83 lines
2.7 KiB
Python
83 lines
2.7 KiB
Python
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"""
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LangGraph 状态图构建模块 - 精简版，仅负责组装图
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所有节点逻辑已拆分到独立模块
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"""
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from langchain_core.language_models import BaseLLM
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from langgraph.graph import StateGraph, START, END
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from .state import MessagesState, GraphContext
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from ..nodes import (
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should_continue,
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create_llm_call_node,
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create_tool_call_node,
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create_retrieve_memory_node,
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create_summarize_node,
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finalize_node,
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)
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from ..nodes.memory_trigger import memory_trigger_node, set_mem0_client
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from ..memory import Mem0Client
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class GraphBuilder:
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"""LangGraph 状态图构建器 - 仅负责组装图"""
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def __init__(self, llm: BaseLLM, tools: list, tools_by_name: dict):
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"""
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初始化构建器
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Args:
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llm: 大语言模型实例
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tools: 工具列表
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tools_by_name: 名称到工具函数的映射
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"""
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self.llm = llm
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self.tools = tools
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self.tools_by_name = tools_by_name
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# ⭐ 创建 Mem0 客户端（懒加载，首次使用时初始化）
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self.mem0_client = Mem0Client(llm)
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def build(self) -> StateGraph:
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"""
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构建未编译的状态图
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Returns:
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StateGraph 实例
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"""
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# 注入全局客户端
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set_mem0_client(self.mem0_client)
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builder = StateGraph(MessagesState, context_schema=GraphContext)
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# ⭐ 通过工厂函数创建节点（依赖注入）
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retrieve_memory_node = create_retrieve_memory_node(self.mem0_client)
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llm_call_node = create_llm_call_node(self.llm, self.tools)
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tool_call_node = create_tool_call_node(self.tools_by_name)
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summarize_node = create_summarize_node(self.mem0_client)
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# 添加节点
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builder.add_node("retrieve_memory", retrieve_memory_node)
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builder.add_node("memory_trigger", memory_trigger_node)
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builder.add_node("llm_call", llm_call_node)
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builder.add_node("tool_node", tool_call_node)
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builder.add_node("summarize", summarize_node)
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builder.add_node("finalize", finalize_node)
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# 添加边
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builder.add_edge(START, "retrieve_memory")
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builder.add_edge("retrieve_memory", "memory_trigger")
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builder.add_edge("memory_trigger", "llm_call")
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builder.add_conditional_edges(
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"llm_call",
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should_continue,
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{
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"tool_node": "tool_node",
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"summarize": "summarize",
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"finalize": "finalize"
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}
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)
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builder.add_edge("tool_node", "llm_call")
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builder.add_edge("summarize", "finalize")
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builder.add_edge("finalize", END)
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return builder
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