def main()

in evaluations/genai_evaluation.py [0:0]
74 lines of code
12 McCabe index (conditional complexity)

def main():
    """
    Main function to execute the evaluation process.
    """
    args = parse_arguments()
    data_file_to_use = args.test_data

    # Check if the specified data file exists
    if not os.path.exists(data_file_to_use):
        logger.error(f"The specified data file '{data_file_to_use}' does not exist.")
        sys.exit(1)

    print(f"Using data file: {data_file_to_use}")

    load_dotenv()
    current_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")

    use_rest_api = os.getenv('USE_REST_API', "False").lower() == "true"
    if use_rest_api:
        orchestrator_endpoint, function_key = get_rest_api_config()
        print("Configured to use REST API for processing questions.")
    else:
        orchestrator_endpoint = None
        function_key = None
        print("Configured to use local execution for processing questions.")

    # Azure configuration (used if needed)
    azure_config = {
        "aoai_endpoint": os.environ.get('AZURE_OPENAI_ENDPOINT', ''),
        "aoai_api_version": os.environ.get('AZURE_OPENAI_API_VERSION', '2024-02-01'),
        "aoai_api_key": os.environ.get('AZURE_OPENAI_API_KEY', ''),
        "subscription_id": os.environ.get('AZURE_SUBSCRIPTION_ID', ''),
        "resource_group": os.environ.get('AZURE_RESOURCE_GROUP', ''),
        "project_name": os.environ.get('AZUREAI_PROJECT_NAME', '')
    }
    print("Azure configuration loaded.")

    # Ensure 'evaluations' directory exists
    os.makedirs('evaluations', exist_ok=True)
    print("Ensured 'evaluations' directory exists.")

    output_jsonl_file = f"evaluations/responses_{current_time}.jsonl"
    output_excel_file = f"evaluations/responses_{current_time}.xlsx"  # Excel output file
    conversation_id = ""
    last_response_data = None

    # Initialize a list to collect all output data for Excel
    excel_data = []

    # Process each question in the test dataset
    with open(data_file_to_use, 'r', encoding='utf-8') as f_in, open(output_jsonl_file, 'w', encoding='utf-8') as f_out:
        print("Opened data file and output JSONL file.")
        for line_number, line in enumerate(f_in, start=1):
            line = line.strip()
            if not line:
                continue
            try:
                data = json.loads(line)
                question = data.get('question', '')
                ground_truth = data.get('ground_truth', '')
                print(f"Processing question {line_number}: {question}")

                start_time = time.time()
                # Process the question
                response_data = process_question(
                    question,
                    use_rest_api,
                    orchestrator_endpoint if use_rest_api else None,
                    function_key if use_rest_api else None,
                    conversation_id
                )
                duration = time.time() - start_time

                # Prepare the output data
                output_data = {
                    "Question": question,
                    "Ground ground_truth": ground_truth,
                    "Answer": response_data.get('answer', 'No answer provided.'),
                    "Context": response_data.get('data_points', 'No data points provided.'),
                    "Reasoning": response_data.get('reasoning', 'No reasoning provided.'),
                    "Processing Time (seconds)": duration
                }
                f_out.write(json.dumps(output_data) + '\n')

                # Append to excel_data list
                excel_data.append(output_data)

            except Exception as e:
                logger.exception(f"Error processing line {line_number}: {e}")

    print("Finished processing all questions.")
    # Optionally prettify the JSONL file
    prettify_jsonl_file(output_jsonl_file)

    # Save results to Excel
    try:
        df = pd.DataFrame(excel_data)
        df.to_excel(output_excel_file, index=False)
        print(f"Results have been saved to Excel file: '{output_excel_file}'")
    except Exception as e:
        logger.exception(f"Failed to save results to Excel: {e}")
        print(f"Error: Could not save results to Excel file. {e}")