AutoGPT/classic/benchmark/agbenchmark/config.py

129 lines
4.3 KiB
Python

import json
import sys
from datetime import datetime
from pathlib import Path
from typing import Optional
from pydantic import Field, ValidationInfo, field_validator
from pydantic_settings import BaseSettings
def _calculate_info_test_path(base_path: Path, benchmark_start_time: datetime) -> Path:
"""
Calculates the path to the directory where the test report will be saved.
"""
# Ensure the reports path exists
base_path.mkdir(parents=True, exist_ok=True)
# Get current UTC date-time stamp
date_stamp = benchmark_start_time.strftime("%Y%m%dT%H%M%S")
# Default run name
run_name = "full_run"
# Map command-line arguments to their respective labels
arg_labels = {
"--test": None,
"--category": None,
"--maintain": "maintain",
"--improve": "improve",
"--explore": "explore",
}
# Identify the relevant command-line argument
for arg, label in arg_labels.items():
if arg in sys.argv:
test_arg = sys.argv[sys.argv.index(arg) + 1] if label is None else None
run_name = arg.strip("--")
if test_arg:
run_name = f"{run_name}_{test_arg}"
break
# Create the full new directory path with ISO standard UTC date-time stamp
report_path = base_path / f"{date_stamp}_{run_name}"
# Ensure the new directory is created
# FIXME: this is not a desirable side-effect of loading the config
report_path.mkdir(exist_ok=True)
return report_path
class AgentBenchmarkConfig(BaseSettings, extra="allow"):
"""
Configuration model and loader for the AGBenchmark.
Projects that want to use AGBenchmark should contain an agbenchmark_config folder
with a config.json file that - at minimum - specifies the `host` at which the
subject application exposes an Agent Protocol compliant API.
"""
agbenchmark_config_dir: Path = Field(exclude=True)
"""Path to the agbenchmark_config folder of the subject agent application."""
categories: list[str] | None = None
"""Categories to benchmark the agent for. If omitted, all categories are assumed."""
host: str
"""Host (scheme://address:port) of the subject agent application."""
reports_folder: Path = Field(None)
"""
Path to the folder where new reports should be stored.
Defaults to {agbenchmark_config_dir}/reports.
"""
@classmethod
def load(cls, config_dir: Optional[Path] = None) -> "AgentBenchmarkConfig":
config_dir = config_dir or cls.find_config_folder()
with (config_dir / "config.json").open("r") as f:
return cls(
agbenchmark_config_dir=config_dir,
**json.load(f),
)
@staticmethod
def find_config_folder(for_dir: Path = Path.cwd()) -> Path:
"""
Find the closest ancestor folder containing an agbenchmark_config folder,
and returns the path of that agbenchmark_config folder.
"""
current_directory = for_dir
while current_directory != Path("/"):
if (path := current_directory / "agbenchmark_config").exists():
if (path / "config.json").is_file():
return path
current_directory = current_directory.parent
raise FileNotFoundError(
"No 'agbenchmark_config' directory found in the path hierarchy."
)
@property
def config_file(self) -> Path:
return self.agbenchmark_config_dir / "config.json"
@field_validator("reports_folder", mode="before")
def set_reports_folder(cls, value: Path, info: ValidationInfo):
if not value:
return info.data["agbenchmark_config_dir"] / "reports"
return value
def get_report_dir(self, benchmark_start_time: datetime) -> Path:
return _calculate_info_test_path(self.reports_folder, benchmark_start_time)
@property
def regression_tests_file(self) -> Path:
return self.reports_folder / "regression_tests.json"
@property
def success_rate_file(self) -> Path:
return self.reports_folder / "success_rate.json"
@property
def challenges_already_beaten_file(self) -> Path:
return self.agbenchmark_config_dir / "challenges_already_beaten.json"
@property
def temp_folder(self) -> Path:
return self.agbenchmark_config_dir / "temp_folder"