the 'autouse=True' parameter and 'function' scope. - At the start of each test, it records the current time. - After the test function completes, it calculates the run time and appends it to the test node's user properties. - This allows the run time of each test to be accessed later for reporting or analysis. - - Args: - request (Any): The request object from which the test node is retrieved. - - Yields: - None: Control is yielded back to the test function. - """ - start_time = time.time() - yield - run_time = time.time() - start_time - request.node.user_properties.append(("run_time", run_time)) +test_reports: dict[str, Test] = {} -def pytest_runtest_makereport(item: Any, call: Any) -> None: +def pytest_runtest_makereport(item: pytest.Item, call: pytest.CallInfo) -> None: """ - This function is a pytest hook that is called when a test report is being generated. + Pytest hook that is called when a test report is being generated. It is used to generate and finalize reports for each test. Args: - item (Any): The test item for which the report is being generated. - call (Any): The call object from which the test result is retrieved. + item: The test item for which the report is being generated. + call: The call object from which the test result is retrieved. """ - challenge_data = item.funcargs.get("challenge_data", None) + challenge: type[BaseChallenge] = item.cls # type: ignore + challenge_id = challenge.info.eval_id - print(f"pytest_runtest_makereport Challenge data: {challenge_data}") + if challenge_id not in test_reports: + test_reports[challenge_id] = make_empty_test_report(challenge.info) - if not challenge_data: - # this will only happen for dummy dependency setup tests - return - - challenge_location: str = getattr(item.cls, "CHALLENGE_LOCATION", "") - - flags = ( - "--test" in sys.argv - or "--maintain" in sys.argv - or "--improve" in sys.argv - or "--explore" in sys.argv - ) - - if call.when == "call": - answers = getattr(item, "answers", None) - challenge_location: str = getattr(item.cls, "CHALLENGE_LOCATION", "") + if call.when == "setup": test_name = item.nodeid.split("::")[1] - item.test_name = test_name + item.user_properties.append(("test_name", test_name)) - generate_single_call_report( - item, call, challenge_data, answers, challenge_location, test_name + if call.when == "call": + add_test_result_to_report( + test_reports[challenge_id], item, call, agbenchmark_config ) - if call.when == "teardown": - finalize_reports(item, challenge_data) - def timeout_monitor(start_time: int) -> None: """ - This function is responsible for monitoring the total execution time of the test suite. - It runs in a separate thread and checks every second if the total execution time has exceeded the global timeout. - If the global timeout is exceeded, it terminates the pytest session with a specific return code. + Function that limits the total execution time of the test suite. + This function is supposed to be run in a separate thread and calls `pytest.exit` + if the total execution time has exceeded the global timeout. Args: start_time (int): The start time of the test suite. @@ -287,14 +194,11 @@ def timeout_monitor(start_time: int) -> None: pytest.exit("Test suite exceeded the global timeout", returncode=1) -def pytest_sessionstart(session: Any) -> None: +def pytest_sessionstart(session: pytest.Session) -> None: """ - This function is a pytest hook that is called at the start of the test session. - It starts the timeout monitor in a separate thread. - The timeout monitor checks if the total execution time of the test suite has exceeded the global timeout. + Pytest hook that is called at the start of a test session. - Args: - session (Any): The pytest session object. + Sets up and runs a `timeout_monitor` in a separate thread. """ start_time = time.time() t = threading.Thread(target=timeout_monitor, args=(start_time,)) @@ -302,99 +206,129 @@ def pytest_sessionstart(session: Any) -> None: t.start() -def pytest_sessionfinish(session: Any) -> None: - """ - This function is a pytest hook that is called at the end of the test session. - It is used to finalize and save the test reports. - The reports are saved in a specific location defined in the suite reports. - - Args: - session (Any): The pytest session object. +def pytest_sessionfinish(session: pytest.Session) -> None: """ - session_finish(suite_reports) - + Pytest hook that is called at the end of a test session. -@pytest.fixture -def scores(request: Any) -> None: + Finalizes and saves the test reports. """ - This pytest fixture is responsible for retrieving the scores of the test class. - The scores are retrieved from the test class's 'scores' attribute using the test class name. - This fixture is essential for the pytest system as it provides the necessary scores for each test. + session_finish(agbenchmark_config) - Args: - request (Any): The request object from which the test class is retrieved. - Returns: - None: The scores are directly passed to the test function and do not need to be returned. - """ - test_class_name = request.node.cls.__name__ - return request.node.cls.scores.get(test_class_name) +def pytest_generate_tests(metafunc: pytest.Metafunc): + if type(n := metafunc.config.getoption("-N")) is str: + metafunc.parametrize("i_attempt", range(int(n))) -# this is adding the dependency marker and category markers automatically from the json -def pytest_collection_modifyitems(items: Any, config: Any) -> None: +def pytest_collection_modifyitems( + items: list[pytest.Item], config: pytest.Config +) -> None: """ - This function is a pytest hook that is called after the test collection has been performed. - It is used to modify the collected test items based on the agent benchmark configuration. - The function loads the agent benchmark configuration from the specified path and retrieves the regression reports. - For each test item, it checks if the test method exists and retrieves the dependencies and categories from the test class instance. - If the "--improve" or "--category" options are used, the dependencies are filtered based on the regression data. - If the "--test", "--no_dep", or "--maintain" options are used, the dependencies are cleared. - The function then dynamically adds the 'depends' and 'category' markers to the test item. - This function is essential for the pytest system as it provides the necessary modification of the test items based on the agent benchmark configuration. + Pytest hook that is called after initial test collection has been performed. + Modifies the collected test items based on the agent benchmark configuration, + adding the dependency marker and category markers. Args: - items (Any): The collected test items to be modified. - config (Any): The pytest configuration object from which the agent benchmark configuration path is retrieved. + items: The collected test items to be modified. + config: The active pytest configuration. """ - agent_benchmark_config_path = str(Path.cwd() / "agbenchmark_config" / "config.json") - try: - with open(agent_benchmark_config_path) as f: - agent_benchmark_config = AgentBenchmarkConfig(**json.load(f)) - except json.JSONDecodeError: - print("Error: benchmark_config.json is not a valid JSON file.") - raise + rt_tracker = RegressionTestsTracker(agbenchmark_config.regression_tests_file) - regression_file = agent_benchmark_config.get_regression_reports_path() - data = ( - json.loads(open(regression_file, "r").read()) - if os.path.exists(regression_file) - else {} - ) - - print(f"data??? {data}") + try: + challenges_beaten_in_the_past = json.loads( + agbenchmark_config.challenges_already_beaten_file.read_bytes() + ) + except FileNotFoundError: + challenges_beaten_in_the_past = {} + + selected_tests: tuple[str] = config.getoption("--test") # type: ignore + selected_categories: tuple[str] = config.getoption("--category") # type: ignore + + # Can't use a for-loop to remove items in-place + i = 0 + while i < len(items): + item = items[i] + challenge = item.cls + challenge_name = item.cls.__name__ + + if not issubclass(challenge, BaseChallenge): + item.warn( + pytest.PytestCollectionWarning( + f"Non-challenge item collected: {challenge}" + ) + ) + i += 1 + continue - for item in items: - # Assuming item.cls is your test class - test_class_instance = item.cls() + # --test: remove the test from the set if it's not specifically selected + if selected_tests and challenge.info.name not in selected_tests: + items.remove(item) + continue - print(f"item: {item!r}") + # Filter challenges for --maintain, --improve, and --explore: + # --maintain -> only challenges expected to be passed (= regression tests) + # --improve -> only challenges that so far are not passed (reliably) + # --explore -> only challenges that have never been passed + is_regression_test = rt_tracker.has_regression_test(challenge.info.name) + has_been_passed = challenges_beaten_in_the_past.get(challenge.info.name, False) + if ( + (config.getoption("--maintain") and not is_regression_test) + or (config.getoption("--improve") and is_regression_test) + or (config.getoption("--explore") and has_been_passed) + ): + items.remove(item) + continue - if "test_method" not in item.name: + dependencies = challenge.info.dependencies + if ( + config.getoption("--test") + or config.getoption("--no-dep") + or config.getoption("--maintain") + ): + # Ignore dependencies: + # --test -> user selected specific tests to run, don't care about deps + # --no-dep -> ignore dependency relations regardless of test selection + # --maintain -> all "regression" tests must pass, so run all of them + dependencies = [] + elif config.getoption("--improve"): + # Filter dependencies, keep only deps that are not "regression" tests + dependencies = [ + d for d in dependencies if not rt_tracker.has_regression_test(d) + ] + + # Set category markers + challenge_categories = set(c.value for c in challenge.info.category) + for category in challenge_categories: + item.add_marker(category) + + # Enforce category selection + if selected_categories: + if not challenge_categories.intersection(set(selected_categories)): + items.remove(item) + continue + # # Filter dependencies, keep only deps from selected categories + # dependencies = [ + # d for d in dependencies + # if not set(d.categories).intersection(set(selected_categories)) + # ] + + # Skip items in optional categories that are not selected for the subject agent + challenge_optional_categories = challenge_categories & set(OPTIONAL_CATEGORIES) + if challenge_optional_categories and not ( + agbenchmark_config.categories + and challenge_optional_categories.issubset( + set(agbenchmark_config.categories) + ) + ): + logger.debug( + f"Skipping {challenge_name}: " + f"category {' and '.join(challenge_optional_categories)} is optional, " + "and not explicitly selected in the benchmark config." + ) + items.remove(item) continue - # Then you can access your properties - name = item.parent.cls.__name__ - # dependencies = test_class_instance.data.dependencies - - # Filter dependencies if they exist in regression data if its an improvement test - # if config.getoption("--improve") or config.getoption( - # "--category" - # ): - # dependencies = [dep for dep in dependencies if not data.get(dep, None)] - # if ( - # config.getoption("--test") - # or config.getoption("--no_dep") - # or config.getoption("--maintain") - # ): - print(f"test_class_instance: {test_class_instance!r}") - dependencies = test_class_instance.dependencies - - # Add depends marker dynamically - item.add_marker(pytest.mark.depends(on=dependencies, name=name)) - - categories = test_class_instance.data.category - - # Add category marker dynamically - for category in categories: - item.add_marker(getattr(pytest.mark, category)) + # Add marker for the DependencyManager + item.add_marker(pytest.mark.depends(on=dependencies, name=challenge_name)) + + i += 1 diff --git a/benchmark/agbenchmark/execute_sub_process.py b/benchmark/agbenchmark/execute_sub_process.py deleted file mode 100644 index b981e6be5..000000000 --- a/benchmark/agbenchmark/execute_sub_process.py +++ /dev/null @@ -1,79 +0,0 @@ -import platform -import queue -import select -import subprocess -import time -from threading import Thread -from typing import Any - -import psutil - - -def run_linux_env(process: Any, start_time: float, timeout: float) -> None: - while True: - try: - # This checks if there's data to be read from stdout without blocking. - if process.stdout and select.select([process.stdout], [], [], 0)[0]: - output = process.stdout.readline() - print(output.strip()) - except Exception as e: - continue - - # Check if process has ended, has no more output, or exceeded timeout - if process.poll() is not None or (time.time() - start_time > timeout): - break - - if time.time() - start_time > timeout: - print("The Python function has exceeded the time limit and was terminated.") - parent = psutil.Process(process.pid) - for child in parent.children(recursive=True): - child.kill() - parent.kill() - - else: - print("The Python function has finished running.") - - -def enqueue_output(out: Any, my_queue: Any) -> None: - for line in iter(out.readline, b""): - my_queue.put(line) - out.close() - - -def run_windows_env(process: Any, start_time: float, timeout: float) -> None: - my_queue: Any = queue.Queue() - thread = Thread(target=enqueue_output, args=(process.stdout, my_queue)) - thread.daemon = True - thread.start() - - while True: - try: - output = my_queue.get_nowait().strip() - print(output) - except queue.Empty: - pass - - if process.poll() is not None or (time.time() - start_time > timeout): - break - - if time.time() - start_time > timeout: - print("The Python function has exceeded the time limit and was terminated.") - process.terminate() - - -def execute_subprocess(command, timeout): - process = subprocess.Popen( - command, - stdout=subprocess.PIPE, - stderr=subprocess.STDOUT, - universal_newlines=True, - bufsize=1, - ) - start_time = time.time() - if platform.system() == "Windows": - run_windows_env(process, start_time, timeout) - else: - run_linux_env(process, start_time, timeout) - process.wait() - if process.returncode != 0: - print(f"The agent timed out") diff --git a/benchmark/agbenchmark/generate_test.py b/benchmark/agbenchmark/generate_test.py index 544e09ee7..5bc41971e 100644 --- a/benchmark/agbenchmark/generate_test.py +++ b/benchmark/agbenchmark/generate_test.py @@ -1,225 +1,26 @@ -import glob -import importlib -import json -import os -import sys -import types -from collections import deque -from pathlib import Path -from typing import Any, Dict, Optional, Union - -import pytest - -from agbenchmark.__main__ import CHALLENGES_ALREADY_BEATEN -from agbenchmark.agent_api_interface import append_updates_file -from agbenchmark.agent_protocol_client.models.step import Step -from agbenchmark.utils.challenge import Challenge -from agbenchmark.utils.data_types import AgentBenchmarkConfig, ChallengeData - -DATA_CATEGORY = {} - - -def create_single_test( - data: Dict[str, Any] | ChallengeData, - challenge_location: str, - file_datum: Optional[list[dict[str, Any]]] = None, -) -> None: - challenge_data = None - artifacts_location = None - if isinstance(data, ChallengeData): - challenge_data = data - data = data.get_data() - - DATA_CATEGORY[data["name"]] = data["category"][0] - - # Define test class dynamically - challenge_class = types.new_class(f"Test{data['name']}", (Challenge,)) - print(f"challenge_class: {challenge_class}") - # clean_challenge_location = get_test_path(challenge_location) - setattr(challenge_class, "CHALLENGE_LOCATION", challenge_location) - - setattr( - challenge_class, - "ARTIFACTS_LOCATION", - artifacts_location or str(Path(challenge_location).resolve().parent), - ) - - # Define test method within the dynamically created class - @pytest.mark.asyncio - async def test_method(self, config: Dict[str, Any], request) -> None: # type: ignore - # create a random number between 0 and 1 - test_name = self.data.name - - try: - with open(CHALLENGES_ALREADY_BEATEN, "r") as f: - challenges_beaten_in_the_past = json.load(f) - except: - challenges_beaten_in_the_past = {} +""" +AGBenchmark's test discovery endpoint for Pytest. - if request.config.getoption("--explore") and challenges_beaten_in_the_past.get( - test_name, False - ): - return None +This module is picked up by Pytest's *_test.py file matching pattern, and all challenge +classes in the module that conform to the `Test*` pattern are collected. +""" - # skip optional categories - self.skip_optional_categories(config) - - from helicone.lock import HeliconeLockManager - - if os.environ.get("HELICONE_API_KEY"): - HeliconeLockManager.write_custom_property("challenge", self.data.name) - - cutoff = self.data.cutoff or 60 - - timeout = cutoff - if "--nc" in sys.argv: - timeout = 100000 - if "--cutoff" in sys.argv: - timeout = int(sys.argv[sys.argv.index("--cutoff") + 1]) - - await self.setup_challenge(config, timeout) - - scores = self.get_scores(config) - request.node.answers = ( - scores["answers"] if "--keep-answers" in sys.argv else None - ) - del scores["answers"] # remove answers from scores - request.node.scores = scores # store scores in request.node - is_score_100 = 1 in scores["values"] - - evaluation = "Correct!" if is_score_100 else "Incorrect." - eval_step = Step( - input=evaluation, - additional_input=None, - task_id="irrelevant, this step is a hack", - step_id="irrelevant, this step is a hack", - name="", - status="created", - output=None, - additional_output=None, - artifacts=[], - is_last=True, - ) - await append_updates_file(eval_step) +import importlib +import logging +from itertools import chain - assert is_score_100 +from agbenchmark.challenges.builtin import load_builtin_challenges +from agbenchmark.challenges.webarena import load_webarena_challenges - # Parametrize the method here - test_method = pytest.mark.parametrize( - "challenge_data", - [data], - indirect=True, - )(test_method) +logger = logging.getLogger(__name__) - setattr(challenge_class, "test_method", test_method) - print(f"Challenge Class {challenge_class}") +DATA_CATEGORY = {} - # Attach the new class to a module so it can be discovered by pytest +# Load challenges and attach them to this module +for challenge in chain(load_builtin_challenges(), load_webarena_challenges()): + # Attach the Challenge class to this module so it can be discovered by pytest module = importlib.import_module(__name__) - setattr(module, f"Test{data['name']}", challenge_class) - return challenge_class - - -def create_single_suite_challenge(challenge_data: ChallengeData, path: Path) -> None: - create_single_test(challenge_data, str(path)) - - -def