fix：修复兴趣集未清空，模型失败导致planer失败，绘图插件配置文件问题

.gitignore

@@ -305,3 +305,4 @@ $RECYCLE.BIN/
 src/chat/focus_chat/working_memory/test/test1.txt
 src/chat/focus_chat/working_memory/test/test4.txt
 run_maiserver.bat
+src/plugins/test_plugin_pic/actions/pic_action_config.toml

src/chat/focus_chat/heartFC_chat.py

@@ -54,7 +54,7 @@ CONSECUTIVE_NO_REPLY_THRESHOLD = 3  # 连续不回复的阈值
 logger = get_logger("hfc")  # Logger Name Changed
 
 # 设定处理器超时时间（秒）
-PROCESSOR_TIMEOUT = 40
+PROCESSOR_TIMEOUT = 30
 
 
 async def _handle_cycle_delay(action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str):
@@ -329,11 +329,20 @@ class HeartFChatting:
                     formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒"
                     timer_strings.append(f"{name}: {formatted_time}")
 
+                # 新增：输出每个处理器的耗时
+                processor_time_costs = self._current_cycle.loop_processor_info.get("processor_time_costs", {})
+                processor_time_strings = []
+                for pname, ptime in processor_time_costs.items():
+                    formatted_ptime = f"{ptime * 1000:.2f}毫秒" if ptime < 1 else f"{ptime:.2f}秒"
+                    processor_time_strings.append(f"{pname}: {formatted_ptime}")
+                processor_time_log = ("\n各处理器耗时: " + "; ".join(processor_time_strings)) if processor_time_strings else ""
+
                 logger.info(
                     f"{self.log_prefix} 第{self._current_cycle.cycle_id}次思考,"
                     f"耗时: {self._current_cycle.end_time - self._current_cycle.start_time:.1f}秒, "
                     f"动作: {self._current_cycle.loop_plan_info['action_result']['action_type']}"
                     + (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "")
+                    + processor_time_log
                 )
 
                 await asyncio.sleep(global_config.focus_chat.think_interval)
@@ -369,18 +378,18 @@ class HeartFChatting:
 
     async def _process_processors(
         self, observations: List[Observation], running_memorys: List[Dict[str, Any]], cycle_timers: dict
-    ) -> List[InfoBase]:
+    ) -> tuple[List[InfoBase], Dict[str, float]]:
         # 记录并行任务开始时间
         parallel_start_time = time.time()
         logger.debug(f"{self.log_prefix} 开始信息处理器并行任务")
 
         processor_tasks = []
         task_to_name_map = {}
+        processor_time_costs = {}  # 新增: 记录每个处理器耗时
 
         for processor in self.processors:
             processor_name = processor.__class__.log_prefix
 
-            # 用lambda包裹，便于传参
             async def run_with_timeout(proc=processor):
                 return await asyncio.wait_for(
                     proc.process_info(observations=observations, running_memorys=running_memorys),
@@ -404,22 +413,24 @@ class HeartFChatting:
                 duration_since_parallel_start = task_completed_time - parallel_start_time
 
                 try:
-                    # 使用 await task 来获取结果或触发异常
                     result_list = await task
                     logger.info(f"{self.log_prefix} 处理器 {processor_name} 已完成!")
                     if result_list is not None:
                         all_plan_info.extend(result_list)
                     else:
                         logger.warning(f"{self.log_prefix} 处理器 {processor_name} 返回了 None")
+                    # 记录耗时
+                    processor_time_costs[processor_name] = duration_since_parallel_start
                 except asyncio.TimeoutError:
                     logger.info(f"{self.log_prefix} 处理器 {processor_name} 超时（>{PROCESSOR_TIMEOUT}s），已跳过")
+                    processor_time_costs[processor_name] = PROCESSOR_TIMEOUT
                 except Exception as e:
                     logger.error(
                         f"{self.log_prefix} 处理器 {processor_name} 执行失败，耗时 (自并行开始): {duration_since_parallel_start:.2f}秒. 错误: {e}",
                         exc_info=True,
                     )
                     traceback.print_exc()
-                    # 即使出错，也认为该任务结束了，已从 pending_tasks 中移除
+                    processor_time_costs[processor_name] = duration_since_parallel_start
 
             if pending_tasks:
                 current_progress_time = time.time()
@@ -435,12 +446,11 @@ class HeartFChatting:
         logger.info(f"{self.log_prefix} 所有处理器任务全部完成，总耗时: {total_duration:.2f}秒")
         # logger.debug(f"{self.log_prefix} 所有信息处理器处理后的信息: {all_plan_info}")
 
