preamble

prompt/preamble_prompt.md

@@ -4,13 +4,7 @@ The actual message will be sent later by a smarter agent. Your job is only to ge
 
 ## Scenario Detection Logic
 
-FIRST, determine if this is a SIMPLE CHAT scenario or COMPLEX scenario:
+FIRST, determine if this is a COMPLEX scenario that requires a preamble:
-
-**Simple Chat Scenarios (NO preamble needed - output "<empty>"):**
-- Basic greetings: "hi", "hello", "你好", "在吗", "早上好/晚上好"
-- Simple acknowledgments: "thanks", "ok", "好的", "谢谢"
-- Small talk: "how are you", "天气怎么样", "最近怎么样"
-- Simple farewells: "bye", "goodbye", "再见"
 
 **Complex Scenarios (preamble needed):**
 - Query scenarios: User is asking for information, searching, or looking up data
@@ -19,9 +13,16 @@ FIRST, determine if this is a SIMPLE CHAT scenario or COMPLEX scenario:
 - Problem-solving: User is reporting issues, asking for help with problems
 - Complex requests: Multi-step tasks, detailed instructions needed
 
+**ALL OTHER scenarios (output "<empty>"):**
+- Simple greetings: "hi", "hello", "你好", "在吗", "早上好/晚上好"
+- Simple acknowledgments: "thanks", "ok", "好的", "谢谢"
+- Small talk: "how are you", "天气怎么样", "最近怎么样"
+- Simple farewells: "bye", "goodbye", "再见"
+- Any other scenarios not explicitly listed as complex
+
 ## Preamble Selection
 
-IF this is a COMPLEX scenario, choose from these preamble messages. You must ONLY choose one of these: ###
+ONLY IF this is a COMPLEX scenario, choose from these preamble messages. You must ONLY choose one of these: ###
 {preamble_choices_text}
 ###
 
@@ -29,13 +30,13 @@ Basically, the preamble is something very short that continues the interaction n
 We leave that later response to another agent. Make sure you understand this.
 
 Instructions:
-- For SIMPLE CHAT scenarios: Always output preamble: "<empty>"
 - For COMPLEX scenarios:
   - Note that some of the choices are more generic, and some are more specific to a particular scenario.
   - If you're unsure what to choose --> prefer to go with a more generic, bland choice. This should be 80% of cases.
     Examples of generic choices: "Hey there!", "Just a moment.", "Hello.", "Got it."
   - If you see clear value in saying something more specific and nuanced --> then go with a more specific choice. This should be 20% or less of cases.
     Examples of specific choices: "Let me check that for you.", "Sorry to hear that.", "Thanks for your patience."
+- For ALL OTHER scenarios: Always output preamble: "<empty>"
 
 
 Chat History:
@@ -48,7 +49,7 @@ OUTPUT FORMAT:
 You must now choose the preamble message. You must produce a JSON object with a single key, "preamble", holding the preamble message as a string,
 EXACTLY as it is given (pay attention to subtleties like punctuation and copy your choice EXACTLY as it is given above).The content in JSON format needs to be wrapped in "```json" and "```".
 
