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491 lines
15 KiB
Python
491 lines
15 KiB
Python
import pytest
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from opik_backend.executor_docker import DockerExecutor
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from opik_backend.executor_process import ProcessExecutor
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from opik_backend.payload_types import PayloadType
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EVALUATORS_URL = "/v1/private/evaluators/python"
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@pytest.fixture(params=[DockerExecutor, ProcessExecutor])
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def executor(request):
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"""Fixture that provides both Docker and Process executors."""
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executor_instance = request.param()
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if hasattr(executor_instance, 'start_services'):
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executor_instance.start_services()
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try:
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yield executor_instance
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finally:
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if hasattr(executor_instance, 'cleanup'):
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executor_instance.cleanup()
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@pytest.fixture
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def app(executor):
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"""Create Flask app with the given executor."""
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from opik_backend import create_app
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app = create_app(should_init_executor=False)
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app.executor = executor # Override the executor with our parametrized one
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return app
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@pytest.fixture
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def client(app):
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"""Create test client for the app."""
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return app.test_client()
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USER_DEFINED_METRIC = """
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from typing import Any
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from opik.evaluation.metrics import base_metric, score_result
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class UserDefinedEquals(base_metric.BaseMetric):
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def __init__(
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self,
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name: str = "user_defined_equals_metric",
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):
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super().__init__(
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name=name,
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track=False,
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)
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def score(
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self, output: str, reference: str, **ignored_kwargs: Any
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) -> score_result.ScoreResult:
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value = 1.0 if output == reference else 0.0
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return score_result.ScoreResult(value=value, name=self.name)
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"""
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LIST_RESPONSE_METRIC = """
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from typing import Any
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from opik.evaluation.metrics import base_metric, score_result
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class UserDefinedEquals(base_metric.BaseMetric):
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def __init__(
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self,
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name: str = "user_defined_list_equals_metric",
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):
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super().__init__(
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name=name,
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track=False,
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)
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def score(
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self, output: str, reference: str, **ignored_kwargs: Any
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) -> score_result.ScoreResult:
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value = 1.0 if output == reference else 0.0
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return [score_result.ScoreResult(value=value, name=self.name), score_result.ScoreResult(value=0.5, name=self.name)]
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"""
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INVALID_METRIC = """
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from typing import
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from opik.evaluation.metrics import base_metric, score_result
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class UserDefinedEquals(base_metric.BaseMetric):
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def __init__(
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self,
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name: str = "user_defined_equals_metric",
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):
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super().__init__(
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name=name,
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track=False,
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)
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def score(
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self, output: str, reference: str, **ignored_kwargs: Any
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) -> score_result.ScoreResult:
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value = 1.0 if output == reference else 0.0
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return score_result.ScoreResult(value=value, name=self.name)
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"""
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MISSING_BASE_METRIC = """
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from typing import Any
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from opik.evaluation.metrics import base_metric, score_result
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class UserDefinedEquals():
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def __init__(
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self,
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name: str = "user_defined_equals_metric",
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):
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super().__init__(
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name=name,
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track=False,
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)
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def score(
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self, output: str, reference: str, **ignored_kwargs: Any
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) -> score_result.ScoreResult:
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value = 1.0 if output == reference else 0.0
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return score_result.ScoreResult(value=value, name=self.name)
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"""
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CONSTRUCTOR_EXCEPTION_METRIC = """
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from typing import Any
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from opik.evaluation.metrics import base_metric, score_result
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class UserDefinedEquals(base_metric.BaseMetric):
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def __init__(
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self,
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name: str = "user_defined_equals_metric",
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):
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super().__init__(
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name=name,
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track=False,
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)
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raise Exception("Exception in constructor")
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def score(
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self, output: str, reference: str, **ignored_kwargs: Any
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) -> score_result.ScoreResult:
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value = 1.0 if output == reference else 0.0
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return score_result.ScoreResult(value=value, name=self.name)
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"""
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SCORE_EXCEPTION_METRIC = """
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from typing import Any
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from opik.evaluation.metrics import base_metric, score_result
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class UserDefinedEquals(base_metric.BaseMetric):
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def __init__(
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self,
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name: str = "user_defined_equals_metric",
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):
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super().__init__(
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name=name,