create_challenge( - data: Dict[str, Any], - json_file: str, - json_files: deque, -) -> Union[deque, Any]: - path = Path(json_file).resolve() - print("Creating challenge for", path) - - challenge_class = create_single_test(data, str(path)) - print("Creation complete for", path) - - return json_files, challenge_class - - -def generate_tests() -> None: # sourcery skip: invert-any-all - print("Generating tests...") - - challenges_path = os.path.join(os.path.dirname(__file__), "challenges") - print(f"Looking for challenges in {challenges_path}...") - - json_files = deque( - glob.glob( - f"{challenges_path}/**/data.json", - recursive=True, - ) - ) - - print(f"Found {len(json_files)} challenges.") - print(f"Sample path: {json_files[0]}") - - agent_benchmark_config_path = str(Path.cwd() / "agbenchmark_config" / "config.json") - try: - with open(agent_benchmark_config_path, "r") as f: - agent_benchmark_config = AgentBenchmarkConfig(**json.load(f)) - agent_benchmark_config.agent_benchmark_config_path = ( - agent_benchmark_config_path - ) - except json.JSONDecodeError: - print("Error: benchmark_config.json is not a valid JSON file.") - raise - - regression_reports_path = agent_benchmark_config.get_regression_reports_path() - if regression_reports_path and os.path.exists(regression_reports_path): - with open(regression_reports_path, "r") as f: - regression_tests = json.load(f) - else: - regression_tests = {} - - while json_files: - json_file = ( - json_files.popleft() - ) # Take and remove the first element from json_files - if challenge_should_be_ignored(json_file): - continue - - data = ChallengeData.get_json_from_path(json_file) - - commands = sys.argv - # --by flag - if "--category" in commands: - categories = data.get("category", []) - commands_set = set(commands) - - # Convert the combined list to a set - categories_set = set(categories) - - # If there's no overlap with commands - if not categories_set.intersection(commands_set): - continue - - # --test flag, only run the test if it's the exact one specified - tests = [] - for command in commands: - if command.startswith("--test="): - tests.append(command.split("=")[1]) - - if tests and data["name"] not in tests: - continue - - # --maintain and --improve flag - in_regression = regression_tests.get(data["name"], None) - improve_flag = in_regression and "--improve" in commands - maintain_flag = not in_regression and "--maintain" in commands - if "--maintain" in commands and maintain_flag: - continue - elif "--improve" in commands and improve_flag: - continue - json_files, challenge_class = create_challenge(data, json_file, json_files) - - print(f"Generated test for {data['name']}.") - print(f"- {data}") - print("Test generation complete.") - - -def challenge_should_be_ignored(json_file): - return "challenges/deprecated" in json_file or "challenges/library" in json_file - + setattr(module, challenge.__name__, challenge) -generate_tests() + # Build a map of challenge names and their primary category + DATA_CATEGORY[challenge.info.name] = challenge.info.category[0].value diff --git a/benchmark/agbenchmark/main.py b/benchmark/agbenchmark/main.py new file mode 100644 index 000000000..4cd97bd89 --- /dev/null +++ b/benchmark/agbenchmark/main.py @@ -0,0 +1,158 @@ +import logging +import os +from pathlib import Path +from typing import Optional, Sequence + +from dotenv import load_dotenv + +from agbenchmark.challenges import get_unique_categories +from agbenchmark.config import AgentBenchmarkConfig + +load_dotenv() + +logger = logging.getLogger(__name__) + + +def run_benchmark( + config: AgentBenchmarkConfig, + maintain: bool = False, + improve: bool = False, + explore: bool = False, + tests: tuple[str] = tuple(), + categories: tuple[str] = tuple(), + skip_categories: tuple[str] = tuple(), + attempts_per_challenge: int = 1, + mock: bool = False, + no_dep: bool = False, + no_cutoff: bool = False, + cutoff: Optional[int] = None, + keep_answers: bool = False, + server: bool = False, +) -> int: + """ + Starts the benchmark. If a category flag is provided, only challenges with the + corresponding mark will be run. + """ + import pytest + + from agbenchmark.reports.ReportManager import SingletonReportManager + + validate_args( + maintain=maintain, + improve=improve, + explore=explore, + tests=tests, + categories=categories, + skip_categories=skip_categories, + no_cutoff=no_cutoff, + cutoff=cutoff, + ) + + SingletonReportManager() + + for key, value in vars(config).items(): + logger.debug(f"config.{key} = {repr(value)}") + + pytest_args = ["-vs"] + + if tests: + logger.info(f"Running specific test(s): {' '.join(tests)}") + pytest_args += [f"--test={t}" for t in tests] + else: + all_categories = get_unique_categories() + + if categories or skip_categories: + categories_to_run = set(categories) or all_categories + if skip_categories: + categories_to_run = categories_to_run.difference(set(skip_categories)) + assert categories_to_run, "Error: You can't skip all categories" + pytest_args += [f"--category={c}" for c in categories_to_run] + logger.info(f"Running tests of category: {categories_to_run}") + else: + logger.info("Running all categories") + + if maintain: + logger.info("Running only regression tests") + elif improve: + logger.info("Running only non-regression tests") + elif explore: + logger.info("Only attempt challenges that have never been beaten") + + if mock: + # TODO: unhack + os.environ[ + "IS_MOCK" + ] = "True" # ugly hack to make the mock work when calling from API + + # Pass through flags + for flag, active in { + "--maintain": maintain, + "--improve": improve, + "--explore": explore, + "--no-dep": no_dep, + "--mock": mock, + "--nc": no_cutoff, + "--keep-answers": keep_answers, + }.items(): + if active: + pytest_args.append(flag) + + if attempts_per_challenge > 1: + pytest_args.append(f"--attempts={attempts_per_challenge}") + + if cutoff: + pytest_args.append(f"--cutoff={cutoff}") + logger.debug(f"Setting cuttoff override to {cutoff} seconds.") + + current_dir = Path(__file__).resolve().parent + pytest_args.append(str(current_dir / "generate_test.py")) + + pytest_args.append("--cache-clear") + logger.debug(f"Running Pytest with args: {pytest_args}") + exit_code = pytest.main(pytest_args) + + SingletonReportManager.clear_instance() + return exit_code + + +class InvalidInvocationError(ValueError): + pass + + +def validate_args( + maintain: bool, + improve: bool, + explore: bool, + tests: Sequence[str], + categories: Sequence[str], + skip_categories: Sequence[str], + no_cutoff: bool, + cutoff: Optional[int], +) -> None: + if categories: + all_categories = get_unique_categories() + invalid_categories = set(categories) - all_categories + if invalid_categories: + raise InvalidInvocationError( + "One or more invalid categories were specified: " + f"{', '.join(invalid_categories)}.\n" + f"Valid categories are: {', '.join(all_categories)}." + ) + + if (maintain + improve + explore) > 1: + raise InvalidInvocationError( + "You can't use --maintain, --improve or --explore at the same time. " + "Please choose one." + ) + + if tests and (categories or skip_categories or maintain or improve or explore): + raise InvalidInvocationError( + "If you're running a specific test make sure no other options are " + "selected. Please just pass the --test." + ) + + if no_cutoff and cutoff: + raise InvalidInvocationError( + "You can't use both --nc and --cutoff at the same time. " + "Please choose one." + ) diff --git a/benchmark/agbenchmark/reports/ReportManager.py b/benchmark/agbenchmark/reports/ReportManager.py index 8e56682e5..d04beee43 100644 --- a/benchmark/agbenchmark/reports/ReportManager.py +++ b/benchmark/agbenchmark/reports/ReportManager.py @@ -1,47 +1,51 @@ import copy import json +import logging import os import sys import time from datetime import datetime, timezone +from pathlib import Path +from typing import Any +from agbenchmark.config import AgentBenchmarkConfig from agbenchmark.reports.processing.graphs import save_single_radar_chart -from agbenchmark.reports.processing.process_report import get_agent_category -from agbenchmark.reports.processing.report_types import Report -from agbenchmark.utils.data_types import AgentBenchmarkConfig +from agbenchmark.reports.processing.process_report import ( + get_highest_achieved_difficulty_per_category, +) +from agbenchmark.reports.processing.report_types import MetricsOverall, Report, Test from agbenchmark.utils.utils import get_highest_success_difficulty +logger = logging.getLogger(__name__) + class SingletonReportManager: instance = None - def __new__(cls): - from agbenchmark.reports.agent_benchmark_config import ( - get_agent_benchmark_config, - ) + INFO_MANAGER: "SessionReportManager" + REGRESSION_MANAGER: "RegressionTestsTracker" + SUCCESS_RATE_TRACKER: "SuccessRatesTracker" + def __new__(cls): if not cls.instance: cls.instance = super(SingletonReportManager, cls).__new__(cls) - agent_benchmark_config = get_agent_benchmark_config() + agent_benchmark_config = AgentBenchmarkConfig.load() benchmark_start_time_dt = datetime.now( timezone.utc ) # or any logic to fetch the datetime # Make the Managers class attributes - cls.REGRESSION_MANAGER = ReportManager( - agent_benchmark_config.get_regression_reports_path(), + cls.INFO_MANAGER = SessionReportManager( + agent_benchmark_config.get_report_dir(benchmark_start_time_dt) + / "report.json", benchmark_start_time_dt, ) - cls.INFO_MANAGER = ReportManager( - str( - agent_benchmark_config.get_reports_path(benchmark_start_time_dt) - / "report.json" - ), - benchmark_start_time_dt, + cls.REGRESSION_MANAGER = RegressionTestsTracker( + agent_benchmark_config.regression_tests_file ) - cls.INTERNAL_INFO_MANAGER = ReportManager( - agent_benchmark_config.get_success_rate_path(), benchmark_start_time_dt + cls.SUCCESS_RATE_TRACKER = SuccessRatesTracker( + agent_benchmark_config.success_rate_file ) return cls.instance @@ -49,54 +53,39 @@ class SingletonReportManager: @classmethod def clear_instance(cls): cls.instance = None - cls.REGRESSION_MANAGER = None cls.INFO_MANAGER = None - cls.INTERNAL_INFO_MANAGER = None + cls.REGRESSION_MANAGER = None + cls.SUCCESS_RATE_TRACKER = None -class ReportManager: +class BaseReportManager: """Abstracts interaction with the regression tests file""" - def __init__(self, filename: str, benchmark_start_time: str): - self.filename = filename - self.start_time = time.time() - self.benchmark_start_time = benchmark_start_time + tests: dict[str, Any] + + def __init__(self, report_file: Path): + self.report_file = report_file self.load() def load(self) -> None: - if not os.path.exists(self.filename): - os.makedirs(os.path.dirname(self.filename), exist_ok=True) - with open(self.filename, "w") as f: - pass + if not self.report_file.exists(): + self.report_file.parent.mkdir(exist_ok=True) try: - with open(self.filename, "r") as f: - file_content = ( - f.read().strip() - ) # read the content and remove any leading/trailing whitespace - if file_content: # if file is not empty, load the json - data = json.loads(file_content) - self.tests = {k: data[k] for k in sorted(data)} - else: # if file is empty, assign an empty dictionary - self.tests = {} + with self.report_file.open("r") as f: + data = json.load(f) + self.tests = {k: data[k] for k in sorted(data)} except FileNotFoundError: self.tests = {} - except json.decoder.JSONDecodeError: # If JSON is invalid + except json.decoder.JSONDecodeError as e: + logger.warning(f"Could not parse {self.report_file}: {e}") self.tests = {} - self.save() def save(self) -> None: - with open(self.filename, "w") as f: + with self.report_file.open("w") as f: json.dump(self.tests, f, indent=4) - def add_test(self, test_name: str, test_details: dict | list) -> None: - if test_name.startswith("Test"): - test_name = test_name[4:] - self.tests[test_name] = test_details - - self.save() - def remove_test(self, test_name: str) -> None: if test_name in self.tests: del self.tests[test_name] @@ -106,49 +95,86 @@ class ReportManager: self.tests = {} self.save() - def end_info_report(self, config: AgentBenchmarkConfig) -> None: + +class SessionReportManager(BaseReportManager): + """Abstracts interaction with the regression tests file""" + + tests: dict[str, Test] | Report + + def __init__(self, report_file: Path, benchmark_start_time: datetime): + super().__init__(report_file) + + self.start_time = time.time() + self.benchmark_start_time = benchmark_start_time + + def save(self) -> None: + with self.report_file.open("w") as f: + if isinstance(self.tests, Report): + f.write(self.tests.json(indent=4)) + else: + json.dump({k: v.dict() for k, v in self.tests.items()}, f, indent=4) + + def load(self) -> None: + super().load() + if "tests" in self.tests: # type: ignore + self.tests = Report.parse_obj(self.tests) + else: + self.tests = {n: Test.parse_obj(d) for n, d in self.tests.items()} + + def add_test_report(self, test_name: str, test_report: Test) -> None: + if isinstance(self.tests, Report): + raise RuntimeError("Session report already finalized") + + if test_name.startswith("Test"): + test_name = test_name[4:] + self.tests[test_name] = test_report + + self.save() + + def finalize_session_report(self, config: AgentBenchmarkConfig) -> None: command = " ".join(sys.argv) - self.tests = { - "command": command.split(os.sep)[-1], - "benchmark_git_commit_sha": "---", - "agent_git_commit_sha": "---", - "completion_time": datetime.now(timezone.utc).strftime( + if isinstance(self.tests, Report): + raise RuntimeError("Session report already finalized") + + self.tests = Report( + command=command.split(os.sep)[-1], + benchmark_git_commit_sha="---", + agent_git_commit_sha="---", + completion_time=datetime.now(timezone.utc).strftime( "%Y-%m-%dT%H:%M:%S+00:00" ), - "benchmark_start_time": self.benchmark_start_time.strftime( + benchmark_start_time=self.benchmark_start_time.strftime( "%Y-%m-%dT%H:%M:%S+00:00" ), - "metrics": { - "run_time": str(round(time.time() - self.start_time, 2)) + " seconds", - "highest_difficulty": get_highest_success_difficulty(self.tests), - "total_cost": self.get_total_costs(), - }, - "tests": copy.copy(self.tests), - "config": { - k: v for k, v in json.loads(config.json()).items() if v is not None - }, - } - Report.parse_obj(self.tests) - - converted_data = Report.parse_obj(self.tests) - - agent_categories = get_agent_category(converted_data) + metrics=MetricsOverall( + run_time=str(round(time.time() - self.start_time, 2)) + " seconds", + highest_difficulty=get_highest_success_difficulty(self.tests), + total_cost=self.get_total_costs(), + ), + tests=copy.copy(self.tests), + config=config.dict(exclude_none=True), + ) + + agent_categories = get_highest_achieved_difficulty_per_category(self.tests) if len(agent_categories) > 1: save_single_radar_chart( agent_categories, - config.get_reports_path(self.benchmark_start_time) / "radar_chart.png", + config.get_report_dir(self.benchmark_start_time) / "radar_chart.png", ) self.save() def get_total_costs(self): + if isinstance(self.tests, Report): + tests = self.tests.tests + else: + tests = self.tests + total_cost = 0 all_costs_none = True - for test_name, test_data in self.tests.items(): - cost = test_data["metrics"].get( - "cost", 0 - ) # gets the cost or defaults to 0 if cost is missing + for test_data in tests.values(): + cost = sum(r.cost or 0 for r in test_data.results) if cost is not None: # check if cost is not None all_costs_none = False @@ -156,3 +182,32 @@ class ReportManager: if all_costs_none: total_cost = None return total_cost + + +class RegressionTestsTracker(BaseReportManager): + """Abstracts interaction with the regression tests file""" + + tests: dict[str, dict] + + def add_test(self, test_name: str, test_details: dict) -> None: + if test_name.startswith("Test"): + test_name = test_name[4:] + + self.tests[test_name] = test_details + self.save() + + def has_regression_test(self, test_name: str) -> bool: + return self.tests.get(test_name) is not None + + +class SuccessRatesTracker(BaseReportManager): + """Abstracts interaction with the regression tests file""" + + tests: dict[str, list[bool | None]] + + def update(self, test_name: str, success_history: list[bool | None]) -> None: + if test_name.startswith("Test"): + test_name = test_name[4:] + + self.tests[test_name] = success_history + self.save() diff --git a/benchmark/agbenchmark/reports/agent_benchmark_config.py b/benchmark/agbenchmark/reports/agent_benchmark_config.py deleted file mode 100644 index 3b45ed713..000000000 --- a/benchmark/agbenchmark/reports/agent_benchmark_config.py +++ /dev/null @@ -1,18 +0,0 @@ -import json -from pathlib import Path - -from agbenchmark.utils.data_types import AgentBenchmarkConfig - - -def get_agent_benchmark_config() -> AgentBenchmarkConfig: - agent_benchmark_config_path = str(Path.cwd() / "agbenchmark_config" / "config.json") - try: - with open(agent_benchmark_config_path, "r") as f: - agent_benchmark_config = AgentBenchmarkConfig(**json.load(f)) - agent_benchmark_config.agent_benchmark_config_path = ( - agent_benchmark_config_path - ) - return agent_benchmark_config - except json.JSONDecodeError: - print("Error: benchmark_config.json is not a valid JSON file.") - raise diff --git a/benchmark/agbenchmark/reports/processing/process_report.py b/benchmark/agbenchmark/reports/processing/process_report.py index b390ba2f9..3bb94f9e3 100644 --- a/benchmark/agbenchmark/reports/processing/process_report.py +++ b/benchmark/agbenchmark/reports/processing/process_report.py @@ -1,4 +1,5 @@ import json +import logging import os from pathlib import Path from typing import Any @@ -9,6 +10,8 @@ from agbenchmark.reports.processing.get_files import ( from agbenchmark.reports.processing.report_types import Report, Test from agbenchmark.utils.data_types import STRING_DIFFICULTY_MAP +logger = logging.getLogger(__name__) + def get_reports_data(report_path: str) -> dict[str, Any]: latest_files = get_latest_report_from_agent_directories(report_path) @@ -31,26 +34,23 @@ def get_reports_data(report_path: str) -> dict[str, Any]: return reports_data -def get_agent_category(report: Report) -> dict[str, Any]: +def get_highest_achieved_difficulty_per_category(report: Report) -> dict[str, Any]: categories: dict[str, Any] = {} - def get_highest_category_difficulty(data: Test) -> None: - for category in data.category: - if ( - category == "interface" - or category == "iterate" - or category == "product_advisor" - ): + for _, test_data in report.tests.items(): + for category in test_data.category: + if category in ("interface", "iterate", "product_advisor"): continue categories.setdefault(category, 0) - if data.metrics.success: - num_dif = STRING_DIFFICULTY_MAP[data.metrics.difficulty] + if ( + test_data.results + and all(r.success for r in test_data.results) + and test_data.difficulty + ): + num_dif = STRING_DIFFICULTY_MAP[test_data.difficulty] if num_dif > categories[category]: categories[category] = num_dif - for _, test_data in report.tests.items(): - get_highest_category_difficulty(test_data) - return categories @@ -58,9 +58,9 @@ def all_agent_categories(reports_data: dict[str, Any]) -> dict[str, Any]: all_categories: dict[str, Any] = {} for name, report in reports_data.items(): - categories = get_agent_category(report) + categories = get_highest_achieved_difficulty_per_category(report) if categories: # only add to all_categories if categories is not empty - print(f"Adding {name}: {categories}") + logger.debug(f"Adding {name}: {categories}") all_categories[name] = categories return all_categories diff --git a/benchmark/agbenchmark/reports/processing/report_types.py b/benchmark/agbenchmark/reports/processing/report_types.py index e2fb1bc62..b6deef021 100644 --- a/benchmark/agbenchmark/reports/processing/report_types.py +++ b/benchmark/agbenchmark/reports/processing/report_types.py @@ -1,74 +1,87 @@ -from typing import Any, Dict, List, Union +""" +Model definitions used internally and for reports generated during command-line runs. +""" -from pydantic import BaseModel, Field +from typing import Any, Dict, List -datetime_format = r"^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\+00:00$" -from pydantic import BaseModel, constr - - -class ForbidOptionalMeta(type(BaseModel)): # metaclass to forbid optional fields - def __new__(cls, name: str, bases: tuple, dct: Dict[str, Any]) -> Any: - for attr_name, attr_value in dct.items(): - if ( - getattr(attr_value, "__origin__", None) == Union - and type(None) in attr_value.