add guideline

fastapi_app.py

@@ -1154,6 +1154,38 @@ async def call_guideline_llm(chat_history: str, guidelines_text: str, model_name
         return ""
 
 
+def _get_optimal_batch_size(guidelines_count: int) -> int:
+    """根据guidelines数量决定最优批次数量（并发数）"""
+    if guidelines_count <= 10:
+        return 1
+    elif guidelines_count <= 20:
+        return 2
+    elif guidelines_count <= 30:
+        return 3
+    else:
+        return 5
+
+
+async def process_guideline_batch(
+    guidelines_batch: List[str],
+    chat_history: str,
+    model_name: str,
+    api_key: str,
+    model_server: str
+) -> str:
+    """处理单个guideline批次"""
+    try:
+        # 调用LLM分析这批guidelines
+        batch_guidelines_text = "\n".join(guidelines_batch)
+        batch_analysis = await call_guideline_llm(chat_history, batch_guidelines_text, model_name, api_key, model_server)
+
+        return batch_analysis
+    except Exception as e:
+        print(f"Error processing guideline batch: {e}")
+        return ""
+
+
+
 async def create_agent_and_generate_response(
     bot_id: str,
     api_key: str,
@@ -1176,35 +1208,110 @@ async def create_agent_and_generate_response(
 
     # 1. 从system_prompt提取guideline内容
     guidelines_text = extract_guidelines_from_system_prompt(system_prompt)
+    print(f"guidelines_text: {guidelines_text}")
 
-    # 2. 如果有guideline内容，调用LLM进行分析
+    # 2. 如果有guideline内容，进行并发处理
     guideline_analysis = ""
     if guidelines_text:
-        chat_history = format_messages_to_chat_history(messages)
+        # 按换行符分割guidelines
-        guideline_analysis = await call_guideline_llm(chat_history, guidelines_text, model_name, api_key, model_server)
+        guidelines_list = [g.strip() for g in guidelines_text.split('\n') if g.strip()]
-        print(f"Guideline analysis result: {guideline_analysis}")
+        guidelines_count = len(guidelines_list)
 
-        # 将分析结果添加到最后一个消息的内容中
+        if guidelines_count > 0:
-        if guideline_analysis and messages:
+            # 获取最优批次数量（并发数）
-            last_message = messages[-1]
+            batch_count = _get_optimal_batch_size(guidelines_count)
-            if last_message.get('role') == 'user':
-                messages[-1]['content'] += f"\n\nActive Guidelines:\n{guideline_analysis}\nPlease follow these guidelines in your response."
-                print(messages[-1]['content'])
 
