优化思考

.vscode/settings.json

@@ -1,5 +1,5 @@
 {
-  "python.languageServer": "Pylance",
+  "python.languageServer": "None",
   "python.analysis.indexing": true,
   "python.analysis.autoSearchPaths": true,
   "python.analysis.diagnosticMode": "workspace",

agent/guideline_middleware.py

@@ -4,6 +4,8 @@ from agent.prompt_loader import load_guideline_prompt
 from utils.fastapi_utils import (extract_block_from_system_prompt, format_messages_to_chat_history, get_user_last_message_content)
 from langchain.chat_models import BaseChatModel
 from langgraph.runtime import Runtime
+
+from langchain_core.messages import SystemMessage
 from typing import Any, Callable
 from langchain_core.callbacks import BaseCallbackHandler
 from langchain_core.outputs import LLMResult
@@ -48,13 +50,10 @@ Action: Provide concise, friendly, and personified natural responses.
     def get_guideline_prompt(self, messages: list[dict[str, Any]]) -> str:
         ## 处理terms
         terms_analysis = self.get_term_analysis(messages)
-
         guideline_prompt = ""
-
         if self.guidelines:
             chat_history = format_messages_to_chat_history(messages)
-            query_text = get_user_last_message_content(messages)
+            guideline_prompt = load_guideline_prompt(chat_history, self.guidelines, self.tool_description, self.scenarios, terms_analysis, self.language, self.user_identifier)
-            guideline_prompt = load_guideline_prompt(chat_history, query_text, self.guidelines, self.tool_description, self.scenarios, terms_analysis, self.language, self.user_identifier)
 
         return guideline_prompt
     
@@ -93,17 +92,27 @@ Action: Provide concise, friendly, and personified natural responses.
 
         guideline_prompt = self.get_guideline_prompt(convert_to_openai_messages(state['messages']))
 
+        # 准备完整的消息列表
+        messages = state['messages'].copy()
+
+        # 将guideline_prompt作为系统消息添加到消息列表
+        system_message = SystemMessage(content=guideline_prompt)
+
+        messages = [system_message,messages[-1]]
+
         # 使用回调处理器调用模型
         response = self.model.invoke(
-            guideline_prompt,
+            messages,
             config={"metadata": {"message_tag": "THINK"}}
         )
 
         response.additional_kwargs["message_tag"] = "THINK"
         response.content = f"<think>{response.content}</think>"
-        messages = state['messages']+[response]
+
+        # 将响应添加到原始消息列表
+        final_messages = state['messages'] + [response]
         return {
-            "messages": messages
+            "messages": final_messages
         }
         
     async def abefore_agent(self, state: AgentState, runtime: Runtime) -> dict[str, Any] | None:
@@ -112,17 +121,25 @@ Action: Provide concise, friendly, and personified natural responses.
         
         guideline_prompt = self.get_guideline_prompt(convert_to_openai_messages(state['messages']))
         
+        # 准备完整的消息列表
+        messages = state['messages'].copy()
+
+        # 将guideline_prompt作为系统消息添加到消息列表
+        system_message = SystemMessage(content=guideline_prompt)
+        messages = [system_message,messages[-1]]
+
         # 使用回调处理器调用模型
         response = await self.model.ainvoke(
-            guideline_prompt, 
+            messages,
             config={"metadata": {"message_tag": "THINK"}}
         )
         response.additional_kwargs["message_tag"] = "THINK"
         response.content = f"<think>{response.content}</think>"
 
-        messages = state['messages']+[response]
+        # 将响应添加到原始消息列表
+        final_messages = state['messages'] + [response]
         return {
-            "messages": messages
+            "messages": final_messages
         }
 
     def wrap_model_call(

agent/prompt_loader.py

@@ -244,7 +244,7 @@ async def load_mcp_settings_async(project_dir: str, mcp_settings: list=None, bot
     return merged_settings
 
 
-def load_guideline_prompt(chat_history: str, last_message: str, guidelines_text: str, tools: str, scenarios: str, terms: str, language: str, user_identifier: str = "") -> str:
+def load_guideline_prompt(chat_history:str, guidelines_text: str, tools: str, scenarios: str, terms: str, language: str, user_identifier: str = "") -> str:
     """
     加载并处理guideline提示词
 
@@ -275,7 +275,6 @@ def load_guideline_prompt(chat_history: str, last_message: str, guidelines_text:
     # 替换模板中的占位符
     system_prompt = guideline_template.format(
         chat_history=chat_history,
-        last_message=last_message,
         guidelines_text=guidelines_text,
         terms=terms,
         tools=tools,

prompt/guideline_prompt.md

@@ -28,11 +28,6 @@
 {chat_history}
 ```
 
-## 用户最新问题 (User's Last Message)
-```
-{last_message}
-```
-
 ## 工具列表 (Tools)
 ```
 {tools}

routes/chat.py

@@ -13,7 +13,6 @@ from utils import (
 )
 from agent.sharded_agent_manager import init_global_sharded_agent_manager
 from utils.api_models import ChatRequestV2
-from agent.prompt_loader import load_guideline_prompt
 from utils.fastapi_utils import (
     process_messages, format_messages_to_chat_history,
     create_project_directory, extract_api_key_from_auth, generate_v2_auth_token, fetch_bot_config,
@@ -31,8 +30,6 @@ agent_manager = init_global_sharded_agent_manager(
 )
 
 
-
-
 def append_user_last_message(messages: list, content: str) -> bool:
     """向最后一条用户消息追加内容
 

utils/fastapi_utils.py

@@ -357,7 +357,7 @@ def format_messages_to_chat_history(messages: List[Dict[str, str]]) -> str:
                     arguments = tool_call.get('function').get('arguments')
                     chat_history.append(f"{function_name} call: {arguments}")
 
-    recent_chat_history = chat_history[-15:] if len(chat_history) > 15 else chat_history
+    recent_chat_history = chat_history[-16:-1] if len(chat_history) > 16 else chat_history[:-1]
     return "\n".join(recent_chat_history)