__args__ - ): - raise TypeError( - f"Optional fields are forbidden, but found in {attr_name}" - ) - - return super().__new__(cls, name, bases, dct) +from pydantic import BaseModel, Field, constr, validator +datetime_format = r"^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\+00:00$" -class BaseModelBenchmark(BaseModel, metaclass=ForbidOptionalMeta): - class Config: - extra = "forbid" +class TestResult(BaseModel): + """Result details for a single run of a test/challenge.""" + + success: bool | None = None + """Whether the run was successful""" + run_time: str | None = None + """The (formatted) duration of the run""" + fail_reason: str | None = None + """If applicable, the reason why the run was not successful""" + reached_cutoff: bool | None = None # None if in progress + """Whether the run had to be stopped due to reaching the timeout""" + cost: float | None = None + """The (known) cost incurred by the run, e.g. from using paid LLM APIs""" + + @validator("fail_reason") + def success_xor_fail_reason(cls, v: str | None, values: dict[str, Any]): + if v: + success = values["success"] + assert not success, "fail_reason must only be specified if success=False" + else: + assert values["success"], "fail_reason is required if success=False" + return v + + +class TestMetrics(BaseModel): + """ + Result metrics for a set of runs for a test/challenge. Should be an aggregate of all + results for the same test/challenge within a benchmarking session. + """ -class Metrics(BaseModelBenchmark): - difficulty: str - success: bool - success_percentage: float = Field(..., alias="success_%") - run_time: str - fail_reason: str | None attempted: bool - cost: float | None + """Whether the challenge was attempted during this session""" + is_regression: bool + """Whether the challenge was considered a regression test at the time of running""" + success_percentage: float | None = Field(default=None, alias="success_%") + """Success rate (0-100) for this challenge within the session""" + +class MetricsOverall(BaseModel): + """Global metrics concerning a benchmarking session""" -class MetricsOverall(BaseModelBenchmark): run_time: str + """Duration from beginning to end of the session""" highest_difficulty: str - percentage: float | None - total_cost: float | None + """ + Difficulty of the most difficult challenge that succeeded at least once this session + """ + total_cost: float | None = None + """Total known cost of the session""" -class Test(BaseModelBenchmark): +class Test(BaseModel): + category: List[str] + difficulty: str | None data_path: str - is_regression: bool - answer: str description: str - metrics: Metrics - category: List[str] task: str - reached_cutoff: bool + answer: str + metrics: TestMetrics + results: list[TestResult] + metadata: dict[str, Any] | None = Field(default_factory=dict) -class ReportBase(BaseModelBenchmark): +class ReportBase(BaseModel): command: str - completion_time: str | None + completion_time: str | None = None benchmark_start_time: constr(regex=datetime_format) metrics: MetricsOverall config: Dict[str, str | dict[str, str]] - agent_git_commit_sha: str | None - benchmark_git_commit_sha: str | None - repo_url: str | None + agent_git_commit_sha: str | None = None + benchmark_git_commit_sha: str | None = None + repo_url: str | None = None class Report(ReportBase): tests: Dict[str, Test] - - -class ReportV2(Test, ReportBase): - test_name: str - run_id: str | None - team_name: str | None diff --git a/benchmark/agbenchmark/reports/processing/report_types_v2.py b/benchmark/agbenchmark/reports/processing/report_types_v2.py index 94b53ca97..b26adaa6d 100644 --- a/benchmark/agbenchmark/reports/processing/report_types_v2.py +++ b/benchmark/agbenchmark/reports/processing/report_types_v2.py @@ -1,52 +1,48 @@ -from typing import Dict, List +"""Model definitions for use in the API""" -datetime_format = r"^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\+00:00$" from pydantic import BaseModel, constr - -class BaseModelBenchmark(BaseModel): - class Config: - extra = "forbid" +datetime_format = r"^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\+00:00$" -class TaskInfo(BaseModelBenchmark): +class TaskInfo(BaseModel): data_path: str is_regression: bool | None answer: str description: str - category: List[str] + category: list[str] task: str -class RepositoryInfo(BaseModelBenchmark): - repo_url: str | None - team_name: str | None - benchmark_git_commit_sha: str | None - agent_git_commit_sha: str | None +class RepositoryInfo(BaseModel): + repo_url: str | None = None + team_name: str | None = None + agent_git_commit_sha: str | None = None + benchmark_git_commit_sha: str | None = None -class Metrics(BaseModelBenchmark): - difficulty: str | None +class Metrics(BaseModel): + cost: float | None = None success: bool - success_percentage: float | None - run_time: str | None - fail_reason: str | None attempted: bool - cost: float | None + difficulty: str | None = None + run_time: str | None = None + fail_reason: str | None = None + success_percentage: float | None = None -class RunDetails(BaseModelBenchmark): +class RunDetails(BaseModel): test_name: str - run_id: str | None + run_id: str | None = None command: str - completion_time: str | None + completion_time: str | None = None benchmark_start_time: constr(regex=datetime_format) -class BenchmarkRun(BaseModelBenchmark): +class BenchmarkRun(BaseModel): repository_info: RepositoryInfo run_details: RunDetails task_info: TaskInfo metrics: Metrics - reached_cutoff: bool | None - config: Dict[str, str | dict[str, str]] + reached_cutoff: bool | None = None + config: dict[str, str | dict[str, str]] diff --git a/benchmark/agbenchmark/reports/reports.py b/benchmark/agbenchmark/reports/reports.py index a1164bab7..728d19fd9 100644 --- a/benchmark/agbenchmark/reports/reports.py +++ b/benchmark/agbenchmark/reports/reports.py @@ -1,184 +1,143 @@ import json +import logging import os -import sys -from typing import Any, Dict +from pathlib import Path -from agbenchmark.__main__ import CHALLENGES_ALREADY_BEATEN -from agbenchmark.reports.agent_benchmark_config import get_agent_benchmark_config +import pytest + +from agbenchmark.challenges import ChallengeInfo +from agbenchmark.config import AgentBenchmarkConfig +from agbenchmark.reports.processing.report_types import Test, TestMetrics, TestResult from agbenchmark.reports.ReportManager import SingletonReportManager from agbenchmark.utils.data_types import DifficultyLevel -from agbenchmark.utils.get_data_from_helicone import get_data_from_helicone -from agbenchmark.utils.utils import calculate_success_percentage + +# from agbenchmark.utils.get_data_from_helicone import get_data_from_helicone + +logger = logging.getLogger(__name__) -def get_previous_test_results( - test_name: str, info_details: dict[str, Any] -) -> list[bool]: - agent_tests: dict[str, list[bool]] = {} +def get_and_update_success_history( + test_name: str, success: bool | None +) -> list[bool | None]: mock = os.getenv("IS_MOCK") # Check if --mock is in sys.argv - prev_test_results = SingletonReportManager().INTERNAL_INFO_MANAGER.tests.get( + prev_test_results = SingletonReportManager().SUCCESS_RATE_TRACKER.tests.get( test_name, [] ) if not mock: # only add if it's an actual test - prev_test_results.append(info_details["metrics"]["success"]) - SingletonReportManager().INTERNAL_INFO_MANAGER.add_test( + prev_test_results.append(success) + SingletonReportManager().SUCCESS_RATE_TRACKER.update( test_name, prev_test_results ) - # can calculate success rate regardless of mock - info_details["metrics"]["success_%"] = calculate_success_percentage( - prev_test_results - ) - return prev_test_results def update_regression_tests( - prev_test_results: list[bool], - info_details: dict, + prev_test_results: list[bool | None], + test_report: Test, test_name: str, - test_details: dict, ) -> None: if len(prev_test_results) >= 3 and prev_test_results[-3:] == [True, True, True]: # if the last 3 tests were successful, add to the regression tests - info_details["is_regression"] = True - SingletonReportManager().REGRESSION_MANAGER.add_test(test_name, test_details) - + test_report.metrics.is_regression = True + SingletonReportManager().REGRESSION_MANAGER.add_test( + test_name, test_report.dict(include={"difficulty", "data_path"}) + ) -def generate_single_call_report( - item: Any, - call: Any, - challenge_data: dict[str, Any], - answers: dict[str, Any], - challenge_location, - test_name, -) -> None: - try: - difficulty = challenge_data["info"]["difficulty"] - except KeyError: - return None +def make_empty_test_report( + challenge_info: ChallengeInfo, +) -> Test: + difficulty = challenge_info.difficulty if isinstance(difficulty, DifficultyLevel): difficulty = difficulty.value - # Extract the challenge_location from the class - # challenge_location: str = getattr(item.cls, "CHALLENGE_LOCATION", "") - # test_name = item.nodeid.split("::")[1] - # item.test_name = test_name - - test_details = { - "difficulty": difficulty, - "data_path": challenge_location, - } - - info_details: Any = { - "data_path": challenge_location, - "is_regression": False, - "category": challenge_data["category"], - "task": challenge_data["task"], - "answer": challenge_data["ground"]["answer"], - "description": challenge_data["info"]["description"], - "metrics": { - "difficulty": difficulty, - "success": False, - "attempted": True, - }, - # "answers": answers, - } - if answers: - info_details["answers"] = answers - - if "metadata" in challenge_data: - info_details["metadata"] = challenge_data["metadata"] - - mock = os.getenv("IS_MOCK") # Check if --mock is in sys.argv - if call: - if call.excinfo is None: - info_details["metrics"]["success"] = True - else: - if not mock: # don't remove if it's a mock test - SingletonReportManager().REGRESSION_MANAGER.remove_test(test_name) - info_details["metrics"]["fail_reason"] = str(call.excinfo.value) - if call.excinfo.typename == "Skipped": - info_details["metrics"]["attempted"] = False - - prev_test_results: list[bool] = get_previous_test_results(test_name, info_details) - - update_regression_tests(prev_test_results, info_details, test_name, test_details) - - # user facing reporting - if item: - item.info_details = info_details + return Test( + category=[c.value for c in challenge_info.category], + difficulty=difficulty, + data_path=challenge_info.source_uri, + description=challenge_info.description or "", + task=challenge_info.task, + answer=challenge_info.reference_answer or "", + metrics=TestMetrics(attempted=False, is_regression=False), + results=[], + ) - return info_details +def add_test_result_to_report( + test_report: Test, + item: pytest.Item, + call: pytest.CallInfo, + config: AgentBenchmarkConfig, +) -> None: + user_properties: dict = dict(item.user_properties) + test_name: str = user_properties.get("test_name", "") -def finalize_reports(item: Any, challenge_data: dict[str, Any]) -> None: - run_time = dict(item.user_properties).get("run_time") + mock = os.getenv("IS_MOCK") # Check if --mock is in sys.argv - info_details = getattr(item, "info_details", {}) - test_name = getattr(item, "test_name", "") + if call.excinfo: + if not mock: + SingletonReportManager().REGRESSION_MANAGER.remove_test(test_name) - if info_details and test_name: - if run_time is not None: - cost = None - if "--mock" not in sys.argv and os.environ.get("HELICONE_API_KEY"): - print("Getting cost from Helicone") - cost = get_data_from_helicone(test_name) + test_report.metrics.attempted = call.excinfo.typename != "Skipped" + else: + test_report.metrics.attempted = True - info_details["metrics"]["cost"] = cost + test_report.results.append( + TestResult( + success=call.excinfo is None, + run_time=f"{str(round(call.duration, 3))} seconds", + fail_reason=str(call.excinfo.value) if call.excinfo else None, + reached_cutoff=user_properties.get("timed_out", False), + ) + ) + test_report.metrics.success_percentage = ( + sum(r.success or False for r in test_report.results) + / len(test_report.results) + * 100 + ) - if info_details["metrics"].get("success", None) is None: - info_details["metrics"]["attempted"] = False - info_details["metrics"]["success"] = False - elif ( - info_details["metrics"].get("success") is False - and "attempted" not in info_details["metrics"] - ): - info_details["metrics"]["attempted"] = False + prev_test_results: list[bool | None] = get_and_update_success_history( + test_name, test_report.results[-1].success + ) - info_details["metrics"]["run_time"] = f"{str(round(run_time, 3))} seconds" + update_regression_tests(prev_test_results, test_report, test_name) - info_details["reached_cutoff"] = float(run_time) > challenge_data["cutoff"] + if test_report and test_name: + # if "--mock" not in sys.argv and os.environ.get("HELICONE_API_KEY"): + # logger.debug("Getting cost from Helicone") + # test_report.metrics.cost = get_data_from_helicone(test_name) + # logger.debug(f"Cost: {cost}") - if "--mock" not in sys.argv: - update_challenges_already_beaten(info_details, test_name) - if info_details.get("tests") is not None: - for nested_test_name, nested_test_info in info_details[ - "tests" - ].items(): - update_challenges_already_beaten( - nested_test_info, nested_test_name - ) + if not mock: + update_challenges_already_beaten( + config.challenges_already_beaten_file, test_report, test_name + ) - SingletonReportManager().INFO_MANAGER.add_test(test_name, info_details) + SingletonReportManager().INFO_MANAGER.add_test_report(test_name, test_report) def update_challenges_already_beaten( - info_details: Dict[str, Any], test_name: str + challenges_already_beaten_file: Path, test_report: Test, test_name: str ) -> None: - current_run_successful = info_details["metrics"]["success"] + current_run_successful = any(r.success for r in test_report.results) try: - with open(CHALLENGES_ALREADY_BEATEN, "r") as f: - challenge_data = json.load(f) - except: - challenge_data = {} - challenge_beaten_in_the_past = challenge_data.get(test_name) - - challenge_data[test_name] = True - if challenge_beaten_in_the_past is None and not current_run_successful: - challenge_data[test_name] = False + with open(challenges_already_beaten_file, "r") as f: + challenges_beaten_before = json.load(f) + except FileNotFoundError: + challenges_beaten_before = {} - with open(CHALLENGES_ALREADY_BEATEN, "w") as f: - json.dump(challenge_data, f, indent=4) + has_ever_been_beaten = challenges_beaten_before.get(test_name) + challenges_beaten_before[test_name] = has_ever_been_beaten or current_run_successful + with open(challenges_already_beaten_file, "w") as f: + json.dump(challenges_beaten_before, f, indent=4) -def session_finish(suite_reports: dict) -> None: - agent_benchmark_config = get_agent_benchmark_config() - SingletonReportManager().INTERNAL_INFO_MANAGER.save() - SingletonReportManager().INFO_MANAGER.end_info_report(agent_benchmark_config) +def session_finish(agbenchmark_config: AgentBenchmarkConfig) -> None: + SingletonReportManager().INFO_MANAGER.finalize_session_report(agbenchmark_config) SingletonReportManager().REGRESSION_MANAGER.save() + SingletonReportManager().SUCCESS_RATE_TRACKER.save() diff --git a/benchmark/agbenchmark/schema.py b/benchmark/agbenchmark/schema.py index 4849c2ad6..2aed562da 100644 --- a/benchmark/agbenchmark/schema.py +++ b/benchmark/agbenchmark/schema.py @@ -1,79 +1,14 @@ -# generated by fastapi-codegen: -# filename: ../../postman/schemas/openapi.yaml -# timestamp: 2023-08-25T10:36:11+00:00 - from __future__ import annotations -from datetime import datetime -from enum import Enum -from typing import List, Optional +from typing import Optional from pydantic import BaseModel, Field -class ArtifactUpload(BaseModel): - file: str = Field(..., description="File to upload.", format="binary") - relative_path: str = Field( - ..., - description="Relative path of the artifact in the agent's workspace.", - example="python/code", - ) - - -class Pagination(BaseModel): - total_items: int = Field(..., description="Total number of items.", example=42) - total_pages: int = Field(..., description="Total number of pages.", example=97) - current_page: int = Field(..., description="Current_page page number.", example=1) - page_size: int = Field(..., description="Number of items per page.", example=25) - - class TaskInput(BaseModel): pass -class Artifact(BaseModel): - created_at: datetime = Field( - ..., - description="The creation datetime of the task.", - example="2023-01-01T00:00:00Z", - json_encoders={datetime: lambda v: v.isoformat()}, - ) - modified_at: datetime = Field( - ..., - description="The modification datetime of the task.", - example="2023-01-01T00:00:00Z", - json_encoders={datetime: lambda v: v.isoformat()}, - ) - artifact_id: str = Field( - ..., - description="ID of the artifact.", - example="b225e278-8b4c-4f99-a696-8facf19f0e56", - ) - agent_created: bool = Field( - ..., - description="Whether the artifact