diff options
416 files changed, 1263 insertions, 3080 deletions
diff --git a/.github/labeler.yml b/.github/labeler.yml index 140174388..cef6db432 100644 --- a/.github/labeler.yml +++ b/.github/labeler.yml @@ -14,10 +14,6 @@ Frontend: - changed-files: - any-glob-to-any-file: frontend/** -Arena: -- changed-files: - - any-glob-to-any-file: arena/** - documentation: - changed-files: - any-glob-to-any-file: docs/** diff --git a/.github/workflows/arena-intake.yml b/.github/workflows/arena-intake.yml deleted file mode 100644 index a77540471..000000000 --- a/.github/workflows/arena-intake.yml +++ /dev/null @@ -1,169 +0,0 @@ -name: Arena intake - -on: - # We recommend `pull_request_target` so that github secrets are available. - # In `pull_request` we wouldn't be able to change labels of fork PRs - pull_request_target: - types: [ opened, synchronize ] - paths: - - 'arena/**' - -jobs: - check: - permissions: - pull-requests: write - runs-on: ubuntu-latest - steps: - - name: Checkout PR - uses: actions/checkout@v4 - with: - ref: ${{ github.event.pull_request.head.sha }} - - - name: Check Arena entry - uses: actions/github-script@v7 - with: - script: | - console.log('⚙️ Setting up...'); - - const fs = require('fs'); - const path = require('path'); - - const pr = context.payload.pull_request; - const isFork = pr.head.repo.fork; - - console.log('🔄️ Fetching PR diff metadata...'); - const prFilesChanged = (await github.rest.pulls.listFiles({ - owner: context.repo.owner, - repo: context.repo.repo, - pull_number: pr.number, - })).data; - console.debug(prFilesChanged); - const arenaFilesChanged = prFilesChanged.filter( - ({ filename: file }) => file.startsWith('arena/') && file.endsWith('.json') - ); - const hasChangesInAutogptsFolder = prFilesChanged.some( - ({ filename }) => filename.startsWith('autogpts/') - ); - - console.log(`🗒️ ${arenaFilesChanged.length} arena entries affected`); - console.debug(arenaFilesChanged); - if (arenaFilesChanged.length === 0) { - // If no files in `arena/` are changed, this job does not need to run. - return; - } - - let close = false; - let flagForManualCheck = false; - let issues = []; - - if (isFork) { - if (arenaFilesChanged.length > 1) { - // Impacting multiple entries in `arena/` is not allowed - issues.push('This pull request impacts multiple arena entries'); - } - if (hasChangesInAutogptsFolder) { - // PRs that include the custom agent are generally not allowed - issues.push( - 'This pull request includes changes in `autogpts/`.\n' - + 'Please make sure to only submit your arena entry (`arena/*.json`), ' - + 'and not to accidentally include your custom agent itself.' - ); - } - } - - if (arenaFilesChanged.length === 1) { - const newArenaFile = arenaFilesChanged[0] - const newArenaFileName = path.basename(newArenaFile.filename) - console.log(`🗒️ Arena entry in PR: ${newArenaFile}`); - - if (newArenaFile.status != 'added') { - flagForManualCheck = true; - } - - if (pr.mergeable != false) { - const newArenaEntry = JSON.parse(fs.readFileSync(newArenaFile.filename)); - const allArenaFiles = await (await glob.create('arena/*.json')).glob(); - console.debug(newArenaEntry); - - console.log(`➡️ Checking ${newArenaFileName} against existing entries...`); - for (const file of allArenaFiles) { - const existingEntryName = path.basename(file); - - if (existingEntryName === newArenaFileName) { - continue; - } - - console.debug(`Checking against ${existingEntryName}...`); - - const arenaEntry = JSON.parse(fs.readFileSync(file)); - if (arenaEntry.github_repo_url === newArenaEntry.github_repo_url) { - console.log(`⚠️ Duplicate detected: ${existingEntryName}`); - issues.push( - `The \`github_repo_url\` specified in __${newArenaFileName}__ ` - + `already exists in __${existingEntryName}__. ` - + `This PR will be closed as duplicate.` - ) - close = true; - } - } - } else { - console.log('⚠️ PR has conflicts'); - issues.push( - `__${newArenaFileName}__ conflicts with existing entry with the same name` - ) - close = true; - } - } // end if (arenaFilesChanged.length === 1) - - console.log('🏁 Finished checking against existing entries'); - - if (issues.length == 0) { - console.log('✅ No issues detected'); - if (flagForManualCheck) { - console.log('🤔 Requesting review from maintainers...'); - await github.rest.pulls.requestReviewers({ - owner: context.repo.owner, - repo: context.repo.repo, - pull_number: pr.number, - reviewers: ['Pwuts'], - // team_reviewers: ['maintainers'], // doesn't work: https://stackoverflow.com/a/64977184/4751645 - }); - } else { - console.log('➡️ Approving PR...'); - await github.rest.pulls.createReview({ - owner: context.repo.owner, - repo: context.repo.repo, - pull_number: pr.number, - event: 'APPROVE', - }); - } - } else { - console.log(`⚠️ ${issues.length} issues detected`); - - console.log('➡️ Posting comment indicating issues...'); - await github.rest.issues.createComment({ - owner: context.repo.owner, - repo: context.repo.repo, - issue_number: pr.number, - body: `Our automation found one or more issues with this submission:\n` - + issues.map(i => `- ${i.replace('\n', '\n ')}`).join('\n'), - }); - - console.log("➡️ Applying label 'invalid'..."); - await github.rest.issues.addLabels({ - owner: context.repo.owner, - repo: context.repo.repo, - issue_number: pr.number, - labels: ['invalid'], - }); - - if (close) { - console.log('➡️ Auto-closing PR...'); - await github.rest.pulls.update({ - owner: context.repo.owner, - repo: context.repo.repo, - pull_number: pr.number, - state: 'closed', - }); - } - } diff --git a/.gitignore b/.gitignore index c4f86e958..090f3bdbc 100644 --- a/.gitignore +++ b/.gitignore @@ -172,8 +172,3 @@ pri* # ignore ig* .github_access_token -arena/TestAgent.json - -# evo.ninja -autogpts/evo.ninja/* -!autogpts/evo.ninja/setup diff --git a/.pr_agent.toml b/.pr_agent.toml new file mode 100644 index 000000000..9c059d1b5 --- /dev/null +++ b/.pr_agent.toml @@ -0,0 +1,6 @@ +[pr_reviewer] +num_code_suggestions=0 + +[pr_code_suggestions] +commitable_code_suggestions=false +num_code_suggestions=0 diff --git a/QUICKSTART.md b/QUICKSTART.md index 885533883..dbdde3be2 100644 --- a/QUICKSTART.md +++ b/QUICKSTART.md @@ -39,9 +39,6 @@ This project supports Linux (Debian based), Mac, and Windows Subsystem for Linux The first command you need to use is `./run setup` This will guide you through the process of setting up your system. Initially you will get instructions for installing flutter, chrome and setting up your github access token like the following image: - - > Note: for advanced users. The github access token is only needed for the ./run arena enter command so the system can automatically create a PR -  @@ -92,34 +89,10 @@ Tips for naming your agent: * Give it its own unique name, or name it after yourself * Include an important aspect of your agent in the name, such as its purpose -Examples: `SwiftyosAssistant`, `PwutsPRAgent`, `Narvis`, `evo.ninja` +Examples: `SwiftyosAssistant`, `PwutsPRAgent`, `MySuperAgent`  -### Optional: Entering the Arena - -Entering the Arena is an optional step intended for those who wish to actively participate in the agent leaderboard. If you decide to participate, you can enter the Arena by running `./run arena enter YOUR_AGENT_NAME`. This step is not mandatory for the development or testing of your agent. - -Entries with names like `agent`, `ExampleAgent`, `test_agent` or `MyExampleGPT` will NOT be merged. We also don't accept copycat entries that use the name of other projects, like `AutoGPT` or `evo.ninja`. - - - -> **Note** -> For advanced users, create a new branch and create a file called YOUR_AGENT_NAME.json in the arena directory. Then commit this and create a PR to merge into the main repo. Only single file entries will be permitted. The json file needs the following format: -> ```json -> { -> "github_repo_url": "https://github.com/Swiftyos/YourAgentName", -> "timestamp": "2023-09-18T10:03:38.051498", -> "commit_hash_to_benchmark": "ac36f7bfc7f23ad8800339fa55943c1405d80d5e", -> "branch_to_benchmark": "master" -> } -> ``` -> - `github_repo_url`: the url to your fork -> - `timestamp`: timestamp of the last update of this file -> - `commit_hash_to_benchmark`: the commit hash of your entry. You update each time you have an something ready to be officially entered into the hackathon -> - `branch_to_benchmark`: the branch you are using to develop your agent on, default is master. - - ## Running your Agent Your agent can started using the `./run agent start YOUR_AGENT_NAME` @@ -18,13 +18,6 @@ Be part of the revolution! **AutoGPT** is here to stay, at the forefront of AI i  |  **🛠️ [Build your own Agent - Quickstart](QUICKSTART.md)** -## 🥇 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! - -📈 To challenge evo.ninja, AutoGPT, and others, submit your benchmark run to the [Leaderboard](#-leaderboard), and maybe your agent will be up here next! - ## 🧱 Building blocks ### 🏗️ Forge @@ -46,13 +39,6 @@ This guide will walk you through the process of creating your own agent and usin  |  📘 [Learn More](https://github.com/Significant-Gravitas/AutoGPT/blob/master/benchmark) about the Benchmark -#### 🏆 [Leaderboard][leaderboard] -[leaderboard]: https://leaderboard.agpt.co - -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]. - -[][leaderboard] - ### 💻 UI **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. @@ -78,7 +64,6 @@ Options: 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. ``` diff --git a/arena/480bot.json b/arena/480bot.json deleted file mode 100644 index 819ac9cc9..000000000 --- a/arena/480bot.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/480/AutoGPT", - "timestamp": "2023-10-22T06:49:52.536177", - "commit_hash_to_benchmark": "16e266c65fb4620a1b1397532c503fa426ec191d", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AGENT_GORDON.json b/arena/AGENT_GORDON.json deleted file mode 100644 index 98784273f..000000000 --- a/arena/AGENT_GORDON.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/filipjakubowski/AutoGPT", - "timestamp": "2023-11-01T17:13:24.272333", - "commit_hash_to_benchmark": "78e92234d63a69b5471da0c0e62ce820a9109dd4", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AGENT_JARVIS.json b/arena/AGENT_JARVIS.json deleted file mode 100644 index ac284f6aa..000000000 --- a/arena/AGENT_JARVIS.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/filipjakubowski/AutoGPT", - "timestamp": "2023-11-04T10:13:11.039444", - "commit_hash_to_benchmark": "78e92234d63a69b5471da0c0e62ce820a9109dd4", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AI.json b/arena/AI.json deleted file mode 100644 index a6b27fdb1..000000000 --- a/arena/AI.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/QingquanBao/AutoGPT", - "timestamp": "2023-11-01T16:20:51.086235", - "commit_hash_to_benchmark": "78e92234d63a69b5471da0c0e62ce820a9109dd4", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AKBAgent.json b/arena/AKBAgent.json deleted file mode 100644 index 71e8cea91..000000000 --- a/arena/AKBAgent.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "github_repo_url": "https://github.com/imakb/AKBAgent", - "timestamp": "2023-10-31T00:03:23.000000", - "commit_hash_to_benchmark": "c65b71d51d8f849663172c5a128953b4ca92b2b0", - "branch_to_benchmark": "AKBAgent" -} - diff --git a/arena/ASSISTANT.json b/arena/ASSISTANT.json deleted file mode 100644 index bd0c0f055..000000000 --- a/arena/ASSISTANT.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/hongzzz/AutoGPT", - "timestamp": "2023-10-13T03:22:59.347424", - "commit_hash_to_benchmark": "38790a27ed2c1b63a301b6a67e7590f2d30de53e", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AUTO_ENGINEER.json b/arena/AUTO_ENGINEER.json deleted file mode 100644 index 5f8e28c97..000000000 --- a/arena/AUTO_ENGINEER.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/kaiomagalhaes/AutoGPT", - "timestamp": "2023-10-04T15:25:30.458687", - "commit_hash_to_benchmark": "1bd85cbc09473c0252928fb849ae8373607d6065", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AUTO_GPT_JON001.json b/arena/AUTO_GPT_JON001.json deleted file mode 100644 index f36fad390..000000000 --- a/arena/AUTO_GPT_JON001.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/Jonobinsoftware/AutoGPT-Tutorial", - "timestamp": "2023-10-10T06:01:23.439061", - "commit_hash_to_benchmark": "c77ade5b2f62c5373fc7573e5c45581f003c77a3", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/Adtractive_Agent.json b/arena/Adtractive_Agent.json deleted file mode 100644 index ebec6e6ad..000000000 --- a/arena/Adtractive_Agent.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/aivaras-mazylis/AutoGPT", - "timestamp": "2023-10-17T13:16:16.327237", - "commit_hash_to_benchmark": "1eadc64dc0a693c7c9de77ddaef857f3a36f7950", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AgGPT.json b/arena/AgGPT.json deleted file mode 100644 index 07751b8ec..000000000 --- a/arena/AgGPT.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/althaf004/AutoGPT", - "timestamp": "2023-09-26T03:40:03.658369", - "commit_hash_to_benchmark": "4a8da53d85d466f2eb325c745a2c03cf88792e7d", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AgentJPark.json b/arena/AgentJPark.json deleted file mode 100644 index 636e4d1f7..000000000 --- a/arena/AgentJPark.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/againeureka/AutoGPT", - "timestamp": "2023-10-12T02:20:01.005361", - "commit_hash_to_benchmark": "766796ae1e8c07cf2a03b607621c3da6e1f01a31", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AgentKD.json b/arena/AgentKD.json deleted file mode 100644 index 1aa340eac..000000000 --- a/arena/AgentKD.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/kitdesai/AgentKD", - "timestamp": "2023-10-14T02:35:09.979434", - "commit_hash_to_benchmark": "93e3ec36ed6cd9e5e60585f016ad3bef4e1c52cb", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/Ahmad.json b/arena/Ahmad.json deleted file mode 100644 index 2b5b86f12..000000000 --- a/arena/Ahmad.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/JawadAbu/AutoGPT.git", - "timestamp": "2023-11-05T12:35:35.352028", - "commit_hash_to_benchmark": "a1d60878141116641ea864ef6de7ca6142e9534c", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/Alfred.json b/arena/Alfred.json deleted file mode 100644 index be510f1fd..000000000 --- a/arena/Alfred.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/Shadowless422/Alfred", - "timestamp": "2023-10-03T10:42:45.473477", - "commit_hash_to_benchmark": "949ab477a87cfb7a3668d7961e9443922081e098", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AlphaCISO.json b/arena/AlphaCISO.json deleted file mode 100644 index 06791274b..000000000 --- a/arena/AlphaCISO.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/alphaciso/AutoGPT", - "timestamp": "2023-10-21T08:26:41.961187", - "commit_hash_to_benchmark": "415b4ceed1417d0b21d87d7d4ea0cd38943e264f", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AndersLensway.json b/arena/AndersLensway.json deleted file mode 100644 index 6bbf68fdf..000000000 --- a/arena/AndersLensway.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/4nd3rs/AutoGPT", - "timestamp": "2023-10-11T11:00:08.150159", - "commit_hash_to_benchmark": "57bcbdf45c6c1493a4e5f6a4e72594ea13c10f93", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AntlerTestGPT.json b/arena/AntlerTestGPT.json deleted file mode 100644 index 9df76d4a8..000000000 --- a/arena/AntlerTestGPT.json +++ /dev/null @@ -1 +0,0 @@ -{"github_repo_url": "https://github.com/pjw1/AntlerAI", "timestamp": "2023-10-07T11:46:39Z", "commit_hash_to_benchmark": "f81e086e5647370854ec639c531c900775a99207", "branch_to_benchmark": "master"}