-        return all_plan_info
+        return all_plan_info, processor_time_costs
 
     async def _observe_process_plan_action_loop(self, cycle_timers: dict, thinking_id: str) -> dict:
         try:
             with Timer("观察", cycle_timers):
-                # await self.observations[0].observe()
                 await self.chatting_observation.observe()
                 await self.working_observation.observe()
                 await self.hfcloop_observation.observe()
@@ -461,10 +471,11 @@ class HeartFChatting:
                 running_memorys = await self.memory_activator.activate_memory(observations)
 
             with Timer("执行 信息处理器", cycle_timers):
-                all_plan_info = await self._process_processors(observations, running_memorys, cycle_timers)
+                all_plan_info, processor_time_costs = await self._process_processors(observations, running_memorys, cycle_timers)
 
                 loop_processor_info = {
                     "all_plan_info": all_plan_info,
+                    "processor_time_costs": processor_time_costs,
                 }
 
             with Timer("规划器", cycle_timers):
@@ -483,7 +494,6 @@ class HeartFChatting:
                     plan_result.get("action_result", {}).get("reasoning", "未提供理由"),
                 )
 
-                # 在此处添加日志记录
                 if action_type == "reply":
                     action_str = "回复"
                 elif action_type == "no_reply":

src/chat/focus_chat/info_processors/self_processor.py

@@ -185,7 +185,7 @@ class SelfProcessor(BaseProcessor):
         if content == "None":
             content = ""
         # 记录初步思考结果
-        logger.debug(f"{self.log_prefix} 自我识别prompt: \n{prompt}\n")
+        # logger.debug(f"{self.log_prefix} 自我识别prompt: \n{prompt}\n")
         logger.info(f"{self.log_prefix} 自我认知: {content}")
 
         return content

src/chat/focus_chat/info_processors/working_memory_processor.py

@@ -127,7 +127,7 @@ class WorkingMemoryProcessor(BaseProcessor):
         # 调用LLM处理记忆
         content = ""
         try:
-            logger.debug(f"{self.log_prefix} 处理工作记忆的prompt: {prompt}")
+            # logger.debug(f"{self.log_prefix} 处理工作记忆的prompt: {prompt}")
 
             content, _ = await self.llm_model.generate_response_async(prompt=prompt)
             if not content:

src/chat/focus_chat/memory_activator.py

@@ -107,11 +107,11 @@ class MemoryActivator:
             cached_keywords=cached_keywords_str,
         )
 
-        logger.debug(f"prompt: {prompt}")
+        # logger.debug(f"prompt: {prompt}")
 
         response = await self.summary_model.generate_response(prompt)
 
-        logger.debug(f"response: {response}")
+        # logger.debug(f"response: {response}")
 
         # 只取response的第一个元素（字符串）
         response_str = response[0]
@@ -127,7 +127,7 @@ class MemoryActivator:
 
             # 添加新的关键词到缓存
             self.cached_keywords.update(keywords)
-            logger.debug(f"更新关键词缓存: {self.cached_keywords}")
+            logger.debug(f"当前激活的记忆关键词: {self.cached_keywords}")
 
         # 调用记忆系统获取相关记忆
         related_memory = await HippocampusManager.get_instance().get_memory_from_topic(

src/chat/focus_chat/planners/planner.py

@@ -130,6 +130,7 @@ class ActionPlanner:
             current_mind = ""
             cycle_info = ""
             structured_info = ""
+            is_group_chat = True
             for info in all_plan_info:
                 if isinstance(info, ObsInfo):
                     observed_messages = info.get_talking_message()

src/chat/heart_flow/observation/chatting_observation.py

@@ -179,7 +179,7 @@ class ChattingObservation(Observation):
             "processed_plain_text": find_msg.get("processed_plain_text"),
         }
         find_rec_msg = MessageRecv(message_dict)
-        logger.debug(f"锚定消息处理后：find_rec_msg: {find_rec_msg}")
+        # logger.debug(f"锚定消息处理后：find_rec_msg: {find_rec_msg}")
         return find_rec_msg
 
     async def observe(self):

src/chat/heart_flow/sub_heartflow.py

@@ -111,6 +111,8 @@ class SubHeartflow:
         """
         await self._stop_heart_fc_chat()  # 确保 专注聊天已停止
 