has been created by the agent.", - example=False, - ) - relative_path: str = Field( - ..., - description="Relative path of the artifact in the agents workspace.", - example="/my_folder/my_other_folder/", - ) - file_name: str = Field( - ..., - description="Filename of the artifact.", - example="main.py", - ) - - -class StepInput(BaseModel): - pass - - -class StepOutput(BaseModel): - pass - - class TaskRequestBody(BaseModel): input: str = Field( ..., @@ -86,108 +21,3 @@ class TaskRequestBody(BaseModel): class TaskEvalRequestBody(TaskRequestBody): eval_id: str - - -class Task(TaskRequestBody): - created_at: datetime = Field( - ..., - description="The creation datetime of the task.", - example="2023-01-01T00:00:00Z", - json_encoders={datetime: lambda v: v.isoformat()}, - ) - modified_at: datetime = Field( - ..., - description="The modification datetime of the task.", - example="2023-01-01T00:00:00Z", - json_encoders={datetime: lambda v: v.isoformat()}, - ) - task_id: str = Field( - ..., - description="The ID of the task.", - example="50da533e-3904-4401-8a07-c49adf88b5eb", - ) - artifacts: Optional[List[Artifact]] = Field( - [], - description="A list of artifacts that the task has produced.", - example=[ - "7a49f31c-f9c6-4346-a22c-e32bc5af4d8e", - "ab7b4091-2560-4692-a4fe-d831ea3ca7d6", - ], - ) - - -class StepRequestBody(BaseModel): - name: Optional[str] = Field( - None, description="The name of the task step.", example="Write to file" - ) - input: Optional[str] = Field( - None, - min_length=1, - description="Input prompt for the step.", - example="Washington", - ) - additional_input: Optional[StepInput] = {} - - -class Status(Enum): - created = "created" - running = "running" - completed = "completed" - - -class Step(StepRequestBody): - created_at: datetime = Field( - ..., - description="The creation datetime of the task.", - example="2023-01-01T00:00:00Z", - json_encoders={datetime: lambda v: v.isoformat()}, - ) - modified_at: datetime = Field( - ..., - description="The modification datetime of the task.", - example="2023-01-01T00:00:00Z", - json_encoders={datetime: lambda v: v.isoformat()}, - ) - task_id: str = Field( - ..., - description="The ID of the task this step belongs to.", - example="50da533e-3904-4401-8a07-c49adf88b5eb", - ) - step_id: str = Field( - ..., - description="The ID of the task step.", - example="6bb1801a-fd80-45e8-899a-4dd723cc602e", - ) - name: Optional[str] = Field( - None, description="The name of the task step.", example="Write to file" - ) - status: Status = Field( - ..., description="The status of the task step.", example="created" - ) - output: Optional[str] = Field( - None, - description="Output of the task step.", - example="I am going to use the write_to_file command and write Washington to a file called output.txt <write_to_file('output.txt', 'Washington')", - ) - additional_output: Optional[StepOutput] = {} - artifacts: Optional[List[Artifact]] = Field( - [], description="A list of artifacts that the step has produced." - ) - is_last: bool = Field( - ..., description="Whether this is the last step in the task.", example=True - ) - - -class TaskListResponse(BaseModel): - tasks: Optional[List[Task]] = None - pagination: Optional[Pagination] = None - - -class TaskStepsListResponse(BaseModel): - steps: Optional[List[Step]] = None - pagination: Optional[Pagination] = None - - -class TaskArtifactsListResponse(BaseModel): - artifacts: Optional[List[Artifact]] = None - pagination: Optional[Pagination] = None diff --git a/benchmark/agbenchmark/utils/challenge.py b/benchmark/agbenchmark/utils/challenge.py deleted file mode 100644 index 897ff9905..000000000 --- a/benchmark/agbenchmark/utils/challenge.py +++ /dev/null @@ -1,240 +0,0 @@ -import glob -import math -import os -import subprocess -import sys -from abc import ABC -from pathlib import Path -from typing import Any, Dict, List - -import openai -import pytest - -from agbenchmark.__main__ import OPTIONAL_CATEGORIES, TEMP_FOLDER_ABS_PATH -from agbenchmark.agent_api_interface import run_api_agent -from agbenchmark.utils.data_types import ChallengeData, Ground -from agbenchmark.utils.prompts import ( - END_PROMPT, - FEW_SHOT_EXAMPLES, - PROMPT_MAP, - SCORING_MAP, -) -from agbenchmark.utils.utils import agent_eligibible_for_optional_categories - - -class Challenge(ABC): - """The parent class to all specific challenges classes. - Defines helper methods for running a challenge""" - - _data_cache: Dict[str, ChallengeData] = {} - CHALLENGE_LOCATION: str = "" - scores: dict[str, Any] = {} # this is for suites - - # def __repr__(self) -> str: - # return f"{self.__class__.__name__}(CHALLENGE_LOCATION={self.CHALLENGE_LOCATION}, _data_cache={self._data_cache!r})" - - @property - def data(self) -> ChallengeData: - if self.CHALLENGE_LOCATION not in self._data_cache: - self._data_cache[self.CHALLENGE_LOCATION] = ChallengeData.deserialize( - self.CHALLENGE_LOCATION - ) - return self._data_cache[self.CHALLENGE_LOCATION] - - @property - def task(self) -> str: - return self.data.task - - @property - def dependencies(self) -> list: - print(f"got prop dependencies data: {self.data.dependencies}") - return self.data.dependencies - - async def setup_challenge(self, config: Dict[str, Any], cutoff: int) -> None: - from agbenchmark.agent_interface import copy_artifacts_into_temp_folder - - if not self.task: - return - - print( - f"\033[1;35m============Starting {self.data.name} challenge============\033[0m" - ) - print(f"\033[1;30mTask: {self.task}\033[0m") - - await run_api_agent(self.data, config, self.ARTIFACTS_LOCATION, cutoff) - - # hidden files are added after the agent runs. Hidden files can be python test files. - # We copy them in the temporary folder to make it easy to import the code produced by the agent - artifact_paths = [ - self.ARTIFACTS_LOCATION, - str(Path(self.CHALLENGE_LOCATION).parent), - ] - for path in artifact_paths: - copy_artifacts_into_temp_folder(TEMP_FOLDER_ABS_PATH, "custom_python", path) - - def test_method(self, config: Dict[str, Any]) -> None: - raise NotImplementedError - - def get_artifacts_out( - self, workspace: str | dict[str, str], ground: Ground - ) -> List[str]: - if isinstance(workspace, dict): - workspace = workspace["output"] - - script_dir = workspace - files_contents = [] - - for file_pattern in ground.files: - # Check if it is a file extension - if file_pattern.startswith("."): - # Find all files with the given extension in the workspace - matching_files = glob.glob(os.path.join(script_dir, "*" + file_pattern)) - else: - # Otherwise, it is a specific file - matching_files = [os.path.join(script_dir, file_pattern)] - - for file_path in matching_files: - if ground.eval.type == "python": - result = subprocess.run( - [sys.executable, file_path], - cwd=os.path.abspath(workspace), - capture_output=True, - text=True, - ) - if "error" in result.stderr or result.returncode != 0: - print(result.stderr) - assert False, result.stderr - files_contents.append(f"Output: {result.stdout}\n") - else: - with open(file_path, "r") as f: - files_contents.append(f.read()) - else: - if ground.eval.type == "pytest": - result = subprocess.run( - [sys.executable, "-m", "pytest"], - cwd=TEMP_FOLDER_ABS_PATH, - capture_output=True, - text=True, - ) - if "error" in result.stderr or result.returncode != 0: - print(result.stderr) - assert False, result.stderr - files_contents.append(f"Output: {result.stdout}\n") - - return files_contents - - def scoring(self, config: Dict[str, Any], content: str, ground: Ground) -> float: - print("\033[1;34mScoring content:\033[0m", content) - if ground.should_contain: - for should_contain_word in ground.should_contain: - if not getattr(ground, "case_sensitive", True): - should_contain_word = should_contain_word.lower() - content = content.lower() - print_content = ( - f"\033[1;34mWord that should exist\033[0m - {should_contain_word}:" - ) - if should_contain_word not in content: - print(print_content, "False") - return 0.0 - else: - print(print_content, "True") - - if ground.should_not_contain: - for should_not_contain_word in ground.should_not_contain: - if not getattr(ground, "case_sensitive", True): - should_not_contain_word = should_not_contain_word.lower() - content = content.lower() - print_content = f"\033[1;34mWord that should not exist\033[0m - {should_not_contain_word}:" - if should_not_contain_word in content: - print(print_content, "False") - return 0.0 - else: - print(print_content, "True") - - return 1.0 - - def llm_eval(self, config: Dict[str, Any], content: str, ground: Ground) -> float: - openai.api_key = os.getenv("OPENAI_API_KEY") - if os.getenv("IS_MOCK"): - return 1.0 - - # the validation for this is done in the Eval BaseModel - scoring = SCORING_MAP[ground.eval.scoring] # type: ignore - prompt = PROMPT_MAP[ground.eval.template].format(task=self.data.task, scoring=scoring, answer=ground.answer, response=content) # type: ignore - - if ground.eval.examples: - prompt += FEW_SHOT_EXAMPLES.format(examples=ground.eval.examples) - - prompt += END_PROMPT - - answer = openai.ChatCompletion.create( - model="gpt-4", - messages=[ - {"role": "system", "content": prompt}, - ], - ) - - return float(answer["choices"][0]["message"]["content"]) # type: ignore - - def get_scores(self, config: Dict[str, Any]) -> dict[str, Any]: - scores = [] - scores_dict: Any = {} - percentage = None - answers = {} - try: - if self.data.task == "" and os.getenv("IS_MOCK"): - scores = [1.0] - answers = {"mock": "This is a mock answer"} - elif isinstance(self.data.ground, Ground): - files_contents = self.get_artifacts_out( - TEMP_FOLDER_ABS_PATH, self.data.ground - ) - answers = {"answer": files_contents} - for file_content in files_contents: - score = self.scoring(config, file_content, self.data.ground) - print("\033[1;32mYour score is:\033[0m", score) - scores.append(score) - - if self.data.ground.eval.type == "llm": - llm_eval = self.llm_eval( - config, "\n".join(files_contents), self.data.ground - ) - if self.data.ground.eval.scoring == "percentage": - scores.append(math.ceil(llm_eval / 100)) - elif self.data.ground.eval.scoring == "scale": - scores.append(math.ceil(llm_eval / 10)) - print("\033[1;32mYour score is:\033[0m", llm_eval) - - scores.append(llm_eval) - except Exception as e: - print("Error getting scores", e) - - scores_data = { - "values": scores, - "scores_obj": scores_dict, - "percentage": percentage, - "answers": answers, - } - - self.scores[self.__class__.__name__] = scores_data - - return scores_data - - def get_dummy_scores(self, test_name: str, scores: dict[str, Any]) -> int | None: - return 1 # remove this once this works - if 1 in scores.get("scores_obj", {}).get(test_name, []): - return 1 - - return None - - def skip_optional_categories(self, config: Dict[str, Any]) -> None: - challenge_category = self.data.category - categories = [ - category - for category in OPTIONAL_CATEGORIES - if category in challenge_category - ] - if not agent_eligibible_for_optional_categories( - categories, config.get("category", []) - ): - pytest.skip("Agent is not eligible for this category") diff --git a/benchmark/agbenchmark/utils/data_types.py b/benchmark/agbenchmark/utils/data_types.py index 71feba6ce..9090d1942 100644 --- a/benchmark/agbenchmark/utils/data_types.py +++ b/benchmark/agbenchmark/utils/data_types.py @@ -1,12 +1,7 @@ -import datetime -import json -import sys -from datetime import datetime from enum import Enum -from pathlib import Path -from typing import Any, Dict, List, Optional +from typing import Literal -from pydantic import BaseModel, constr, validator +from pydantic import BaseModel class DifficultyLevel(Enum): @@ -33,231 +28,20 @@ DIFFICULTY_MAP = { STRING_DIFFICULTY_MAP = {e.value: DIFFICULTY_MAP[e] for e in DifficultyLevel} -def calculate_info_test_path(base_path: Path, benchmark_start_time: datetime) -> Path: - """ - Calculates the path to the directory where the test report will be saved. - """ - # Ensure the reports path exists - base_path.mkdir(parents=True, exist_ok=True) - - # Get current UTC date-time stamp - date_stamp = benchmark_start_time.strftime("%Y%m%dT%H%M%S") - - # Default run name - run_name = "full_run" - - # Map command-line arguments to their respective labels - arg_labels = { - "--test": None, - "--category": None, - "--maintain": "maintain", - "--improve": "improve", - "--explore": "explore", - } - - # Identify the relevant command-line argument - for arg, label in arg_labels.items(): - if arg in sys.argv: - test_arg = sys.argv[sys.argv.index(arg) + 1] if label is None else None - run_name = arg.strip("--") - if test_arg: - run_name = f"{run_name}_{test_arg}" - break - - # Create the full new directory path with ISO standard UTC date-time stamp - report_path = base_path / f"{date_stamp}_{run_name}" - - # Ensure the new directory is created - report_path.mkdir(exist_ok=True) - return report_path - - -class AgentBenchmarkConfig(BaseModel): - """ - This class represents the configuration for the Agent agbenchmark. - It includes the following attributes: - - agent_benchmark_config_path: The path to the agent benchmark config that this object was created from. - - reports_folder: The path to the folder where the benchmark reports will be stored. - - host: The host where the benchmark is run. - """ - - agent_benchmark_config_path: Path | None = None - reports_folder: Path | None = None - host: str | None - - def get_reports_location(self) -> Path: - # if not self.reports_folder: - # self.reports_folder = ( - # Path(self.agent_benchmark_config_path).parent / "reports" - # ).resolve() - return Path.cwd() / "agbenchmark_config" / "reports" - - def get_reports_path(self, benchmark_start_time: datetime) -> Path: - return calculate_info_test_path( - self.get_reports_location(), benchmark_start_time - ) - - def get_regression_reports_path(self) -> Path: - return self.get_reports_location() / "regression_tests.json" - - def get_success_rate_path(self) -> Path: - return self.get_reports_location() / "success_rate.json" - - def get_agent_home_directory(self) -> Path: - return Path(self.agent_benchmark_config_path).resolve().parent - - -class Info(BaseModel): - difficulty: DifficultyLevel - description: constr(regex=r"^Tests if the agent can.*") - side_effects: List[str] - - @validator("difficulty", pre=True) - def difficulty_to_enum(cls: "Info", v: str | DifficultyLevel) -> DifficultyLevel: - """Convert a string to an instance of DifficultyLevel.""" - if isinstance(v, DifficultyLevel): - return v - - if isinstance(v, str): - try: - return DifficultyLevel(v.lower()) - except ValueError: - pass - - raise ValueError(f"Cannot convert {v} to DifficultyLevel.") - - -class Eval(BaseModel): - type: str - scoring: Optional[str] - template: Optional[str] - examples: Optional[str] - - @validator("scoring", "template", always=True) - def validate_eval_fields(cls, v, values, field): - if "type" in values and values["type"] == "llm": - if v is None: - raise ValueError(f"{field.name} must be provided when type is 'llm'") - else: - if v is not None: - raise ValueError(f"{field.name} should only exist when type is 'llm'") - return v - - @validator("scoring") - def validate_scoring(cls, v): - if v is not None and v not in ["percentage", "scale", "binary"]: - raise ValueError( - "scoring must be either 'percentage', 'scale', or 'binary'" - ) - return v - - @validator("template") - def validate_template(cls, v): - if v is not None and v not in ["rubric", "reference", "question", "custom"]: - raise ValueError( - "template must be either 'rubric', 'reference', 'question', or 'custom'" - ) - return v - - -class Ground(BaseModel): - answer: str - should_contain: Optional[List[str]] = None - should_not_contain: Optional[List[str]] = None - files: List[str] - case_sensitive: Optional[bool] = True - eval: Eval - - class Category(str, Enum): DATA = "data" GENERALIST = "general" CODING = "coding" SCRAPE_SYNTHESIZE = "scrape_synthesize" VALIDATION = "validation" + WEB = "web" GAIA_1 = "GAIA_1" GAIA_2 = "GAIA_2" GAIA_3 = "GAIA_3" -class ChallengeData(BaseModel): - name: str - category: List[Category] - task: str - dependencies: List[str] - cutoff: int - ground: Ground | Dict[str, Ground] - info: Info | Dict[str, Info] - metadata: Optional[Dict[str, Any]] = None - - def serialize(self, path: str) -> None: - with open(path, "w") as file: - file.write(self.json()) - - def get_data(self) -> dict: - return self.dict() - - @staticmethod - def get_json_from_path(json_path: Path | str) -> dict: - path = Path(json_path).resolve() - with open(path, "r") as file: - data = json.load(file) - return data - - @staticmethod - def deserialize(path: str) -> "ChallengeData": - # this script is in root/agbenchmark/utils/define_task_types.py - script_dir = Path(__file__).resolve().parent.parent.parent - json_path = script_dir / Path(path) - - with open(json_path, "r") as file: - data = json.load(file) - try: - return ChallengeData(**data) - except: - print(f"FAILED TO PARSE: {data}") - test = "ok" - - def challenge_from_datum(self, file_datum: list[dict[str, Any]]) -> "ChallengeData": - same_task_data = { - "name": self.prefix, - "dependencies": self.dependencies, - "category": self.shared_category, - "task": self.task, - "cutoff": self.cutoff, - } - - if not self.info: - same_task_data["info"] = { - datum["name"]: datum["info"] for datum in file_datum - } - else: - same_task_data["info"] = self.info - - if not self.ground: - same_task_data["ground"] = { - datum["name"]: datum["ground"] for datum in file_datum - } - else: - same_task_data["ground"] = self.ground - - return ChallengeData(**same_task_data) - - def challenge_from_test_data(self, data: dict[str, Any]) -> "ChallengeData": - same_task_data = { - "name": data["name"], - "dependencies": data["dependencies"], - "category": data["category"], - "info": data["info"], - "ground": data["ground"], - } - - if self.same_task: - same_task_data["category"].extend(self.shared_category) - same_task_data["task"] = self.task - same_task_data["cutoff"] = self.cutoff - else: - same_task_data["task"] = data["task"] - same_task_data["cutoff"] = data["cutoff"] - - return ChallengeData(**same_task_data) +class EvalResult(BaseModel): + result: str + result_source: Literal["step_output"] | str + score: float + passed: bool diff --git a/benchmark/agbenchmark/utils/dependencies/graphs.py b/benchmark/agbenchmark/utils/dependencies/graphs.py index 8155e2bfd..47d3d5c09 100644 --- a/benchmark/agbenchmark/utils/dependencies/graphs.py +++ b/benchmark/agbenchmark/utils/dependencies/graphs.py @@ -1,3 +1,5 @@ +import json +import logging import math from pathlib import Path from typing import Any, Dict, List, Tuple @@ -11,6 +13,8 @@ from pyvis.network import Network from agbenchmark.generate_test import DATA_CATEGORY from agbenchmark.utils.utils import write_pretty_json +logger = logging.getLogger(__name__) + def bezier_curve( src: np.ndarray, ctrl: List[float], dst: np.ndarray @@ -221,8 +225,8 @@ def graph_interactive_network( f"{source_id_str}_to_{target_id_str}" # Construct a unique edge id ) if not (source_id_str in nt.get_nodes() and target_id_str in nt.get_nodes()): - print( - f"Skipping edge {source_id_str} -> {target_id_str} due to missing nodes." + logger.warning( + f"Skipping edge {source_id_str} -> {target_id_str} due to missing nodes" ) continue nt.add_edge(source_id_str, target_id_str, id=edge_id_str) @@ -271,9 +275,12 @@ def graph_interactive_network( "layout": {"hierarchical": hierarchical_options}, } - # Serialize the graph to JSON + # Serialize the graph to JSON and save in appropriate locations graph_data = {"nodes": nt.nodes, "edges": nt.edges} + logger.debug(f"Generated graph data:\n{json.dumps(graph_data, indent=4)}") + # FIXME: use more reliable method to find the right location for these files. + # This will fail in all cases except if run from the root of our repo. home_path = Path.cwd() write_pretty_json(graph_data, home_path / "frontend" / "public" / "graph.json") @@ -284,7 +291,6 @@ def graph_interactive_network( # this literally only works in the AutoGPT repo, but this part of the code is not reached if BUILD_SKILL_TREE is false write_pretty_json(graph_data, flutter_app_path / "tree_structure.json") validate_skill_tree(graph_data, "") - import json # Extract node IDs with category "coding" @@ -317,9 +323,6 @@ def graph_interactive_network( scrape_synthesize_tree, flutter_app_path / "scrape_synthesize_tree_structure.json", ) - # If you want to convert back to JSON - filtered_json = json.dumps(graph_data, indent=4) - print(filtered_json) if html_graph_path: file_path = str(Path(html_graph_path).resolve()) diff --git a/benchmark/agbenchmark/utils/get_data_from_helicone.py b/benchmark/agbenchmark/utils/get_data_from_helicone.py index 1e2f5fcbd..dabb2c8b0 100644 --- a/benchmark/agbenchmark/utils/get_data_from_helicone.py +++ b/benchmark/agbenchmark/utils/get_data_from_helicone.py @@ -1,4 +1,5 @@ import json +import logging import os from typing import Optional @@ -7,6 +8,8 @@ import requests from agbenchmark.