\ No newline at end of file diff --git a/arena/AppleGPT.json b/arena/AppleGPT.json deleted file mode 100644 index 7fe3a7bee..000000000 --- a/arena/AppleGPT.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/Nimit3-droid/AutoGPT", - "timestamp": "2023-10-03T11:59:15.495902", - "commit_hash_to_benchmark": "d8d7fc4858a8d13407f6d7da360c6b5d398f2175", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AquaAgent.json b/arena/AquaAgent.json deleted file mode 100644 index 6deb549db..000000000 --- a/arena/AquaAgent.json +++ /dev/null @@ -1 +0,0 @@ -{"github_repo_url": "https://github.com/somnistudio/SomniGPT", "timestamp": "2023-10-06T16:40:14Z", "commit_hash_to_benchmark": "47eb5124fa97187d7f3fa4036e422cd771cf0ae7", "branch_to_benchmark": "master"}
\ No newline at end of file diff --git a/arena/ArtistManagerGPT.json b/arena/ArtistManagerGPT.json deleted file mode 100644 index 881ed049b..000000000 --- a/arena/ArtistManagerGPT.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/AmahAjavon/AutoGPT", - "timestamp": "2023-10-28T20:32:15.845741", - "commit_hash_to_benchmark": "2bd05827f97e471af798b8c2f04e8772dad101d3", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AskOpie.json b/arena/AskOpie.json deleted file mode 100644 index a2f6bd393..000000000 --- a/arena/AskOpie.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/arunqa/AutoGPT", - "timestamp": "2023-09-26T05:13:24.466017", - "commit_hash_to_benchmark": "4a8da53d85d466f2eb325c745a2c03cf88792e7d", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/Auto.json b/arena/Auto.json deleted file mode 100644 index 9bad9db50..000000000 --- a/arena/Auto.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/Nikhil8652/AutoGPT", - "timestamp": "2023-10-16T09:12:17.452121", - "commit_hash_to_benchmark": "2f79caa6b901d006a78c1ac9e69db4465c0f971a", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AutoGPT-ariel.json b/arena/AutoGPT-ariel.json deleted file mode 100644 index cefa43620..000000000 --- a/arena/AutoGPT-ariel.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/RedTachyon/AutoGPT", - "timestamp": "2023-10-21T22:31:30.871023", - "commit_hash_to_benchmark": "eda21d51921899756bf866cf5c4d0f2dcd3e2e23", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AutoGPT2.json b/arena/AutoGPT2.json deleted file mode 100644 index 11a71f66f..000000000 --- a/arena/AutoGPT2.json +++ /dev/null @@ -1 +0,0 @@ -{"github_repo_url": "https://github.com/SarahGrevy/AutoGPT", "timestamp": "2023-10-20T17:21:22Z", "commit_hash_to_benchmark": "32300906c9aafea8c550fa2f9edcc113fbfc512c", "branch_to_benchmark": "master"}
\ No newline at end of file diff --git a/arena/AutoGenius.json b/arena/AutoGenius.json deleted file mode 100644 index 3974b9dcc..000000000 --- a/arena/AutoGenius.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/JasonDRZ/AutoGPT", - "timestamp": "2023-10-26T13:27:58.805270", - "commit_hash_to_benchmark": "ab2a61833584c42ededa805cbac50718c72aa5ae", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AutoTDD.json b/arena/AutoTDD.json deleted file mode 100644 index ea61ddd82..000000000 --- a/arena/AutoTDD.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/vshneer/AutoTDD", - "timestamp": "2023-10-11T19:14:30.939747", - "commit_hash_to_benchmark": "766796ae1e8c07cf2a03b607621c3da6e1f01a31", - "branch_to_benchmark": "master" -}
\ No newline at end of file diff --git a/arena/AutoTestGenerator.json b/arena/AutoTestGenerator.json deleted file mode 100644 index c28d6da87..000000000 --- a/arena/AutoTestGenerator.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "github_repo_url": "https://github.com/cagdasbas/AutoGPT", - "timestamp": "2023-10-15T08:43:40.193080", - "commit_hash_to_benchmark": "74ee69daf1c0a2603f19bdb1edcfdf1f4e06bcff", - "branch_to_benchmark": "master" -}
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\ No newline at end of file diff --git a/autogpts/autogpt/.env.template b/autogpts/autogpt/.env.template index ba514c56b..14c7bcaa5 100644 --- a/autogpts/autogpt/.env.template +++ b/autogpts/autogpt/.env.template @@ -2,8 +2,11 @@ ### AutoGPT - GENERAL SETTINGS ################################################################################ -## OPENAI_API_KEY - OpenAI API Key (Example: my-openai-api-key) -OPENAI_API_KEY=your-openai-api-key +## OPENAI_API_KEY - OpenAI API Key (Example: sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx) +# OPENAI_API_KEY= + +## ANTHROPIC_API_KEY - Anthropic API Key (Example: sk-ant-api03-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx) +# ANTHROPIC_API_KEY= ## TELEMETRY_OPT_IN - Share telemetry on errors and other issues with the AutoGPT team, e.g. through Sentry. ## This helps us to spot and solve problems earlier & faster. (Default: DISABLED) diff --git a/autogpts/autogpt/.pre-commit-config.yaml b/autogpts/autogpt/.pre-commit-config.yaml index d2a061a4d..955d49fa3 100644 --- a/autogpts/autogpt/.pre-commit-config.yaml +++ b/autogpts/autogpt/.pre-commit-config.yaml @@ -22,6 +22,11 @@ repos: - id: black language_version: python3.10 + - repo: https://github.com/PyCQA/flake8 + rev: 7.0.0 + hooks: + - id: flake8 + # - repo: https://github.com/pre-commit/mirrors-mypy # rev: 'v1.3.0' # hooks: diff --git a/autogpts/autogpt/agbenchmark_config/benchmarks.py b/autogpts/autogpt/agbenchmark_config/benchmarks.py index 1281f9fff..c574dc303 100644 --- a/autogpts/autogpt/agbenchmark_config/benchmarks.py +++ b/autogpts/autogpt/agbenchmark_config/benchmarks.py @@ -5,8 +5,7 @@ from pathlib import Path from autogpt.agent_manager.agent_manager import AgentManager from autogpt.agents.agent import Agent, AgentConfiguration, AgentSettings -from autogpt.agents.prompt_strategies.one_shot import OneShotAgentPromptStrategy -from autogpt.app.main import _configure_openai_provider, run_interaction_loop +from autogpt.app.main import _configure_llm_provider, run_interaction_loop from autogpt.config import AIProfile, ConfigBuilder from autogpt.file_storage import FileStorageBackendName, get_storage from autogpt.logs.config import configure_logging @@ -38,10 +37,6 @@ def bootstrap_agent(task: str, continuous_mode: bool) -> Agent: ai_goals=[task], ) - agent_prompt_config = OneShotAgentPromptStrategy.default_configuration.copy( - deep=True - ) - agent_prompt_config.use_functions_api = config.openai_functions agent_settings = AgentSettings( name=Agent.default_settings.name, agent_id=AgentManager.generate_id("AutoGPT-benchmark"), @@ -53,7 +48,6 @@ def bootstrap_agent(task: str, continuous_mode: bool) -> Agent: allow_fs_access=not config.restrict_to_workspace, use_functions_api=config.openai_functions, ), - prompt_config=agent_prompt_config, history=Agent.default_settings.history.copy(deep=True), ) @@ -66,7 +60,7 @@ def bootstrap_agent(task: str, continuous_mode: bool) -> Agent: agent = Agent( settings=agent_settings, - llm_provider=_configure_openai_provider(config), + llm_provider=_configure_llm_provider(config), file_storage=file_storage, legacy_config=config, ) diff --git a/autogpts/autogpt/autogpt/agents/README.md b/autogpts/autogpt/autogpt/agents/README.md index adc158547..4ab573243 120000..100644 --- a/autogpts/autogpt/autogpt/agents/README.md +++ b/autogpts/autogpt/autogpt/agents/README.md @@ -1 +1,37 @@ -../../../../docs/content/AutoGPT/component agent/agents.md
\ No newline at end of file +# 🤖 Agents + +Agent is composed of [🧩 Components](./components.md) and responsible for executing pipelines and some additional logic. The base class for all agents is `BaseAgent`, it has the necessary logic to collect components and execute protocols. + +## Important methods + +`BaseAgent` provides two abstract methods needed for any agent to work properly: +1. `propose_action`: This method is responsible for proposing an action based on the current state of the agent, it returns `ThoughtProcessOutput`. +2. `execute`: This method is responsible for executing the proposed action, returns `ActionResult`. + +## AutoGPT Agent + +`Agent` is the main agent provided by AutoGPT. It's a subclass of `BaseAgent`. It has all the [Built-in Components](./built-in-components.md). `Agent` implements the essential abstract methods from `BaseAgent`: `propose_action` and `execute`. + +## Building your own Agent + +The easiest way to build your own agent is to extend the `Agent` class and add additional components. By doing this you can reuse the existing components and the default logic for executing [⚙️ Protocols](./protocols.md). + +```py +class MyComponent(AgentComponent): + pass + +class MyAgent(Agent): + def __init__( + self, + settings: AgentSettings, + llm_provider: ChatModelProvider, + file_storage: FileStorage, + legacy_config: Config, + ): + # Call the parent constructor to bring in the default components + super().__init__(settings, llm_provider, file_storage, legacy_config) + # Add your custom component + self.my_component = MyComponent() +``` + +For more customization, you can override the `propose_action` and `execute` or even subclass `BaseAgent` directly. This way you can have full control over the agent's components and behavior. Have a look at the [implementation of Agent](https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/autogpt/autogpt/agents/agent.py) for more details. diff --git a/autogpts/autogpt/autogpt/agents/agent.py b/autogpts/autogpt/autogpt/agents/agent.py index 3572cbed0..4a66a7ca4 100644 --- a/autogpts/autogpt/autogpt/agents/agent.py +++ b/autogpts/autogpt/autogpt/agents/agent.py @@ -19,7 +19,6 @@ from autogpt.components.event_history import EventHistoryComponent from autogpt.core.configuration import Configurable from autogpt.core.prompting import ChatPrompt from autogpt.core.resource.model_providers import ( - AssistantChatMessage, AssistantFunctionCall, ChatMessage, ChatModelProvider, @@ -27,7 +26,7 @@ from autogpt.core.resource.model_providers import ( ) from autogpt.core.runner.client_lib.logging.helpers import dump_prompt from autogpt.file_storage.base import FileStorage -from autogpt.llm.providers.openai import get_openai_command_specs +from autogpt.llm.providers.openai import function_specs_from_commands from autogpt.logs.log_cycle import ( CURRENT_CONTEXT_FILE_NAME, NEXT_ACTION_FILE_NAME, @@ -46,7 +45,6 @@ from autogpt.utils.exceptions import ( AgentException, AgentTerminated, CommandExecutionError, - InvalidArgumentError, UnknownCommandError, ) @@ -104,7 +102,11 @@ class Agent(BaseAgent, Configurable[AgentSettings]): self.ai_profile = settings.ai_profile self.directives = settings.directives prompt_config = OneShotAgentPromptStrategy.default_configuration.copy(deep=True) - prompt_config.use_functions_api = settings.config.use_functions_api + prompt_config.use_functions_api = ( + settings.config.use_functions_api + # Anthropic currently doesn't support tools + prefilling :( + and self.llm.provider_name != "anthropic" + ) self.prompt_strategy = OneShotAgentPromptStrategy(prompt_config, logger) self.commands: list[Command] = [] @@ -172,7 +174,7 @@ class Agent(BaseAgent, Configurable[AgentSettings]): task=self.state.task, ai_profile=self.state.ai_profile, ai_directives=directives, - commands=get_openai_command_specs(self.commands), + commands=function_specs_from_commands(self.commands), include_os_info=self.legacy_config.execute_local_commands, ) @@ -202,12 +204,9 @@ class Agent(BaseAgent, Configurable[AgentSettings]): ] = await self.llm_provider.create_chat_completion( prompt.messages, model_name=self.llm.name, - completion_parser=self.parse_and_validate_response, - functions=( - get_openai_command_specs(self.commands) - if self.config.use_functions_api - else [] - ), + completion_parser=self.prompt_strategy.parse_response_content, + functions=prompt.functions, + prefill_response=prompt.prefill_response, ) result = response.parsed_result @@ -223,28 +222,6 @@ class Agent(BaseAgent, Configurable[AgentSettings]): return result - def parse_and_validate_response( - self, llm_response: AssistantChatMessage - ) -> OneShotAgentActionProposal: - parsed_response = self.prompt_strategy.parse_response_content(llm_response) - - # Validate command arguments - command_name = parsed_response.use_tool.name - command = self._get_command(command_name) - if arg_errors := command.validate_args(parsed_response.use_tool.arguments)[1]: - fmt_errors = [ - f"{'.'