session_id

agent/deep_assistant.py

@@ -1,15 +1,22 @@
 import json
 import logging
+import os
+import sqlite3
 from typing import Any, Dict, Optional
 from langchain.chat_models import init_chat_model
 # from deepagents import create_deep_agent
 from langchain.agents import create_agent
+from langchain.agents.middleware import SummarizationMiddleware
 from langchain_mcp_adapters.client import MultiServerMCPClient
 from langchain_core.callbacks import BaseCallbackHandler
+from langgraph.checkpoint.memory import MemorySaver
 from utils.fastapi_utils import detect_provider
 
 from .guideline_middleware import GuidelineMiddleware
 
+MAX_CONTEXT_TOKENS = int(os.getenv("MAX_CONTEXT_TOKENS", 65536))
+MAX_OUTPUT_TOKENS = int(os.getenv("MAX_OUTPUT_TOKENS", 8000))
+SUMMARIZATION_MAX_TOKENS = MAX_CONTEXT_TOKENS - MAX_OUTPUT_TOKENS - 1000
 
 class LoggingCallbackHandler(BaseCallbackHandler):
     """自定义的 CallbackHandler，使用项目的 logger 来记录日志"""
@@ -120,7 +127,24 @@ async def get_tools_from_mcp(mcp):
 
 async def init_agent(bot_id: str, model_name="qwen3-next", api_key=None,
                     model_server=None, generate_cfg=None,
-                    system_prompt=None, mcp=None, robot_type=None, language="jp", user_identifier=None):
+                    system_prompt=None, mcp=None, robot_type=None, language="jp", user_identifier=None,
+                    session_id=None):
+    """
+    初始化 Agent，支持持久化内存和对话摘要
+
+    Args:
+        bot_id: Bot ID
+        model_name: 模型名称
+        api_key: API密钥
+        model_server: 模型服务器地址
+        generate_cfg: 生成配置
+        system_prompt: 系统提示
+        mcp: MCP配置
+        robot_type: 机器人类型
+        language: 语言
+        user_identifier: 用户标识
+        session_id: 会话ID（如果为None，则不启用持久化内存）
+    """
     system = system_prompt if system_prompt else read_system_prompt()
     mcp = mcp if mcp else read_mcp_settings()
     mcp_tools = await get_tools_from_mcp(mcp)
@@ -143,14 +167,33 @@ async def init_agent(bot_id: str, model_name="qwen3-next", api_key=None,
     # 创建自定义的日志处理器
     logging_handler = LoggingCallbackHandler()
 
+    # 构建中间件列表
+    middleware = [GuidelineMiddleware(bot_id, llm_instance, system, robot_type, language, user_identifier)]
+
+    # 初始化 checkpointer 和中间件
+    checkpointer = None
+
+    if session_id:
+        checkpointer = MemorySaver()
+        summarization_middleware = SummarizationMiddleware(
+            model=llm_instance,  
+            max_tokens_before_summary=SUMMARIZATION_MAX_TOKENS, 
+            messages_to_keep=20,  # 摘要后保留最近 20 条消息
+            summary_prompt="请简洁地总结以上对话的要点，包括重要的用户信息、讨论过的话题和关键结论。"
+        )
+        middleware.append(summarization_middleware)
+
     agent = create_agent(
         model=llm_instance,
         system_prompt=system,
         tools=mcp_tools,
-        middleware=[GuidelineMiddleware(bot_id, llm_instance, system, robot_type, language, user_identifier)]
+        middleware=middleware,
+        checkpointer=checkpointer  # 传入 checkpointer 以启用持久化
     )
 
-    # 将 handler 存储在 agent 的属性中，方便在调用时使用
+    # 将 handler 和 checkpointer 存储在 agent 的属性中，方便在调用时使用
     agent.logging_handler = logging_handler
-
+    agent.checkpointer = checkpointer
+    agent.bot_id = bot_id
+    agent.session_id = session_id
     return agent

agent/sharded_agent_manager.py

@@ -127,7 +127,8 @@ class ShardedAgentManager:
                                  system_prompt: Optional[str] = None,
                                  mcp_settings: Optional[List[Dict]] = None,
                                  robot_type: Optional[str] = "general_agent",
-                                 user_identifier: Optional[str] = None):
+                                 user_identifier: Optional[str] = None,
+                                 session_id: Optional[str] = None):
         """获取或创建文件预加载的助手实例"""
         
         # 更新请求统计
@@ -201,6 +202,7 @@ class ShardedAgentManager:
                 robot_type=robot_type,
                 language=language,
                 user_identifier=user_identifier,
+                session_id=session_id
             )
             