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track=False,
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)
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def score(
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self, output: str, reference: str, **ignored_kwargs: Any
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) -> score_result.ScoreResult:
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raise Exception("Exception while scoring")
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"""
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MISSING_SCORE_METRIC = """
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from typing import Any
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from opik.evaluation.metrics import base_metric, score_result
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class UserDefinedEquals(base_metric.BaseMetric):
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def __init__(
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self,
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name: str = "user_defined_equals_metric",
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):
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super().__init__(
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name=name,
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track=False,
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)
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def score(
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self, output: str, reference: str, **ignored_kwargs: Any
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) -> score_result.ScoreResult:
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return None
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"""
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FLASK_INJECTION_METRIC = """
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from typing import Any
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import flask
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from opik.evaluation.metrics import base_metric, score_result
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class FlaskInjectionMetric(base_metric.BaseMetric):
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def __init__(self, name: str = "flask_injection_metric", ):
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super().__init__(name=name, track=False)
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def score(self, **ignored_kwargs: Any) -> score_result.ScoreResult:
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# Replace all view functions with a function that returns an error
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def error_response(*args, **kwargs):
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return "Service Unavailable because it was hacked", 503
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for endpoint in flask.current_app.view_functions:
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flask.current_app.view_functions[endpoint] = error_response
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return score_result.ScoreResult(value=0.0, name=self.name)
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"""
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DATA = {
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"output": "abc",
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"reference": "abc"
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}
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@pytest.mark.parametrize("data,code, expected", [
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(
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DATA,
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USER_DEFINED_METRIC,
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[
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{
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"metadata": None,
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"name": 'user_defined_equals_metric',
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"reason": None,
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"scoring_failed": False,
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"value": 1.0
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}
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]
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),
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(
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{"output": "abc", "reference": "ab"},
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USER_DEFINED_METRIC,
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[
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{
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"metadata": None,
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"name": 'user_defined_equals_metric',
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"reason": None,
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"scoring_failed": False,
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"value": 0.0
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}
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]
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),
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(
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DATA,
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LIST_RESPONSE_METRIC,
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[
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{
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"metadata": None,
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"name": 'user_defined_list_equals_metric',
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"reason": None,
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"scoring_failed": False,
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"value": 1.0
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},
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{
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"metadata": None,
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"name": 'user_defined_list_equals_metric',
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"reason": None,
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"scoring_failed": False,
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"value": 0.5
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},
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]
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),
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])
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def test_success(client, data, code, expected):
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response = client.post(EVALUATORS_URL, json={
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"data": data,
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"code": code
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})
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assert response.status_code == 200
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scores = response.json['scores']
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assert all(s.get('category_name') is None for s in scores)
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assert [{k: v for k, v in s.items() if k != 'category_name'} for s in scores] == expected
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def test_options_method_returns_ok(client):
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response = client.options(EVALUATORS_URL)
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assert response.status_code == 200
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assert response.get_json() is None
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def test_other_method_returns_method_not_allowed(client):
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response = client.get(EVALUATORS_URL)
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assert response.status_code == 405
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def test_missing_request_returns_bad_request(client):
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response = client.post(EVALUATORS_URL, json=None)
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assert response.status_code == 400
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assert response.json[
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"error"] == "400 Bad Request: The browser (or proxy) sent a request that this server could not understand."
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def test_missing_code_returns_bad_request(client):
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response = client.post(EVALUATORS_URL, json={
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"data": DATA
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})
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assert response.status_code == 400
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assert response.json["error"] == "400 Bad Request: Field 'code' is missing in the request"
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def test_missing_data_returns_bad_request(client):
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response = client.post(EVALUATORS_URL, json={
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"code": USER_DEFINED_METRIC
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})
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assert response.status_code == 400
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assert response.json["error"] == "400 Bad Request: Field 'data' is missing in the request"
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# Test how the evaluator handles invalid code, including syntax errors and Flask injection attempts
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@pytest.mark.parametrize("code, stacktraces", [
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(
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INVALID_METRIC,
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[
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"""SyntaxError: invalid syntax""", # DockerExecutor format
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"""SyntaxError: Expected one or more names after 'import'""" # ProcessExecutor format