.join(str(p) for p in f.path)}: {f.message}" - if f.path - else f.message - for f in arg_errors - ] - raise InvalidArgumentError( - f"The set of arguments supplied for {command_name} is invalid:\n" - + "\n".join(fmt_errors) - ) - - return parsed_response - async def execute( self, proposal: OneShotAgentActionProposal, diff --git a/autogpts/autogpt/autogpt/agents/base.py b/autogpts/autogpt/autogpt/agents/base.py index cf8e3cac8..515515701 100644 --- a/autogpts/autogpt/autogpt/agents/base.py +++ b/autogpts/autogpt/autogpt/agents/base.py @@ -39,11 +39,12 @@ from autogpt.core.configuration import ( SystemSettings, UserConfigurable, ) -from autogpt.core.resource.model_providers import AssistantFunctionCall -from autogpt.core.resource.model_providers.openai import ( - OPEN_AI_CHAT_MODELS, - OpenAIModelName, +from autogpt.core.resource.model_providers import ( + CHAT_MODELS, + AssistantFunctionCall, + ModelName, ) +from autogpt.core.resource.model_providers.openai import OpenAIModelName from autogpt.models.utils import ModelWithSummary from autogpt.prompts.prompt import DEFAULT_TRIGGERING_PROMPT @@ -56,8 +57,8 @@ P = ParamSpec("P") class BaseAgentConfiguration(SystemConfiguration): allow_fs_access: bool = UserConfigurable(default=False) - fast_llm: OpenAIModelName = UserConfigurable(default=OpenAIModelName.GPT3_16k) - smart_llm: OpenAIModelName = UserConfigurable(default=OpenAIModelName.GPT4) + fast_llm: ModelName = UserConfigurable(default=OpenAIModelName.GPT3_16k) + smart_llm: ModelName = UserConfigurable(default=OpenAIModelName.GPT4) use_functions_api: bool = UserConfigurable(default=False) default_cycle_instruction: str = DEFAULT_TRIGGERING_PROMPT @@ -174,7 +175,7 @@ class BaseAgent(Configurable[BaseAgentSettings], metaclass=AgentMeta): llm_name = ( self.config.smart_llm if self.config.big_brain else self.config.fast_llm ) - return OPEN_AI_CHAT_MODELS[llm_name] + return CHAT_MODELS[llm_name] @property def send_token_limit(self) -> int: diff --git a/autogpts/autogpt/autogpt/agents/prompt_strategies/one_shot.py b/autogpts/autogpt/autogpt/agents/prompt_strategies/one_shot.py index 53fadaa7c..ff08f4669 100644 --- a/autogpts/autogpt/autogpt/agents/prompt_strategies/one_shot.py +++ b/autogpts/autogpt/autogpt/agents/prompt_strategies/one_shot.py @@ -122,7 +122,7 @@ class OneShotAgentPromptStrategy(PromptStrategy): 1. System prompt 3. `cycle_instruction` """ - system_prompt = self.build_system_prompt( + system_prompt, response_prefill = self.build_system_prompt( ai_profile=ai_profile, ai_directives=ai_directives, commands=commands, @@ -131,24 +131,34 @@ class OneShotAgentPromptStrategy(PromptStrategy): final_instruction_msg = ChatMessage.user(self.config.choose_action_instruction) - prompt = ChatPrompt( + return ChatPrompt( messages=[ ChatMessage.system(system_prompt), ChatMessage.user(f'"""{task}"""'), *messages, final_instruction_msg, ], + prefill_response=response_prefill, + functions=commands if self.config.use_functions_api else [], ) - return prompt - def build_system_prompt( self, ai_profile: AIProfile, ai_directives: AIDirectives, commands: list[CompletionModelFunction], include_os_info: bool, - ) -> str: + ) -> tuple[str, str]: + """ + Builds the system prompt. + + Returns: + str: The system prompt body + str: The desired start for the LLM's response; used to steer the output + """ + response_fmt_instruction, response_prefill = self.response_format_instruction( + self.config.use_functions_api + ) system_prompt_parts = ( self._generate_intro_prompt(ai_profile) + (self._generate_os_info() if include_os_info else []) @@ -169,16 +179,16 @@ class OneShotAgentPromptStrategy(PromptStrategy): " in the next message. Your job is to complete the task while following" " your directives as given above, and terminate when your task is done." ] - + [ - "## RESPONSE FORMAT\n" - + self.response_format_instruction(self.config.use_functions_api) - ] + + ["## RESPONSE FORMAT\n" + response_fmt_instruction] ) # Join non-empty parts together into paragraph format - return "\n\n".join(filter(None, system_prompt_parts)).strip("\n") + return ( + "\n\n".join(filter(None, system_prompt_parts)).strip("\n"), + response_prefill, + ) - def response_format_instruction(self, use_functions_api: bool) -> str: + def response_format_instruction(self, use_functions_api: bool) -> tuple[str, str]: response_schema = self.response_schema.copy(deep=True) if ( use_functions_api @@ -193,11 +203,15 @@ class OneShotAgentPromptStrategy(PromptStrategy): "\n", response_schema.to_typescript_object_interface(_RESPONSE_INTERFACE_NAME), ) + response_prefill = f'{{\n "{list(response_schema.properties.keys())[0]}":' return ( - f"YOU MUST ALWAYS RESPOND WITH A JSON OBJECT OF THE FOLLOWING TYPE:\n" - f"{response_format}" - + ("\n\nYOU MUST ALSO INVOKE A TOOL!" if use_functions_api else "") + ( + f"YOU MUST ALWAYS RESPOND WITH A JSON OBJECT OF THE FOLLOWING TYPE:\n" + f"{response_format}" + + ("\n\nYOU MUST ALSO INVOKE A TOOL!" if use_functions_api else "") + ), + response_prefill, ) def _generate_intro_prompt(self, ai_profile: AIProfile) -> list[str]: diff --git a/autogpts/autogpt/autogpt/app/agent_protocol_server.py b/autogpts/autogpt/autogpt/app/agent_protocol_server.py index cdaf1f460..2eb09706e 100644 --- a/autogpts/autogpt/autogpt/app/agent_protocol_server.py +++ b/autogpts/autogpt/autogpt/app/agent_protocol_server.py @@ -34,7 +34,6 @@ from autogpt.agent_manager import AgentManager from autogpt.app.utils import is_port_free from autogpt.config import Config from autogpt.core.resource.model_providers import ChatModelProvider, ModelProviderBudget -from autogpt.core.resource.model_providers.openai import OpenAIProvider from autogpt.file_storage import FileStorage from autogpt.models.action_history import ActionErrorResult, ActionSuccessResult from autogpt.utils.exceptions import AgentFinished @@ -464,20 +463,18 @@ class AgentProtocolServer: 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"), - ) - - if task_llm_provider and task_llm_provider._budget: - self._task_budgets[task.task_id] = task_llm_provider._budget + settings = self.llm_provider._settings.copy() + settings.budget = task_llm_budget + settings.configuration = task_llm_provider_config + task_llm_provider = self.llm_provider.__class__( + settings=settings, + logger=logger.getChild( + f"Task-{task.task_id}_{self.llm_provider.__class__.__name__}" + ), + ) + self._task_budgets[task.task_id] = task_llm_provider._budget # type: ignore - return task_llm_provider or self.llm_provider + return task_llm_provider def task_agent_id(task_id: str | int) -> str: diff --git a/autogpts/autogpt/autogpt/app/configurator.py b/autogpts/autogpt/autogpt/app/configurator.py index 085d5dbf1..2463b6fcf 100644 --- a/autogpts/autogpt/autogpt/app/configurator.py +++ b/autogpts/autogpt/autogpt/app/configurator.py @@ -10,7 +10,7 @@ from colorama import Back, Fore, Style from autogpt.config import Config from autogpt.config.config import GPT_3_MODEL, GPT_4_MODEL -from autogpt.core.resource.model_providers.openai import OpenAIModelName, OpenAIProvider +from autogpt.core.resource.model_providers import ModelName, MultiProvider from autogpt.logs.helpers import request_user_double_check from autogpt.memory.vector import get_supported_memory_backends from autogpt.utils import utils @@ -150,11 +150,11 @@ async def apply_overrides_to_config( async def check_model( - model_name: OpenAIModelName, model_type: Literal["smart_llm", "fast_llm"] -) -> OpenAIModelName: + model_name: ModelName, model_type: Literal["smart_llm", "fast_llm"] +) -> ModelName: """Check if model is available for use. If not, return gpt-3.5-turbo.""" - openai = OpenAIProvider() - models = await openai.get_available_models() + multi_provider = MultiProvider() + models = await multi_provider.get_available_models() if any(model_name == m.name for m in models): return model_name diff --git a/autogpts/autogpt/autogpt/app/main.py b/autogpts/autogpt/autogpt/app/main.py index aaab5fe48..04354fb10 100644 --- a/autogpts/autogpt/autogpt/app/main.py +++ b/autogpts/autogpt/autogpt/app/main.py @@ -35,7 +35,7 @@ from autogpt.config import ( ConfigBuilder, assert_config_has_openai_api_key, ) -from autogpt.core.resource.model_providers.openai import OpenAIProvider +from autogpt.core.resource.model_providers import MultiProvider from autogpt.core.runner.client_lib.utils import coroutine from autogpt.file_storage import FileStorageBackendName, get_storage from autogpt.logs.config import configure_logging @@ -123,7 +123,7 @@ async def run_auto_gpt( skip_news=skip_news, ) - llm_provider = _configure_openai_provider(config) + llm_provider = _configure_llm_provider(config) logger = logging.getLogger(__name__) @@ -399,7 +399,7 @@ async def run_auto_gpt_server( allow_downloads=allow_downloads, ) - llm_provider = _configure_openai_provider(config) + llm_provider = _configure_llm_provider(config) # Set up & start server database = AgentDB( @@ -421,24 +421,12 @@ async def run_auto_gpt_server( ) -def _configure_openai_provider(config: Config) -> OpenAIProvider: - """Create a configured OpenAIProvider object. - - Args: - config: The program's configuration. - - Returns: - A configured OpenAIProvider object. - """ - if config.openai_credentials is None: - raise RuntimeError("OpenAI key is not configured") - - openai_settings = OpenAIProvider.default_settings.copy(deep=True) - openai_settings.credentials = config.openai_credentials - return OpenAIProvider( - settings=openai_settings, - logger=logging.getLogger("OpenAIProvider"), - ) +def _configure_llm_provider(config: Config) -> MultiProvider: + multi_provider = MultiProvider() + for model in [config.smart_llm, config.fast_llm]: + # Ensure model providers for configured LLMs are available + multi_provider.get_model_provider(model) + return multi_provider def _get_cycle_budget(continuous_mode: bool, continuous_limit: int) -> int | float: diff --git a/autogpts/autogpt/autogpt/command_decorator.py b/autogpts/autogpt/autogpt/command_decorator.py index 6902939a0..cf074b16c 100644 --- a/autogpts/autogpt/autogpt/command_decorator.py +++ b/autogpts/autogpt/autogpt/command_decorator.py @@ -1,21 +1,18 @@ import re -from typing import Callable, Optional, ParamSpec, TypeVar +from typing import Callable, Concatenate, Optional, TypeVar +from autogpt.agents.protocols import CommandProvider from autogpt.core.utils.json_schema import JSONSchema -from autogpt.models.command import Command, CommandOutput, CommandParameter +from autogpt.models.command import CO, Command, CommandParameter, P -# Unique identifier for AutoGPT commands -AUTO_GPT_COMMAND_IDENTIFIER = "auto_gpt_command" - -P = ParamSpec("P") -CO = TypeVar("CO", bound=CommandOutput) +_CP = TypeVar("_CP", bound=CommandProvider) def command( names: list[str] = [], description: Optional[str] = None, parameters: dict[str, JSONSchema] = {}, -) -> Callable[[Callable[P, CommandOutput]], Command]: +) -> Callable[[Callable[Concatenate[_CP, P], CO]], Command[P, CO]]: """ The command decorator is used to make a Command from a function. @@ -29,7 +26,7 @@ def command( that the command executes. """ - def decorator(func: Callable[P, CO]) -> Command: + def decorator(func: Callable[Concatenate[_CP, P], CO]) -> Command[P, CO]: doc = func.__doc__ or "" # If names is not provided, use the function name command_names = names or [func.__name__] diff --git a/autogpts/autogpt/autogpt/commands/README.md b/autogpts/autogpt/autogpt/commands/README.md index 86a1c78ea..5575f0bcb 120000..100644 --- a/autogpts/autogpt/autogpt/commands/README.md +++ b/autogpts/autogpt/autogpt/commands/README.md @@ -1 +1,128 @@ -../../../../docs/content/AutoGPT/component agent/components.md
\ No newline at end of file +# 🧩 Components + +Components are the building blocks of [🤖 Agents](./agents.md). They are classes inheriting `AgentComponent` or implementing one or more [⚙️ Protocols](./protocols.md) that give agent additional abilities or processing. + +Components can be used to implement various functionalities like providing messages to the prompt, executing code, or interacting with external services. +They can be enabled or disabled, ordered, and can rely on each other. + +Components assigned in the agent's `__init__` via `self` are automatically detected upon the agent's instantiation. +For example inside `__init__`: `self.my_component = MyComponent()`. +You can use any valid Python variable name, what matters for the component to be detected is its type (`AgentComponent` or any protocol inheriting from it). + +Visit [Built-in Components](./built-in-components.md) to see what components are available out of the box. + +```py +from autogpt.agents import Agent +from autogpt.agents.components import AgentComponent + +class HelloComponent(AgentComponent): + pass + +class SomeComponent(AgentComponent): + def __init__(self, hello_component: HelloComponent): + self.hello_component = hello_component + +class MyAgent(Agent): + def __init__(self): + # These components will be automatically discovered and used + self.hello_component = HelloComponent() + # We pass HelloComponent to SomeComponent + self.some_component = SomeComponent(self.hello_component) +``` + +## Ordering components + +The execution order of components is important because the latter ones may depend on the results of the former ones. + +### Implicit order + +Components can be ordered implicitly by the agent; each component can set `run_after` list to specify which components should run before it. This is useful when components rely on each other or need to be executed in a specific order. Otherwise, the order of components is alphabetical. + +```py +# This component will run after HelloComponent +class CalculatorComponent(AgentComponent): + run_after = [HelloComponent] +``` + +### Explicit order + +Sometimes it may be easier to order components explicitly by setting `self.components` list in the agent's `__init__` method. This way you can also ensure there's no circular dependencies and `run_after` is ignored. + +!!! warning + Be sure to include all components - by setting `self.components` list, you're overriding the default behavior of discovering components automatically. Since it's usually not intended agent will inform you in the terminal if some components were skipped. + +```py +class MyAgent(Agent): + def __init__(self): + self.hello_component = HelloComponent() + self.calculator_component = CalculatorComponent(self.hello_component) + # Explicitly set components list + self.components = [self.hello_component, self.calculator_component] +``` + +## Disabling components + +You can control which components are enabled by setting their `_enabled` attribute. +Either provide a `bool` value or a `Callable[[], bool]`, will be checked each time +the component is about to be executed. This way you can dynamically enable or disable +components based on some conditions. +You can also provide a reason for disabling the component by setting `_disabled_reason`. +The reason will be visible in the debug information. + +```py +class DisabledComponent(MessageProvider): + def __init__(self): + # Disable this component + self._enabled = False + self._disabled_reason = "This component is disabled because of reasons." + + # Or disable based on some condition, either statically...: + self._enabled = self.some_property is not None + # ... or dynamically: + self._enabled = lambda: self.some_property is not None + + # This method will never be called + def get_messages(self) -> Iterator[ChatMessage]: + yield ChatMessage.user("This message won't be seen!") + + def some_condition(self) -> bool: + return False +``` + +If you don't want the component at all, you can just remove it from the agent's `__init__` method. If you want to remove components you inherit from the parent class you can set the relevant attribute to `None`: + +!!! Warning + Be careful when removing components that are required by other components. This may lead to errors and unexpected behavior. + +```py +class MyAgent(Agent): + def __init__(self): + super().