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import logging
import os
from abc import ABC, abstractmethod
from typing import ClassVar, Iterator, Literal
import pytest
import requests
from agent_protocol_client import AgentApi, Step
from pydantic import BaseModel, validator, ValidationError
from agbenchmark.config import AgentBenchmarkConfig
from agbenchmark.utils.data_types import Category, EvalResult
from .base import BaseChallenge, ChallengeInfo
logger = logging.getLogger(__name__)
EvalType = Literal["string_match", "url_match", "program_html"]
WebArenaSite = Literal[
"gitlab", "map", "reddit", "shopping", "shopping_admin", "wikipedia"
]
ReferenceAnswerType = Literal["exact_match", "fuzzy_match", "must_include"]
class WebArenaSiteInfo(BaseModel):
base_url: str
available: bool = True
additional_info: str = ""
unavailable_reason: str = ""
_git_user, _git_password = os.getenv("WEBARENA_GIT_CREDENTIALS", ":").split(":")
site_info_map: dict[WebArenaSite, WebArenaSiteInfo] = {
"gitlab": WebArenaSiteInfo(
base_url="http://git.junglegym.ai",
available=bool(_git_user and _git_password),
additional_info=(
f"To log in to {{url}}, use the username '{_git_user}' "
f"and password '{_git_password}'."
),
unavailable_reason=(
"WEBARENA_GIT_CREDENTIALS not set (correctly): "
f"'{os.getenv('WEBARENA_GIT_CREDENTIALS', '')}', "
"should be USERNAME:PASSWORD."
),
),
"map": WebArenaSiteInfo(
base_url="http://ec2-3-131-244-37.us-east-2.compute.amazonaws.com:3000/"
),
"reddit": WebArenaSiteInfo(base_url="http://forum.junglegym.ai"),
"shopping": WebArenaSiteInfo(base_url="http://shop.junglegym.ai"),
"shopping_admin": WebArenaSiteInfo(
base_url="http://cms.junglegym.ai/admin",
additional_info=(
"To log in to {url}, use the username 'admin' and password 'admin1234'."
),
),
"wikipedia": WebArenaSiteInfo(base_url="http://wiki.junglegym.ai"),
}
def get_site_info(site: WebArenaSite) -> WebArenaSiteInfo:
if site not in site_info_map:
raise ValueError(f"JungleGym site '{site}' unknown, cannot resolve URL")
return site_info_map[site]
def get_site_url(site: WebArenaSite) -> str:
return get_site_info(site).base_url
def resolve_uri(uri: str) -> str:
"""
Resolves URIs with mock hosts, like `__WIKI__/wiki/Octopus`, with the corresponding
JungleGym site mirror host.
"""
segments = uri.split("__")
if len(segments) > 2 and (site := segments[1]).lower() in site_info_map:
return uri.replace(f"__{site}__", get_site_url(site.lower())) # type: ignore
return uri
class Eval(ABC):
@abstractmethod
def evaluate(self, string: str) -> bool:
...
@property
@abstractmethod
def description(self) -> str:
...
class StringEval(BaseModel, Eval):
type: ReferenceAnswerType
class ExactStringMatchEval(StringEval):
type: Literal["exact_match"] = "exact_match"
reference_answer: str
@property
def description(self) -> str:
return f"Answer must be '{self.reference_answer}'"
def evaluate(self, string: str) -> bool:
return string == self.reference_answer
class FuzzyStringMatchEval(StringEval):
type: Literal["fuzzy_match"] = "fuzzy_match"
reference_answer: str
@property
def description(self) -> str:
return f"Answer must contain something like '{self.reference_answer}'"
def evaluate(self, string: str) -> bool:
# TODO: use LLM for matching (or something else that's flexible/robust)
return self.reference_answer.lower() in string.lower()
class MustIncludeStringEval(StringEval):
type: Literal["must_include"] = "must_include"
reference_answer: str
@property
def description(self) -> str:
return f"Answer must include '{self.reference_answer}'"
def evaluate(self, string: str) -> bool:
return self.reference_answer.lower() in string.lower()
class UrlMatchEval(BaseModel, Eval):
url: str
"""Example: `"__WIKI__/wiki/Octopus"`"""
@property
def description(self) -> str:
return f"Agent must navigate to '{self.url}'"
def evaluate(self, url: str) -> bool:
return url == resolve_uri(self.url)
class ProgramHtmlEval(BaseModel):
url: str
locator: str
"""JavaScript code that returns the value to check"""
required_contents: str
@property
def description(self) -> str:
return (
f"On the webpage {self.url}, "
f"`{self.locator}` should contain '{self.required_contents}'"
)
def evaluate(self, selenium_instance) -> bool:
result = selenium_instance.execute_script(
self.locator or "return document.body.innerHTML;"
)
return self.required_contents in result
_Eval = StringEval | UrlMatchEval | ProgramHtmlEval
class WebArenaChallengeSpec(BaseModel):
task_id: int
sites: list[WebArenaSite]
"""The sites needed to complete the task"""
start_url: str
"""The full URL at which to start"""
start_url_junglegym: str
"""The JungleGym site (base URL) at which to start"""
require_login: bool
require_reset: bool
storage_state: str | None
intent: str
intent_template: str
intent_template_id: int
instantiation_dict: dict[str, str | list[str]]
available: bool = True
unavailable_reason: str = ""
