from deepagents.middleware.filesystem import FilesystemMiddleware from deepagents.middleware.patch_tool_calls import PatchToolCallsMiddleware from deepagents.middleware.subagents import SubAgentMiddleware from langchain.agents import create_agent from langchain.agents.middleware import ( TodoListMiddleware, ToolCallLimitMiddleware, ) from yuxi.agents import BaseAgent, BaseState, load_chat_model from yuxi.agents.backends import create_agent_composite_backend from yuxi.agents.middlewares import ( RuntimeConfigMiddleware, SummaryOffloadMiddleware, save_attachments_to_fs, ) from yuxi.agents.middlewares.knowledge_base_middleware import KnowledgeBaseMiddleware from yuxi.agents.middlewares.skills_middleware import SkillsMiddleware from yuxi.agents.toolkits.buildin.tools import _create_tavily_search from yuxi.services.mcp_service import get_tools_from_all_servers from yuxi.services.subagent_service import get_subagents_from_names from yuxi.utils import logger from .prompt import DEEP_PROMPT class DeepAgent(BaseAgent): name = "深度分析" description = "具备规划、深度分析和子智能体协作能力的智能体,可以处理复杂的多步骤任务" capabilities = ["file_upload", "files"] # 支持文件上传功能 metadata = {"examples": ["调研一下多模态 GraphRAG 的相关论文"]} def __init__(self, **kwargs): super().__init__(**kwargs) self.graph = None self.checkpointer = None async def get_tools(self): """返回 Deep Agent 的专用工具""" from yuxi import config tools = [] if config.enable_web_search: tavily = _create_tavily_search() if tavily: tools.append(tavily) if not tools: logger.warning("No search tools configured, DeepAgent will work without web search") return tools async def get_graph(self, context=None, **kwargs): context = context or self.context_schema() # 获取上下文配置 system_prompt = f"{DEEP_PROMPT.strip()}\n\n{context.system_prompt or ''}" model = load_chat_model(context.model) sub_model = load_chat_model(context.subagents_model) search_tools = await self.get_tools() all_mcp_tools = await get_tools_from_all_servers() # 合并搜索工具和 MCP 工具 # 从数据库加载 subagent specs(工具名称已解析) user_subagents = await get_subagents_from_names(context.subagents) # 主 Agent 上下文优化:90k tokens 触发压缩(128k context window 的 70%) summary_middleware = SummaryOffloadMiddleware( model=model, trigger=("tokens", 90000), trim_tokens_to_summarize=4000, summary_offload_threshold=500, max_retention_ratio=0.5, ) subagents_middleware = SubAgentMiddleware( default_model=sub_model, default_tools=search_tools, subagents=user_subagents, default_middleware=[ FilesystemMiddleware(backend=create_agent_composite_backend), # 文件系统后端 PatchToolCallsMiddleware(), summary_middleware, # 子 Agent 搜索工具限制:tavily_search 最多 8 次 ToolCallLimitMiddleware( tool_name="tavily_search", run_limit=8, exit_behavior="continue", ), ], general_purpose_agent=True, ) # 使用 create_deep_agent 创建深度智能体 graph = create_agent( model=model, system_prompt=system_prompt, middleware=[ FilesystemMiddleware(backend=create_agent_composite_backend), # 文件系统后端 RuntimeConfigMiddleware(extra_tools=all_mcp_tools), SkillsMiddleware(), # Skills 中间件(提示词注入、依赖展开、动态激活) save_attachments_to_fs, # 附件注入提示词 TodoListMiddleware(system_prompt="任务结束前,应该检查维护的待办事项列表是否结束。"), PatchToolCallsMiddleware(), KnowledgeBaseMiddleware(), # 知识库工具 subagents_middleware, summary_middleware, # 工具调用限制:tavily_search 总调用最多 20 次 ToolCallLimitMiddleware( tool_name="tavily_search", thread_limit=20, exit_behavior="continue", ), # 总工具调用轮次限制:防止单次运行无限循环 ToolCallLimitMiddleware( run_limit=50, exit_behavior="end", ), ], state_schema=BaseState, checkpointer=await self._get_checkpointer(), ) return graph