__init__(...) + # Disable WatchdogComponent that is in the parent class + self.watchdog = None + +``` + +## Exceptions + +Custom errors are provided which can be used to control the execution flow in case something went wrong. All those errors can be raised in protocol methods and will be caught by the agent. +By default agent will retry three times and then re-raise an exception if it's still not resolved. All passed arguments are automatically handled and the values are reverted when needed. +All errors accept an optional `str` message. There are following errors ordered by increasing broadness: + +1. `ComponentEndpointError`: A single endpoint method failed to execute. Agent will retry the execution of this endpoint on the component. +2. `EndpointPipelineError`: A pipeline failed to execute. Agent will retry the execution of the endpoint for all components. +3. `ComponentSystemError`: Multiple pipelines failed. + +**Example** + +```py +from autogpt.agents.components import ComponentEndpointError +from autogpt.agents.protocols import MessageProvider + +# Example of raising an error +class MyComponent(MessageProvider): + def get_messages(self) -> Iterator[ChatMessage]: + # This will cause the component to always fail + # and retry 3 times before re-raising the exception + raise ComponentEndpointError("Endpoint error!") +``` diff --git a/autogpts/autogpt/autogpt/commands/system.py b/autogpts/autogpt/autogpt/commands/system.py index 85ab5c100..ce2640529 100644 --- a/autogpts/autogpt/autogpt/commands/system.py +++ b/autogpts/autogpt/autogpt/commands/system.py @@ -31,7 +31,9 @@ class SystemComponent(DirectiveProvider, MessageProvider, CommandProvider): def get_messages(self) -> Iterator[ChatMessage]: # Clock - yield ChatMessage.system(f"The current time and date is {time.strftime('%c')}") + yield ChatMessage.system( + f"## Clock\nThe current time and date is {time.strftime('%c')}" + ) def get_commands(self) -> Iterator[Command]: yield self.finish diff --git a/autogpts/autogpt/autogpt/config/config.py b/autogpts/autogpt/autogpt/config/config.py index 8dd648188..11d35b673 100644 --- a/autogpts/autogpt/autogpt/config/config.py +++ b/autogpts/autogpt/autogpt/config/config.py @@ -17,8 +17,8 @@ from autogpt.core.configuration.schema import ( SystemSettings, UserConfigurable, ) +from autogpt.core.resource.model_providers import CHAT_MODELS, ModelName from autogpt.core.resource.model_providers.openai import ( - OPEN_AI_CHAT_MODELS, OpenAICredentials, OpenAIModelName, ) @@ -74,11 +74,11 @@ class Config(SystemSettings, arbitrary_types_allowed=True): ) # Model configuration - fast_llm: OpenAIModelName = UserConfigurable( + fast_llm: ModelName = UserConfigurable( default=OpenAIModelName.GPT3, from_env="FAST_LLM", ) - smart_llm: OpenAIModelName = UserConfigurable( + smart_llm: ModelName = UserConfigurable( default=OpenAIModelName.GPT4_TURBO, from_env="SMART_LLM", ) @@ -206,8 +206,8 @@ class Config(SystemSettings, arbitrary_types_allowed=True): def validate_openai_functions(cls, v: bool, values: dict[str, Any]): if v: smart_llm = values["smart_llm"] - assert OPEN_AI_CHAT_MODELS[smart_llm].has_function_call_api, ( - f"Model {smart_llm} does not support OpenAI Functions. " + assert CHAT_MODELS[smart_llm].has_function_call_api, ( + f"Model {smart_llm} does not support tool calling. " "Please disable OPENAI_FUNCTIONS or choose a suitable model." ) return v diff --git a/autogpts/autogpt/autogpt/core/prompting/schema.py b/autogpts/autogpt/autogpt/core/prompting/schema.py index 45efc40fe..fcc7c6b61 100644 --- a/autogpts/autogpt/autogpt/core/prompting/schema.py +++ b/autogpts/autogpt/autogpt/core/prompting/schema.py @@ -24,6 +24,7 @@ class LanguageModelClassification(str, enum.Enum): class ChatPrompt(BaseModel): messages: list[ChatMessage] functions: list[CompletionModelFunction] = Field(default_factory=list) + prefill_response: str = "" def raw(self) -> list[ChatMessageDict]: return [m.dict() for m in self.messages] diff --git a/autogpts/autogpt/autogpt/core/resource/model_providers/__init__.py b/autogpts/autogpt/autogpt/core/resource/model_providers/__init__.py index b896760d2..7fb98170e 100644 --- a/autogpts/autogpt/autogpt/core/resource/model_providers/__init__.py +++ b/autogpts/autogpt/autogpt/core/resource/model_providers/__init__.py @@ -1,3 +1,4 @@ +from .multi import CHAT_MODELS, ModelName, MultiProvider from .openai import ( OPEN_AI_CHAT_MODELS, OPEN_AI_EMBEDDING_MODELS, @@ -42,11 +43,13 @@ __all__ = [ "ChatModelProvider", "ChatModelResponse", "CompletionModelFunction", + "CHAT_MODELS", "Embedding", "EmbeddingModelInfo", "EmbeddingModelProvider", "EmbeddingModelResponse", "ModelInfo", + "ModelName", "ModelProvider", "ModelProviderBudget", "ModelProviderCredentials", @@ -56,6 +59,7 @@ __all__ = [ "ModelProviderUsage", "ModelResponse", "ModelTokenizer", + "MultiProvider", "OPEN_AI_MODELS", "OPEN_AI_CHAT_MODELS", "OPEN_AI_EMBEDDING_MODELS", diff --git a/autogpts/autogpt/autogpt/core/resource/model_providers/anthropic.py b/autogpts/autogpt/autogpt/core/resource/model_providers/anthropic.py new file mode 100644 index 000000000..3d5967f1c --- /dev/null +++ b/autogpts/autogpt/autogpt/core/resource/model_providers/anthropic.py @@ -0,0 +1,495 @@ +from __future__ import annotations + +import enum +import logging +from typing import TYPE_CHECKING, Callable, Optional, ParamSpec, TypeVar + +import sentry_sdk +import tenacity +import tiktoken +from anthropic import APIConnectionError, APIStatusError +from pydantic import SecretStr + +from autogpt.core.configuration import Configurable, UserConfigurable +from autogpt.core.resource.model_providers.schema import ( + AssistantChatMessage, + AssistantFunctionCall, + AssistantToolCall, + ChatMessage, + ChatModelInfo, + ChatModelProvider, + ChatModelResponse, + CompletionModelFunction, + ModelProviderBudget, + ModelProviderConfiguration, + ModelProviderCredentials, + ModelProviderName, + ModelProviderSettings, + ModelTokenizer, + ToolResultMessage, +) + +from .utils import validate_tool_calls + +if TYPE_CHECKING: + from anthropic.types.beta.tools import MessageCreateParams + from anthropic.types.beta.tools import ToolsBetaMessage as Message + from anthropic.types.beta.tools import ToolsBetaMessageParam as MessageParam + +_T = TypeVar("_T") +_P = ParamSpec("_P") + + +class AnthropicModelName(str, enum.Enum): + CLAUDE3_OPUS_v1 = "claude-3-opus-20240229" + CLAUDE3_SONNET_v1 = "claude-3-sonnet-20240229" + CLAUDE3_HAIKU_v1 = "claude-3-haiku-20240307" + + +ANTHROPIC_CHAT_MODELS = { + info.name: info + for info in [ + ChatModelInfo( + name=AnthropicModelName.CLAUDE3_OPUS_v1, + provider_name=ModelProviderName.ANTHROPIC, + prompt_token_cost=15 / 1e6, + completion_token_cost=75 / 1e6, + max_tokens=200000, + has_function_call_api=True, + ), + ChatModelInfo( + name=AnthropicModelName.CLAUDE3_SONNET_v1, + provider_name=ModelProviderName.ANTHROPIC, + prompt_token_cost=3 / 1e6, + completion_token_cost=15 / 1e6, + max_tokens=200000, + has_function_call_api=True, + ), + ChatModelInfo( + name=AnthropicModelName.CLAUDE3_HAIKU_v1, + provider_name=ModelProviderName.ANTHROPIC, + prompt_token_cost=0.25 / 1e6, + completion_token_cost=1.25 / 1e6, + max_tokens=200000, + has_function_call_api=True, + ), + ] +} + + +class AnthropicConfiguration(ModelProviderConfiguration): + fix_failed_parse_tries: int = UserConfigurable(3) + + +class AnthropicCredentials(ModelProviderCredentials): + """Credentials for Anthropic.""" + + api_key: SecretStr = UserConfigurable(from_env="ANTHROPIC_API_KEY") + api_base: Optional[SecretStr] = UserConfigurable( + default=None, from_env="ANTHROPIC_API_BASE_URL" + ) + + def get_api_access_kwargs(self) -> dict[str, str]: + return { + 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, + }.items() + if v is not None + } + + +class AnthropicSettings(ModelProviderSettings): + configuration: AnthropicConfiguration + credentials: Optional[AnthropicCredentials] + budget: ModelProviderBudget + + +class AnthropicProvider(Configurable[AnthropicSettings], ChatModelProvider): + default_settings = AnthropicSettings( + name="anthropic_provider", + description="Provides access to Anthropic's API.", + configuration=AnthropicConfiguration( + retries_per_request=7, + ), + credentials=None, + budget=ModelProviderBudget(), + ) + + _settings: AnthropicSettings + _configuration: AnthropicConfiguration + _credentials: AnthropicCredentials + _budget: ModelProviderBudget + + def __init__( + self, + settings: Optional[AnthropicSettings] = None, + logger: Optional[logging.Logger] = None, + ): + if not settings: + settings = self.default_settings.copy(deep=True) + if not settings.credentials: + settings.credentials = AnthropicCredentials.from_env() + + super(AnthropicProvider, self).__init__(settings=settings, logger=logger) + + from anthropic import AsyncAnthropic + + self._client = AsyncAnthropic(**self._credentials.get_api_access_kwargs()) + + async def get_available_models(self) -> list[ChatModelInfo]: + return list(ANTHROPIC_CHAT_MODELS.values()) + + def get_token_limit(self, model_name: str) -> int: + """Get the token limit for a given model.""" + return ANTHROPIC_CHAT_MODELS[model_name].max_tokens + + @classmethod + def get_tokenizer(cls, model_name: AnthropicModelName) -> ModelTokenizer: + # HACK: No official tokenizer is available for Claude 3 + return tiktoken.encoding_for_model(model_name) + + @classmethod + def count_tokens(cls, text: str, model_name: AnthropicModelName) -> int: + return 0 # HACK: No official tokenizer is available for Claude 3 + + @classmethod + def count_message_tokens( + cls, + messages: ChatMessage | list[ChatMessage], + model_name: AnthropicModelName, + ) -> int: + return 0 # HACK: No official tokenizer is available for Claude 3 + + async def create_chat_completion( + self, + model_prompt: list[ChatMessage], + model_name: AnthropicModelName, + completion_parser: Callable[[AssistantChatMessage], _T] = lambda _: None, + functions: Optional[list[CompletionModelFunction]] = None, + max_output_tokens: Optional[int] = None, + prefill_response: str = "", + **kwargs, + ) -> ChatModelResponse[_T]: + """Create a completion using the Anthropic API.""" + anthropic_messages, completion_kwargs = self._get_chat_completion_args( + prompt_messages=model_prompt, + model=model_name, + functions=functions, + max_output_tokens=max_output_tokens, + **kwargs, + ) + + total_cost = 0.0 + attempts = 0 + while True: + completion_kwargs["messages"] = anthropic_messages.copy() + if prefill_response: + completion_kwargs["messages"].append( + {"role": "assistant", "content": prefill_response} + ) + + ( + _assistant_msg, + cost, + t_input, + t_output, + ) = await self._create_chat_completion(completion_kwargs) + total_cost += cost + self._logger.debug( + f"Completion usage: {t_input} input, {t_output} output " + f"- ${round(cost, 5)}" + ) + + # Merge prefill into generated response + if prefill_response: + first_text_block = next( + b for b in _assistant_msg.content if b.type == "text" + ) + first_text_block.text = prefill_response + first_text_block.text + + assistant_msg = AssistantChatMessage( + content="\n\n".join( + b.text for b in _assistant_msg.content if b.type == "text" + ), + tool_calls=self._parse_assistant_tool_calls(_assistant_msg), + ) + + # If parsing the response fails, append the error to the prompt, and let the + # LLM fix its mistake(s). + attempts += 1 + tool_call_errors = [] + try: + # Validate tool calls + if assistant_msg.tool_calls and functions: + tool_call_errors = validate_tool_calls( + assistant_msg.tool_calls, functions + ) + if tool_call_errors: + raise ValueError( + "Invalid tool use(s):\n" + + "\n".join(str(e) for e in tool_call_errors) + ) + + parsed_result = completion_parser(assistant_msg) + break + except Exception as e: + self._logger.debug( + f"Parsing failed on response: '''{_assistant_msg}'''" + ) + self._logger.warning(f"Parsing attempt #{attempts} failed: {e}") + sentry_sdk.capture_exception( + error=e, + extras={"assistant_msg": _assistant_msg, "i_attempt": attempts}, + ) + if attempts < self._configuration.fix_failed_parse_tries: + anthropic_messages.append( + _assistant_msg.dict(include={"role", "content"}) + ) + anthropic_messages.append( + { + "role": "user", + "content": [ + *( + # tool_result is required if last assistant message + # had tool_use block(s) + { + "type": "tool_result", + "tool_use_id": tc.id, + "is_error": True, + "content": [ + { + "type": "text", + "text": "Not executed because parsing " + "of your last message failed" + if not tool_call_errors + else str(e) + if ( + e := next( + ( + tce + for tce in tool_call_errors + if tce.name + == tc.function.name + ), + None, + ) + ) + else "Not executed because validation " + "of tool input failed", + } + ], + } + for tc in assistant_msg.tool_calls or [] + ), + { + "type": "text", + "text": ( + "ERROR PARSING YOUR RESPONSE:\n\n" + f"{e.__class__.