class EvalSet(BaseModel):
class StringMatchEvalSet(BaseModel):
exact_match: str | None
fuzzy_match: list[str] | None
must_include: list[str] | None
reference_answers: StringMatchEvalSet | None
"""For string_match eval, a set of criteria to judge the final answer"""
reference_answer_raw_annotation: str | None
string_note: str | None
annotation_note: str | None
reference_url: str | None
"""For url_match eval, the last URL that should be visited"""
url_note: str | None
program_html: list[ProgramHtmlEval]
"""For program_html eval, a list of criteria to judge the site state by"""
eval_types: list[EvalType]
@validator("eval_types")
def check_eval_parameters(cls, v: list[EvalType], values):
if "string_match" in v and not values.get("reference_answers"):
raise ValueError("'string_match' eval_type requires reference_answers")
if "url_match" in v and not values.get("reference_url"):
raise ValueError("'url_match' eval_type requires reference_url")
if "program_html" in v and not values.get("program_html"):
raise ValueError(
"'program_html' eval_type requires at least one program_html eval"
)
return v
@property
def evaluators(self) -> list[_Eval]:
evaluators: list[_Eval] = []
if self.reference_answers:
if self.reference_answers.exact_match:
evaluators.append(
ExactStringMatchEval(
reference_answer=self.reference_answers.exact_match
)
)
if self.reference_answers.fuzzy_match:
evaluators.extend(
FuzzyStringMatchEval(reference_answer=a)
for a in self.reference_answers.fuzzy_match
)
if self.reference_answers.must_include:
evaluators.extend(
MustIncludeStringEval(reference_answer=a)
for a in self.reference_answers.must_include
)
if self.reference_url:
evaluators.append(UrlMatchEval(url=self.reference_url))
evaluators.extend(self.program_html)
return evaluators
eval: EvalSet
"""Evaluation criteria by which to judge the agent's performance"""
@property
def assignment_for_agent(self):
sites = [get_site_info(s) for s in self.sites]
nav_constraint = (
"You are ONLY allowed to access URLs in "
f"{' and '.join(s.base_url for s in sites)}.\n\n"
+ "\n".join(
s.additional_info.format(url=s.base_url)
for s in sites if s.additional_info
)
).strip()
return (
f"First of all, go to {self.start_url}. "
f"{self.intent.rstrip('.')}.\n"
f"{nav_constraint}"
)
class WebArenaChallenge(BaseChallenge):
_spec: ClassVar[WebArenaChallengeSpec]
SOURCE_URI_PREFIX = "__JUNGLEGYM__/webarena/tasks/"
SOURCE_URI_TEMPLATE = f"{SOURCE_URI_PREFIX}{{task_id}}"
@classmethod
def from_source_uri(cls, source_uri: str) -> type["WebArenaChallenge"]:
if not source_uri.startswith(cls.SOURCE_URI_PREFIX):
raise ValueError(f"Invalid source_uri for WebArenaChallenge: {source_uri}")
source_url = source_uri.replace(
cls.SOURCE_URI_PREFIX,
"https://api.junglegym.ai/get_webarena_by_task_id?task_id=",
)
results = requests.get(source_url).json()["data"]
if not results:
raise ValueError(f"Could not fetch challenge {source_uri}")
return cls.from_challenge_spec(WebArenaChallengeSpec.parse_obj(results[0]))
@classmethod
def from_challenge_spec(
cls, spec: WebArenaChallengeSpec
) -> type["WebArenaChallenge"]:
challenge_info = ChallengeInfo(
eval_id=f"junglegym-webarena-{spec.task_id}",
name=f"WebArenaTask_{spec.task_id}",
task=spec.assignment_for_agent,
category=[
Category.GENERALIST,
Category.WEB,
], # TODO: make categories more specific
reference_answer=spec.eval.reference_answer_raw_annotation,
source_uri=cls.SOURCE_URI_TEMPLATE.format(task_id=spec.task_id),
available=spec.available,
unavailable_reason=spec.unavailable_reason,
)
return type(
f"Test{challenge_info.name}",
(WebArenaChallenge,),
{
"info": challenge_info,
"_spec": spec,
},
)
@classmethod
def evaluate_answer(cls, answer: str) -> list[tuple[_Eval, EvalResult]]:
results: list[tuple[_Eval, EvalResult]] = []
for evaluator in cls._spec.eval.evaluators:
if isinstance(evaluator, StringEval): # string_match
results.append(
(
evaluator,
EvalResult(
result=answer,
result_source="step_output",
score=evaluator.evaluate(answer),
passed=evaluator.evaluate(answer),
),
)
)
return results
@classmethod
def evaluate_step_result(
cls, step: Step, *, mock: bool = False
) -> list[tuple[_Eval, EvalResult]]:
if mock:
step.output = cls.info.reference_answer
assert step.output
eval_results = cls.evaluate_answer(step.output)
for eval in cls._spec.eval.evaluators:
if isinstance(eval, UrlMatchEval):
passed = resolve_uri(eval.url) in step.output # HACK: url_match bodge
eval_results.append(
(
eval,
EvalResult(
result=step.output,
result_source="step_output",
score=1.0 if passed else 0.0,
passed=passed,
),
)
)
# TODO: add support for program_html evals
return eval_results
@classmethod
async def evaluate_task_state(
cls, agent: AgentApi, task_id: str
) -> list[EvalResult]:
steps: list[Step] = (await agent.list_agent_task_steps(task_id)).steps
eval_results_per_step = [cls.evaluate_step_result(step) for step in steps]