-    # 从全局管理器获取或创建助手实例
+            # 计算每个批次应该包含多少条guideline
-    agent = await agent_manager.get_or_create_agent(
+            guidelines_per_batch = max(1, guidelines_count // batch_count)
-        bot_id=bot_id,
+            
-        project_dir=project_dir,
+            # 分批处理guidelines
-        model_name=model_name,
+            batches = []
-        api_key=api_key,
+            for i in range(0, guidelines_count, guidelines_per_batch):
-        model_server=model_server,
+                batch = guidelines_list[i:i + guidelines_per_batch]
-        generate_cfg=generate_cfg,
+                batches.append(batch)
-        language=language,
+            
-        system_prompt=system_prompt,
+            # 确保批次数量不超过要求的并发数
-        mcp_settings=mcp_settings,
+            while len(batches) > batch_count:
-        robot_type=robot_type,
+                # 将最后一个批次合并到倒数第二个批次
-        user_identifier=user_identifier
+                batches[-2].extend(batches[-1])
-    )
+                batches.pop()
+
+            print(f"Processing {guidelines_count} guidelines in {len(batches)} batches with {batch_count} concurrent batches")
+
+            # 准备chat_history
+            chat_history = format_messages_to_chat_history(messages)
+
+            # 并发执行所有任务：guideline批次处理 + agent创建
+            import asyncio
+            tasks = []
+
+            # 添加所有guideline批次任务
+            for batch in batches:
+                task = process_guideline_batch(
+                    guidelines_batch=batch,
+                    chat_history=chat_history,
+                    model_name=model_name,
+                    api_key=api_key,
+                    model_server=model_server
+                )
+                tasks.append(task)
+
+            # 添加agent创建任务
+            agent_task = agent_manager.get_or_create_agent(
+                bot_id=bot_id,
+                project_dir=project_dir,
+                model_name=model_name,
+                api_key=api_key,
+                model_server=model_server,
+                generate_cfg=generate_cfg,
+                language=language,
+                system_prompt=system_prompt,
+                mcp_settings=mcp_settings,
+                robot_type=robot_type,
+                user_identifier=user_identifier
+            )
+            tasks.append(agent_task)
+
+            # 等待所有任务完成
+            all_results = await asyncio.gather(*tasks, return_exceptions=True)
+
+            # 处理结果：最后一个结果是agent，前面的是guideline批次结果
+            agent = all_results[-1]  # agent创建的结果
+            batch_results = all_results[:-1]  # guideline批次的结果
+
+            # 合并guideline分析结果
+            valid_results = []
+            for i, result in enumerate(batch_results):
+                if isinstance(result, Exception):
+                    print(f"Guideline batch {i} failed: {result}")
+                    continue
+                if result and result.strip():
+                    valid_results.append(result.strip())
+
+            if valid_results:
+                guideline_analysis = "\n\n".join(valid_results)
+                print(f"Merged guideline analysis result: {guideline_analysis}")
+
+                # 将分析结果添加到最后一个消息的内容中
+                if guideline_analysis and messages:
+                    last_message = messages[-1]
+                    if last_message.get('role') == 'user':
+                        messages[-1]['content'] += f"\n\nActive Guidelines:\n{guideline_analysis}\nPlease follow these guidelines in your response."
+    else:
+        # 3. 从全局管理器获取或创建助手实例
+        agent = await agent_manager.get_or_create_agent(
+            bot_id=bot_id,
+            project_dir=project_dir,
+            model_name=model_name,
+            api_key=api_key,
+            model_server=model_server,
+            generate_cfg=generate_cfg,
+            language=language,
+            system_prompt=system_prompt,
+            mcp_settings=mcp_settings,
+            robot_type=robot_type,
+            user_identifier=user_identifier
+        )
 
     # 根据stream参数决定返回流式还是非流式响应
     if stream:

prompt/guideline_prompt.md

@@ -13,9 +13,7 @@ to the most recent state of an interaction between yourself (an AI agent) and a
 
 Examples of Guideline Match Evaluations:
 ```
-  示例 1: 旅游咨询
+  Example #1: travel consultation
-
-  Example #1: ###
   - **Chat History**:
     user: Hi, I'm planning a trip to Italy next month. What can I do there?
     ai_agent: That sounds exciting! I can help you with that. Do you prefer exploring cities or enjoying scenic landscapes?
@@ -52,9 +50,8 @@ Examples of Guideline Match Evaluations:
     ]
   }
   ```
-  示例 2: 课程咨询
 
-  Example #2: ###
+  Example #2: Course Consultation
   - **Chat History**:
     user:Hi, I'm interested in your Python programming course, but I'm not sure if I'm ready for it.
     ai_agent:Happy to help! Could you share a bit about your background or experience with programming so far?
@@ -93,9 +90,7 @@ Examples of Guideline Match Evaluations:
   }
   ```
 
-  示例 3: 登录问题
+  Example #3: Login issue
-
-  Example #3: ###
   - **Chat History**:
   user:I'm having trouble logging into my account.
   ai_agent:I'm sorry to hear that. Can you tell me what happens when you try to log in?
@@ -119,9 +114,7 @@ Examples of Guideline Match Evaluations:
     ]
   }
 
-  示例 4: 退货政策
+  Example #4: Return Policy
-
-  Example #4: ###
   - **Chat History**:
   user: Hi, I'm thinking about ordering this coat, but I need to know — what's your return policy?
   ai_agent: You can return items within 30 days either in-store or using our prepaid return label.
@@ -152,6 +145,7 @@ Guidelines List:
 {guidelines_text}
 
 OUTPUT FORMAT:
+The content in JSON format needs to be wrapped in "```json" and "```".
 Please specify the applicability of each guideline:
 ```json
 {{