__name__}: {e}" + ), + }, + ], + } + ) + else: + raise + + if attempts > 1: + self._logger.debug( + f"Total cost for {attempts} attempts: ${round(total_cost, 5)}" + ) + + return ChatModelResponse( + response=assistant_msg, + parsed_result=parsed_result, + model_info=ANTHROPIC_CHAT_MODELS[model_name], + prompt_tokens_used=t_input, + completion_tokens_used=t_output, + ) + + def _get_chat_completion_args( + self, + prompt_messages: list[ChatMessage], + model: AnthropicModelName, + functions: Optional[list[CompletionModelFunction]] = None, + max_output_tokens: Optional[int] = None, + **kwargs, + ) -> tuple[list[MessageParam], MessageCreateParams]: + """Prepare arguments for message completion API call. + + Args: + prompt_messages: List of ChatMessages. + model: The model to use. + functions: Optional list of functions available to the LLM. + kwargs: Additional keyword arguments. + + Returns: + list[MessageParam]: Prompt messages for the Anthropic call + dict[str, Any]: Any other kwargs for the Anthropic call + """ + kwargs["model"] = model + + if functions: + kwargs["tools"] = [ + { + "name": f.name, + "description": f.description, + "input_schema": { + "type": "object", + "properties": { + name: param.to_dict() + for name, param in f.parameters.items() + }, + "required": [ + name + for name, param in f.parameters.items() + if param.required + ], + }, + } + for f in functions + ] + + kwargs["max_tokens"] = max_output_tokens or 4096 + + if extra_headers := self._configuration.extra_request_headers: + kwargs["extra_headers"] = kwargs.get("extra_headers", {}) + kwargs["extra_headers"].update(extra_headers.copy()) + + system_messages = [ + m for m in prompt_messages if m.role == ChatMessage.Role.SYSTEM + ] + if (_n := len(system_messages)) > 1: + self._logger.warning( + f"Prompt has {_n} system messages; Anthropic supports only 1. " + "They will be merged, and removed from the rest of the prompt." + ) + kwargs["system"] = "\n\n".join(sm.content for sm in system_messages) + + messages: list[MessageParam] = [] + for message in prompt_messages: + if message.role == ChatMessage.Role.SYSTEM: + continue + elif message.role == ChatMessage.Role.USER: + # Merge subsequent user messages + if messages and (prev_msg := messages[-1])["role"] == "user": + if isinstance(prev_msg["content"], str): + prev_msg["content"] += f"\n\n{message.content}" + else: + assert isinstance(prev_msg["content"], list) + prev_msg["content"].append( + {"type": "text", "text": message.content} + ) + else: + messages.append({"role": "user", "content": message.content}) + # TODO: add support for image blocks + elif message.role == ChatMessage.Role.ASSISTANT: + if isinstance(message, AssistantChatMessage) and message.tool_calls: + messages.append( + { + "role": "assistant", + "content": [ + *( + [{"type": "text", "text": message.content}] + if message.content + else [] + ), + *( + { + "type": "tool_use", + "id": tc.id, + "name": tc.function.name, + "input": tc.function.arguments, + } + for tc in message.tool_calls + ), + ], + } + ) + elif message.content: + messages.append( + { + "role": "assistant", + "content": message.content, + } + ) + elif isinstance(message, ToolResultMessage): + messages.append( + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": message.tool_call_id, + "content": [{"type": "text", "text": message.content}], + "is_error": message.is_error, + } + ], + } + ) + + return messages, kwargs # type: ignore + + async def _create_chat_completion( + self, completion_kwargs: MessageCreateParams + ) -> tuple[Message, float, int, int]: + """ + Create a chat completion using the Anthropic API with retry handling. + + Params: + completion_kwargs: Keyword arguments for an Anthropic Messages API call + + Returns: + Message: The message completion object + float: The cost ($) of this completion + int: Number of input tokens used + int: Number of output tokens used + """ + + @self._retry_api_request + async def _create_chat_completion_with_retry( + completion_kwargs: MessageCreateParams, + ) -> Message: + return await self._client.beta.tools.messages.create( + **completion_kwargs # type: ignore + ) + + response = await _create_chat_completion_with_retry(completion_kwargs) + + cost = self._budget.update_usage_and_cost( + model_info=ANTHROPIC_CHAT_MODELS[completion_kwargs["model"]], + input_tokens_used=response.usage.input_tokens, + output_tokens_used=response.usage.output_tokens, + ) + return response, cost, response.usage.input_tokens, response.usage.output_tokens + + def _parse_assistant_tool_calls( + self, assistant_message: Message + ) -> list[AssistantToolCall]: + return [ + AssistantToolCall( + id=c.id, + type="function", + function=AssistantFunctionCall(name=c.name, arguments=c.input), + ) + for c in assistant_message.content + if c.type == "tool_use" + ] + + def _retry_api_request(self, func: Callable[_P, _T]) -> Callable[_P, _T]: + return tenacity.retry( + retry=( + tenacity.retry_if_exception_type(APIConnectionError) + | tenacity.retry_if_exception( + lambda e: isinstance(e, APIStatusError) and e.status_code >= 500 + ) + ), + wait=tenacity.wait_exponential(), + stop=tenacity.stop_after_attempt(self._configuration.retries_per_request), + after=tenacity.after_log(self._logger, logging.DEBUG), + )(func) + + def __repr__(self): + return "AnthropicProvider()" diff --git a/autogpts/autogpt/autogpt/core/resource/model_providers/multi.py b/autogpts/autogpt/autogpt/core/resource/model_providers/multi.py new file mode 100644 index 000000000..f194e0256 --- /dev/null +++ b/autogpts/autogpt/autogpt/core/resource/model_providers/multi.py @@ -0,0 +1,162 @@ +from __future__ import annotations + +import logging +from typing import Callable, Iterator, Optional, TypeVar + +from pydantic import ValidationError + +from autogpt.core.configuration import Configurable + +from .anthropic import ANTHROPIC_CHAT_MODELS, AnthropicModelName, AnthropicProvider +from .openai import OPEN_AI_CHAT_MODELS, OpenAIModelName, OpenAIProvider +from .schema import ( + AssistantChatMessage, + ChatMessage, + ChatModelInfo, + ChatModelProvider, + ChatModelResponse, + CompletionModelFunction, + ModelProviderBudget, + ModelProviderConfiguration, + ModelProviderName, + ModelProviderSettings, + ModelTokenizer, +) + +_T = TypeVar("_T") + +ModelName = AnthropicModelName | OpenAIModelName + +CHAT_MODELS = {**ANTHROPIC_CHAT_MODELS, **OPEN_AI_CHAT_MODELS} + + +class MultiProvider(Configurable[ModelProviderSettings], ChatModelProvider): + default_settings = ModelProviderSettings( + name="multi_provider", + description=( + "Provides access to all of the available models, regardless of provider." + ), + configuration=ModelProviderConfiguration( + retries_per_request=7, + ), + budget=ModelProviderBudget(), + ) + + _budget: ModelProviderBudget + + _provider_instances: dict[ModelProviderName, ChatModelProvider] + + def __init__( + self, + settings: Optional[ModelProviderSettings] = None, + logger: Optional[logging.Logger] = None, + ): + super(MultiProvider, self).__init__(settings=settings, logger=logger) + self._budget = self._settings.budget or ModelProviderBudget() + + self._provider_instances = {} + + async def get_available_models(self) -> list[ChatModelInfo]: + models = [] + for provider in self.get_available_providers(): + models.extend(await provider.get_available_models()) + return models + + def get_token_limit(self, model_name: ModelName) -> int: + """Get the token limit for a given model.""" + return self.get_model_provider(model_name).get_token_limit(model_name) + + @classmethod + def get_tokenizer(cls, model_name: ModelName) -> ModelTokenizer: + return cls._get_model_provider_class(model_name).get_tokenizer(model_name) + + @classmethod + def count_tokens(cls, text: str, model_name: ModelName) -> int: + return cls._get_model_provider_class(model_name).count_tokens( + text=text, model_name=model_name + ) + + @classmethod + def count_message_tokens( + cls, messages: ChatMessage | list[ChatMessage], model_name: ModelName + ) -> int: + return cls._get_model_provider_class(model_name).count_message_tokens( + messages=messages, model_name=model_name + ) + + async def create_chat_completion( + self, + model_prompt: list[ChatMessage], + model_name: ModelName, + completion_parser: Callable[[AssistantChatMessage], _T] = lambda _: None, + functions: Optional[list[CompletionModelFunction]] = None, + max_output_tokens: Optional[int] = None, + prefill_response: str = "", + **kwargs, + ) -> ChatModelResponse[_T]: + """Create a completion using the Anthropic API.""" + return await self.get_model_provider(model_name).create_chat_completion( + model_prompt=model_prompt, + model_name=model_name, + completion_parser=completion_parser, + functions=functions, + max_output_tokens=max_output_tokens, + prefill_response=prefill_response, + **kwargs, + ) + + def get_model_provider(self, model: ModelName) -> ChatModelProvider: + model_info = CHAT_MODELS[model] + return self._get_provider(model_info.provider_name) + + def get_available_providers(self) -> Iterator[ChatModelProvider]: + for provider_name in ModelProviderName: + try: + yield self._get_provider(provider_name) + except Exception: + pass + + def _get_provider(self, provider_name: ModelProviderName) -> ChatModelProvider: + _provider = self._provider_instances.get(provider_name) + if not _provider: + Provider = self._get_provider_class(provider_name) + settings = Provider.default_settings.copy(deep=True) + settings.budget = self._budget + settings.configuration.extra_request_headers.update( + self._settings.configuration.extra_request_headers + ) + if settings.credentials is None: + try: + Credentials = settings.__fields__["credentials"].type_ + settings.credentials = Credentials.from_env() + except ValidationError as e: + raise ValueError( + f"{provider_name} is unavailable: can't load credentials" + ) from e + + self._provider_instances[provider_name] = _provider = Provider( + settings=settings, logger=self._logger + ) + _provider._budget = self._budget # Object binding not preserved by Pydantic + return _provider + + @classmethod + def _get_model_provider_class( + cls, model_name: ModelName + ) -> type[AnthropicProvider | OpenAIProvider]: + return cls._get_provider_class(CHAT_MODELS[model_name].provider_name) + + @classmethod + def _get_provider_class( + cls, provider_name: ModelProviderName + ) -> type[AnthropicProvider | OpenAIProvider]: + try: + return { + ModelProviderName.ANTHROPIC: AnthropicProvider, + ModelProviderName.OPENAI: OpenAIProvider, + }[provider_name] + except KeyError: + raise ValueError(f"{provider_name} is not a known provider") from None + + def __repr__(self): + return f"{self.__class__.__name__}()" diff --git a/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py b/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py index 0e50f1fa3..c3c5aabb4 100644 --- a/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py +++ b/autogpts/autogpt/autogpt/core/resource/model_providers/openai.py @@ -42,6 +42,8 @@ from autogpt.core.resource.model_providers.schema import ( from autogpt.core.utils.json_schema import JSONSchema from autogpt.core.utils.json_utils import json_loads +from .utils import validate_tool_calls + _T = TypeVar("_T") _P = ParamSpec("_P") @@ -298,6 +300,7 @@ class OpenAIProvider( budget=ModelProviderBudget(), ) + _settings: OpenAISettings _configuration: OpenAIConfiguration _credentials: OpenAICredentials _budget: ModelProviderBudget @@ -312,11 +315,7 @@ class OpenAIProvider( if not settings.credentials: settings.credentials = OpenAICredentials.from_env() - self._settings = settings - - self._configuration = settings.configuration - self._credentials = settings.credentials - self._budget = settings.budget + super(OpenAIProvider, self).__init__(settings=settings, logger=logger) if self._credentials.api_type == "azure": from openai import AsyncAzureOpenAI @@ -329,8 +328,6 @@ class OpenAIProvider( self._client = AsyncOpenAI(**self._credentials.get_api_access_kwargs()) - self._logger = logger or logging.getLogger(__name__) - async def get_available_models(self) -> list[ChatModelInfo]: _models = (await self._client.models.list()).data return [OPEN_AI_MODELS[m.id] for m in _models if m.id in OPEN_AI_MODELS] @@ -398,6 +395,7 @@ class OpenAIProvider( completion_parser: Callable[[AssistantChatMessage], _T] = lambda _: None, functions: Optional[list[CompletionModelFunction]] = None, max_output_tokens: Optional[int] = None, + prefill_response: str = "", # not supported by OpenAI **kwargs, ) -> ChatModelResponse[_T]: """Create a completion using the OpenAI API and parse it.""" @@ -432,6 +430,10 @@ class OpenAIProvider( ) parse_errors += _errors + # Validate tool calls + if not parse_errors and tool_calls and functions: + parse_errors += validate_tool_calls(tool_calls, functions) + assistant_msg = AssistantChatMessage( content=_assistant_msg.content, tool_calls=tool_calls or None, diff --git a/autogpts/autogpt/autogpt/core/resource/model_providers/schema.py b/autogpts/autogpt/autogpt/core/resource/model_providers/schema.py index 60df855f2..bb2e29490 100644 --- a/autogpts/autogpt/autogpt/core/resource/model_providers/schema.py +++ b/autogpts/autogpt/autogpt/core/resource/model_providers/schema.py @@ -1,8 +1,10 @@ import abc import enum +import logging import math from collections import defaultdict from typing import ( + TYPE_CHECKING, Any, Callable, ClassVar, @@ -28,6 +30,9 @@ from autogpt.core.resource.schema import ( from autogpt.core.utils.json_schema import JSONSchema from autogpt.logs.utils import fmt_kwargs +if TYPE_CHECKING: + from jsonschema import ValidationError + class ModelProviderService(str, enum.Enum): """A ModelService describes what kind of service the model provides.""" @@ -39,6 +44,7 @@ class ModelProviderService(str, enum.Enum): class ModelProviderName(str, enum.Enum): OPENAI = "openai" + ANTHROPIC = "anthropic" class ChatMessage(BaseModel): @@ -100,6 +106,12 @@ class AssistantChatMessage(ChatMessage): tool_calls: Optional[list[AssistantToolCall]] = None +class ToolResultMessage(ChatMessage): + role: Literal[ChatMessage.Role.TOOL] = ChatMessage.Role.TOOL + is_error: bool = False + tool_call_id: str + + class AssistantChatMessageDict(TypedDict, total=False): role: str content: str @@ -146,6 +158,30 @@ class CompletionModelFunction(BaseModel): ) return f"{self.name}: {self.description}. Params: ({params})" + def validate_call( + self, function_call: AssistantFunctionCall + ) -> tuple[bool, list["ValidationError"]]: + """ + Validates the given function call against the function's parameter specs + + Returns: + bool: Whether the given set of arguments is valid for this command + list[ValidationError]: Issues with the set of arguments (if any) + + Raises: + ValueError: If the function_call doesn't call this function + """ + if function_call.name != self.name: + raise ValueError( + f"Can't validate {function_call.name} call using {self.name} spec" + ) + + params_schema = JSONSchema( + type=JSONSchema.Type.OBJECT, + properties={name: spec for name, spec in self.parameters.items()}, + ) + return params_schema.validate_object(function_call.arguments) + class ModelInfo(BaseModel): """Struct for model information. @@ -229,7 +265,7 @@ class ModelProviderBudget(ProviderBudget): class ModelProviderSettings(ProviderSettings): resource_type: ResourceType = ResourceType.MODEL configuration: ModelProviderConfiguration - credentials: ModelProviderCredentials + credentials: Optional[ModelProviderCredentials] = None budget: Optional[ModelProviderBudget] = None @@ -238,9 +274,28 @@ class ModelProvider(abc.ABC): default_settings: ClassVar[ModelProviderSettings] + _settings: ModelProviderSettings _configuration: ModelProviderConfiguration + _credentials: Optional[ModelProviderCredentials] = None _budget: Optional[ModelProviderBudget] = None + _logger: logging.Logger + + def __init__( + self, + settings: Optional[ModelProviderSettings] = None, + logger: Optional[logging.Logger] = None, + ): + if not settings: + settings = self.default_settings.copy(deep=True) + + self._settings = settings + self._configuration = settings.configuration + self._credentials = settings.credentials + self._budget = settings.budget + + self._logger = logger or logging.getLogger(self.