-For SIMPLE CHAT scenarios:
+For ALL OTHER scenarios:
 ```json
 {
   "preamble": "<empty>"

routes/chat.py

@@ -311,30 +311,22 @@ 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]
-    pre_message_list: Optional[list]
 ):
     """增强的渐进式流式响应生成器"""
     try:
-        # 第一阶段：立即传输preamble_text
+        # 第一阶段：并行启动preamble_text生成和第二阶段处理
-        if pre_message_list:
+        query_text = get_user_last_message_content(messages)
-            chunk_data = {
+        chat_history = format_messages_to_chat_history(messages)
-                "id": f"chatcmpl-preamble",
-                "object": "chat.completion.chunk",
-                "created": int(__import__('time').time()),
-                "model": model_name,
-                "choices": [{
-                    "index": 0,
-                    "delta": {
-                        "content": get_content_from_messages(pre_message_list, tool_response=tool_response)
-                    },
-                    "finish_reason": None
-                }]
-            }
-            yield f"data: {json.dumps(chunk_data, ensure_ascii=False)}\n\n"
 
-        # 第二阶段：使用公共函数处理guideline分析和agent创建
+        # 创建preamble_text生成任务
-        agent, _, guideline_analysis, _ = await process_guidelines_and_terms(
+        preamble_task = asyncio.create_task(
+            call_preamble_llm(chat_history, query_text, get_preamble_text(language), language, model_name, api_key, model_server)
+        )
+
+        # 创建guideline分析和agent创建任务
+        guidelines_task = asyncio.create_task(
+            process_guidelines_and_terms(
                 bot_id=bot_id,
                 api_key=api_key,
                 model_name=model_name,
@@ -349,6 +341,35 @@ async def enhanced_generate_stream_response(
                 robot_type=robot_type,
                 user_identifier=user_identifier
             )
+        )
+
+        # 等待preamble_text任务完成
+        try:
+            preamble_text = await preamble_task
+            # 只有当preamble_text不为空且不为"<empty>"时才输出
+            if preamble_text and preamble_text.strip() and preamble_text != "<empty>":
+                chunk_data = {
+                    "id": f"chatcmpl-preamble",
+                    "object": "chat.completion.chunk",
+                    "created": int(__import__('time').time()),
+                    "model": model_name,
+                    "choices": [{
+                        "index": 0,
+                        "delta": {
+                            "content": get_content_from_messages([{"role": "assistant","content": preamble_text + "\n"}], tool_response=tool_response)
+                        },
+                        "finish_reason": None
+                    }]
+                }
+                yield f"data: {json.dumps(chunk_data, ensure_ascii=False)}\n\n"
+                logger.info(f"Stream mode: Generated preamble text ({len(preamble_text)} chars)")
+            else:
+                logger.info("Stream mode: Skipped empty preamble text")
+        except Exception as e:
+            logger.error(f"Error generating preamble text: {e}")
+
+        # 等待guideline分析任务完成
+        agent, _, guideline_analysis, _ = await guidelines_task
 
         # 立即发送guideline_analysis
         if guideline_analysis:
@@ -360,7 +381,7 @@ async def enhanced_generate_stream_response(
                 "choices": [{
                     "index": 0,
                     "delta": {
-                        "content": get_content_from_messages([{"role": "assistant","reasoning_content": guideline_analysis}], tool_response=tool_response)
+                        "content": get_content_from_messages([{"role": "assistant","reasoning_content": guideline_analysis+ "\n"}], tool_response=tool_response)
                     },
                     "finish_reason": None
                 }]
@@ -462,21 +483,6 @@ async def create_agent_and_generate_response(
     if generate_cfg is None:
         generate_cfg = {}
 
-    pre_message_list = []
-    # 只在stream=True时生成preamble_text
-    preamble_text = ""
-    if stream:
-        query_text = get_user_last_message_content(messages)
-        chat_history = format_messages_to_chat_history(messages)
-        preamble_text = await call_preamble_llm(chat_history, query_text, get_preamble_text(language), language, model_name, api_key, model_server)
-        # 只有当preamble_text不为空且不为"<empty>"时才添加到消息列表
-        if preamble_text and preamble_text.strip() and preamble_text != "<empty>":
-            pre_message_list.append({"role": "assistant","content": preamble_text+"\n"})
-            logger.info(f"Stream mode: Generated preamble text ({len(preamble_text)} chars)")
-        else:
-            logger.info("Stream mode: Skipped empty preamble text")
-
-
     # 如果是流式模式，使用增强的流式响应生成器
     if stream:
         return StreamingResponse(
@@ -494,8 +500,7 @@ 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
-                pre_message_list=pre_message_list
             ),
             media_type="text/event-stream",
             headers={"Cache-Control": "no-cache", "Connection": "keep-alive"}
@@ -526,7 +531,7 @@ async def create_agent_and_generate_response(
 
     if guideline_analysis:
         final_messages = append_user_last_message(final_messages, f"\n\nActive Guidelines:\n{guideline_analysis}\nPlease follow these guidelines in your response.")
-        pre_message_list.append({"role": "assistant","reasoning_content": guideline_analysis})
+        pre_message_list.append({"role": "assistant","reasoning_content": guideline_analysis+ "\n"})
 
     # 非流式响应
     agent_responses = agent.run_nonstream(final_messages)