__main__ import BENCHMARK_START_TIME from agbenchmark.agent_interface import HELICONE_GRAPHQL_LOGS +logger = logging.getLogger(__name__) + def get_data_from_helicone(challenge: str) -> Optional[float]: # Define the endpoint of your GraphQL server @@ -38,8 +41,8 @@ query ExampleQuery($properties: [PropertyFilter!]){ ] } if HELICONE_GRAPHQL_LOGS: - print(query) - print(json.dumps(variables, indent=4)) + logger.debug(f"Executing Helicone query:\n{query.strip()}") + logger.debug(f"Query variables:\n{json.dumps(variables, indent=4)}") operation_name = "ExampleQuery" @@ -59,24 +62,22 @@ query ExampleQuery($properties: [PropertyFilter!]){ data = response.json() except requests.HTTPError as http_err: - print(f"HTTP error occurred: {http_err}") - return None # Re-raise the exception to stop execution + logger.error(f"Helicone returned an HTTP error: {http_err}") + return None except json.JSONDecodeError: - print(f"Invalid JSON response: {response.text if response else 'No response'}") + raw_response = response.text # type: ignore + logger.error( + f"Helicone returned an invalid JSON response: '''{raw_response}'''" + ) return None except Exception as err: - print(f"Other error occurred: {err}") + logger.error(f"Error while trying to get data from Helicone: {err}") return None - try: - if data is None or data.get("data") is None: - print("Invalid response received from server: no data") - return None - return ( - data.get("data", {}) - .get("aggregatedHeliconeRequest", {}) - .get("costUSD", None) - ) - except Exception as err: - print(f"Error occurred while parsing response: {err}") + if data is None or data.get("data") is None: + logger.error("Invalid response received from Helicone: no data") + logger.error(f"Offending response: {response}") return None + return ( + data.get("data", {}).get("aggregatedHeliconeRequest", {}).get("costUSD", None) + ) diff --git a/benchmark/agbenchmark/utils/logging.py b/benchmark/agbenchmark/utils/logging.py new file mode 100644 index 000000000..9a8f9f41d --- /dev/null +++ b/benchmark/agbenchmark/utils/logging.py @@ -0,0 +1,74 @@ +from __future__ import annotations + +import logging + +from colorama import Fore, Style + +SIMPLE_LOG_FORMAT = "[%(asctime)s] %(levelname)s %(message)s" +DEBUG_LOG_FORMAT = "[%(asctime)s] %(levelname)s %(filename)s:%(lineno)03d %(message)s" + + +def configure_logging( + level: int = logging.INFO, +) -> None: + """Configure the native logging module.""" + + # Auto-adjust default log format based on log level + log_format = DEBUG_LOG_FORMAT if level == logging.DEBUG else SIMPLE_LOG_FORMAT + + console_handler = logging.StreamHandler() + console_handler.setFormatter(FancyConsoleFormatter(log_format)) + + # Configure the root logger + logging.basicConfig( + level=level, + format=log_format, + handlers=[console_handler], + ) + + +class FancyConsoleFormatter(logging.Formatter): + """ + A custom logging formatter designed for console output. + + This formatter enhances the standard logging output with color coding. The color + coding is based on the level of the log message, making it easier to distinguish + between different types of messages in the console output. + + The color for each level is defined in the LEVEL_COLOR_MAP class attribute. + """ + + # level -> (level & text color, title color) + LEVEL_COLOR_MAP = { + logging.DEBUG: Fore.LIGHTBLACK_EX, + logging.INFO: Fore.BLUE, + logging.WARNING: Fore.YELLOW, + logging.ERROR: Fore.RED, + logging.CRITICAL: Fore.RED + Style.BRIGHT, + } + + def format(self, record: logging.LogRecord) -> str: + # Make sure `msg` is a string + if not hasattr(record, "msg"): + record.msg = "" + elif not type(record.msg) is str: + record.msg = str(record.msg) + + # Justify the level name to 5 characters minimum + record.levelname = record.levelname.ljust(5) + + # Determine default color based on error level + level_color = "" + if record.levelno in self.LEVEL_COLOR_MAP: + level_color = self.LEVEL_COLOR_MAP[record.levelno] + record.levelname = f"{level_color}{record.levelname}{Style.RESET_ALL}" + + # Determine color for message + color = getattr(record, "color", level_color) + color_is_specified = hasattr(record, "color") + + # Don't color INFO messages unless the color is explicitly specified. + if color and (record.levelno != logging.INFO or color_is_specified): + record.msg = f"{color}{record.msg}{Style.RESET_ALL}" + + return super().format(record) diff --git a/benchmark/agbenchmark/utils/utils.py b/benchmark/agbenchmark/utils/utils.py index 2fc51d212..eaa713730 100644 --- a/benchmark/agbenchmark/utils/utils.py +++ b/benchmark/agbenchmark/utils/utils.py @@ -1,18 +1,23 @@ # radio charts, logs, helper functions for tests, anything else relevant. import json +import logging import os import re from pathlib import Path -from typing import Any, List, Optional +from typing import Any, Optional from dotenv import load_dotenv -load_dotenv() +from agbenchmark.reports.processing.report_types import Test from agbenchmark.utils.data_types import DIFFICULTY_MAP, DifficultyLevel +load_dotenv() + AGENT_NAME = os.getenv("AGENT_NAME") REPORT_LOCATION = os.getenv("REPORT_LOCATION", None) +logger = logging.getLogger(__name__) + def replace_backslash(value: Any) -> Any: if isinstance(value, str): @@ -27,17 +32,6 @@ def replace_backslash(value: Any) -> Any: return value -def calculate_success_percentage(results: list[bool]) -> float: - # Take the last 10 results or all if less than 10 - last_results = results[-10:] if len(results) > 10 else results - success_count = last_results.count(True) - total_count = len(last_results) - if total_count == 0: - return 0 - success_percentage = (success_count / total_count) * 100 # as a percentage - return round(success_percentage, 2) - - def get_test_path(json_file: str | Path) -> str: if isinstance(json_file, str): json_file = Path(json_file) @@ -59,41 +53,41 @@ def get_test_path(json_file: str | Path) -> str: def get_highest_success_difficulty( - data: dict, just_string: Optional[bool] = None + data: dict[str, Test], just_string: Optional[bool] = None ) -> str: highest_difficulty = None highest_difficulty_level = 0 for test_name, test_data in data.items(): try: - if test_data.get("tests", None): - highest_difficulty_str = test_data["metrics"]["highest_difficulty"] + if any(r.success for r in test_data.results): + difficulty_str = test_data.difficulty + if not difficulty_str: + continue + try: - highest_difficulty = DifficultyLevel[highest_difficulty_str] - highest_difficulty_level = DIFFICULTY_MAP[highest_difficulty] + difficulty_enum = DifficultyLevel[difficulty_str.lower()] + difficulty_level = DIFFICULTY_MAP[difficulty_enum] + + if difficulty_level > highest_difficulty_level: + highest_difficulty = difficulty_enum + highest_difficulty_level = difficulty_level except KeyError: - print( - f"Unexpected difficulty level '{highest_difficulty_str}' in test '{test_name}'" + logger.warning( + f"Unexpected difficulty level '{difficulty_str}' " + f"in test '{test_name}'" ) continue - else: - if test_data["metrics"]["success"]: - difficulty_str = test_data["metrics"]["difficulty"] - - try: - difficulty_enum = DifficultyLevel[difficulty_str.lower()] - difficulty_level = DIFFICULTY_MAP[difficulty_enum] - - if difficulty_level > highest_difficulty_level: - highest_difficulty = difficulty_enum - highest_difficulty_level = difficulty_level - except KeyError: - print( - f"Unexpected difficulty level '{difficulty_str}' in test '{test_name}'" - ) - continue - except Exception: - print(f"Make sure you selected the right test, no reports were generated.") + except Exception as e: + logger.warning( + "An unexpected error [1] occurred while analyzing report [2]." + "Please notify a maintainer.\n" + f"Report data [1]: {data}\n" + f"Error [2]: {e}" + ) + logger.warning( + "Make sure you selected the right test, no reports were generated." + ) break if highest_difficulty is not None: @@ -116,22 +110,13 @@ def get_highest_success_difficulty( # remote_url = remote_url[:-4] # git_commit_sha = f"{remote_url}/tree/{repo.head.commit.hexsha}" -# # print(f"GIT_COMMIT_SHA: {git_commit_sha}") +# # logger.debug(f"GIT_COMMIT_SHA: {git_commit_sha}") # return git_commit_sha # except Exception: -# # print(f"{directory} is not a git repository!") +# # logger.error(f"{directory} is not a git repository!") # return None -def agent_eligibible_for_optional_categories( - optional_challenge_categories: List, agent_categories: List -) -> bool: - for element in optional_challenge_categories: - if element not in agent_categories: - return False - return True - - def write_pretty_json(data, json_file): sorted_data = deep_sort(data) json_graph = json.dumps(sorted_data, indent=4) diff --git a/benchmark/notebooks/LLM Score Experimentation.ipynb b/benchmark/notebooks/LLM Score Experimentation.ipynb index b14577fdb..745913971 100644 --- a/benchmark/notebooks/LLM Score Experimentation.ipynb +++ b/benchmark/notebooks/LLM Score Experimentation.ipynb @@ -7,23 +7,21 @@ "metadata": {}, "outputs": [], "source": [ - "import openai\n", "import os\n", "from dotenv import load_dotenv\n", + "from openai import OpenAI\n", "\n", "load_dotenv()\n", "\n", - "OPENAI_API_KEY = os.getenv(\"OPENAI_API_KEY\")\n", - "\n", "def llm_eval(evaluation: str) -> float:\n", - " openai.api_key = OPENAI_API_KEY\n", - " answer = openai.ChatCompletion.create(\n", + " openai_client = OpenAI()\n", + " answer = openai_client.chat.completions.create(\n", " model=\"gpt-4\",\n", " messages=[\n", " {\"role\": \"system\", \"content\": evaluation},\n", " ],\n", " )\n", - " return answer[\"choices\"][0][\"message\"][\"content\"]" + " return answer.choices[0].message.content" ] }, { diff --git a/benchmark/poetry.lock b/benchmark/poetry.lock index 9a27d456f..057b89aa4 100644 --- a/benchmark/poetry.lock +++ b/benchmark/poetry.lock @@ -1,112 +1,117 @@ # This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. 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= "^2.31.0" -openai = "^0.27.8" +openai = "^1.7.2" pydantic = "^1.10.9" python-dotenv = "^1.0.0" click = "^8.1.3" @@ -30,8 +30,10 @@ uvicorn = "^0.23.2" fastapi = "^0.99.0" python-multipart = "^0.0.6" toml = "^0.10.2" -helicone = "^1.0.9" +# helicone = "^1.0.9" # incompatible with openai@^1.0.0 httpx = "^0.24.0" +agent-protocol-client = "^1.1.0" +click-default-group = "^1.2.4" [tool.poetry.group.dev.dependencies] flake8 = "^3.9.2" diff --git a/benchmark/server.py b/benchmark/server.py deleted file mode 100644 index e7f639eb8..000000000 --- a/benchmark/server.py +++ /dev/null @@ -1,121 +0,0 @@ -import io -import json -import logging -import shutil -from pathlib import Path -from random import randint -from typing import Annotated, Any, Dict, List - -from fastapi import FastAPI, File, Form, HTTPException, UploadFile -from fastapi.responses import StreamingResponse -from pydantic import BaseModel - -# Set up logging -logging.basicConfig(level=logging.INFO) -logger = logging.getLogger(__name__) - -app = FastAPI() -artifacts: List[Dict[str, Any]] = [] - - -class Task(BaseModel): - input: str - - -@app.post("/agent/tasks/{task_id}/artifacts") -async def upload_file( - task_id: str, file: Annotated[UploadFile, File()], relative_path: str = Form("") -) -> Dict[str, Any]: - logger.info( - "Uploading file for task_id: %s with relative path: %s", task_id, relative_path - ) - absolute_directory_path = Path(__file__).parent.absolute() - save_path = ( - absolute_directory_path - / "agent/gpt-engineer" - / "projects/my-new-project/workspace" - ) - - random_string = str(randint(0, 100000)) - while random_string in artifacts: - random_string = str(randint(0, 100000)) - - artifact_data = await file.read() - artifacts.append( - { - "binary": artifact_data, - "relative_path": relative_path, - "file_name": file.filename, - "artifact_id": random_string, - } - ) - - print(artifacts) - return { - "artifact_id": random_string, - "file_name": "file_name", - "relative_path": "relative_path", - } - - -@app.get("/agent/tasks/{task_id}/artifacts") -async def get_files() -> List[Dict[str, Any]]: - logger.info("Fetching list of files for task") - return artifacts - - -@app.get("/agent/tasks/{task_id}/artifacts/{artifact_id}") -async def get_file(artifact_id: str): - for artifact in artifacts: - if artifact["artifact_id"] == artifact_id: - break - else: - logger.error("Attempt to access nonexistent artifact with ID: %s", artifact_id) - raise HTTPException(status_code=404, detail="Artifact not found") - - logger.info("Fetching artifact with ID: %s", artifact_id) - # find aritifact where artifact_id = artifact_id - - for artifact in artifacts: - if artifact["artifact_id"] == artifact_id: - return StreamingResponse( - io.BytesIO(artifact["binary"]), - media_type="application/octet-stream", - headers={"Content-Disposition": f"attachment; filename=test.txt"}, - ) - # return 404 - return HTTPException(status_code=404, detail="Artifact not found") - - -@app.post("/agent/tasks/{task_id}/steps") -async def create_steps(task_id: str): - logger.info("Creating step for task_id: %s", task_id) - return { - "input": "random", - "additional_input": {}, - "task_id": task_id, - "step_id": "random_step", - "name": "random", - "status": "created", - "output": "random", - "additional_output": {}, - "artifacts": [], - "is_last": True, - } - - -@app.post("/agent/tasks") -async def create_tasks(task: Task): - artifacts.clear() - return { - "input": "random", - "additional_input": {}, - "task_id": "static_task_id", - "artifacts": [], - } - - -if __name__ == "__main__": - import uvicorn - - uvicorn.run(app, host="0.0.0.0", port=8000) @@ -64,7 +64,7 @@ d88P 888 "Y88888 "Y888 "Y88P" "Y8888P88 888 888 install_error = True try: - # Check if GitHub user name is configured + # Check if git user is configured user_name = ( subprocess.check_output(["git", "config", "user.name"]) .decode("utf-8") @@ -79,7 +79,7 @@ d88P 888 "Y88888 "Y888 "Y88P" "Y8888P88 888 888 if user_name and user_email: click.echo( click.style( - f"✅ GitHub account is configured with username: {user_name} and email: {user_email}", + f"✅ Git is configured with name '{user_name}' and email '{user_email}'", fg="green", ) ) @@ -90,25 +90,27 @@ d88P 888 "Y88888 "Y888 "Y88P" "Y8888P88 888 888 except subprocess.CalledProcessError: # If the GitHub account is not configured, print instructions on how to set it up - click.echo(click.style("❌ GitHub account is not configured.", fg="red")) + click.echo(click.style("⚠️ Git user is not configured.", fg="red")) click.echo( click.style( - "To configure your GitHub account, use the following commands:", + "To configure Git with your user info, use the following commands:", fg="red", ) ) click.echo( click.style( - ' git config --global user.name "Your GitHub Username"', fg="red" + ' git config --global user.name "Your (user)name"', fg="red" ) ) click.echo( click.style( - ' git config --global user.email "Your GitHub Email"', fg="red" + ' git config --global user.email "Your email"', fg="red" ) ) install_error = True + print_access_token_instructions = False + # Check for the existence of the .github_access_token file if os.path.exists(".github_access_token"): with open(".github_access_token", "r") as file: @@ -169,7 +171,7 @@ d88P 888 "Y88888 "Y888 "Y88P" "Y8888P88 888 888 # Instructions to set up GitHub access token click.echo( click.style( - "❌ To configure your GitHub access token, follow these steps:", fg="red" + "💡 To configure your GitHub access token, follow these steps:", fg="red" ) ) click.echo( @@ -195,6 +197,7 @@ d88P 888 "Y88888 "Y888 "Y88P" "Y8888P88 888 888 click.echo( click.style("\t7. Save the file and run the setup command again.", fg="red") ) + if install_error: click.echo( click.style( @@ -219,7 +222,7 @@ def create(agent_name): import re import shutil - if not re.match("\w*$", agent_name): + if not re.match(r"\w*$", agent_name): click.echo( click.style( f"😞 Agent name '{agent_name}' is not valid. It should not contain spaces or special characters other than -_", @@ -241,12 +244,6 @@ def create(agent_name): fg="green", ) ) - click.echo( - click.style( - f"🚀 If you would like to enter the arena, run './run arena enter {agent_name}'", - fg="yellow", - ) - ) else: click.echo( click.style( @@ -260,7 +257,11 @@ def create(agent_name): @agent.command() @click.argument("agent_name") -@click.option("--no-setup", is_flag=True, help="Rebuilds your poetry