__module__) + @abc.abstractmethod def count_tokens(self, text: str, model_name: str) -> int: ... @@ -358,6 +413,7 @@ class ChatModelProvider(ModelProvider): completion_parser: Callable[[AssistantChatMessage], _T] = lambda _: None, functions: Optional[list[CompletionModelFunction]] = None, max_output_tokens: Optional[int] = None, + prefill_response: str = "", **kwargs, ) -> ChatModelResponse[_T]: ... diff --git a/autogpts/autogpt/autogpt/core/resource/model_providers/utils.py b/autogpts/autogpt/autogpt/core/resource/model_providers/utils.py new file mode 100644 index 000000000..5b83b047b --- /dev/null +++ b/autogpts/autogpt/autogpt/core/resource/model_providers/utils.py @@ -0,0 +1,71 @@ +from typing import Any + +from .schema import AssistantToolCall, CompletionModelFunction + + +class InvalidFunctionCallError(Exception): + def __init__(self, name: str, arguments: dict[str, Any], message: str): + self.message = message + self.name = name + self.arguments = arguments + super().__init__(message) + + def __str__(self) -> str: + return f"Invalid function call for {self.name}: {self.message}" + + +def validate_tool_calls( + tool_calls: list[AssistantToolCall], functions: list[CompletionModelFunction] +) -> list[InvalidFunctionCallError]: + """ + Validates a list of tool calls against a list of functions. + + 1. Tries to find a function matching each tool call + 2. If a matching function is found, validates the tool call's arguments, + reporting any resulting errors + 2. If no matching function is found, an error "Unknown function X" is reported + 3. A list of all errors encountered during validation is returned + + Params: + tool_calls: A list of tool calls to validate. + functions: A list of functions to validate against. + + Returns: + list[InvalidFunctionCallError]: All errors encountered during validation. + """ + errors: list[InvalidFunctionCallError] = [] + for tool_call in tool_calls: + function_call = tool_call.function + + if function := next( + (f for f in functions if f.name == function_call.name), + None, + ): + is_valid, validation_errors = function.validate_call(function_call) + if not is_valid: + fmt_errors = [ + f"{'.'.join(str(p) for p in f.path)}: {f.message}" + if f.path + else f.message + for f in validation_errors + ] + errors.append( + InvalidFunctionCallError( + name=function_call.name, + arguments=function_call.arguments, + message=( + "The set of arguments supplied is invalid:\n" + + "\n".join(fmt_errors) + ), + ) + ) + else: + errors.append( + InvalidFunctionCallError( + name=function_call.name, + arguments=function_call.arguments, + message=f"Unknown function {function_call.name}", + ) + ) + + return errors diff --git a/autogpts/autogpt/autogpt/core/runner/client_lib/logging/helpers.py b/autogpts/autogpt/autogpt/core/runner/client_lib/logging/helpers.py index d341f16ca..53d0964d4 100644 --- a/autogpts/autogpt/autogpt/core/runner/client_lib/logging/helpers.py +++ b/autogpts/autogpt/autogpt/core/runner/client_lib/logging/helpers.py @@ -3,21 +3,25 @@ from typing import TYPE_CHECKING if TYPE_CHECKING: from autogpt.core.prompting import ChatPrompt + from autogpt.core.resource.model_providers import ChatMessage SEPARATOR_LENGTH = 42 -def dump_prompt(prompt: "ChatPrompt") -> str: +def dump_prompt(prompt: "ChatPrompt | list[ChatMessage]") -> str: def separator(text: str): half_sep_len = (SEPARATOR_LENGTH - 2 - len(text)) / 2 return f"{floor(half_sep_len)*'-'} {text.upper()} {ceil(half_sep_len)*'-'}" + if not isinstance(prompt, list): + prompt = prompt.messages + formatted_messages = "\n".join( - [f"{separator(m.role)}\n{m.content}" for m in prompt.messages] + [f"{separator(m.role)}\n{m.content}" for m in prompt] ) return f""" ============== {prompt.__class__.__name__} ============== -Length: {len(prompt.messages)} messages +Length: {len(prompt)} messages {formatted_messages} ========================================== """ diff --git a/autogpts/autogpt/autogpt/llm/providers/openai.py b/autogpts/autogpt/autogpt/llm/providers/openai.py index 18a9d2b07..e6423827c 100644 --- a/autogpts/autogpt/autogpt/llm/providers/openai.py +++ b/autogpts/autogpt/autogpt/llm/providers/openai.py @@ -14,7 +14,7 @@ logger = logging.getLogger(__name__) T = TypeVar("T", bound=Callable) -def get_openai_command_specs( +def function_specs_from_commands( commands: Iterable[Command], ) -> list[CompletionModelFunction]: """Get OpenAI-consumable function specs for the agent's available commands. diff --git a/autogpts/autogpt/autogpt/models/command.py b/autogpts/autogpt/autogpt/models/command.py index c629e5126..e88db4a70 100644 --- a/autogpts/autogpt/autogpt/models/command.py +++ b/autogpts/autogpt/autogpt/models/command.py @@ -1,9 +1,7 @@ from __future__ import annotations import inspect -from typing import Any, Callable - -from autogpt.core.utils.json_schema import JSONSchema +from typing import Any, Callable, Generic, ParamSpec, TypeVar from .command_parameter import CommandParameter from .context_item import ContextItem @@ -11,8 +9,11 @@ from .context_item import ContextItem CommandReturnValue = Any CommandOutput = CommandReturnValue | tuple[CommandReturnValue, ContextItem] +P = ParamSpec("P") +CO = TypeVar("CO", bound=CommandOutput) + -class Command: +class Command(Generic[P, CO]): """A class representing a command. Attributes: @@ -25,7 +26,7 @@ class Command: self, names: list[str], description: str, - method: Callable[..., CommandOutput], + method: Callable[P, CO], parameters: list[CommandParameter], ): # Check if all parameters are provided @@ -42,20 +43,6 @@ class Command: def is_async(self) -> bool: return inspect.iscoroutinefunction(self.method) - def validate_args(self, args: dict[str, Any]): - """ - Validates the given arguments against the command's parameter specifications - - Returns: - bool: Whether the given set of arguments is valid for this command - list[ValidationError]: Issues with the set of arguments (if any) - """ - params_schema = JSONSchema( - type=JSONSchema.Type.OBJECT, - properties={p.name: p.spec for p in self.parameters}, - ) - return params_schema.validate_object(args) - def _parameters_match( self, func: Callable, parameters: list[CommandParameter] ) -> bool: @@ -71,7 +58,7 @@ class Command: # Check if sorted lists of names/keys are equal return sorted(func_param_names) == sorted(names) - def __call__(self, *args, **kwargs) -> Any: + def __call__(self, *args: P.args, **kwargs: P.kwargs) -> CO: return self.method(*args, **kwargs) def __str__(self) -> str: diff --git a/autogpts/autogpt/poetry.lock b/autogpts/autogpt/poetry.lock index 77b64e79c..251cbb3bd 100644 --- a/autogpts/autogpt/poetry.lock +++ b/autogpts/autogpt/poetry.lock @@ -168,6 +168,30 @@ files = [ frozenlist = ">=1.1.0" [[package]] +name = "anthropic" +version = "0.25.1" +description = "The official Python library for the anthropic API" +optional = false +python-versions = ">=3.7" +files = [ + {file = "anthropic-0.25.1-py3-none-any.whl", hash = "sha256:95d0cedc2a4b5beae3a78f9030aea4001caea5f46c6d263cce377c891c594e71"}, + {file = "anthropic-0.25.1.tar.gz", hash = "sha256:0c01b30b77d041a8d07c532737bae69da58086031217150008e4541f52a64bd9"}, +] + +[package.dependencies] +anyio = ">=3.5.0,<5" +distro = ">=1.7.0,<2" +httpx = ">=0.23.0,<1" +pydantic = ">=1.9.0,<3" +sniffio = "*" +tokenizers = ">=0.13.0" +typing-extensions = ">=4.7,<5" + +[package.extras] +bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"] +vertex = ["google-auth (>=2,<3)"] + +[[package]] name = "anyio" version = "4.2.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" @@ -7234,4 +7258,4 @@ benchmark = ["agbenchmark"] [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "e6eab5c079d53f075ce701e86a2007e7ebeb635ac067d25f555bfea363bcc630" +content-hash = "ad1e3c4706465733d04ddab975af630975bd528efce152c1da01eded53069eca" diff --git a/autogpts/autogpt/pyproject.toml b/autogpts/autogpt/pyproject.toml index e1b0c32f6..99f58774b 100644 --- a/autogpts/autogpt/pyproject.toml +++ b/autogpts/autogpt/pyproject.toml @@ -22,6 +22,7 @@ serve = "autogpt.app.cli:serve" [tool.poetry.dependencies] python = "^3.10" +anthropic = "^0.25.1" # autogpt-forge = { path = "../forge" } autogpt-forge = {git = "https://github.com/Significant-Gravitas/AutoGPT.git", subdirectory = "autogpts/forge"} beautifulsoup4 = "^4.12.2" diff --git a/autogpts/autogpt/scripts/git_log_to_release_notes.py b/autogpts/autogpt/scripts/git_log_to_release_notes.py new file mode 100755 index 000000000..8b03dff68 --- /dev/null +++ b/autogpts/autogpt/scripts/git_log_to_release_notes.py @@ -0,0 +1,141 @@ +#!/usr/bin/env python3 + +import logging +from pathlib import Path +from typing import Optional + +import click +from git import Repo, TagReference + +from autogpt.core.resource.model_providers import ChatMessage, MultiProvider +from autogpt.core.resource.model_providers.anthropic import AnthropicModelName +from autogpt.core.runner.client_lib.utils import coroutine + + +@click.command() +@click.option( + "--repo-path", + type=click.Path(file_okay=False, exists=True), + help="Path to the git repository", +) +@coroutine +async def generate_release_notes(repo_path: Optional[Path] = None): + logger = logging.getLogger(generate_release_notes.name) + + repo = Repo(repo_path, search_parent_directories=True) + tags = list(repo.tags) + if not tags: + click.echo("No tags found in the repository.") + return + + click.echo("Available tags:") + for index, tag in enumerate(tags): + click.echo(f"{index + 1}: {tag.name}") + + last_release_index = ( + click.prompt("Enter the number for the last release tag", type=int) - 1 + ) + if last_release_index >= len(tags) or last_release_index < 0: + click.echo("Invalid tag number entered.") + return + last_release_tag: TagReference = tags[last_release_index] + + new_release_ref = click.prompt( + "Enter the name of the release branch or git ref", + default=repo.active_branch.name, + ) + try: + new_release_ref = repo.heads[new_release_ref].name + except IndexError: + try: + new_release_ref = repo.tags[new_release_ref].name + except IndexError: + new_release_ref = repo.commit(new_release_ref).hexsha + logger.debug(f"Selected release ref: {new_release_ref}") + + git_log = repo.git.log( + f"{last_release_tag.name}...{new_release_ref}", + "autogpts/autogpt/", + no_merges=True, + follow=True, + ) + logger.debug(f"-------------- GIT LOG --------------\n\n{git_log}\n") + + model_provider = MultiProvider() + chat_messages = [ + ChatMessage.system(SYSTEM_PROMPT), + ChatMessage.user(content=git_log), + ] + click.echo("Writing release notes ...") + completion = await model_provider.create_chat_completion( + model_prompt=chat_messages, + model_name=AnthropicModelName.CLAUDE3_OPUS_v1, + # model_name=OpenAIModelName.GPT4_v4, + ) + + click.echo("-------------- LLM RESPONSE --------------\n") + click.echo(completion.response.content) + + +EXAMPLE_RELEASE_NOTES = """ +First some important notes w.r.t. using the application: +* `run.sh` has been renamed to `autogpt.sh` +* The project has been restructured. The AutoGPT Agent is now located in `autogpts/autogpt`. +* The application no longer uses a single workspace for all tasks. Instead, every task that you run the agent on creates a new workspace folder. See the [usage guide](https://docs.agpt.co/autogpt/usage/#workspace) for more information. + +## New features ✨ + +* **Agent Protocol 🔌** + Our agent now works with the [Agent Protocol](/#-agent-protocol), a REST API that allows creating tasks and executing the agent's step-by-step process. This allows integration with other applications, and we also use it to connect to the agent through the UI. +* **UI 💻** + With the aforementioned Agent Protocol integration comes the benefit of using our own open-source Agent UI. Easily create, use, and chat with multiple agents from one interface. + When starting the application through the project's new [CLI](/#-cli), it runs with the new frontend by default, with benchmarking capabilities. Running `autogpt.sh serve` in the subproject folder (`autogpts/autogpt`) will also serve the new frontend, but without benchmarking functionality. + Running the application the "old-fashioned" way, with the terminal interface (let's call it TTY mode), is still possible with `autogpt.sh run`. +* **Resuming agents 🔄️** + In TTY mode, the application will now save the agent's state when quitting, and allows resuming where you left off at a later time! +* **GCS and S3 workspace backends 📦** + To further support running the application as part of a larger system, Google Cloud Storage and S3 workspace backends were added. Configuration options for this can be found in [`.env.template`](/autogpts/autogpt/.env.template). +* **Documentation Rewrite 📖** + The [documentation](https://docs.agpt.co) has been restructured and mostly rewritten to clarify and simplify the instructions, and also to accommodate the other subprojects that are now in the repo. +* **New Project CLI 🔧** + The project has a new CLI to provide easier usage of all of the components that are now in the repo: different agents, frontend and benchmark. More info can be found [here](/#-cli). +* **Docker