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)