mirror of
https://github.com/aljazceru/Auto-GPT.git
synced 2025-12-25 18:04:28 +01:00
138 lines
4.7 KiB
Python
138 lines
4.7 KiB
Python
import glob
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import os
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import subprocess
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from abc import ABC
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from typing import Any, Dict, List
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from dotenv import load_dotenv
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from agbenchmark.challenges.define_task_types import ChallengeData, Ground
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from agbenchmark.start_benchmark import CURRENT_DIRECTORY
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load_dotenv()
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mock_test_str = os.getenv("MOCK_TEST")
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MOCK_TEST = mock_test_str.lower() == "true" if mock_test_str else False
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class Challenge(ABC):
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"""The parent class to all specific challenges classes.
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Defines helper methods for running a challenge"""
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_data_cache: Dict[str, ChallengeData] = {}
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CHALLENGE_LOCATION: str = ""
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@property
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def data(self) -> ChallengeData:
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file_path = f"{CURRENT_DIRECTORY}/../{self.CHALLENGE_LOCATION}/data.json"
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if file_path not in Challenge._data_cache:
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Challenge._data_cache[file_path] = ChallengeData.deserialize(file_path)
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return Challenge._data_cache[file_path]
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@property
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def task(self) -> str:
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return self.data.task
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@property
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def dependencies(self) -> list:
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return self.data.dependencies
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def setup_challenge(self, config: Dict[str, Any]) -> None:
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from agbenchmark.agent_interface import copy_artifacts_into_workspace, run_agent
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copy_artifacts_into_workspace(
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config["workspace"], "artifacts_in", self.CHALLENGE_LOCATION
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)
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run_agent(self.task, config, self.CHALLENGE_LOCATION)
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def test_method(self, config: Dict[str, Any]) -> None:
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raise NotImplementedError
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@staticmethod
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def open_file(workspace: str, filename: str) -> str:
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script_dir = workspace
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workspace_dir = os.path.join(script_dir, filename)
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with open(workspace_dir, "r") as f:
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return f.read()
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def get_artifacts_out(self, workspace: str, file_patterns: list) -> List[str]:
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script_dir = workspace
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files_contents = []
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for file_pattern in file_patterns:
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# Check if it is a file extension
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if file_pattern.startswith("."):
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# Find all files with the given extension in the workspace
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matching_files = glob.glob(os.path.join(script_dir, "*" + file_pattern))
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else:
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# Otherwise, it is a specific file
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matching_files = [os.path.join(script_dir, file_pattern)]
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for file_path in matching_files:
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if self.data.ground.type == "execute_python_code":
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result = subprocess.run(
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["python3", file_path],
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cwd=os.path.abspath(workspace),
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capture_output=True,
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text=True,
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)
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files_contents.append(result.stdout)
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else:
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with open(file_path, "r") as f:
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files_contents.append(f.read())
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return files_contents
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@staticmethod
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def write_to_file(workspace: str, filename: str, content: str) -> None:
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script_dir = workspace
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print("Writing file at", script_dir)
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workspace_dir = os.path.join(script_dir, filename)
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# Open the file in write mode.
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with open(workspace_dir, "w") as f:
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# Write the content to the file.
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f.write(content)
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def get_filenames_in_workspace(self, workspace: str) -> List[str]:
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return [
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filename
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for filename in os.listdir(workspace)
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if os.path.isfile(os.path.join(workspace, filename))
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]
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def scoring(self, content: str, ground: Ground) -> float:
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if ground.should_contain:
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for should_contain_word in ground.should_contain:
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if should_contain_word not in content:
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return 0.0
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else:
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print(
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f"Word that should exist: {should_contain_word} exists in the content"
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)
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if ground.should_not_contain:
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for should_not_contain_word in ground.should_not_contain:
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if should_not_contain_word in content:
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return 0.0
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else:
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print(
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f"Word that should not exist: {should_not_contain_word} does not exist in the content"
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)
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return 1.0
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def get_scores(self, config: Dict[str, Any]) -> List[float]:
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files_contents = self.get_artifacts_out(
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config["workspace"], self.data.ground.files
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)
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scores = []
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for file_content in files_contents:
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score = self.scoring(file_content, self.data.ground)
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print("Your score is:", score)
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scores.append(score)
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return scores
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