env") +@click.option( + "--no-setup", + is_flag=True, + help="Disables running the setup script before starting the agent", +) def start(agent_name, no_setup): """Start agent command""" import os diff --git a/docs/content/configuration/imagegen.md b/docs/content/AutoGPT/configuration/imagegen.md index 1f4e91aa8..1f4e91aa8 100644 --- a/docs/content/configuration/imagegen.md +++ b/docs/content/AutoGPT/configuration/imagegen.md diff --git a/docs/content/configuration/options.md b/docs/content/AutoGPT/configuration/options.md index 12df23c33..12df23c33 100644 --- a/docs/content/configuration/options.md +++ b/docs/content/AutoGPT/configuration/options.md diff --git a/docs/content/configuration/search.md b/docs/content/AutoGPT/configuration/search.md index 4640d63c6..4640d63c6 100644 --- a/docs/content/configuration/search.md +++ b/docs/content/AutoGPT/configuration/search.md diff --git a/docs/content/configuration/voice.md b/docs/content/AutoGPT/configuration/voice.md index 8aa37d7b6..223a48def 100644 --- a/docs/content/configuration/voice.md +++ b/docs/content/AutoGPT/configuration/voice.md @@ -3,7 +3,7 @@ Enter this command to use TTS _(Text-to-Speech)_ for AutoGPT ```shell -python -m autogpt --speak +./autogpt.sh --speak ``` Eleven Labs provides voice technologies such as voice design, speech synthesis, and diff --git a/docs/content/AutoGPT/index.md b/docs/content/AutoGPT/index.md new file mode 100644 index 000000000..aad7cc37d --- /dev/null +++ b/docs/content/AutoGPT/index.md @@ -0,0 +1,29 @@ +# AutoGPT Agent + +[🔧 **Setup**](./setup) + |  +[💻 **User guide**](./usage.md) + |  +[🐙 **GitHub**](https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/autogpt) + +**Location:** `autogpts/autogpt/` in the GitHub repo + +AutoGPT was conceived when OpenAI published their GPT-4 model accompanied by a paper +outlining the advanced reasoning and task-solving abilities of the model. The concept +was (and still is) fairly simple: let an LLM decide what to do over and over, while +feeding the results of its actions back into the prompt. This allows the program to +iteratively and incrementally work towards its objective. + +The fact that this program is able to execute actions on behalf of its user makes +it an **agent**. In the case of AutoGPT, the user still has to authorize every action, +but as the project progresses we'll be able to give the agent more autonomy and only +require consent for select actions. + +AutoGPT is a **generalist agent**, meaning it is not designed with a specific task in +mind. Instead, it is designed to be able to execute a wide range of tasks across many +disciplines, as long as it can be done on a computer. + +## Coming soon +* How does AutoGPT work? +* What can I use AutoGPT for? +* What does the future of AutoGPT look like? diff --git a/docs/content/plugins.md b/docs/content/AutoGPT/plugins.md index 4733a8b3d..4733a8b3d 100644 --- a/docs/content/plugins.md +++ b/docs/content/AutoGPT/plugins.md diff --git a/docs/content/AutoGPT/setup/docker.md b/docs/content/AutoGPT/setup/docker.md new file mode 100644 index 000000000..35bd7c2c1 --- /dev/null +++ b/docs/content/AutoGPT/setup/docker.md @@ -0,0 +1,197 @@ +# AutoGPT + Docker guide + +!!! important + Docker Compose version 1.29.0 or later is required to use version 3.9 of the Compose file format. + You can check the version of Docker Compose installed on your system by running the following command: + + ```shell + docker compose version + ``` + + This will display the version of Docker Compose that is currently installed on your system. + + If you need to upgrade Docker Compose to a newer version, you can follow the installation instructions in the Docker documentation: https://docs.docker.com/compose/install/ + +## Basic Setup + +1. Make sure you have Docker installed, see [requirements](#requirements) +2. Create a project directory for AutoGPT + + ```shell + mkdir AutoGPT + cd AutoGPT + ``` + +3. In the project directory, create a file called `docker-compose.yml`: + + <details> + <summary> + <code>docker-compose.yml></code> for <= v0.4.7 + </summary> + + ```yaml + version: "3.9" + services: + auto-gpt: + image: significantgravitas/auto-gpt + env_file: + - .env + profiles: ["exclude-from-up"] + volumes: + - ./auto_gpt_workspace:/app/auto_gpt_workspace + - ./data:/app/data + ## allow auto-gpt to write logs to disk + - ./logs:/app/logs + ## uncomment following lines if you want to make use of these files + ## you must have them existing in the same folder as this docker-compose.yml + #- type: bind + # source: ./azure.yaml + # target: /app/azure.yaml + #- type: bind + # source: ./ai_settings.yaml + # target: /app/ai_settings.yaml + #- type: bind + # source: ./prompt_settings.yaml + # target: /app/prompt_settings.yaml + ``` + </details> + + <details> + <summary> + <code>docker-compose.yml></code> for > v0.4.7 (including <code>master</code>) + </summary> + + ```yaml + version: "3.9" + services: + auto-gpt: + image: significantgravitas/auto-gpt + env_file: + - .env + ports: + - "8000:8000" # remove this if you just want to run a single agent in TTY mode + profiles: ["exclude-from-up"] + volumes: + - ./data:/app/data + ## allow auto-gpt to write logs to disk + - ./logs:/app/logs + ## uncomment following lines if you want to make use of these files + ## you must have them existing in the same folder as this docker-compose.yml + #- type: bind + # source: ./ai_settings.yaml + # target: /app/ai_settings.yaml + #- type: bind + # source: ./prompt_settings.yaml + # target: /app/prompt_settings.yaml + ``` + </details> + + +4. Download [`.env.template`][.env.template] and save it as `.env` in the AutoGPT folder. +5. Follow the [configuration](#configuration) steps. +6. Pull the latest image from [Docker Hub] + + ```shell + docker pull significantgravitas/auto-gpt + ``` + +!!! note "Docker only supports headless browsing" + AutoGPT uses a browser in headless mode by default: `HEADLESS_BROWSER=True`. + Please do not change this setting in combination with Docker, or AutoGPT will crash. + +[.env.template]: https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/autogpt/.env.template +[Docker Hub]: https://hub.docker.com/r/significantgravitas/auto-gpt + +## Configuration + +1. Open the `.env` file in a text editor. This file may + be hidden by default in some operating systems due to the dot prefix. To reveal + hidden files, follow the instructions for your specific operating system: + [Windows][show hidden files/Windows], [macOS][show hidden files/macOS]. +2. Find the line that says `OPENAI_API_KEY=`. +3. After the `=`, enter your unique OpenAI API Key *without any quotes or spaces*. +4. Enter any other API keys or tokens for services you would like to use. + + !!! note + To activate and adjust a setting, remove the `# ` prefix. + +5. Save and close the `.env` file. + +Templates for the optional extra configuration files (e.g. `prompt_settings.yml`) can be +found in the [repository]. + +!!! info "Using a GPT Azure-instance" + If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and + make an Azure configuration file: + + - Rename `azure.yaml.template` to `azure.yaml` and provide the relevant `azure_api_base`, `azure_api_version` and all the deployment IDs for the relevant models in the `azure_model_map` section: + - `fast_llm_deployment_id`: your gpt-3.5-turbo or gpt-4 deployment ID + - `smart_llm_deployment_id`: your gpt-4 deployment ID + - `embedding_model_deployment_id`: your text-embedding-ada-002 v2 deployment ID + + Example: + + ```yaml + # Please specify all of these values as double-quoted strings + # Replace string in angled brackets (<>) to your own deployment Name + azure_model_map: + fast_llm_deployment_id: "<auto-gpt-deployment>" + ... + ``` + + Details can be found in the [openai-python docs], and in the [Azure OpenAI docs] for the embedding model. + If you're on Windows you may need to install an [MSVC library](https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170). + + **Note:** Azure support has been dropped in `master`, so these instructions will only work with v0.4.7 (or earlier). + +[repository]: https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/autogpt +[show hidden files/Windows]: https://support.microsoft.com/en-us/windows/view-hidden-files-and-folders-in-windows-97fbc472-c603-9d90-91d0-1166d1d9f4b5 +[show hidden files/macOS]: https://www.pcmag.com/how-to/how-to-access-your-macs-hidden-files +[openai-python docs]: https://github.com/openai/openai-python#microsoft-azure-endpoints +[Azure OpenAI docs]: https://learn.microsoft.com/en-us/azure/cognitive-services/openai/tutorials/embeddings?tabs=command-line + +## Developer Setup + +!!! tip + Use this setup if you have cloned the repository and have made (or want to make) + changes to the codebase. + +1. Copy `.env.template` to `.env`. +2. Follow the standard [configuration](#configuration) steps above. + +## Running AutoGPT with Docker + +After following setup instructions above, you can run AutoGPT with the following command: + +```shell +docker compose run --rm auto-gpt +``` + +This creates and starts an AutoGPT container, and removes it after the application stops. +This does not mean your data will be lost: data generated by the application is stored +in the `data` folder. + +Subcommands and arguments work the same as described in the [user guide]: + +* Run AutoGPT: + ```shell + docker compose run --rm auto-gpt serve + ``` +* Run AutoGPT in TTY mode, with continuous mode. + ```shell + docker compose run --rm auto-gpt run --continuous + ``` +* Run AutoGPT in TTY mode and install dependencies for all active plugins: + ```shell + docker compose run --rm auto-gpt run --install-plugin-deps + ``` + +If you dare, you can also build and run it with "vanilla" docker commands: + +```shell +docker build -t autogpt . +docker run -it --env-file=.env -v $PWD:/app autogpt +docker run -it --env-file=.env -v $PWD:/app --rm autogpt --gpt3only --continuous +``` + +[user guide]: /autogpt/usage/#command-line-interface diff --git a/docs/content/AutoGPT/setup/for-developers.md b/docs/content/AutoGPT/setup/for-developers.md new file mode 100644 index 000000000..fa5871d1a --- /dev/null +++ b/docs/content/AutoGPT/setup/for-developers.md @@ -0,0 +1,9 @@ +Coming soon... + +TODO: +- Running and developing AutoGPT with [VSCode + devcontainer](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) +- Resources + - Prompt engineering guides + - Related projects + - Papers +- Technical documentation diff --git a/docs/content/AutoGPT/setup/get-repo-dialog.png b/docs/content/AutoGPT/setup/get-repo-dialog.png Binary files differnew file mode 100644 index 000000000..813160e45 --- /dev/null +++ b/docs/content/AutoGPT/setup/get-repo-dialog.png diff --git a/docs/content/AutoGPT/setup/index.md b/docs/content/AutoGPT/setup/index.md new file mode 100644 index 000000000..5ef214b61 --- /dev/null +++ b/docs/content/AutoGPT/setup/index.md @@ -0,0 +1,127 @@ +# AutoGPT Agent setup + +[🐋 **Set up & Run with Docker**](./docker.md) + |  +[👷🏼 **For Developers**](./for-developers.md) + +## 📋 Requirements + +### Linux / macOS + +- Python 3.10 or later +- Poetry ([instructions](https://python-poetry.org/docs/#installation)) + +### Windows (WSL) + +- WSL 2 + - See also the [requirements for Linux](#linux--macos) +- [Docker Desktop](https://docs.docker.com/desktop/install/windows-install/) + +### Windows + +!!! attention + We recommend setting up AutoGPT with WSL. Some things don't work exactly the same on + Windows and we currently can't provide specialized instructions for all those cases. + +- Python 3.10 or later ([instructions](https://www.tutorialspoint.com/how-to-install-python-in-windows)) +- Poetry ([instructions](https://python-poetry.org/docs/#installation)) +- [Docker Desktop](https://docs.docker.com/desktop/install/windows-install/) + + +### 🗝️ Getting an OpenAI API key + +Get your OpenAI API key from: +[https://platform.openai.com/account/api-keys](https://platform.openai.com/account/api-keys). + +!!! attention + To use the OpenAI API with AutoGPT, we strongly recommend **setting up billing** + (AKA paid account). Free accounts are [limited][openai/api limits] to 3 API calls per + minute, which can cause the application to crash. + + You can set up a paid account at [Manage account > Billing > Overview](https://platform.openai.com/account/billing/overview). + +[openai/api limits]: https://platform.openai.com/docs/guides/rate-limits/free-tier-rate-limits + +!!! important + It's highly recommended that you keep track of your API costs on [the Usage page](https://platform.openai.com/account/usage). + You can also set limits on how much you spend on [the Usage limits page](https://platform.openai.com/account/billing/limits). + + + + +## Setting up AutoGPT + +### Getting AutoGPT + +Since we don't ship AutoGPT as a desktop application, you'll need to download the +[project] from GitHub and give it a place on your computer. + + + +* To get the latest bleeding edge version, use `master`. +* If you're looking for more stability, check out the latest AutoGPT [release][releases]. + +[project]: https://github.com/Significant-Gravitas/AutoGPT +[releases]: https://github.com/Significant-Gravitas/AutoGPT/releases + +!!! note + These instructions don't apply if you're looking to run AutoGPT as a docker image. + Instead, check out the [Docker setup](./docker.md) guide. + +### Completing the Setup + +Once you have cloned or downloaded the project, you can find the AutoGPT Agent in the +`autogpts/autogpt/` folder. In this folder: + +1. Find the file named `.env.template`. This file may + be hidden by default in some operating systems due to the dot prefix. To reveal + hidden files, follow the instructions for your specific operating system: + [Windows][show hidden files/Windows] and [macOS][show hidden files/macOS]. +2. Create a copy of `.env.template` and call it `.env`; + if you're already in a command prompt/terminal window: + ```shell + cp .env.template .env + ``` +3. Open the `.env` file in a text editor. +4. Find the line that says `OPENAI_API_KEY=`. +5. Insert your OpenAI API Key directly after = without quotes or spaces.. + ```yaml + OPENAI_API_KEY=sk-qwertykeys123456 + ``` + + !!! info "Using a GPT Azure-instance" + If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and + make an Azure configuration file. + + Rename `azure.yaml.template` to `azure.yaml` and provide the relevant + `azure_api_base`, `azure_api_version` and deployment IDs for the models that you + want to use. + + E.g. if you want to use `gpt-3.5-turbo-16k` and `gpt-4-0314`: + + ```yaml + # Please specify all of these values as double-quoted strings + # Replace string in angled brackets (<>) to your own deployment Name + azure_model_map: + gpt-3.5-turbo-16k: "<auto-gpt-deployment>" + ... + ``` + + Details can be found in the [openai-python docs], and in the [Azure OpenAI docs] for the embedding model. + If you're on Windows you may need to install an [MSVC library](https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170). + +6. Enter any other API keys or tokens for services you would like to use. + + !!! note + To activate and adjust a setting, remove the `# ` prefix. + +7. Save and close the `.env` file. +8. _Optional: run `poetry install` to install all required dependencies._ The + application also checks for and installs any required dependencies when it starts. + +You should now be able to explore the CLI (`./autogpt.sh --help`) and run the application. + +See the [user guide](../usage.md) for further instructions. + +[show hidden files/Windows]: https://support.microsoft.com/en-us/windows/view-hidden-files-and-folders-in-windows-97fbc472-c603-9d90-91d0-1166d1d9f4b5 +[show hidden files/macOS]: https://www.pcmag.com/how-to/how-to-access-your-macs-hidden-files diff --git a/docs/content/share-your-logs.md b/docs/content/AutoGPT/share-your-logs.md index 9fc6fef3d..3f4139ce1 100644 --- a/docs/content/share-your-logs.md +++ b/docs/content/AutoGPT/share-your-logs.md @@ -9,9 +9,9 @@ Activity, Error, and Debug logs are located in `./logs` To print out debug logs: ```shell -./run.sh --debug # on Linux / macOS +./autogpt.sh --debug # on Linux / macOS -.\run.bat --debug # on Windows +.\autogpt.bat --debug # on Windows docker-compose run --rm auto-gpt --debug # in Docker ``` diff --git a/docs/content/testing.md b/docs/content/AutoGPT/testing.md index ef8176abf..ef8176abf 100644 --- a/docs/content/testing.md +++ b/docs/content/AutoGPT/testing.md diff --git a/docs/content/AutoGPT/usage.md b/docs/content/AutoGPT/usage.md new file mode 100644 index 000000000..09447f03d --- /dev/null +++ b/docs/content/AutoGPT/usage.md @@ -0,0 +1,229 @@ +# AutoGPT Agent User Guide + +!!! note + This guide assumes you are in the `autogpts/autogpt` folder, where the AutoGPT Agent + is located. + +## Command Line Interface + +Running `./autogpt.sh` (or any of its subcommands) with `--help` lists all the possible +sub-commands and arguments you can use: + +```shell +$ ./autogpt.sh --help +Usage: python -m autogpt [OPTIONS] COMMAND [ARGS]... + +Options: + --help Show this message and exit. + +Commands: + run Sets up and runs an agent, based on the task specified by the... + serve Starts an Agent Protocol compliant AutoGPT server, which creates... +``` + +!!! important "For Windows users" + On Windows, use `.