修复长期记忆bug

app/backend.py

@@ -15,7 +15,7 @@ from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver
 from app.agent import AIAgentService
-from app.history import ThreadHistoryService
+from app.agent.history import ThreadHistoryService
 from app.logger import info, error
 
 # 加载 .env 文件

app/config.py

@@ -20,6 +20,11 @@ QDRANT_URL = os.getenv("QDRANT_URL", "http://127.0.0.1:6333")
 QDRANT_COLLECTION_NAME = os.getenv("QDRANT_COLLECTION_NAME", "mem0_user_memories")
 QDRANT_API_KEY = os.getenv("QDRANT_API_KEY", "your-qdrant-api-key")
 
+# ==========    llm 配置 ==========
+# LLM 模型配置
+VLLM_BASE_URL = os.getenv("VLLM_BASE_URL", "http://127.0.0.1:8081/v1")
+LLM_API_KEY = os.getenv("LLM_API_KEY", "your-ai-api-key")
+
 # llama.cpp Embedding 服务地址 (用于 Mem0 的向量化)
 LLAMACPP_EMBEDDING_URL = os.getenv("LLAMACPP_EMBEDDING_URL", "http://127.0.0.1:8082/v1")
 LLAMACPP_API_KEY = os.getenv("LLAMACPP_API_KEY", "your-llamacpp-api-key")

app/memory/mem0_client.py

@@ -1,3 +1,6 @@
+from app.config import LLM_API_KEY
+from app.config import VLLM_BASE_URL
+import time
 """
 Mem0 记忆层客户端封装模块
 负责 Mem0 的初始化、检索和存储
@@ -7,7 +10,11 @@ import asyncio
 from typing import Optional, List, Dict
 from mem0 import AsyncMemory
 
-from app.config import QDRANT_URL, QDRANT_COLLECTION_NAME, QDRANT_API_KEY, LLAMACPP_EMBEDDING_URL, LLAMACPP_API_KEY
+from app.config import (
+    QDRANT_URL,QDRANT_COLLECTION_NAME,QDRANT_API_KEY,
+    VLLM_BASE_URL, LLM_API_KEY,
+    LLAMACPP_EMBEDDING_URL, LLAMACPP_API_KEY
+)
 from app.logger import info, warning, error
 
 class Mem0Client:
@@ -42,9 +49,13 @@ class Mem0Client:
                     }
                 },
                 "llm": {
-                    "provider": "langchain",
+                    "provider": "openai",
                     "config": {
-                        "model": self.llm
+                        "model": "LLM_MODEL",
+                        "api_key": LLM_API_KEY,
+                        "openai_base_url": VLLM_BASE_URL,  
+                        "temperature": 0.1,
+                        "max_tokens": 2000,
                     }
                 },
                 "embedder": {
@@ -118,36 +129,18 @@ class Mem0Client:
             warning(f"⚠️ Mem0 检索失败: {e}")
             return []
 
-    async def add_memories(self, messages: List[Dict[str, str]], user_id: str) -> bool:
+    async def add_memories(self, messages, user_id):
-        """
+      if not self.mem0:
-        添加记忆（自动提取事实并存储）
+        return False
-
+      try:
-        Args:
+        start = time.time()
-            messages: 消息列表，格式为 [{"role": "user/assistant/system", "content": "..."}]
+        info(f"📝 开始 Mem0 add，消息数: {len(messages)}")
-            user_id: 用户 ID
+        await asyncio.wait_for(
-
+            self.mem0.add(messages, user_id=user_id, metadata={"type": "conversation"}),
-        Returns:
+            timeout=60.0
-            bool: 是否成功
+        )
-        """
+        info(f"✅ Mem0 add 完成，耗时: {time.time() - start:.2f}s")
-        if not self.mem0:
+        return True
-            warning("⚠️ Mem0 未初始化，跳过记忆添加")
+      except asyncio.TimeoutError:
-            return False
+        error(f"❌ Mem0 记忆添加超时 (60s)，已等待 {time.time() - start:.2f}s")
-
+        return False
-        try:
-            await asyncio.wait_for(
-                self.mem0.add(
-                    messages,
-                    user_id=user_id,
-                    metadata={"type": "conversation"}
-                ),
-                timeout=60.0
-            )
-            info("📝 [记忆添加] 已提交给 Mem0 进行事实提取")
-            return True
-
-        except asyncio.TimeoutError:
-            error("❌ Mem0 记忆添加超时 (60s)")
-            return False
-        except Exception as e:
-            error(f"❌ Mem0 记忆添加失败: {e}")
-            return False

app/nodes/memory_trigger.py

@@ -31,8 +31,8 @@ async def memory_trigger_node(state: MessagesState, config: RunnableConfig) -> D
         if not _mem0_client._initialized:
             await _mem0_client.initialize()
         # 将用户消息作为事实来源提交给 Mem0
+        info(f"📌 检测到记忆指令，已主动触发 Mem0 存储")
         mem0_messages = [{"role": "user", "content": content}]
         await _mem0_client.add_memories(mem0_messages, user_id=user_id)
-        info(f"📌 检测到记忆指令，已主动触发 Mem0 存储")
 
     return {}  # 不修改状态

rag_core/client.py

@@ -3,6 +3,7 @@ import os
 from typing import Optional
 from qdrant_client import QdrantClient
 
+
 QDRANT_URL = os.getenv("QDRANT_URL", "http://127.0.0.1:6333")
 QDRANT_API_KEY = os.getenv("QDRANT_API_KEY")
 

rag_core/store/factory.py

@@ -10,8 +10,10 @@ from typing import Optional, Tuple
 
 from langchain_core.stores import BaseStore
 from rag_core.store.postgres import PostgresDocStore
+from dotenv import load_dotenv
+load_dotenv()
 
-logger = logging.getLogger(__name__)
+logger = logging.getLogger(__name__)        
 
 # 默认连接字符串（从环境变量读取）
 DEFAULT_DB_URI = os.getenv(