dev build 🐳** + In addition to the regular Docker release [images](https://hub.docker.com/r/significantgravitas/auto-gpt/tags) (`latest`, `v0.5.0` in this case), we now also publish a `latest-dev` image that always contains the latest working build from `master`. This allows you to try out the latest bleeding edge version, but be aware that these builds may contain bugs! + +## Architecture changes & improvements 👷🏼 +* **PromptStrategy** + To make it easier to harness the power of LLMs and use them to fulfil tasks within the application, we adopted the `PromptStrategy` class from `autogpt.core` (AKA re-arch) to encapsulate prompt generation and response parsing throughout the application. +* **Config modularization** + To reduce the complexity of the application's config structure, parts of the monolithic `Config` have been moved into smaller, tightly scoped config objects. Also, the logic for building the configuration from environment variables was decentralized to make it all a lot more maintainable. + This is mostly made possible by the `autogpt.core.configuration` module, which was also expanded with a few new features for it. Most notably, the new `from_env` attribute on the `UserConfigurable` field decorator and corresponding logic in `SystemConfiguration.from_env()` and related functions. +* **Monorepo** + As mentioned, the repo has been restructured to accommodate the AutoGPT Agent, Forge, AGBenchmark and the new Frontend. + * AutoGPT Agent has been moved to `autogpts/autogpt` + * Forge now lives in `autogpts/forge`, and the project's new CLI makes it easy to create new Forge-based agents. + * AGBenchmark -> `benchmark` + * Frontend -> `frontend` + + See also the [README](/#readme). +""".lstrip() # noqa + + +SYSTEM_PROMPT = f""" +Please generate release notes based on the user's git log and the example release notes. + +Here is an example of what we like our release notes to look and read like: +--------------------------------------------------------------------------- +{EXAMPLE_RELEASE_NOTES} +--------------------------------------------------------------------------- +NOTE: These example release notes are not related to the git log that you should write release notes for! +Do not mention the changes in the example when writing your release notes! +""".lstrip() # noqa + +if __name__ == "__main__": + import dotenv + + from autogpt.logs.config import configure_logging + + configure_logging(debug=True) + + dotenv.load_dotenv() + generate_release_notes() diff --git a/autogpts/autogpt/tests/conftest.py b/autogpts/autogpt/tests/conftest.py index 29479f6f0..64376446d 100644 --- a/autogpts/autogpt/tests/conftest.py +++ b/autogpts/autogpt/tests/conftest.py @@ -8,9 +8,9 @@ import pytest from pytest_mock import MockerFixture from autogpt.agents.agent import Agent, AgentConfiguration, AgentSettings -from autogpt.app.main import _configure_openai_provider +from autogpt.app.main import _configure_llm_provider from autogpt.config import AIProfile, Config, ConfigBuilder -from autogpt.core.resource.model_providers import ChatModelProvider, OpenAIProvider +from autogpt.core.resource.model_providers import ChatModelProvider from autogpt.file_storage.local import ( FileStorage, FileStorageConfiguration, @@ -73,8 +73,8 @@ def setup_logger(config: Config): @pytest.fixture -def llm_provider(config: Config) -> OpenAIProvider: - return _configure_openai_provider(config) +def llm_provider(config: Config) -> ChatModelProvider: + return _configure_llm_provider(config) @pytest.fixture diff --git a/autogpts/autogpt/tests/unit/test_config.py b/autogpts/autogpt/tests/unit/test_config.py index f52efcd8c..d6120dec6 100644 --- a/autogpts/autogpt/tests/unit/test_config.py +++ b/autogpts/autogpt/tests/unit/test_config.py @@ -14,7 +14,6 @@ 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.core.resource.model_providers.openai import OpenAIModelName from autogpt.core.resource.model_providers.schema import ( ChatModelInfo, ModelProviderName, @@ -39,8 +38,8 @@ async def test_fallback_to_gpt3_if_gpt4_not_available( """ Test if models update to gpt-3.5-turbo if gpt-4 is not available. """ - config.fast_llm = OpenAIModelName.GPT4_TURBO - config.smart_llm = OpenAIModelName.GPT4_TURBO + config.fast_llm = GPT_4_MODEL + config.smart_llm = GPT_4_MODEL mock_list_models.return_value = asyncio.Future() mock_list_models.return_value.set_result( @@ -56,8 +55,8 @@ async def test_fallback_to_gpt3_if_gpt4_not_available( gpt4only=False, ) - assert config.fast_llm == "gpt-3.5-turbo" - assert config.smart_llm == "gpt-3.5-turbo" + assert config.fast_llm == GPT_3_MODEL + assert config.smart_llm == GPT_3_MODEL def test_missing_azure_config(config: Config) -> None: @@ -148,8 +147,7 @@ def test_azure_config(config_with_azure: Config) -> None: @pytest.mark.asyncio async def test_create_config_gpt4only(config: Config) -> None: with mock.patch( - "autogpt.core.resource.model_providers.openai." - "OpenAIProvider.get_available_models" + "autogpt.core.resource.model_providers.multi.MultiProvider.get_available_models" ) as mock_get_models: mock_get_models.return_value = [ ChatModelInfo( @@ -169,8 +167,7 @@ async def test_create_config_gpt4only(config: Config) -> None: @pytest.mark.asyncio async def test_create_config_gpt3only(config: Config) -> None: with mock.patch( - "autogpt.core.resource.model_providers.openai." - "OpenAIProvider.get_available_models" + "autogpt.core.resource.model_providers.multi.MultiProvider.get_available_models" ) as mock_get_models: mock_get_models.return_value = [ ChatModelInfo( diff --git a/autogpts/evo.ninja/setup b/autogpts/evo.ninja/setup deleted file mode 100755 index 3d1c2f708..000000000 --- a/autogpts/evo.ninja/setup +++ /dev/null @@ -1,17 +0,0 @@ -#!/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/tutorials/001_getting_started.md b/autogpts/forge/tutorials/001_getting_started.md index a971451e7..4d9f86e55 100644 --- a/autogpts/forge/tutorials/001_getting_started.md +++ b/autogpts/forge/tutorials/001_getting_started.md @@ -84,7 +84,6 @@ This command forcefully stops the agent. You can also restart it using the start ## To Recap - We've forked the AutoGPT repo and cloned it locally on your machine. - we connected the library with our personal github access token as part of the setup. -- We've created and named our first agent, and entered it into the arena! - We've run the agent and it's tasking server successfully without an error. - We've logged into the server site at localhost:8000 using our github account. @@ -63,139 +63,6 @@ d88P 888 "Y88888 "Y888 "Y88P" "Y8888P88 888 888 ) install_error = True - try: - # Check if git user is configured - user_name = ( - subprocess.check_output(["git", "config", "user.name"]) - .decode("utf-8") - .strip() - ) - user_email = ( - subprocess.check_output(["git", "config", "user.email"]) - .decode("utf-8") - .strip() - ) - - if user_name and user_email: - click.echo( - click.style( - f"✅ Git is configured with name '{user_name}' and email '{user_email}'", - fg="green", - ) - ) - else: - raise subprocess.CalledProcessError( - returncode=1, cmd="git config user.name or user.email" - ) - - except subprocess.CalledProcessError: - # If the GitHub account is not configured, print instructions on how to set it up - click.echo(click.style("⚠️ Git user is not configured.", fg="red")) - click.echo( - click.style( - "To configure Git with your user info, use the following commands:", - fg="red", - ) - ) - click.echo( - click.style(' git config --global user.name "Your (user)name"', fg="red") - ) - click.echo( - click.style(' 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: - github_access_token = file.read().strip() - if github_access_token: - click.echo( - click.style( - "✅ GitHub access token loaded successfully.", fg="green" - ) - ) - # Check if the token has the required permissions - import requests - - headers = {"Authorization": f"token {github_access_token}"} - response = requests.get("https://api.github.com/user", headers=headers) - if response.status_code == 200: - scopes = response.headers.get("X-OAuth-Scopes") - if "public_repo" in scopes or "repo" in scopes: - click.echo( - click.style( - "✅ GitHub access token has the required permissions.", - fg="green", - ) - ) - else: - install_error = True - click.echo( - click.style( - "❌ GitHub access token does not have the required permissions. Please ensure it has 'public_repo' or 'repo' scope.", - fg="red", - ) - ) - else: - install_error = True - click.echo( - click.style( - "❌ Failed to validate GitHub access token. Please ensure it is correct.", - fg="red", - ) - ) - else: - install_error = True - click.echo( - click.style( - "❌ GitHub access token file is empty. Please follow the instructions below to set up your GitHub access token.", - fg="red", - ) - ) - print_access_token_instructions = True - else: - # Create the .github_access_token file if it doesn't exist - with open(".github_access_token", "w") as file: - file.write("") - install_error = True - print_access_token_instructions = True - - if print_access_token_instructions: - # Instructions to set up GitHub access token - click.echo( - click.style( - "💡 To configure your GitHub access token, follow these steps:", fg="red" - ) - ) - click.echo( - click.style("\t1. Ensure you are logged into your GitHub account", fg="red") - ) - click.echo( - click.style("\t2. Navigate to https://github.com/settings/tokens", fg="red") - ) - click.echo(click.style("\t3. Click on 'Generate new token'.", fg="red")) - click.echo( - click.style("\t4. Click on 'Generate new token (classic)'.", fg="red") - ) - click.echo( - click.style( - "\t5. Fill out the form to generate a new token. Ensure you select the 'repo' scope.", - fg="red", - ) - ) - click.echo( - click.style( - "\t6. Open the '.github_access_token' file in the same directory as this script and paste the token into this file.", - fg="red", - ) - ) - click.echo( - click.style("\t7. Save the file and run the setup command again.", fg="red") - ) - if install_error: click.echo( click.style( @@ -605,306 +472,6 @@ def benchmark_tests_details(test_name): continue -@cli.group() -def arena(): - """Commands to enter the arena""" - pass - - -@arena.command() -@click.argument("agent_name") -@click.option("--branch", default="master", help="Branch to use instead of master") -def enter(agent_name, branch): - import json - import os - import subprocess - from datetime import datetime - - from github import Github - - # Check if the agent_name directory exists in the autogpts directory - agent_dir = f"./autogpts/{agent_name}" - if not os.path.exists(agent_dir): - click.echo( - click.style( - f"❌ The directory for agent '{agent_name}' does not exist in the autogpts directory.", - fg="red", - ) - ) - click.echo( - click.style( - f"🚀 Run './run agent create {agent_name}' to create the agent.", - fg="yellow", - ) - ) - - return - else: - # Check if the agent has already entered the arena - try: - subprocess.check_output( - [ - "git", - "rev-parse", - "--verify", - "--quiet", - f"arena_submission_{agent_name}", - ] - ) - except subprocess.CalledProcessError: - pass - else: - click.echo( - click.style( - f"⚠️ The agent '{agent_name}' has already entered the arena. To update your submission, follow these steps:", - fg="yellow", - ) - ) - click.echo( - click.style( - f"1. Get the git hash of your submission by running 'git rev-parse HEAD' on the branch you want to submit to the arena.", - fg="yellow", - ) - ) - click.echo( - click.style( - f"2. Change the branch to 'arena_submission_{agent_name}' by running 'git checkout arena_submission_{agent_name}'.", - fg="yellow", - ) - ) - click.echo( - click.style( - f"3. Modify the 'arena/{agent_name}.json' to include the new commit hash of your submission (the hash you got from step 1) and an up-to-date timestamp by running './run arena update {agent_name} hash --branch x'.", - fg="yellow", - ) - ) - click.echo( - click.style( - f"Note: The '--branch' option is only needed if you want to change the branch that will be used.", - fg="yellow", - ) - ) - return - - # Check if there are staged changes - staged_changes = [ - line - for line in subprocess.check_output(["git", "status", "--porcelain"]) - .decode("utf-8") - .split("\n") - if line and line[0] in ("A", "M", "D", "R", "C") - ] - if staged_changes: - click.echo( - click.style( - f"❌ There are staged changes. Please commit or stash them and run the command again.", - fg="red", - ) - ) - return - - try: - # Load GitHub access token from file - with open(".github_access_token", "r") as file: - github_access_token = file.read().strip() - - # Get GitHub repository URL - github_repo_url = ( - subprocess.check_output(["git", "config", "--get", "remote.origin.url"]) - .decode("utf-8") - .strip() - ) - - if github_repo_url.startswith("git@"): - github_repo_url = ( - github_repo_url.replace(":", "/") - .replace("git@", "https://") - .replace(".git", "") - ) - - # If --branch is passed, use it instead of master - if branch: - branch_to_use = branch - else: - branch_to_use = "master" - - # Get the commit hash of HEAD of the branch_to_use - commit_hash_to_benchmark = ( - subprocess.check_output(["git", "rev-parse", branch_to_use]) - .decode("utf-8") - .strip() - ) - - arena_submission_branch = f"arena_submission_{agent_name}" - # Create a new branch called arena_submission_{agent_name} - subprocess.check_call(["git", "checkout", "-b", arena_submission_branch]) - # Create a dictionary with the necessary fields - data = { - "github_repo_url": github_repo_url, - "timestamp": datetime.utcnow().isoformat(), - "commit_hash_to_benchmark": commit_hash_to_benchmark, - } - - # If --branch was passed, add branch_to_benchmark to the JSON file - if branch: - data["branch_to_benchmark"] = branch - - # Create agent directory if it does not exist - subprocess.check_call(["mkdir", "-p", "arena"]) - - # Create a JSON file with the data - with open(f"arena/{agent_name}.json", "w") as json_file: - json.dump(data, json_file, indent=4) - - # Create a commit with the specified message - subprocess.check_call(["git", "add", f"arena/{agent_name}.json"]) - subprocess.check_call( - ["git", "commit", "-m", f"{agent_name} entering the arena"] - ) - - # Push the commit - subprocess.check_call(["git", "push", "origin", arena_submission_branch]) - - # Create a PR into the parent repository - g = Github(github_access_token) - repo_name = github_repo_url.replace("https://github.com/", "") - repo = g.get_repo(repo_name) - parent_repo = repo.parent - if parent_repo: - pr_message = f""" -### 🌟 Welcome to the AutoGPT Arena Hacks Hackathon! 