文件变更

app/graph/graph_builder.py

@@ -0,0 +1,79 @@
+"""
+LangGraph 状态图构建模块 - 精简版，仅负责组装图
+所有节点逻辑已拆分到独立模块
+"""
+
+from langchain_core.language_models import BaseLLM
+from langgraph.graph import StateGraph, START, END
+
+# 本地模块
+from app.graph.state import MessagesState, GraphContext
+from app.nodes import (
+    create_llm_call_node,
+    create_tool_call_node,
+    create_retrieve_memory_node,
+    create_summarize_node,
+    should_continue
+)
+from app.memory import Mem0Client
+from app.nodes.finalize import finalize_node
+
+
+class GraphBuilder:
+    """LangGraph 状态图构建器 - 仅负责组装图"""
+
+    def __init__(self, llm: BaseLLM, tools: list, tools_by_name: dict):
+        """
+        初始化构建器
+        
+        Args:
+            llm: 大语言模型实例
+            tools: 工具列表
+            tools_by_name: 名称到工具函数的映射
+        """
+        self.llm = llm
+        self.tools = tools
+        self.tools_by_name = tools_by_name
+        
+        # ⭐ 创建 Mem0 客户端（懒加载，首次使用时初始化）
+        self.mem0_client = Mem0Client(llm)
+
+    def build(self) -> StateGraph:
+        """
+        构建未编译的状态图
+        
+        Returns:
+            StateGraph 实例
+        """
+        builder = StateGraph(MessagesState, context_schema=GraphContext)
+        
+        # ⭐ 通过工厂函数创建节点（依赖注入）
+        retrieve_memory_node = create_retrieve_memory_node(self.mem0_client)
+        llm_call_node = create_llm_call_node(self.llm, self.tools)
+        tool_call_node = create_tool_call_node(self.tools_by_name)
+        summarize_node = create_summarize_node(self.mem0_client)
+        
+        # 添加节点
+        builder.add_node("retrieve_memory", retrieve_memory_node)
+        builder.add_node("llm_call", llm_call_node)
+        builder.add_node("tool_node", tool_call_node)
+        builder.add_node("summarize", summarize_node)
+        builder.add_node("finalize", finalize_node)
+
+        # 添加边
+        builder.add_edge(START, "retrieve_memory")
+        builder.add_edge("retrieve_memory", "llm_call")
+        builder.add_conditional_edges(
+            "llm_call",
+            should_continue,
+            {
+                "tool_node": "tool_node",
+                "summarize": "summarize",
+                "finalize": "finalize"
+            }
+        )
+        builder.add_edge("tool_node", "llm_call")
+        builder.add_edge("summarize", "finalize")
+        builder.add_edge("finalize", END)
+        
+        return builder

app/graph/graph_tools.py

@@ -0,0 +1,103 @@
+"""
+工具定义模块 - 纯函数工具，无依赖 AIAgent 类
+"""
+
+# 标准库
+import os
+from pathlib import Path
+
+# 第三方库
+import pandas as pd
+import pypdf
+import requests
+from bs4 import BeautifulSoup
+from langchain_core.tools import tool
+
+
+def _file_allow_check(filename: str) -> Path:
+    """检查用户文件名是否位于允许目录 './user_docs' 下，防止路径遍历攻击。"""
+    allowed_dir = Path("./user_docs").resolve()
+    allowed_dir.mkdir(exist_ok=True)
+
+    file_path = (allowed_dir / filename).resolve()
+    if not str(file_path).startswith(str(allowed_dir)):
+        raise ValueError("错误：非法文件路径。")
+
+    if not file_path.exists():
+        raise FileNotFoundError(f"错误：文件 '{filename}' 不存在。")
+
+    return file_path
+
+
+@tool
+def get_current_temperature(location: str) -> str:
+    """获取指定地点的当前温度。"""
+    return f'当前{location}的温度为25℃'
+
+
+@tool
+def read_local_file(filename: str) -> str:
+    """读取用户指定名称的本地文本文件内容并返回摘要。"""
+    try:
+        file_path = _file_allow_check(filename)
+        with open(file_path, 'r', encoding='utf-8') as f:
+            content = f.read()
+        return f"文件 '{filename}' 的内容开头：\n{content[:1000]}..."
+    except Exception as e:
+        return f"读取文件时出错：{str(e)}"
+
+
+@tool
+def read_pdf_summary(filename: str) -> str:
+    """读取PDF文件并返回内容文本摘要。"""
+    try:
+        file_path = _file_allow_check(filename)
+        text = ""
+        with open(file_path, 'rb') as f:
+            reader = pypdf.PdfReader(f)
+            for page in reader.pages[:3]:
+                text += page.extract_text()
+        return f"PDF文件 '{filename}' 的前几页内容：\n{text[:2000]}..."
+    except Exception as e:
+        return f"读取PDF出错：{e}"
+
+
+@tool
+def read_excel_as_markdown(filename: str) -> str:
+    """读取Excel文件，并将其主要数据转换为Markdown表格格式。"""
+    try:
+        file_path = _file_allow_check(filename)
+        df = pd.read_excel(file_path)
+        markdown_table = df.head(10).to_markdown(index=False)
+        return f"Excel文件 '{filename}' 的数据预览（前10行）：\n{markdown_table}"
+    except Exception as e:
+        return f"读取Excel出错：{e}"
+
+
+@tool
+def fetch_webpage_content(url: str) -> str:
+    """抓取给定URL的网页正文内容，并返回清晰的纯文本。"""
+    try:
+        response = requests.get(url, timeout=10)
+        response.raise_for_status()
+        soup = BeautifulSoup(response.text, 'html.parser')
+        for script in soup(["script", "style"]):
+            script.decompose()
+        text = soup.get_text()
+        lines = (line.strip() for line in text.splitlines())
+        chunks = (phrase.strip() for line in lines for phrase in line.split("  "))
+        text = '\n'.join(chunk for chunk in chunks if chunk)
+        return f"成功抓取网页 {url}，正文内容开头：\n{text[:1500]}..."
+    except Exception as e:
+        return f"抓取网页时出错：{str(e)}"
+
+
+# 工具列表和映射（全局常量）
+AVAILABLE_TOOLS = [
+    get_current_temperature,
+    read_local_file,
+    fetch_webpage_content,
+    read_pdf_summary,
+    read_excel_as_markdown
+]
+TOOLS_BY_NAME = {tool.name: tool for tool in AVAILABLE_TOOLS}

