Querying Unassessed Spans in Evaluation Process with Python Code

def get_qa_with_reference(obj: CanQuerySpans) -> pd.DataFrame:
    return pd.concat(
        cast(
            List[pd.DataFrame],
            obj.query_spans(
                SpanQuery().select(**IO).where(IS_ROOT),
                SpanQuery()
                .where(IS_RETRIEVER)
                .select(span_id="parent_id")
                .concat(
                    RETRIEVAL_DOCUMENTS,
                    reference=DOCUMENT_CONTENT,
                ),
            ),
        ),
        axis=1,
        join="inner",
    )

hallucination_evaluator = HallucinationEvaluator(eval_model)
    qa_correctness_evaluator = QAEvaluator(eval_model)
    relevance_evaluator = RelevanceEvaluator(eval_model)

    hallucination_eval_df, qa_correctness_eval_df = run_evals(
        dataframe=queries_df,
        evaluators=[hallucination_evaluator, qa_correctness_evaluator],
        provide_explanation=True,
    )
    relevance_eval_df = run_evals(
        dataframe=retrieved_documents_df,
        evaluators=[relevance_evaluator],
        provide_explanation=True,
    )[0]
    
    px.log_evaluations(
        SpanEvaluations(eval_name="Hallucination", dataframe=hallucination_eval_df),
        SpanEvaluations(eval_name="QA Correctness", dataframe=qa_correctness_eval_df),
        DocumentEvaluations(eval_name="Relevance", dataframe=relevance_eval_df),
    )