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| import asyncio | |
| import time | |
| from lagent.agents.stream import PLUGIN_CN, get_plugin_prompt | |
| from lagent.distributed import AsyncHTTPAgentClient, AsyncHTTPAgentServer, HTTPAgentClient, HTTPAgentServer | |
| from lagent.llms import INTERNLM2_META | |
| from lagent.schema import AgentMessage | |
| from lagent.utils import create_object | |
| loop = asyncio.new_event_loop() | |
| asyncio.set_event_loop(loop) | |
| server = HTTPAgentServer( | |
| '1', | |
| { | |
| 'type': 'lagent.agents.AsyncAgent', | |
| 'llm': { | |
| 'type': 'lagent.llms.AsyncLMDeployPipeline', | |
| 'path': 'internlm/internlm2_5-7b-chat', | |
| 'meta_template': INTERNLM2_META, | |
| } | |
| }, | |
| port=8090, | |
| ) | |
| print(server.is_alive) | |
| message = AgentMessage(sender='user', content='hello') | |
| result = server(message) | |
| print(result) | |
| server.shutdown() | |
| # math coder | |
| server = AsyncHTTPAgentServer( | |
| '1', | |
| { | |
| 'type': 'lagent.agents.AsyncMathCoder', | |
| 'llm': { | |
| 'type': 'lagent.llms.AsyncLMDeployPipeline', | |
| 'path': 'internlm/internlm2_5-7b-chat', | |
| 'meta_template': INTERNLM2_META, | |
| 'tp': 1, | |
| 'top_k': 1, | |
| 'temperature': 1.0, | |
| 'stop_words': ['<|im_end|>', '<|action_end|>'], | |
| 'max_new_tokens': 1024, | |
| }, | |
| 'interpreter': { | |
| 'type': 'lagent.actions.AsyncIPythonInterpreter', | |
| 'max_kernels': 100 | |
| }, | |
| }, | |
| port=8091, | |
| ) | |
| message = AgentMessage( | |
| sender='user', | |
| content= | |
| ('Marie is thinking of a multiple of 63, while Jay is thinking of a factor ' | |
| 'of 63. They happen to be thinking of the same number. There are two ' | |
| 'possibilities for the number that each of them is thinking of, one ' | |
| 'positive and one negative. Find the product of these two numbers.')) | |
| result = server(message) | |
| print(loop.run_until_complete(result)) | |
| print(server.state_dict()) | |
| client = AsyncHTTPAgentClient(port=8091) | |
| result = client('hello', session_id=1) | |
| print(loop.run_until_complete(result)) | |
| print(client.state_dict(1)) | |
| client = HTTPAgentClient(port=8091) | |
| print(client.state_dict(1)) | |
| print(client('introduce yourself', session_id=1)) | |
| print(client.state_dict(1)) | |
| server.shutdown() | |
| # plugins | |
| plugins = [dict(type='lagent.actions.AsyncArxivSearch')] | |
| server_cfg = dict( | |
| type='lagent.distributed.AsyncHTTPAgentServer', | |
| gpu_id='1', | |
| config={ | |
| 'type': 'lagent.agents.AsyncAgentForInternLM', | |
| 'llm': { | |
| 'type': 'lagent.llms.AsyncLMDeployPipeline', | |
| 'path': 'internlm/internlm2_5-7b-chat', | |
| 'meta_template': INTERNLM2_META, | |
| 'tp': 1, | |
| 'top_k': 1, | |
| 'temperature': 1.0, | |
| 'stop_words': ['<|im_end|>', '<|action_end|>'], | |
| 'max_new_tokens': 1024, | |
| }, | |
| 'plugins': plugins, | |
| 'output_format': { | |
| 'type': 'lagent.prompts.parsers.PluginParser', | |
| 'template': PLUGIN_CN, | |
| 'prompt': get_plugin_prompt(plugins), | |
| } | |
| }, | |
| port=8091, | |
| ) | |
| server = create_object(server_cfg) | |
| tic = time.time() | |
| coros = [ | |
| server(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('-' * 120) | |
| print(f'time elapsed: {time.time() - tic}') | |
| server.shutdown() | |