\autogpt.bat` instead of `./autogpt.sh`. + Everything else (subcommands, arguments) should work the same. + +!!! info "Usage with Docker" + For use with Docker, replace the script in the examples with + `docker compose run --rm auto-gpt`: + + ```shell + docker compose run --rm auto-gpt --ai-settings <filename> + docker compose run --rm auto-gpt serve + ``` + +### `run` – CLI mode + +The `run` sub-command starts AutoGPT with the legacy CLI interface. + +<details> +<summary> +<code>./autogpt.sh run --help</code> +</summary> + +```shell +$ ./autogpt.sh run --help +Usage: python -m autogpt run [OPTIONS] + + Sets up and runs an agent, based on the task specified by the user, or + resumes an existing agent. + +Options: + -c, --continuous Enable Continuous Mode + -y, --skip-reprompt Skips the re-prompting messages at the + beginning of the script + -C, --ai-settings FILE Specifies which ai_settings.yaml file to + use, relative to the AutoGPT root directory. + Will also automatically skip the re-prompt. + -P, --prompt-settings FILE Specifies which prompt_settings.yaml file to + use. + -l, --continuous-limit INTEGER Defines the number of times to run in + continuous mode + --speak Enable Speak Mode + --debug Enable Debug Mode + --gpt3only Enable GPT3.5 Only Mode + --gpt4only Enable GPT4 Only Mode + -b, --browser-name TEXT Specifies which web-browser to use when + using selenium to scrape the web. + --allow-downloads Dangerous: Allows AutoGPT to download files + natively. + --skip-news Specifies whether to suppress the output of + latest news on startup. + --install-plugin-deps Installs external dependencies for 3rd party + plugins. + --ai-name TEXT AI name override + --ai-role TEXT AI role override + --constraint TEXT Add or override AI constraints to include in + the prompt; may be used multiple times to + pass multiple constraints + --resource TEXT Add or override AI resources to include in + the prompt; may be used multiple times to + pass multiple resources + --best-practice TEXT Add or override AI best practices to include + in the prompt; may be used multiple times to + pass multiple best practices + --override-directives If specified, --constraint, --resource and + --best-practice will override the AI's + directives instead of being appended to them + --help Show this message and exit. +``` +</details> + +This mode allows running a single agent, and saves the agent's state when terminated. +This means you can *resume* agents at a later time. See also [agent state]. + +!!! note + For legacy reasons, the CLI will default to the `run` subcommand when none is + specified: running `./autogpt.sh run [OPTIONS]` does the same as `./autogpt.sh [OPTIONS]`, + but this may change in the future. + +#### 💀 Continuous Mode ⚠️ + +Run the AI **without** user authorization, 100% automated. +Continuous mode is NOT recommended. +It is potentially dangerous and may cause your AI to run forever or carry out actions you would not usually authorize. +Use at your own risk. + +```shell +./autogpt.sh --continuous +``` + +To exit the program, press ++ctrl+c++ + +### `serve` – Agent Protocol mode with UI + +With `serve`, the application exposes an Agent Protocol compliant API and serves a +frontend, by default on `http://localhost:8000`. You can configure the port it is served on with the `AP_SERVER_PORT` environment variable. + +<details> +<summary> +<code>./autogpt.sh serve --help</code> +</summary> + +```shell +$ ./autogpt.sh serve --help +Usage: python -m autogpt serve [OPTIONS] + + Starts an Agent Protocol compliant AutoGPT server, which creates a custom + agent for every task. + +Options: + -P, --prompt-settings FILE Specifies which prompt_settings.yaml file to + use. + --debug Enable Debug Mode + --gpt3only Enable GPT3.5 Only Mode + --gpt4only Enable GPT4 Only Mode + -b, --browser-name TEXT Specifies which web-browser to use when using + selenium to scrape the web. + --allow-downloads Dangerous: Allows AutoGPT to download files + natively. + --install-plugin-deps Installs external dependencies for 3rd party + plugins. + --help Show this message and exit. +``` +</details> + +For more information about the API of the application, see [agentprotocol.ai](https://agentprotocol.ai). + +<!-- TODO: add guide/manual for frontend --> + +### Arguments + +!!! attention + Most arguments are equivalent to configuration options. See [`.env.template`][.env.template] + for all available configuration options. + +!!! note + Replace anything in angled brackets (<>) to a value you want to specify + +Here are some common arguments you can use when running AutoGPT: + +* Run AutoGPT with a different AI Settings file + + ```shell + ./autogpt.sh --ai-settings <filename> + ``` + +* Run AutoGPT with a different Prompt Settings file + + ```shell + ./autogpt.sh --prompt-settings <filename> + ``` + +!!! note + There are shorthands for some of these flags, for example `-P` for `--prompt-settings`. + Use `./autogpt.sh --help` for more information. + +[.env.template]: https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/autogpt/.env.template + +## Agent State +[agent state]: #agent-state + +The state of individual agents is stored in the `data/agents` folder. You can use this +in various ways: + +* Resume your agent at a later time. +* Create "checkpoints" for your agent so you can always go back to specific points in + its history. +* Share your agent! + +## Workspace +[workspace]: #workspace + +Agents can read and write files. This happens in the `workspace` folder, which +is in `data/agents/<agent_id>/`. Files outside of this folder can not be accessed by the +agent *unless* `RESTRICT_TO_WORKSPACE` is set to `False`. + +!!! warning + We do not recommend disabling `RESTRICT_TO_WORKSPACE`, unless AutoGPT is running in + a sandbox environment where it couldn't do any damage (e.g. Docker or a VM). + +## Logs + +Activity, Error, and Debug logs are located in `logs`. + +!!! tip + Do you notice weird behavior with your agent? Do you have an interesting use case? Do you have a bug you want to report? + Follow the step below to enable your logs. You can include these logs when making an issue report or discussing an issue with us. + +To print out debug logs: + +```shell +./autogpt.sh --debug +``` + +## Disabling Command Categories + +If you want to selectively disable some command groups, you can use the +`DISABLED_COMMAND_CATEGORIES` config in your `.env`. You can find the list of available +categories [here][command categories]. + +For example, to disable coding related features, set it to the value below: + +```ini +DISABLED_COMMAND_CATEGORIES=autogpt.commands.execute_code +``` + +[command categories]: https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpts/autogpt/autogpt/commands/__init__.py diff --git a/docs/content/challenges/introduction.md b/docs/content/challenges/introduction.md index 5f8e8d9ea..4da7d4fe0 100644 --- a/docs/content/challenges/introduction.md +++ b/docs/content/challenges/introduction.md @@ -1,4 +1,3 @@ -introduction.md # Introduction to Challenges Welcome to the AutoGPT Challenges page! This is a space where we encourage community members to collaborate and contribute towards improving AutoGPT by identifying and solving challenges that AutoGPT is not yet able to achieve. diff --git a/docs/content/configuration/memory.md b/docs/content/configuration/memory.md deleted file mode 100644 index 7606f1ae1..000000000 --- a/docs/content/configuration/memory.md +++ /dev/null @@ -1,251 +0,0 @@ -!!! warning - The Pinecone, Milvus, Redis, and Weaviate memory backends were rendered incompatible - by work on the memory system, and have been removed. - Whether support will be added back in the future is subject to discussion, - feel free to pitch in: https://github.com/Significant-Gravitas/AutoGPT/discussions/4280 - -## Setting Your Cache Type - -By default, AutoGPT set up with Docker Compose will use Redis as its memory backend. -Otherwise, the default is LocalCache (which stores memory in a JSON file). - -To switch to a different backend, change the `MEMORY_BACKEND` in `.env` -to the value that you want: - -* `json_file` uses a local JSON cache file -* `pinecone` uses the Pinecone.io account you configured in your ENV settings -* `redis` will use the redis cache that you configured -* `milvus` will use the milvus cache that you configured -* `weaviate` will use the weaviate cache that you configured - -!!! warning - The Pinecone, Milvus, Redis, and Weaviate memory backends were rendered incompatible - by work on the memory system, and have been removed. - Whether support will be added back in the future is subject to discussion, - feel free to pitch in: https://github.com/Significant-Gravitas/AutoGPT/discussions/4280 - -## Memory Backend Setup - -Links to memory backends - -- [Pinecone](https://www.pinecone.io/) -- [Milvus](https://milvus.io/) – [self-hosted](https://milvus.io/docs), or managed with [Zilliz Cloud](https://zilliz.com/) -- [Redis](https://redis.io) -- [Weaviate](https://weaviate.io) - -!!! warning - The Pinecone, Milvus, Redis, and Weaviate memory backends were rendered incompatible - by work on the memory system, and have been removed. - Whether support will be added back in the future is subject to discussion, - feel free to pitch in: https://github.com/Significant-Gravitas/AutoGPT/discussions/4280 - -### Redis Setup - -!!! important - If you have set up AutoGPT using Docker Compose, then Redis is included, no further - setup needed. - -!!! caution - This setup is not intended to be publicly accessible and lacks security measures. - Avoid exposing Redis to the internet without a password or at all! - -1. Launch Redis container - - ```shell - docker run -d --name redis-stack-server -p 6379:6379 redis/redis-stack-server:latest - ``` - -3. Set the following settings in `.env` - - ```shell - MEMORY_BACKEND=redis - REDIS_HOST=localhost - REDIS_PORT=6379 - REDIS_PASSWORD=<PASSWORD> - ``` - - Replace `<PASSWORD>` by your password, omitting the angled brackets (<>). - - Optional configuration: - - - `WIPE_REDIS_ON_START=False` to persist memory stored in Redis between runs. - - `MEMORY_INDEX=<WHATEVER>` to specify a name for the memory index in Redis. - The default is `auto-gpt`. - -!!! info - See [redis-stack-server](https://hub.docker.com/r/redis/redis-stack-server) for - setting a password and additional configuration. - -!!! warning - The Pinecone, Milvus, Redis, and Weaviate memory backends were rendered incompatible - by work on the memory system, and have been removed. - Whether support will be added back in the future is subject to discussion, - feel free to pitch in: https://github.com/Significant-Gravitas/AutoGPT/discussions/4280 - -### 🌲 Pinecone API Key Setup - -Pinecone lets you store vast amounts of vector-based memory, allowing the agent to load only relevant memories at any given time. - -1. Go to [pinecone](https://app.pinecone.io/) and make an account if you don't already have one. -2. Choose the `Starter` plan to avoid being charged. -3. Find your API key and region under the default project in the left sidebar. - -In the `.env` file set: - -- `PINECONE_API_KEY` -- `PINECONE_ENV` (example: `us-east4-gcp`) -- `MEMORY_BACKEND=pinecone` - -!!! warning - The Pinecone, Milvus, Redis, and Weaviate memory backends were rendered incompatible - by work on the memory system, and have been removed. - Whether support will be added back in the future is subject to discussion, - feel free to pitch in: https://github.com/Significant-Gravitas/AutoGPT/discussions/4280 - -### Milvus Setup - -[Milvus](https://milvus.io/) is an open-source, highly scalable vector database to store -huge amounts of vector-based memory and provide fast relevant search. It can be quickly -deployed with docker, or as a cloud service provided by [Zilliz Cloud](https://zilliz.com/). - -1. Deploy your Milvus service, either locally using docker or with a managed Zilliz Cloud database: - - [Install and deploy Milvus locally](https://milvus.io/docs/install_standalone-operator.md) - - - Set up a managed Zilliz Cloud database - 1. Go to [Zilliz Cloud](https://zilliz.com/) and sign up if you don't already have account. - 2. In the *Databases* tab, create a new database. - - Remember your username and password - - Wait until the database status is changed to RUNNING. - 3. In the *Database detail* tab of the database you have created, the public cloud endpoint, such as: - `https://xxx-xxxx.xxxx.xxxx.zillizcloud.com:443`. - -2. Run `pip3 install pymilvus` to install the required client library. - Make sure your PyMilvus version and Milvus version are [compatible](https://github.com/milvus-io/pymilvus#compatibility) - to avoid issues. - See also the [PyMilvus installation instructions](https://github.com/milvus-io/pymilvus#installation). - -3. Update `.env`: - - `MEMORY_BACKEND=milvus` - - One of: - - `MILVUS_ADDR=host:ip` (for local instance) - - `MILVUS_ADDR=https://xxx-xxxx.xxxx.xxxx.zillizcloud.com:443` (for Zilliz Cloud) - - The following settings are **optional**: - - - `MILVUS_USERNAME='username-of-your-milvus-instance'` - - `MILVUS_PASSWORD='password-of-your-milvus-instance'` - - `MILVUS_SECURE=True` to use a secure connection. - Only use if your Milvus instance has TLS enabled. - *Note: setting `MILVUS_ADDR` to a `https://` URL will override this setting.* - - `MILVUS_COLLECTION` to change the collection name to use in Milvus. - Defaults to `autogpt`. - -!!! warning - The Pinecone, Milvus, Redis, and Weaviate memory backends were rendered incompatible - by work on the memory system, and have been removed. - Whether support will be added back in the future is subject to discussion, - feel free to pitch in: https://github.com/Significant-Gravitas/AutoGPT/discussions/4280 - -### Weaviate Setup -[Weaviate](https://weaviate.io/) is an open-source vector database. It allows to store -data objects and vector embeddings from ML-models and scales seamlessly to billion of -data objects. To set up a Weaviate database, check out their [Quickstart Tutorial](https://weaviate.io/developers/weaviate/quickstart). - -Although still experimental, [Embedded Weaviate](https://weaviate.io/developers/weaviate/installation/embedded) -is supported which allows the AutoGPT process itself to start a Weaviate instance. -To enable it, set `USE_WEAVIATE_EMBEDDED` to `True` and make sure you `poetry add weaviate-client@^3.15.4`. - -#### Install the Weaviate client - -Install the Weaviate client before usage. - -```shell -$ poetry add weaviate-client -``` - -#### Setting up environment variables - -In your `.env` file set the following: - -```ini -MEMORY_BACKEND=weaviate -WEAVIATE_HOST="127.0.0.1" # the IP or domain of the running Weaviate instance -WEAVIATE_PORT="8080" -WEAVIATE_PROTOCOL="http" -WEAVIATE_USERNAME="your username" -WEAVIATE_PASSWORD="your password" -WEAVIATE_API_KEY="your weaviate API key if you have one" -WEAVIATE_EMBEDDED_PATH="/home/me/.local/share/weaviate" # this is optional and indicates where the data should be persisted when running an embedded instance -USE_WEAVIATE_EMBEDDED=False # set to True to run Embedded Weaviate -MEMORY_INDEX="Autogpt" # name of the index to create for the application -``` - -## View Memory Usage - -View memory usage by using the `--debug` flag :) - - -## 🧠 Memory pre-seeding - -!!! warning - Data ingestion is broken in v0.4.7 and possibly earlier versions. This is a known issue that will be addressed in future releases. Follow these issues for updates. - [Issue 4435](https://github.com/Significant-Gravitas/AutoGPT/issues/4435) - [Issue 4024](https://github.com/Significant-Gravitas/AutoGPT/issues/4024) - [Issue 2076](https://github.com/Significant-Gravitas/AutoGPT/issues/2076) - - - -Memory pre-seeding allows you to ingest files into memory and pre-seed it before running AutoGPT. - -```shell -$ python data_ingestion.py -h -usage: data_ingestion.py [-h] (--file FILE | --dir DIR) [--init] [--overlap OVERLAP] [--max_length MAX_LENGTH] - -Ingest a file or a directory with multiple files into memory. Make sure to set your .env before running this script. - -options: - -h, --help show this help message and exit - --file FILE The file to ingest. - --dir DIR The directory containing the files to ingest. - --init Init the memory and wipe its content (default: False) - --overlap OVERLAP The overlap size between chunks when ingesting files (default: 200) - --max_length MAX_LENGTH The max_length of each chunk when ingesting files (default: 4000) - -# python data_ingestion.py --dir DataFolder --init --overlap 100 --max_length 2000 -``` - -In the example above, the script initializes the memory, ingests all files within the `AutoGPT/auto_gpt_workspace/DataFolder` directory into memory with an overlap between chunks of 100 and a maximum length of each chunk of 2000. - -Note that you can also use the `--file` argument to ingest a single file into memory and that data_ingestion.py will only ingest files within the `/auto_gpt_workspace` directory. - -The DIR path is relative to the auto_gpt_workspace directory, so `python data_ingestion.py --dir . --init` will ingest everything in `auto_gpt_workspace` directory. - -You can adjust the `max_length` and `overlap` parameters to fine-tune the way the - documents are presented to the AI when it "recall" that memory: - -- Adjusting the overlap value allows the AI to access more contextual information - from each chunk when recalling information, but will result in more chunks being - created and therefore increase memory backend usage and OpenAI API requests. -- Reducing the `max_length` value will create more chunks, which can save prompt - tokens by allowing for more message history in the context, but will also - increase the number of chunks. -- Increasing the `max_length` value will provide the AI with more contextual - information from each chunk, reducing the number of chunks created and saving on - OpenAI API requests. However, this may also use more prompt tokens and decrease - the overall context available to the AI. - -Memory pre-seeding is a technique for improving AI accuracy by ingesting relevant data -into its memory. Chunks of data are split and added to memory, allowing the AI to access -them quickly and generate more accurate responses. It's useful for large datasets or when -specific information needs to be accessed quickly. Examples include ingesting API or -GitHub documentation before running AutoGPT. - -!!! attention - If you use Redis for memory, make sure to run AutoGPT with `WIPE_REDIS_ON_START=False` - - For other memory backends, we currently forcefully wipe the memory when starting - AutoGPT. To ingest data with those memory backends, you can call the - `data_ingestion.py` script anytime during an AutoGPT run. - -Memories will be available to the AI immediately as they are ingested, even if ingested -while AutoGPT is running. diff --git a/docs/content/forge/get-started.md b/docs/content/forge/get-started.md new file mode 100644 index 000000000..f1ca63e17 --- /dev/null +++ b/docs/content/forge/get-started.md @@ -0,0 +1,31 @@ +# AutoGPT Forge
+
+### 🛠️ Build your own Agent 🛠️
+
+Forge is a ready-to-go template for *your* agent application. All the boilerplate code is already handled, letting you channel all your creativity into the things that set *your* agent apart.
+
+---
+
+### 🛠️ **Why AutoGPT Forge?**
+- 💤 **No More Boilerplate!** - Don't let the mundane tasks stop you. Fork and build without the headache of starting from scratch!
+- 🧠 **Brain-centric Development!** - All the tools you need so you can spend 100% of your time on what matters - crafting the brain of your AI!
+- 🛠️ **Tooling ecosystem!** - We work with the best in class tools to bring you the best experience possible!
+---
+
+### 🚀 **Get Started!**
+
+The getting started [tutorial series](https://aiedge.medium.com/autogpt-forge-e3de53cc58ec) will guide you through the process of setting up your project all the way through to building a generalist agent.