             # 缓存实例

routes/chat.py

@@ -82,7 +82,8 @@ async def enhanced_generate_stream_response(
     robot_type: str,
     project_dir: Optional[str],
     generate_cfg: Optional[dict],
-    user_identifier: Optional[str]
+    user_identifier: Optional[str],
+    session_id: Optional[str] = None,
 ):
     """增强的渐进式流式响应生成器 - 并发优化版本"""
     try:
@@ -133,7 +134,8 @@ async def enhanced_generate_stream_response(
                     system_prompt=system_prompt,
                     mcp_settings=mcp_settings,
                     robot_type=robot_type,
-                    user_identifier=user_identifier
+                    user_identifier=user_identifier,
+                    session_id=session_id,
                 )
                 
                 # 开始流式处理
@@ -141,7 +143,11 @@ async def enhanced_generate_stream_response(
                 chunk_id = 0
                 message_tag = ""
                 
-                config = {"callbacks": [agent.logging_handler]} if hasattr(agent, 'logging_handler') else {}
+                config = {}
+                if session_id:
+                    config["configurable"] = {"thread_id": session_id}
+                if hasattr(agent, 'logging_handler'):
+                    config["callbacks"] = [agent.logging_handler]
                 async for msg, metadata in agent.astream({"messages": messages}, stream_mode="messages", config=config):
                     new_content = ""
                     
@@ -265,7 +271,8 @@ async def create_agent_and_generate_response(
     robot_type: str,
     project_dir: Optional[str] = None,
     generate_cfg: Optional[dict] = None,
-    user_identifier: Optional[str] = None
+    user_identifier: Optional[str] = None,
+    session_id: Optional[str] = None
 ) -> Union[ChatResponse, StreamingResponse]:
     """创建agent并生成响应的公共逻辑"""
     if generate_cfg is None:
@@ -288,7 +295,8 @@ async def create_agent_and_generate_response(
                 robot_type=robot_type,
                 project_dir=project_dir,
                 generate_cfg=generate_cfg,
-                user_identifier=user_identifier
+                user_identifier=user_identifier,
+                session_id=session_id
             ),
             media_type="text/event-stream",
             headers={"Cache-Control": "no-cache", "Connection": "keep-alive"}
@@ -307,14 +315,19 @@ async def create_agent_and_generate_response(
         system_prompt=system_prompt,
         mcp_settings=mcp_settings,
         robot_type=robot_type,
-        user_identifier=user_identifier
+        user_identifier=user_identifier,
+        session_id=session_id,
     )
 
     # 准备最终的消息
     final_messages = messages.copy()
 
     # 非流式响应
-    config = {"callbacks": [agent.logging_handler]} if hasattr(agent, 'logging_handler') else {}
+    config = {}
+    if session_id:
+        config["configurable"] = {"thread_id": session_id}
+    if hasattr(agent, 'logging_handler'):
+        config["callbacks"] = [agent.logging_handler]
     agent_responses = await agent.ainvoke({"messages": final_messages}, config=config)
     append_messages = agent_responses["messages"][len(final_messages):]
     response_text = ""
@@ -396,7 +409,7 @@ async def chat_completions(request: ChatRequest, authorization: Optional[str] =
         project_dir = create_project_directory(request.dataset_ids, bot_id, request.robot_type)
         
         # 收集额外参数作为 generate_cfg
-        exclude_fields = {'messages', 'model', 'model_server', 'dataset_ids', 'language', 'tool_response', 'system_prompt', 'mcp_settings' ,'stream', 'robot_type', 'bot_id', 'user_identifier'}
+        exclude_fields = {'messages', 'model', 'model_server', 'dataset_ids', 'language', 'tool_response', 'system_prompt', 'mcp_settings' ,'stream', 'robot_type', 'bot_id', 'user_identifier', 'session_id'}
         generate_cfg = {k: v for k, v in request.model_dump().items() if k not in exclude_fields}
         
         # 处理消息
@@ -417,7 +430,8 @@ async def chat_completions(request: ChatRequest, authorization: Optional[str] =
             robot_type=request.robot_type,
             project_dir=project_dir,
             generate_cfg=generate_cfg,
-            user_identifier=request.user_identifier
+            user_identifier=request.user_identifier,
+            session_id=request.session_id
         )
 
     except Exception as e:

utils/api_models.py

@@ -52,6 +52,7 @@ class ChatRequest(BaseModel):
     mcp_settings: Optional[List[Dict]] = None
     robot_type: Optional[str] = "general_agent"
     user_identifier: Optional[str] = ""
+    session_id: Optional[str] = None
 
 
 class ChatRequestV2(BaseModel):
@@ -61,6 +62,7 @@ class ChatRequestV2(BaseModel):
     bot_id: str
     language: Optional[str] = "zh"
     user_identifier: Optional[str] = ""
+    session_id: Optional[str] = None
 
 
 class FileProcessRequest(BaseModel):