# Get the column aggregate (highest scored EvalResult for each Eval)
# from the matrix of EvalResults per step.
return [
max(step_results_for_eval, key=lambda r: r[1].score)[1]
for step_results_for_eval in zip(*eval_results_per_step)
]
@pytest.mark.asyncio
async def test_method(
self,
config: AgentBenchmarkConfig,
request: pytest.FixtureRequest,
i_attempt: int = 0,
) -> None:
if not self._spec.available:
pytest.skip(self._spec.unavailable_reason)
# if os.environ.get("HELICONE_API_KEY"):
# from helicone.lock import HeliconeLockManager
# HeliconeLockManager.write_custom_property("challenge", self.info.name)
timeout = 120
if request.config.getoption("--nc"):
timeout = 100000
elif cutoff := request.config.getoption("--cutoff"):
timeout = int(cutoff)
timed_out = None
eval_results_per_step: list[list[tuple[_Eval, EvalResult]]] = []
try:
async for step in self.run_challenge(
config, timeout, mock=request.config.getoption("--mock")
):
if not step.output:
logger.warn(f"Step has no output: {step}")
continue
step_eval_results = self.evaluate_step_result(
step, mock=request.config.getoption("--mock")
)
logger.debug(f"Intermediary results: {step_eval_results}")
eval_results_per_step.append(step_eval_results)
if step.is_last:
request.node.user_properties.append(
(
"answers",
step.output
if request.config.getoption("--keep-answers")
else None,
)
)
timed_out = False
except TimeoutError:
timed_out = True
request.node.user_properties.append(("timed_out", timed_out))
# Get the column aggregate (highest score for each Eval)
# from the matrix of EvalResults per step.
evals_results = [
max(step_results_for_eval, key=lambda r: r[1].score)
for step_results_for_eval in zip(*eval_results_per_step)
]
if not evals_results:
if timed_out:
raise TimeoutError("Timed out, no results to evaluate")
else:
raise ValueError("No results to evaluate")
request.node.user_properties.append(
("scores", [r[1].score for r in evals_results])
)
# FIXME: arbitrary threshold
assert all(r[1].score > 0.9 for r in evals_results), (
"Scores insufficient:\n\n"
if not timed_out
else "Timed out; scores insufficient:\n\n"
) + "\n".join(f"{repr(r[0])}\n -> {repr(r[1])}" for r in evals_results)
def load_webarena_challenges(
skip_unavailable: bool = True
) -> Iterator[type[WebArenaChallenge]]:
logger.info("Loading WebArena challenges...")
for site, info in site_info_map.items():
if not info.available and skip_unavailable:
logger.warning(
f"JungleGym site '{site}' is not available: {info.unavailable_reason} "
"Skipping all challenges which use this site."
)
# response = requests.get("https://api.junglegym.ai/get_full_webarena_dataset")
# challenge_dicts = response.json()["data"]
# Until the full WebArena challenge set is supported, use a hand-picked selection
import json
from pathlib import Path
challenge_dicts = json.loads(
(Path(__file__).parent / "webarena_selection.json").read_bytes()
)
logger.debug(
"Fetched WebArena dataset. "
f"Constructing {len(challenge_dicts)} WebArenaChallenges..."
)
loaded = 0
failed = 0
skipped = 0
for entry in challenge_dicts:
try:
challenge_spec = WebArenaChallengeSpec.parse_obj(entry)
except ValidationError as e:
failed += 1
logger.warning(f"Error validating WebArena challenge entry: {entry}")
logger.warning(f"Error details: {e}")
continue
# Check all required sites for availability
for site in challenge_spec.sites:
site_info = site_info_map.get(site)
if site_info is None:
challenge_spec.available = False
challenge_spec.unavailable_reason = (
f"WebArena task {challenge_spec.task_id} requires unknown site "
f"'{site}'"
)
elif not site_info.available:
challenge_spec.available = False
challenge_spec.unavailable_reason = (
f"WebArena task {challenge_spec.task_id} requires unavailable "
f"site '{site}'"
)
if not challenge_spec.available and skip_unavailable:
logger.debug(f"{challenge_spec.unavailable_reason}; skipping...")
skipped += 1
continue
yield WebArenaChallenge.from_challenge_spec(challenge_spec)
loaded += 1
logger.info(
"Loading WebArena challenges complete: "
f"loaded {loaded}, skipped {skipped}."
+ (f" {failed} challenges failed to load." if failed else "")
)
|