Help Needed: Issue with Phoenix Evaluation and Project Access Error

·Oct 21, 2024 02:44 PM

Hello team! Can you help to resolve the following issue? I pulled spans from my instance of Phoenix. Run the evaluation using run_eval. The evaluation process was partially completed, was interrupted due to the problem:

Retries exhausted after 11 attempts: Error code: 400 - {'error': {'message': "Sorry, I can't answer that question.", 'type': 'invalid_request_error', 'code': '400', 'display_message': "Sorry, I can't answer that question."}}

And now I can't open the required project in the Phoenix web app. The error appears:

Error fetching GraphQL query 'ProjectPageQuery' with variables '{"id":"UHJvamVjdDoy","timeRange":{"start":"2024-10-20T14:00:00.000Z","end":"2025-10-21T14:00:00.000Z"}}': [{"message":"an unexpected error occurred","locations":[{"line":64,"column":11}],"path":["project","rootSpans","edges",0,"rootSpan","spanAnnotations",0,"score"]},{"message":"an unexpected error occurred","locations":[{"line":64,"column":11}],"path":["project","rootSpans","edges",17,"rootSpan","spanAnnotations",1,"score"]},{"message":"an unexpected error occurred","locations":[{"line":64,"column":11}],"path":["project","rootSpans","edges",36,"rootSpan","spanAnnotations",0,"score"]}]

Could you be so kind to suggest how I can resolve it? Thanks in advance!

from phoenix.evals import ( HallucinationEvaluator, OpenAIModel, QAEvaluator, RelevanceEvaluator, run_evals, ) # DEFINE EVALUATION MODEL eval_model = OpenAIModel( api_version=env_config.openai_api_version, azure_deployment=env_config.model_name, azure_endpoint=env_config.gsl_endpoint, api_key=api_key, temperature=0.0, max_tokens=3000, ) # Define your evaluators hallucination_evaluator = HallucinationEvaluator(eval_model) qa_evaluator = QAEvaluator(eval_model) relevance_evaluator = RelevanceEvaluator(eval_model)

import nest_asyncio nest_asyncio.apply() RUN EVALUATIONS [hallucination_eval_df] = run_evals( dataframe=qa_with_reference, evaluators=[hallucination_evaluator], provide_explanation=True, ) [qa_eval_df] = run_evals( dataframe=qa_with_reference, evaluators=[qa_evaluator], provide_explanation=True, ) [relevancy_eval_df] = run_evals( dataframe=retrieved_documents, evaluators=[relevance_evaluator], provide_explanation=True, ) # ANALYZE RESULTS results_qa = qa_with_reference.copy() results_qa["qa_eval"] = qa_eval_df["label"] results_qa["qa_explanation"] = qa_eval_df["explanation"] results_qa.head() results_hal = qa_with_reference.copy() results_hal["hallucination_eval"] = hallucination_eval_df["label"] results_hal["hallucination_explanation"] = hallucination_eval_df["explanation"] results_hal.head() results_rel = retrieved_documents.copy() results_rel["hallucination_eval"] = relevancy_eval_df["label"] results_rel["hallucination_explanation"] = relevancy_eval_df["explanation"] results_rel.head() # PUSH RESULTS TO PHOENIX px.Client().log_evaluations( SpanEvaluations(eval_name="Hallucination", dataframe=hallucination_eval_df), SpanEvaluations(eval_name="QA Correctness", dataframe=qa_eval_df), DocumentEvaluations(eval_name="Relevance", dataframe=relevancy_eval_df), )

Exception in worker on attempt 1: raised BadRequestError('Error code: 400 - {\'error\': {\'message\': "Sorry, I can\'t answer that question.", \'type\': \'invalid_request_error\', \'code\': \'400\', \'display_message\': "Sorry, I can\'t answer that question."}}')

3 comments