+
+1. [AutoGPT Forge: A Comprehensive Guide to Your First Steps](https://aiedge.medium.com/autogpt-forge-a-comprehensive-guide-to-your-first-steps-a1dfdf46e3b4)
+2. [AutoGPT Forge: The Blueprint of an AI Agent](https://aiedge.medium.com/autogpt-forge-the-blueprint-of-an-ai-agent-75cd72ffde6)
+3. [AutoGPT Forge: Interacting with your Agent](https://aiedge.medium.com/autogpt-forge-interacting-with-your-agent-1214561b06b)
+4. [AutoGPT Forge: Crafting Intelligent Agent Logic](https://medium.com/@aiedge/autogpt-forge-crafting-intelligent-agent-logic-bc5197b14cb4)
+
+
+Coming soon:
+
+
+5. Interacting with and Benchmarking your Agent
+6. Abilities
+7. The Planning Loop
+8. Memories
diff --git a/docs/content/index.md b/docs/content/index.md index 0f32a9f47..7cf600880 100644 --- a/docs/content/index.md +++ b/docs/content/index.md @@ -1,8 +1,115 @@ -# AutoGPT docs +# AutoGPT Documentation -Welcome to AutoGPT. Please follow the [Installation](/setup/) guide to get started. +Welcome to the AutoGPT Documentation. -!!! note - It is recommended to use a virtual machine/container (docker) for tasks that require high security measures to prevent any potential harm to the main computer's system and data. If you are considering to use AutoGPT outside a virtualized/containerized environment, you are *strongly* advised to use a separate user account just for running AutoGPT. This is even more important if you are going to allow AutoGPT to write/execute scripts and run shell commands! +The AutoGPT project consists of four main components: -It is for these reasons that executing python scripts is explicitly disabled when running outside a container environment. +* The [Agent](#agent) – also known as just "AutoGPT" +* The [Benchmark](#benchmark) – AKA `agbenchmark` +* The [Forge](#forge) +* The [Frontend](#frontend) + +To tie these together, we also have a [CLI] at the root of the project. + +--- + +## 🤖 Agent + +**[📖 About AutoGPT](AutoGPT/index.md)** + |  +**[🔧 Setup](AutoGPT/setup/index.md)** + |  +**[💻 Usage](AutoGPT/usage.md)** + +The heart of AutoGPT, and the project that kicked it all off: a semi-autonomous agent powered by LLMs to execute any task for you*. + +We continue to develop this project with the goal of providing access to AI assistance to the masses, and building the future transparently and together. + +- 💡 **Explore** - See what AI can do and be inspired by a glimpse of the future. + +- 🚀 **Build with us** - We welcome any input, whether it's code or ideas for new features or improvements! Join us on [Discord](https://discord.gg/autogpt) and find out how you can join in on the action. + +<small>* it isn't quite there yet, but that is the ultimate goal that we are still pursuing</small> + +--- + +## 🎯 Benchmark + +**[🗒️ Readme](https://github.com/Significant-Gravitas/AutoGPT/blob/master/benchmark/README.md)** + +Measure your agent's performance! The `agbenchmark` can be used with any agent that supports the agent protocol, and the integration with the project's [CLI] makes it even easier to use with AutoGPT and forge-based agents. The benchmark offers a stringent testing environment. Our framework allows for autonomous, objective performance evaluations, ensuring your agents are primed for real-world action. + +<!-- TODO: insert visual demonstrating the benchmark --> + +- 📦 [**`agbenchmark`**](https://pypi.org/project/agbenchmark/) on Pypi + +- 🔌 **Agent Protocol Standardization** - AutoGPT uses the agent protocol from the AI Engineer Foundation to ensure compatibility with many agents, both from within and outside the project. + +--- + +## 🏗️ Forge + +**[📖 Introduction](forge/get-started.md)** + |  +**[🚀 Quickstart](https://github.com/Significant-Gravitas/AutoGPT/blob/master/QUICKSTART.md)** + +<!-- TODO: have the guides all in one place --> + +Forge your own agent! The Forge is a ready-to-go template for your agent application. All the boilerplate code is already handled, letting you channel all your creativity into the things that set *your* agent apart. + +- 🛠️ **Building with Ease** - We've set the groundwork so you can focus on your agent's personality and capabilities. Comprehensive tutorials are available [here](https://aiedge.medium.com/autogpt-forge-e3de53cc58ec). + +--- + +## 💻 Frontend + +**[🗒️ Readme](https://github.com/Significant-Gravitas/AutoGPT/blob/master/frontend/README.md)** + +An easy-to-use and open source frontend for any Agent Protocol-compliant agent. + +- 🎮 **User-Friendly Interface** - Manage your agents effortlessly. + +- 🔄 **Seamless Integration** - Smooth connectivity between your agent and our benchmarking system. + +--- + +## 🔧 CLI +[CLI]: #cli + +The project CLI makes it easy to use all of the components in the repo, separately or +together. To install its dependencies, simply run `./run setup`, and you're ready to go! + +```shell +$ ./run +Usage: cli.py [OPTIONS] COMMAND [ARGS]... + +Options: + --help Show this message and exit. + +Commands: + agent Commands to create, start and stop agents + arena Commands to enter the arena + benchmark Commands to start the benchmark and list tests and categories + setup Installs dependencies needed for your system. +``` + +Common commands: + +* `./run agent start autogpt` – [runs](./AutoGPT/usage.md#serve-agent-protocol-mode-with-ui) the AutoGPT agent +* `./run agent create <name>` – creates a new Forge-based agent project at `autogpts/<name>` +* `./run benchmark start <agent>` – benchmarks the specified agent + +--- + +🤔 Join the AutoGPT Discord server for any queries: +[discord.gg/autogpt](https://discord.gg/autogpt) + +### Glossary of Terms + +- **Repository**: Space where your project resides. +- **Forking**: Copying a repository under your account. +- **Cloning**: Making a local copy of a repository. +- **Agent**: The AutoGPT you'll create and develop. +- **Benchmarking**: Testing your agent's skills in the Forge. +- **Forge**: The template for building your AutoGPT agent. +- **Frontend**: The UI for tasks, logs, and task history. diff --git a/docs/content/setup.md b/docs/content/setup.md deleted file mode 100644 index 19fb7b9b5..000000000 --- a/docs/content/setup.md +++ /dev/null @@ -1,257 +0,0 @@ -# Setting up AutoGPT - -## 📋 Requirements - -Choose an environment to run AutoGPT in (pick one): - - - [Docker](https://docs.docker.com/get-docker/) (*recommended*) - - Python 3.10 or later (instructions: [for Windows](https://www.tutorialspoint.com/how-to-install-python-in-windows)) - - [VSCode + devcontainer](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) - - -## 🗝️ Getting an API key - -Get your OpenAI API key from: [https://platform.openai.com/account/api-keys](https://platform.openai.com/account/api-keys). - -!!! attention - To use the OpenAI API with AutoGPT, we strongly recommend **setting up billing** - (AKA paid account). Free accounts are [limited][openai/api limits] to 3 API calls per - minute, which can cause the application to crash. - - You can set up a paid account at [Manage account > Billing > Overview](https://platform.openai.com/account/billing/overview). - -[openai/api limits]: https://platform.openai.com/docs/guides/rate-limits/overview#:~:text=Free%20trial%20users,RPM%0A40%2C000%20TPM - -!!! important - It's highly recommended that you keep track of your API costs on [the Usage page](https://platform.openai.com/account/usage). - You can also set limits on how much you spend on [the Usage limits page](https://platform.openai.com/account/billing/limits). - - - - -## Setting up AutoGPT - -### Set up with Docker - -1. Make sure you have Docker installed, see [requirements](#requirements) -2. Create a project directory for AutoGPT - - ```shell - mkdir AutoGPT - cd AutoGPT - ``` - -3. In the project directory, create a file called `docker-compose.yml` with the following contents: - - ```yaml - version: "3.9" - services: - auto-gpt: - image: significantgravitas/auto-gpt - env_file: - - .env - profiles: ["exclude-from-up"] - volumes: - - ./auto_gpt_workspace:/app/auto_gpt_workspace - - ./data:/app/data - ## allow auto-gpt to write logs to disk - - ./logs:/app/logs - ## uncomment following lines if you want to make use of these files - ## you must have them existing in the same folder as this docker-compose.yml - #- type: bind - # source: ./azure.yaml - # target: /app/azure.yaml - #- type: bind - # source: ./ai_settings.yaml - # target: /app/ai_settings.yaml - ``` - -4. Create the necessary [configuration](#configuration) files. If needed, you can find - templates in the [repository]. -5. Pull the latest image from [Docker Hub] - - ```shell - docker pull significantgravitas/auto-gpt - ``` - -6. Continue to [Run with Docker](#run-with-docker) - -!!! note "Docker only supports headless browsing" - AutoGPT uses a browser in headless mode by default: `HEADLESS_BROWSER=True`. - Please do not change this setting in combination with Docker, or AutoGPT will crash. - -[Docker Hub]: https://hub.docker.com/r/significantgravitas/auto-gpt -[repository]: https://github.com/Significant-Gravitas/AutoGPT - - -### Set up with Git - -!!! important - Make sure you have [Git](https://git-scm.com/downloads) installed for your OS. - -!!! info "Executing commands" - To execute the given commands, open a CMD, Bash, or Powershell window. - On Windows: press ++win+x++ and pick *Terminal*, or ++win+r++ and enter `cmd` - -1. Clone the repository - - ```shell - git clone https://github.com/Significant-Gravitas/AutoGPT.git - ``` - -2. Navigate to the directory where you downloaded the repository - - ```shell - cd AutoGPT/autogpts/autogpt - ``` - -### Set up without Git/Docker - -!!! warning - We recommend to use Git or Docker, to make updating easier. Also note that some features such as Python execution will only work inside docker for security reasons. - -1. Download `Source code (zip)` from the [latest release](https://github.com/Significant-Gravitas/AutoGPT/releases/latest) -2. Extract the zip-file into a folder - - -### Configuration - -1. Find the file named `.env.template` in the main `Auto-GPT` folder. This file may - be hidden by default in some operating systems due to the dot prefix. To reveal - hidden files, follow the instructions for your specific operating system: - [Windows][show hidden files/Windows], [macOS][show hidden files/macOS]. -2. Create a copy of `.env.template` and call it `.env`; - if you're already in a command prompt/terminal window: `cp .env.template .env`. -3. Open the `.env` file in a text editor. -4. Find the line that says `OPENAI_API_KEY=`. -5. After the `=`, enter your unique OpenAI API Key *without any quotes or spaces*. -6. Enter any other API keys or tokens for services you would like to use. - - !!! note - To activate and adjust a setting, remove the `# ` prefix. - -7. Save and close the `.env` file. - -!!! info "Using a GPT Azure-instance" - If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and - make an Azure configuration file: - - - Rename `azure.yaml.template` to `azure.yaml` and provide the relevant `azure_api_base`, `azure_api_version` and all the deployment IDs for the relevant models in the `azure_model_map` section: - - `fast_llm_deployment_id`: your gpt-3.5-turbo or gpt-4 deployment ID - - `smart_llm_deployment_id`: your gpt-4 deployment ID - - `embedding_model_deployment_id`: your text-embedding-ada-002 v2 deployment ID - - Example: - - ```yaml - # Please specify all of these values as double-quoted strings - # Replace string in angled brackets (<>) to your own deployment Name - azure_model_map: - fast_llm_deployment_id: "<auto-gpt-deployment>" - ... - ``` - - Details can be found in the [openai-python docs], and in the [Azure OpenAI docs] for the embedding model. - If you're on Windows you may need to install an [MSVC library](https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170). - -[show hidden files/Windows]: https://support.microsoft.com/en-us/windows/view-hidden-files-and-folders-in-windows-97fbc472-c603-9d90-91d0-1166d1d9f4b5 -[show hidden files/macOS]: https://www.pcmag.com/how-to/how-to-access-your-macs-hidden-files -[openai-python docs]: https://github.com/openai/openai-python#microsoft-azure-endpoints -[Azure OpenAI docs]: https://learn.microsoft.com/en-us/azure/cognitive-services/openai/tutorials/embeddings?tabs=command-line - - -## Running AutoGPT - -### Run with Docker - -Easiest is to use `docker compose`. - -Important: Docker Compose version 1.29.0 or later is required to use version 3.9 of the Compose file format. -You can check the version of Docker Compose installed on your system by running the following command: - -```shell -docker compose version -``` - -This will display the version of Docker Compose that is currently installed on your system. - -If you need to upgrade Docker Compose to a newer version, you can follow the installation instructions in the Docker documentation: https://docs.docker.com/compose/install/ - -Once you have a recent version of Docker Compose, run the commands below in your AutoGPT folder. - -1. Build the image. If you have pulled the image from Docker Hub, skip this step (NOTE: You *will* need to do this if you are modifying requirements.txt to add/remove dependencies like Python libs/frameworks) - - ```shell - docker compose build auto-gpt - ``` - -2. Run AutoGPT - - ```shell - docker compose run --rm auto-gpt - ``` - - By default, this will also start and attach a Redis memory backend. If you do not - want this, comment or remove the `depends: - redis` and `redis:` sections from - `docker-compose.yml`. - - For related settings, see [Memory > Redis setup](./configuration/memory.md#redis-setup). - -You can pass extra arguments, e.g. running with `--gpt3only` and `--continuous`: - -```shell -docker compose run --rm auto-gpt --gpt3only --continuous -``` - -If you dare, you can also build and run it with "vanilla" docker commands: - -```shell -docker build -t auto-gpt . -docker run -it --env-file=.env -v $PWD:/app auto-gpt -docker run -it --env-file=.env -v $PWD:/app --rm auto-gpt --gpt3only --continuous -``` - -[Docker Compose file]: https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpts/autogpt/docker-compose.yml - - -### Run with Dev Container - -1. Install the [Remote - Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers) extension in VS Code. - -2. Open command palette with ++f1++ and type `Dev Containers: Open Folder in Container`. - -3. Run `./run.sh`. - - -### Run without Docker - -#### Create a Virtual Environment - -Create a virtual environment to run in. - -```shell -python -m venv .venv -source .venv/bin/activate -pip3 install --upgrade pip -``` - -!!! warning - Due to security reasons, certain features (like Python execution) will by default be disabled when running without docker. So, even if you want to run the program outside a docker container, you currently still need docker to actually run scripts. - -Simply run the startup script in your terminal. This will install any necessary Python -packages and launch AutoGPT. - -- On Linux/MacOS: - - ```shell - ./run.sh - ``` - -- On Windows: - - ```shell - .\run.bat - ``` - -If this gives errors, make sure you have a compatible Python version installed. See also -the [requirements](./installation.md#requirements). diff --git a/docs/content/usage.md b/docs/content/usage.md deleted file mode 100644 index 48b24a5c5..000000000 --- a/docs/content/usage.md +++ /dev/null @@ -1,122 +0,0 @@ -# Usage - -## Command Line Arguments -Running with `--help` lists all the possible command line arguments you can pass: - -```shell -./run.sh --help # on Linux / macOS - -.\run.bat --help # on Windows -``` - -!!! info - For use with Docker, replace the script in the examples with - `docker compose run --rm auto-gpt`: - - ```shell - docker compose run --rm auto-gpt --help - docker compose run --rm auto-gpt --ai-settings <filename> - ``` - -!!! note - Replace anything in angled brackets (<>) to a value you want to specify - -Here are some common arguments you can use when running AutoGPT: - -* Run AutoGPT with a different AI Settings file - -```shell -./run.sh --ai-settings <filename> -``` - -* Run AutoGPT with a different Prompt Settings file - -```shell -./run.sh --prompt-settings <filename> -``` - -* Specify a memory backend - -```shell -./run.sh --use-memory <memory-backend> -``` - -!!! note - There are shorthands for some of these flags, for example `-m` for `--use-memory`. - Use `./run.sh --help` for more information. - -### Speak Mode - -Enter this command to use TTS _(Text-to-Speech)_ for AutoGPT - -```shell -./run.sh --speak -``` - -### 💀 Continuous Mode ⚠️ - -Run the AI **without** user authorization, 100% automated. -Continuous mode is NOT recommended. -It is potentially dangerous and may cause your AI to run forever or carry out actions you would not usually authorize. -Use at your own risk. - -```shell -./run.sh --continuous -``` - -To exit the program, press ++ctrl+c++ - -### ♻️ Self-Feedback Mode ⚠️ - -Running Self-Feedback will **INCREASE** token use and thus cost more. This feature enables the agent to provide self-feedback by verifying its own actions and checking if they align with its current goals. If not, it will provide better feedback for the next loop. To enable this feature for the current loop, input `S` into the input field. - -### GPT-3.5 ONLY Mode - -If you don't have access to GPT-4, this mode allows you to use AutoGPT! - -```shell -./run.sh --gpt3only -``` - -You can achieve the same by setting `SMART_LLM` in `.env` to `gpt-3.5-turbo`. - -### GPT-4 ONLY Mode - -If you have access to GPT-4, this mode allows you to use AutoGPT solely with GPT-4. -This may give your bot increased intelligence. - -```shell -./run.sh --gpt4only -``` - -!!! warning - Since GPT-4 is more expensive to use, running AutoGPT in GPT-4-only mode will - increase your API costs. - -## Logs - -Activity, Error, and Debug logs are located in `./logs` - -!!! tip - Do you notice weird behavior with your agent? Do you have an interesting use case? Do you have a bug you want to report? - Follow the step below to enable your logs. You can include these logs when making an issue report or discussing an issue with us. - -To print out debug logs: - -```shell -./run.sh --debug # on Linux / macOS - -.\run.bat --debug # on Windows - -docker-compose run --rm auto-gpt --debug # in Docker -``` - -## Disabling Command Categories - -If you want to selectively disable some command groups, you can use the `DISABLED_COMMAND_CATEGORIES` config in your `.env`. You can find the list of categories in your `.env.template` - -For example, to disable coding related features, set it to the value below: - -```ini -DISABLED_COMMAND_CATEGORIES=autogpt.commands.execute_code -``` diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml index 3c73b5c9a..3628df6c7 100644 --- a/docs/mkdocs.yml +++ b/docs/mkdocs.yml @@ -4,42 +4,56 @@ repo_url: https://github.com/Significant-Gravitas/AutoGPT docs_dir: content nav: - Home: index.md - - Setup: setup.md - - Usage: usage.md - - Plugins: plugins.md - - Configuration: - - Options: configuration/options.md - - Search: configuration/search.md - - Memory: configuration/memory.md - - Voice: configuration/voice.md - - Image Generation: configuration/imagegen.md - - Help us improve AutoGPT: - - Share your debug logs with us: share-your-logs.md - - Contribution guide: contributing.md - - Running tests: testing.md - - Code of Conduct: code-of-conduct.md + - AutoGPT Agent: + - Introduction: AutoGPT/index.md + - Setup: + - Setting up AutoGPT: AutoGPT/setup/index.md + - Set up with Docker: AutoGPT/setup/docker.md + - Usage: AutoGPT/usage.md + - Plugins: AutoGPT/plugins.md + # - Configuration: + # - Options: AutoGPT/configuration/options.md + # - Search: AutoGPT/configuration/search.md + # - Memory: AutoGPT/configuration/memory.md + # - Voice: AutoGPT/configuration/voice.md + # - Image Generation: AutoGPT/configuration/imagegen.md + - Help us improve AutoGPT: + - Share your debug logs with us: AutoGPT/share-your-logs.md + - Contribution guide: contributing.md + - Running tests: AutoGPT/testing.md + - Code of Conduct: code-of-conduct.md - - Challenges: - - Introduction: challenges/introduction.md - - List of Challenges: - - Memory: - - Introduction: challenges/memory/introduction.md - - Memory Challenge A: challenges/memory/challenge_a.md - - Memory Challenge B: challenges/memory/challenge_b.md - - Memory Challenge C: challenges/memory/challenge_c.md - - Memory Challenge D: challenges/memory/challenge_d.md - - Information retrieval: - - Introduction: challenges/information_retrieval/introduction.md - - Information Retrieval Challenge A: challenges/information_retrieval/challenge_a.md - - Information Retrieval Challenge B: challenges/information_retrieval/challenge_b.md - - Submit a Challenge: challenges/submit.md - - Beat a Challenge: challenges/beat.md + - Benchmark: + - Readme: https://github.com/Significant-Gravitas/AutoGPT/blob/master/benchmark/README.md + + - Forge: + - Introduction: forge/get-started.md + + - Frontend: + - Readme: https://github.com/Significant-Gravitas/AutoGPT/blob/master/frontend/README.md + + # - Challenges: + # - Introduction: challenges/introduction.md + # - List of Challenges: + # - Memory: + # - Introduction: challenges/memory/introduction.md + # - Memory Challenge A: challenges/memory/challenge_a.md + # - Memory Challenge B: challenges/memory/challenge_b.md + # - Memory Challenge C: challenges/memory/challenge_c.md + # - Memory Challenge D: challenges/memory/challenge_d.md + # - Information retrieval: + # - Introduction: challenges/information_retrieval/introduction.md + # - Information Retrieval Challenge A: challenges/information_retrieval/challenge_a.md + # - Information Retrieval Challenge B: challenges/information_retrieval/challenge_b.md + # - Submit a Challenge: challenges/submit.md + # - Beat a Challenge: challenges/beat.md - License: https://github.com/Significant-Gravitas/AutoGPT/blob/master/LICENSE theme: name: material + custom_dir: overrides icon: logo: material/book-open-variant favicon: favicon.png diff --git a/docs/overrides/main.html b/docs/overrides/main.html new file mode 100644 index 000000000..b376724b8 --- /dev/null +++ b/docs/overrides/main.html @@ -0,0 +1,61 @@ +{% extends "base.html" %}
+
+
+{% block extrahead %}
+<style>
+ svg.ms-w-12 {
+ width: 2rem !important;
+ }
+ svg.ms-h-12 {
+ height: 2rem !important;
+ }
+ /* Temporary solution for the font sizes */
+ #headlessui-dialog-panel-2 p{
+ font-size: 16px;
+ }
+ #headlessui-dialog-panel-2 textarea{
+ font-size: 16px;
+ }
+ #headlessui-dialog-panel-2 span{
+ font-size: 14px;
+
+ }
+ #headlessui-dialog-panel-2 div{
+ font-size: 16px;
+ }
+ #headlessui-dialog-panel-2 a{
+ font-size: 14px;
+ line-height: 1rem;
+ }
+ #headlessui-dialog-panel-2 button{
+ border: 1px solid #0000001d;
+ line-height: 1rem;
+
+}
+ /* Temporary solution for the font size */
+ #headlessui-dialog-panel-2 > div > div > div > div.ms-w-full.ms-rounded-xl.ms-flex.ms-flex-col.ms-relative > div > div > div > div > div.ms-flex.ms-flex-row.ms-items-center.ms-justify-between.ms-gap-1 > p{
+ font-size: 14px;
+ line-height: 1rem;
+ }
+
+</style>
+
+<div id="my-component-root" class="mendable-search"></div>
+
+<script src="https://unpkg.com/@mendable/search@0.0.155/dist/umd/mendable-bundle.min.js"></script>
+{% raw %}
+<script>
+ Mendable.initialize({
+ anon_key: 'a0bd44db-eb3b-412f-8924-b31c58244a64',
+ type: 'floatingButton',
+ style : { accentColor: '#3F51B5', darkMode: false },
+ floatingButtonStyle:{
+ backgroundColor: '#3F51B5',
+ color: '#fff',
+ },
+ icon: "https://mendable-storage.s3.amazonaws.com/autoGPT.gif",
+ botIcon: "https://mendable-storage.s3.amazonaws.com/autoGPTbot.gif",
+ })
+ </script>
+{% endraw %}
+{% endblock %}
\ No newline at end of file diff --git a/frontend/README.md b/frontend/README.md index 6e52dabaf..4a248bd55 100644 --- a/frontend/README.md +++ b/frontend/README.md @@ -41,6 +41,8 @@ flutter pub get 4. **Run the app:** ``` +#For chromium users on linux: +#export CHROME_EXECUTABLE=/usr/bin/chromium flutter run -d chrome --web-port 5000 ``` |
