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