wehub-resource-sync
93 lines
3.6 KiB
Python
93 lines
3.6 KiB
Python
from constant import DOCKER_WORKPLACE_NAME
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from autoagent.environment.docker_container import init_container
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from autoagent.io_utils import read_yaml_file, get_md5_hash_bytext
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from autoagent.agents import get_rag_agent
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from autoagent.core import AutoAgent
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from autoagent.environment.docker_env import DockerEnv, DockerConfig, with_env
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import argparse
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import asyncio
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import csv
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from tqdm import trange
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import os
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import json
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import time
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def get_args():
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parser = argparse.ArgumentParser(description="working@tjb-tech")
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parser.add_argument('--container_name', type=str, default='gaia_test')
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parser.add_argument('--model', type=str, default='gpt-4o-mini-2024-07-18')
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parser.add_argument('--git_clone', action='store_true', default=False)
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parser.add_argument('--setup_package', type=str, default='lite_pkgs')
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parser.add_argument('--debug', action='store_true', default=False)
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args = parser.parse_args()
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return args
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def get_env(container_name: str = 'gaia_test', model: str = 'gpt-4o-mini-2024-07-18', git_clone: bool = False, setup_package: str = 'lite_pkgs', test_pull_name: str = 'test_pull_1010', debug: bool = True):
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workplace_name = DOCKER_WORKPLACE_NAME
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docker_config = DockerConfig(container_name=container_name, workplace_name=workplace_name, communication_port=12345, conda_path='/home/user/micromamba')
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docker_env = DockerEnv(docker_config)
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return docker_env
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def append_to_json(file_path, entry):
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if os.path.exists(file_path):
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with open(file_path, 'r', encoding='utf-8') as json_file:
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data = json.load(json_file)
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else:
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data = []
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data.append(entry)
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with open(file_path, 'w', encoding='utf-8') as json_file:
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json.dump(data, json_file, ensure_ascii=False, indent=4)
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async def main(container_name: str = 'gaia_test', model: str = 'gpt-4o-mini-2024-07-18', git_clone: bool = False, setup_package: str = 'lite_pkgs', test_pull_name: str = 'test_pull_1010', debug: bool = True, task_instructions: str = None):
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workplace_name = DOCKER_WORKPLACE_NAME
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# docker_env = get_env(container_name, model, git_clone, setup_package, test_pull_name, debug)
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# docker_env.init_container()
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csv_file_path = './MultiHopRAG.csv'
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json_path = './result.json'
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question_list=[]
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GA_LIST=[]
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with open(csv_file_path, mode='r', encoding='utf-8') as question_file:
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reader = csv.DictReader(question_file)
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for row in reader:
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question_list.append(row['query'])
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GA_LIST.append(row['answer'])
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row_count = 0
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with open(json_path, 'r', encoding='utf-8') as json_file:
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data = json.load(json_file)
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row_count = len(data)
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for QUESTIONid in trange(row_count,len(question_list)):#
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task_instructions = question_list[QUESTIONid]
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#answer: row[1]
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codeact_agent = get_rag_agent(model)#, rag_env=docker_env)
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mc = MetaChain()
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# try:
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context_variables = {"working_dir": DOCKER_WORKPLACE_NAME,"user_query": task_instructions}
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messages = [{"role": "user", "content": task_instructions}]
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response = await mc.run_async(agent=codeact_agent, messages=messages,max_turns=10, context_variables=context_variables, debug=debug)
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data_new = {
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"query": task_instructions,
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"gold_answer": GA_LIST[QUESTIONid],
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"answer": response.messages[-1]['content']
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}
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append_to_json(json_path, data_new)
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if __name__ == "__main__":
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args = get_args()
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asyncio.run(main(args.container_name, args.model, args.git_clone, args.setup_package, args.test_pull_name, args.debug))
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