🌟 - -Hey there amazing builders! We're thrilled to have you join this exciting journey. Before you dive deep into building, we'd love to know more about you and the awesome project you are envisioning. Fill out the template below to kickstart your hackathon journey. May the best agent win! 🏆 - -#### 🤖 Team Introduction - -- **Agent Name:** {agent_name} -- **Team Members:** (Who are the amazing minds behind this team? Do list everyone along with their roles!) -- **Repository Link:** [{github_repo_url.replace('https://github.com/', '')}]({github_repo_url}) - -#### 🌟 Project Vision - -- **Starting Point:** (Are you building from scratch or starting with an existing agent? Do tell!) -- **Preliminary Ideas:** (Share your initial ideas and what kind of project you are aiming to build. We are all ears!) - -#### 🏆 Prize Category - -- **Target Prize:** (Which prize caught your eye? Which one are you aiming for?) -- **Why this Prize:** (We'd love to know why this prize feels like the right fit for your team!) - -#### 🎬 Introduction Video - -- **Video Link:** (If you'd like, share a short video where you introduce your team and talk about your project. We'd love to see your enthusiastic faces!) - -#### 📝 Notes and Compliance - -- **Additional Notes:** (Any other things you want to share? We're here to listen!) -- **Compliance with Hackathon Rules:** (Just a gentle reminder to stick to the rules outlined for the hackathon) - -#### ✅ Checklist - -- [ ] We have read and are aligned with the [Hackathon Rules](https://lablab.ai/event/autogpt-arena-hacks). -- [ ] We confirm that our project will be open-source and adhere to the MIT License. -- [ ] Our lablab.ai registration email matches our OpenAI account to claim the bonus credits (if applicable). -""" - head = f"{repo.owner.login}:{arena_submission_branch}" - pr = parent_repo.create_pull( - title=f"{agent_name} entering the arena", - body=pr_message, - head=head, - base=branch_to_use, - ) - click.echo( - click.style( - f"🚀 {agent_name} has entered the arena! Please edit your PR description at the following URL: {pr.html_url}", - fg="green", - ) - ) - else: - click.echo( - click.style( - "❌ This repository does not have a parent repository to sync with.", - fg="red", - ) - ) - return - - # Switch back to the master branch - subprocess.check_call(["git", "checkout", branch_to_use]) - - except Exception as e: - click.echo(click.style(f"❌ An error occurred: {e}", fg="red")) - # Switch back to the master branch - subprocess.check_call(["git", "checkout", branch_to_use]) - - -@arena.command() -@click.argument("agent_name") -@click.argument("hash") -@click.option("--branch", default=None, help="Branch to use instead of current branch") -def update(agent_name, hash, branch): - import json - import os - import subprocess - from datetime import datetime - - # Check if the agent_name.json file exists in the arena directory - agent_json_file = f"./arena/{agent_name}.json" - # Check if they are on the correct branch - current_branch = ( - subprocess.check_output(["git", "rev-parse", "--abbrev-ref", "HEAD"]) - .decode("utf-8") - .strip() - ) - correct_branch = f"arena_submission_{agent_name}" - if current_branch != correct_branch: - click.echo( - click.style( - f"❌ You are not on the correct branch. Please switch to the '{correct_branch}' branch.", - fg="red", - ) - ) - return - - if not os.path.exists(agent_json_file): - click.echo( - click.style( - f"❌ The file for agent '{agent_name}' does not exist in the arena directory.", - fg="red", - ) - ) - click.echo( - click.style( - f"⚠️ You need to enter the arena first. Run './run arena enter {agent_name}'", - fg="yellow", - ) - ) - return - else: - # Load the existing data - with open(agent_json_file, "r") as json_file: - data = json.load(json_file) - - # Update the commit hash and timestamp - data["commit_hash_to_benchmark"] = hash - data["timestamp"] = datetime.utcnow().isoformat() - - # If --branch was passed, update the branch_to_benchmark in the JSON file - if branch: - data["branch_to_benchmark"] = branch - - # Write the updated data back to the JSON file - with open(agent_json_file, "w") as json_file: - json.dump(data, json_file, indent=4) - - click.echo( - click.style( - f"🚀 The file for agent '{agent_name}' has been updated in the arena directory.", - fg="green", - ) - ) - - def wait_until_conn_ready(port: int = 8000, timeout: int = 30): """ Polls localhost:{port} until it is available for connections diff --git a/docs/content/AutoGPT/components/agents.md b/docs/content/AutoGPT/components/agents.md index 4ab573243..7d3808a14 100644..120000 --- a/docs/content/AutoGPT/components/agents.md +++ b/docs/content/AutoGPT/components/agents.md @@ -1,37 +1 @@ -# 🤖 Agents - -Agent is composed of [🧩 Components](./components.md) and responsible for executing pipelines and some additional logic. The base class for all agents is `BaseAgent`, it has the necessary logic to collect components and execute protocols. - -## Important methods - -`BaseAgent` provides two abstract methods needed for any agent to work properly: -1. `propose_action`: This method is responsible for proposing an action based on the current state of the agent, it returns `ThoughtProcessOutput`. -2. `execute`: This method is responsible for executing the proposed action, returns `ActionResult`. - -## AutoGPT Agent - -`Agent` is the main agent provided by AutoGPT. It's a subclass of `BaseAgent`. It has all the [Built-in Components](./built-in-components.md). `Agent` implements the essential abstract methods from `BaseAgent`: `propose_action` and `execute`. - -## Building your own Agent - -The easiest way to build your own agent is to extend the `Agent` class and add additional components. By doing this you can reuse the existing components and the default logic for executing [⚙️ Protocols](./protocols.md). - -```py -class MyComponent(AgentComponent): - pass - -class MyAgent(Agent): - def __init__( - self, - settings: AgentSettings, - llm_provider: ChatModelProvider, - file_storage: FileStorage, - legacy_config: Config, - ): - # Call the parent constructor to bring in the default components - super().__init__(settings, llm_provider, file_storage, legacy_config) - # Add your custom component - self.my_component = MyComponent() -``` - -For more customization, you can override the `propose_action` and `execute` or even subclass `BaseAgent` directly. This way you can have full control over the agent's components and behavior. Have a look at the [implementation of Agent](https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/autogpt/autogpt/agents/agent.py) for more details. +../../../../autogpts/autogpt/autogpt/agents/README.md
\ No newline at end of file diff --git a/docs/content/AutoGPT/components/components.md b/docs/content/AutoGPT/components/components.md index 5575f0bcb..8f836ac3d 100644..120000 --- a/docs/content/AutoGPT/components/components.md +++ b/docs/content/AutoGPT/components/components.md @@ -1,128 +1 @@ -# 🧩 Components - -Components are the building blocks of [🤖 Agents](./agents.md). They are classes inheriting `AgentComponent` or implementing one or more [⚙️ Protocols](./protocols.md) that give agent additional abilities or processing. - -Components can be used to implement various functionalities like providing messages to the prompt, executing code, or interacting with external services. -They can be enabled or disabled, ordered, and can rely on each other. - -Components assigned in the agent's `__init__` via `self` are automatically detected upon the agent's instantiation. -For example inside `__init__`: `self.my_component = MyComponent()`. -You can use any valid Python variable name, what matters for the component to be detected is its type (`AgentComponent` or any protocol inheriting from it). - -Visit [Built-in Components](./built-in-components.md) to see what components are available out of the box. - -```py -from autogpt.agents import Agent -from autogpt.agents.components import AgentComponent - -class HelloComponent(AgentComponent): - pass - -class SomeComponent(AgentComponent): - def __init__(self, hello_component: HelloComponent): - self.hello_component = hello_component - -class MyAgent(Agent): - def __init__(self): - # These components will be automatically discovered and used - self.hello_component = HelloComponent() - # We pass HelloComponent to SomeComponent - self.some_component = SomeComponent(self.hello_component) -``` - -## Ordering components - -The execution order of components is important because the latter ones may depend on the results of the former ones. - -### Implicit order - -Components can be ordered implicitly by the agent; each component can set `run_after` list to specify which components should run before it. This is useful when components rely on each other or need to be executed in a specific order. Otherwise, the order of components is alphabetical. - -```py -# This component will run after HelloComponent -class CalculatorComponent(AgentComponent): - run_after = [HelloComponent] -``` - -### Explicit order - -Sometimes it may be easier to order components explicitly by setting `self.components` list in the agent's `__init__` method. This way you can also ensure there's no circular dependencies and `run_after` is ignored. - -!!! warning - Be sure to include all components - by setting `self.components` list, you're overriding the default behavior of discovering components automatically. Since it's usually not intended agent will inform you in the terminal if some components were skipped. - -```py -class MyAgent(Agent): - def __init__(self): - self.hello_component = HelloComponent() - self.calculator_component = CalculatorComponent(self.hello_component) - # Explicitly set components list - self.components = [self.hello_component, self.calculator_component] -``` - -## Disabling components - -You can control which components are enabled by setting their `_enabled` attribute. -Either provide a `bool` value or a `Callable[[], bool]`, will be checked each time -the component is about to be executed. This way you can dynamically enable or disable -components based on some conditions. -You can also provide a reason for disabling the component by setting `_disabled_reason`. -The reason will be visible in the debug information. - -```py -class DisabledComponent(MessageProvider): - def __init__(self): - # Disable this component - self._enabled = False - self._disabled_reason = "This component is disabled because of reasons." - - # Or disable based on some condition, either statically...: - self._enabled = self.some_property is not None - # ... or dynamically: - self._enabled = lambda: self.some_property is not None - - # This method will never be called - def get_messages(self) -> Iterator[ChatMessage]: - yield ChatMessage.user("This message won't be seen!") - - def some_condition(self) -> bool: - return False -``` - -If you don't want the component at all, you can just remove it from the agent's `__init__` method. If you want to remove components you inherit from the parent class you can set the relevant attribute to `None`: - -!!! Warning - Be careful when removing components that are required by other components. This may lead to errors and unexpected behavior. - -```py -class MyAgent(Agent): - def __init__(self): - super().__init__(...) - # Disable WatchdogComponent that is in the parent class - self.watchdog = None - -``` - -## Exceptions - -Custom errors are provided which can be used to control the execution flow in case something went wrong. All those errors can be raised in protocol methods and will be caught by the agent. -By default agent will retry three times and then re-raise an exception if it's still not resolved. All passed arguments are automatically handled and the values are reverted when needed. -All errors accept an optional `str` message. There are following errors ordered by increasing broadness: - -1. `ComponentEndpointError`: A single endpoint method failed to execute. Agent will retry the execution of this endpoint on the component. -2. `EndpointPipelineError`: A pipeline failed to execute. Agent will retry the execution of the endpoint for all components. -3. `ComponentSystemError`: Multiple pipelines failed. - -**Example** - -```py -from autogpt.agents.components import ComponentEndpointError -from autogpt.agents.protocols import MessageProvider - -# Example of raising an error -class MyComponent(MessageProvider): - def get_messages(self) -> Iterator[ChatMessage]: - # This will cause the component to always fail - # and retry 3 times before re-raising the exception - raise ComponentEndpointError("Endpoint error!") -``` +../../../../autogpts/autogpt/autogpt/commands/README.md
\ No newline at end of file diff --git a/docs/content/AutoGPT/configuration/options.md b/docs/content/AutoGPT/configuration/options.md index 9003c7378..17602102b 100644 --- a/docs/content/AutoGPT/configuration/options.md +++ b/docs/content/AutoGPT/configuration/options.md @@ -7,6 +7,7 @@ Configuration is controlled through the `Config` object. You can set configurati - `AI_SETTINGS_FILE`: Location of the AI Settings file relative to the AutoGPT root directory. Default: ai_settings.yaml - `AUDIO_TO_TEXT_PROVIDER`: Audio To Text Provider. Only option currently is `huggingface`. Default: huggingface - `AUTHORISE_COMMAND_KEY`: Key response accepted when authorising commands. Default: y +- `ANTHROPIC_API_KEY`: Set this if you want to use Anthropic models with AutoGPT - `AZURE_CONFIG_FILE`: Location of the Azure Config file relative to the AutoGPT root directory. Default: azure.yaml - `BROWSE_CHUNK_MAX_LENGTH`: When browsing website, define the length of chunks to summarize. Default: 3000 - `BROWSE_SPACY_LANGUAGE_MODEL`: [spaCy language model](https://spacy.io/usage/models) to use when creating chunks. Default: en_core_web_sm diff --git a/docs/content/index.md b/docs/content/index.md index 7cf600880..d027ca4af 100644 --- a/docs/content/index.md +++ b/docs/content/index.md @@ -88,7 +88,6 @@ Options: 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. ``` |