63 lines
2.2 KiB
Python
63 lines
2.2 KiB
Python
import json
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from langchain.chat_models import init_chat_model
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# from deepagents import create_deep_agent
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from langchain.agents import create_agent
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from langchain_mcp_adapters.client import MultiServerMCPClient
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from utils.fastapi_utils import detect_provider
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from .guideline_middleware import GuidelineMiddleware
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# Utility functions
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def read_system_prompt():
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"""读取通用的无状态系统prompt"""
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with open("./prompt/system_prompt_default.md", "r", encoding="utf-8") as f:
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return f.read().strip()
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def read_mcp_settings():
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"""读取MCP工具配置"""
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with open("./mcp/mcp_settings.json", "r") as f:
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mcp_settings_json = json.load(f)
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return mcp_settings_json
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async def init_agent(bot_id: str, model_name="qwen3-next", api_key=None,
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model_server=None, generate_cfg=None,
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system_prompt=None, mcp=None, robot_type=None, language="jp", user_identifier=None):
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system = system_prompt if system_prompt else read_system_prompt()
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mcp = mcp if mcp else read_mcp_settings()
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# 修改mcp[0]["mcpServers"]列表，把 type 字段改成 transport ，如果没有的话，就默认transport:stdio
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if mcp and "mcpServers" in mcp[0]:
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for cfg in mcp[0]["mcpServers"].values():
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if "type" in cfg:
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cfg.pop("type")
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if "transport" not in cfg:
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cfg["transport"] = "http" if "url" in cfg else "stdio"
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mcp_client = MultiServerMCPClient(mcp[0]["mcpServers"])
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mcp_tools = await mcp_client.get_tools()
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# 检测或使用指定的提供商
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model_provider,base_url = detect_provider(model_name,model_server)
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# 构建模型参数
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model_kwargs = {
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"model": model_name,
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"model_provider": model_provider,
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"temperature": 0.8,
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"base_url": base_url,
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"api_key": api_key
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}
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if generate_cfg:
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model_kwargs.update(generate_cfg)
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llm_instance = init_chat_model(**model_kwargs)
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agent = create_agent(
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model=llm_instance,
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system_prompt=system,
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tools=mcp_tools,
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middleware=[GuidelineMiddleware(bot_id, llm_instance, system, robot_type, language, user_identifier)]
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)
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return agent
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