app/graph/retrieve_memory.py

@@ -0,0 +1,78 @@
+"""
+记忆检索节点模块
+负责从 Mem0 检索相关长期记忆
+"""
+
+from typing import Any, Dict
+from langgraph.runtime import Runtime
+
+# 本地模块
+from app.graph.state import MessagesState, GraphContext
+from app.memory.mem0_client import Mem0Client
+from app.utils.logging import log_state_change
+from app.logger import debug
+
+
+def create_retrieve_memory_node(mem0_client: Mem0Client):
+    """
+    工厂函数：创建记忆检索节点
+    
+    Args:
+        mem0_client: Mem0 客户端实例
+        
+    Returns:
+        异步节点函数
+    """
+    
+    from langchain_core.runnables.config import RunnableConfig
+    
+    async def retrieve_memory(state: MessagesState, config: RunnableConfig) -> Dict[str, Any]:
+        """
+        记忆检索节点 - 使用 Mem0
+        
+        Args:
+            state: 当前对话状态
+            config: 运行时配置
+            
+        Returns:
+            包含 memory_context 的状态更新
+        """
+        log_state_change("retrieve_memory", state, "进入")
+
+        # 从 metadata 中获取 user_id
+        user_id = config.get("metadata", {}).get("user_id", "default_user")
+        
+        # 兼容 dict 和对象两种消息格式
+        last_msg = state["messages"][-1]
+        if isinstance(last_msg, dict):
+            query = str(last_msg.get("content", ""))
+        else:
+            query = str(last_msg.content)
+        memory_text_parts = []
+
+        # 确保 Mem0 已初始化（懒加载）
+        if not mem0_client._initialized:
+            await mem0_client.initialize()
+
+        if mem0_client.mem0:
+            try:
+                # 异步调用 Mem0 语义检索
+                facts = await mem0_client.search_memories(query, user_id=user_id, limit=5)
+                
+                if facts:
+                    memory_text_parts.append(f"【相关长期记忆】\n" + "\n".join(f"- {f}" for f in facts))
+                else:
+                    debug("🔍 [记忆检索] 未找到相关记忆")
+            except Exception as e:
+                from app.logger import warning
+                warning(f"⚠️ Mem0 检索失败: {e}")
+        else:
+            from app.logger import warning
+            warning("⚠️ Mem0 未初始化，跳过记忆检索")
+
+        memory_context = "\n\n".join(memory_text_parts) if memory_text_parts else "暂无用户信息"
+        result = {"memory_context": memory_context}
+        log_state_change("retrieve_memory", {**state, **result}, "离开")
+        return result
+    
+    return retrieve_memory

app/graph/state.py

@@ -0,0 +1,27 @@
+"""
+LangGraph 状态定义模块
+包含 MessagesState 和 GraphContext
+"""
+
+import operator
+from typing import Annotated, Any
+from typing_extensions import TypedDict
+from dataclasses import dataclass
+from langchain_core.messages import AnyMessage
+
+
+class MessagesState(TypedDict):
+    """对话状态类型定义"""
+    messages: Annotated[list[AnyMessage], operator.add]
+    llm_calls: int
+    memory_context: str
+    last_token_usage: dict  # 本次调用的 token 使用详情
+    last_elapsed_time: float  # 本次调用耗时（秒）
+    turns_since_last_summary: int  # 距离上次生成摘要的轮数
+
+
+@dataclass
+class GraphContext:
+    """图执行上下文"""
+    user_id: str
+    # 可扩展更多上下文信息