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]
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),
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pytest.param(
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FLASK_INJECTION_METRIC,
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["""ModuleNotFoundError: No module named 'flask'"""],
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marks=pytest.mark.skipif(
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lambda: isinstance(app.executor, ProcessExecutor),
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reason="Flask injection test only makes sense for DockerExecutor"
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)
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)
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])
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def test_invalid_code_returns_bad_request(client, code, stacktraces):
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response = client.post(EVALUATORS_URL, json={
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"data": DATA,
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"code": code
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})
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assert response.status_code == 400
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assert "400 Bad Request: Field 'code' contains invalid Python code" in str(response.json["error"])
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# Check that the expected error message is in the response
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error_message = str(response.json["error"])
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# Check if any of the expected stacktraces match
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assert any(stacktrace in error_message for stacktrace in stacktraces), f"None of the expected stacktraces found in error message: {error_message}"
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def test_missing_metric_returns_bad_request(client):
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response = client.post(EVALUATORS_URL, json={
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"data": DATA,
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"code": MISSING_BASE_METRIC
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})
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assert response.status_code == 400
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assert response.json[
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"error"] == "400 Bad Request: Field 'code' in the request doesn't contain a subclass implementation of 'opik.evaluation.metrics.BaseMetric'"
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@pytest.mark.parametrize("code, stacktrace", [
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(
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CONSTRUCTOR_EXCEPTION_METRIC,
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"""Exception: Exception in constructor"""
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),
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(
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SCORE_EXCEPTION_METRIC,
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"""Exception: Exception while scoring"""
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)
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])
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def test_evaluation_exception_returns_bad_request(client, code, stacktrace):
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response = client.post(EVALUATORS_URL, json={
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"data": DATA,
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"code": code
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})
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assert response.status_code == 400
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assert "400 Bad Request: The provided 'code' and 'data' fields can't be evaluated" in str(response.json["error"])
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# Check that the expected error message is in the response
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error_message = str(response.json["error"])
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assert stacktrace in error_message
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def test_no_scores_returns_bad_request(client):
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response = client.post(EVALUATORS_URL, json={
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"data": DATA,
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"code": MISSING_SCORE_METRIC
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})
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assert response.status_code == 400
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assert response.json[
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"error"] == "400 Bad Request: The provided 'code' field didn't return any 'opik.evaluation.metrics.ScoreResult'"
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# ConversationThreadMetric test definitions
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CONVERSATION_THREAD_METRIC = """
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from typing import Union, List, Any
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from opik.evaluation.metrics import score_result
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from opik.evaluation.metrics.conversation import conversation_thread_metric, types
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class TestConversationThreadMetric(conversation_thread_metric.ConversationThreadMetric):
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def __init__(
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self,
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name: str = "test_conversation_thread_metric",
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):
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super().__init__(
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name=name,
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)
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def score(
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self, conversation: types.Conversation, **kwargs: Any
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) -> Union[score_result.ScoreResult, List[score_result.ScoreResult]]:
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# Simple test metric that counts the number of messages in conversation
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message_count = len(conversation)
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# Score based on whether the conversation has an appropriate length
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value = 1.0 if 2 <= message_count <= 10 else 0.0
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return score_result.ScoreResult(
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value=value,
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name=self.name,
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reason=f"Conversation has {message_count} messages"
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)
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"""
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def test_conversation_thread_metric_wrong_data_structure_fails(client, app):
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"""Test that ConversationThreadMetric fails when data is a list without type: trace_thread."""
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# This demonstrates the WRONG way - data as a list without type: trace_thread
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wrong_payload = {
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"data": [ # ❌ This is wrong when type is not "trace_thread"
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|
{
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|
"role": "user",
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|
"content": {
|
|
"query": "My phone won't work",
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|
"thread_id": "test-123"
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|
}
|
|
},
|
|
{
|
|
"role": "assistant",
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|
"content": {
|
|
"output": "Let me help you with that."
|
|
}
|
|
}
|
|
],
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|
# ❌ Missing "type": "trace_thread" - so backend tries **data unpacking
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|
"code": CONVERSATION_THREAD_METRIC
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|
}
|
|
|
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response = client.post(EVALUATORS_URL, json=wrong_payload)
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|
|
|
# Should fail with 400 error about evaluation failure
|
|
assert response.status_code == 400
|
|
assert "400 Bad Request: The provided 'code' and 'data' fields can't be evaluated" in str(response.json["error"])
|
|
|
|
|
|
def test_conversation_thread_metric_with_trace_thread_type(client, app):
|
|
"""Test that ConversationThreadMetric works with trace_thread type and direct data array."""
|
|
# Test the NEW way - using type: trace_thread with data as direct array
|
|
trace_thread_payload = {
|
|
"data": [ # ✅ Data as direct array works with type: trace_thread
|
|
{
|
|
"role": "user",
|
|
"content": {
|
|
"query": "My phone won't work",
|
|
"thread_id": "test-123"
|
|
}
|
|
},
|
|
{
|
|
"role": "assistant",
|
|
"content": {
|
|
"output": "Let me help you with that."
|
|
}
|
|
}
|
|
],
|
|
"type": PayloadType.TRACE_THREAD.value, # ✅ This tells backend to pass data as first positional arg
|
|
"code": CONVERSATION_THREAD_METRIC
|
|
}
|
|
|
|
response = client.post(EVALUATORS_URL, json=trace_thread_payload)
|
|
|
|
# Should work correctly now
|
|
assert response.status_code == 200
|
|
scores = response.json['scores']
|
|
assert len(scores) == 1
|
|
|
|
score = scores[0]
|
|
assert score['name'] == 'test_conversation_thread_metric'
|
|
assert score['value'] == 1.0 # 2 messages is within 2-10 range
|
|
assert score['reason'] == "Conversation has 2 messages"
|
|
assert score['scoring_failed'] is False
|