Fernanda M.

Hi everyone, I'm getting a "Could not parse XXX" error when using a different LLM in the evaluations for the RAG example notebook: link. The issue occurs when I replace the example model with another one. Any tips on what might be causing this error? Please see the screenshot for error message details. Here's the modified code. Thank you!

# Original evaluators
# qa_evaluator = QAEvaluator(OpenAIModel(model="gpt-4-turbo-preview"))
# hallucination_evaluator = HallucinationEvaluator(OpenAIModel(model="gpt-4-turbo-preview"))

# Modified evaluators
qa_evaluator = QAEvaluator(BedrockModel(
    # model_id="anthropic.claude-3-sonnet-20240229-v1:0",
    client=bedrock_client))
hallucination_evaluator = HallucinationEvaluator(BedrockModel(
    # model_id="meta.llama2-70b-chat-v1",
    client=bedrock_client))

qa_correctness_eval_df, hallucination_eval_df = run_evals(
    evaluators=[qa_evaluator, hallucination_evaluator],
    dataframe=qa_with_reference_df,
    provide_explanation=True,
    concurrency=20,
    verbose=True)

Hey everyone, I'm new to Arize Phoenix and need some help. How can I integrate evaluations and display them with pre-existing trace data, as mentioned in the evals_quickstart Jupyter notebook? I'm trying to use Amazon Bedrock integration, but my Phoenix UI is empty without any trace data. See the screenshot below of my Phoenix UI and the PDF with the Jupyter notebook changes for Bedrock. Thank you!