import asyncio import json import time from datasets import load_dataset from lagent.agents.stream import PLUGIN_CN, AsyncAgentForInternLM, AsyncMathCoder, get_plugin_prompt from lagent.llms import INTERNLM2_META from lagent.llms.lmdeploy_wrapper import AsyncLMDeployPipeline from lagent.prompts.parsers import PluginParser # set up the loop loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) # initialize the model model = AsyncLMDeployPipeline( path='internlm/internlm2_5-7b-chat', meta_template=INTERNLM2_META, model_name='internlm-chat', tp=1, top_k=1, temperature=1.0, stop_words=['<|im_end|>', '<|action_end|>'], max_new_tokens=1024, ) # ----------------------- interpreter ----------------------- print('-' * 80, 'interpreter', '-' * 80) ds = load_dataset('lighteval/MATH', split='test') problems = [item['problem'] for item in ds.select(range(0, 5000, 2))] coder = AsyncMathCoder( llm=model, interpreter=dict( type='lagent.actions.AsyncIPythonInterpreter', max_kernels=300), max_turn=11) tic = time.time() coros = [coder(query, session_id=i) for i, query in enumerate(problems)] res = loop.run_until_complete(asyncio.gather(*coros)) # print([r.model_dump_json() for r in res]) print('-' * 120) print(f'time elapsed: {time.time() - tic}') with open('./tmp_1.json', 'w') as f: json.dump([coder.get_steps(i) for i in range(len(res))], f, ensure_ascii=False, indent=4) # ----------------------- plugin ----------------------- print('-' * 80, 'plugin', '-' * 80) plugins = [dict(type='lagent.actions.AsyncArxivSearch')] agent = AsyncAgentForInternLM( llm=model, plugins=plugins, output_format=dict( type=PluginParser, template=PLUGIN_CN, prompt=get_plugin_prompt(plugins))) tic = time.time() coros = [ agent(query, session_id=i) for i, query in enumerate(['LLM智能体方向的最新论文有哪些?'] * 50) ] res = loop.run_until_complete(asyncio.gather(*coros)) # print([r.model_dump_json() for r in res]) print('-' * 120) print(f'time elapsed: {time.time() - tic}')