def uptrain_evaluate(
        self,
        evaluation_name: str,
        data: List[Dict[str, str]],
        checks: List[str],
    ) -> None:
        """Run an evaluation on the UpTrain server using UpTrain client."""
        if self.uptrain_client.__class__.__name__ == "APIClient":
            uptrain_result = self.uptrain_client.log_and_evaluate(
                project_name=self.schema.project_name,
                evaluation_name=evaluation_name,
                data=data,
                checks=checks,
            )
        else:
            uptrain_result = self.uptrain_client.evaluate(
                project_name=self.schema.project_name,
                evaluation_name=evaluation_name,
                data=data,
                checks=checks,
            )
        self.schema.uptrain_results[self.schema.project_name].append(uptrain_result)

        score_name_map = {
            "score_context_relevance": "Context Relevance Score",
            "score_factual_accuracy": "Factual Accuracy Score",
            "score_response_completeness": "Response Completeness Score",
            "score_sub_query_completeness": "Sub Query Completeness Score",
            "score_context_reranking": "Context Reranking Score",
            "score_context_conciseness": "Context Conciseness Score",
        }

        # Print the results
        for row in uptrain_result:
            columns = list(row.keys())
            for column in columns:
                if column == "question":
                    print(f"\nQuestion: {row[column]}")
                elif column == "response":
                    print(f"Response: {row[column]}\n")
                elif column.startswith("score"):
                    if column in score_name_map:
                        print(f"{score_name_map[column]}: {row[column]}")
                    else:
                        print(f"{column}: {row[column]}")
            print()
Run an evaluation on the UpTrain server using UpTrain client.
llama-index-integrations/callbacks/llama-index-callbacks-uptrain/llama_index/callbacks/uptrain/base.py