autogen/samples/tools/testbed/utils/collate_human_eval.py

import os
import errno
import shutil
import subprocess
import json
import sys
import time
import pathlib
import argparse


def collate(results_dir):
    """
    Collate the results of running human eval.

    Args:
        results_dir (path): The folder were results were be saved.
    """

    all_results = list()
    max_instances = 0

    for test_id in os.listdir(results_dir):
        test_path = os.path.join(results_dir, test_id)

        # Collect the reslts vector
        results = [test_id]

        instance = 0
        instance_dir = os.path.join(test_path, str(instance))
        while os.path.isdir(instance_dir):
            console_log = os.path.join(instance_dir, "console_log.txt")
            if os.path.isfile(console_log):
                with open(console_log, "rt") as fh:
                    content = fh.read()
                    if "ALL TESTS PASSED !#!#" in content:
                        results.append(
                            str(content.count("assistant (to user_proxy):"))
                        )  # The number of assistant replies (which is also equal to the number of GPT calls in this case)
                    else:
                        results.append("-1")

            else:
                # Missing results will appear as blanks
                results.append("")

            instance += 1
            instance_dir = os.path.join(test_path, str(instance))

        max_instances = max(max_instances, instance)

        # Buffer the results
        all_results.append(results)

    # Create a header
    header = "TestId"
    for i in range(0, max_instances):
        header += ",Trial" + str(i)
    print(header)

    # Print a fully-populated table of results
    for r in all_results:
        while len(r) < max_instances + 1:
            r.append("")
        print(",".join(r))


###############################################################################
if __name__ == "__main__":
    script_path = os.path.realpath(__file__)
    script_name = os.path.basename(script_path)
    script_dir = os.path.dirname(script_path)

    # Path to the default results directory
    # (relative to this script, up on directory, then into the results folder)
    default_results_dir = os.path.realpath(
        os.path.join(script_dir, os.path.pardir, "results", "human_eval_two_agents_gpt4")
    )

    parser = argparse.ArgumentParser(
        description=f"""
{script_name} will collate the results of the HumanEval scenarios and output them to a CSV. The CSV format is as follows:

TestId,      Trial0, Trial1, ...,    TrialN
HumanEval_1, x_10,   x_11,   ...,    X_1N
HumanEval_2, x_20,   x_21,   ...,    X_2N
...
HumanEval_M, x_M0,   x_M1,   ...,    X_MN


Where x_ij is the number of AsssitantAgent conversation turns needed to pass all the tests for problem i, in Trial/repetition j. If the agent was not able to pass the tests by the end of the conversation, the value will be -1. If data for the trial is missing, the value will be an empty string "".
""".strip(),
        formatter_class=argparse.RawTextHelpFormatter,
    )

    parser.add_argument(
        "scenario",
        nargs="?",
        help="Path to the scenario results. (default: " + default_results_dir + ")",
        default=default_results_dir,
    )
    args = parser.parse_args()
    collate(args.scenario)