+        self.interest_dict.clear()
+
         log_prefix = self.log_prefix
         try:
             # 获取聊天流并创建 NormalChat 实例 (同步部分)

src/plugins/test_plugin_pic/actions/generate_pic_config.py

@@ -1,20 +1,15 @@
 import os
 
 CONFIG_CONTENT = """\
-# 请替换为您的火山引擎 Access Key ID
-volcano_ak = "YOUR_VOLCANO_ENGINE_ACCESS_KEY_ID_HERE"
-# 请替换为您的火山引擎 Secret Access Key
-volcano_sk = "YOUR_VOLCANO_ENGINE_SECRET_ACCESS_KEY_HERE"
 # 火山方舟 API 的基础 URL
 base_url = "https://ark.cn-beijing.volces.com/api/v3"
+# 用于图片生成的API密钥
+volcano_generate_api_key = "YOUR_VOLCANO_GENERATE_API_KEY_HERE"
 # 默认图片生成模型
 default_model = "doubao-seedream-3-0-t2i-250415"
 # 默认图片尺寸
 default_size = "1024x1024"
-# 用于图片生成的API密钥
+
-# PicAction 当前配置为在HTTP请求体和Authorization头中使用此密钥。
-# 如果您的API认证方式不同，请相应调整或移除。
-volcano_generate_api_key = "YOUR_VOLCANO_GENERATE_API_KEY_HERE"
 
 # 是否默认开启水印
 default_watermark = true
@@ -38,7 +33,7 @@ def generate_config():
             with open(config_file_path, "w", encoding="utf-8") as f:
                 f.write(CONFIG_CONTENT)
             print(f"配置文件已生成: {config_file_path}")
-            print("请记得编辑该文件，填入您的火山引擎 AK/SK 和 API 密钥。")
+            print("请记得编辑该文件，填入您的火山引擎API 密钥。")
         except IOError as e:
             print(f"错误：无法写入配置文件 {config_file_path}。原因: {e}")
     else:

src/plugins/test_plugin_pic/actions/pic_action.py

@@ -22,7 +22,7 @@ class PicAction(PluginAction):
     """根据描述使用火山引擎HTTP API生成图片的动作处理类"""
 
     action_name = "pic_action"
-    action_description = "可以根据特定的描述，使用火山引擎模型生成并发送一张图片 (通过HTTP API)"
+    action_description = "可以根据特定的描述，生成并发送一张图片，如果没提供描述，就根据聊天内容生成"
     action_parameters = {
         "description": "图片描述，输入你想要生成并发送的图片的描述，必填",
         "size": "图片尺寸，例如 '1024x1024' (可选, 默认从配置或 '1024x1024')",
@@ -31,7 +31,7 @@ class PicAction(PluginAction):
         "当有人要求你生成并发送一张图片时使用",
         "当有人让你画一张图时使用",
     ]
-    default = False
+    default = True
     action_config_file_name = "pic_action_config.toml"
 
     def __init__(

src/plugins/test_plugin_pic/actions/pic_action_config.toml

@@ -1,24 +0,0 @@
-# 请替换为您的火山引擎 Access Key ID
-volcano_ak = "YOUR_VOLCANO_ENGINE_ACCESS_KEY_ID_HERE"
-# 请替换为您的火山引擎 Secret Access Key
-volcano_sk = "YOUR_VOLCANO_ENGINE_SECRET_ACCESS_KEY_HERE"
-# 火山方舟 API 的基础 URL
-base_url = "https://ark.cn-beijing.volces.com/api/v3"
-# 默认图片生成模型
-default_model = "doubao-seedream-3-0-t2i-250415"
-# 默认图片尺寸
-default_size = "1024x1024"
-# 用于图片生成的API密钥
-# PicAction 当前配置为在HTTP请求体和Authorization头中使用此密钥。
-# 如果您的API认证方式不同，请相应调整或移除。
-volcano_generate_api_key = "YOUR_VOLCANO_GENERATE_API_KEY_HERE"
-
-# 是否默认开启水印
-default_watermark = true
-# 默认引导强度
-default_guidance_scale = 2.5
-# 默认随机种子
-default_seed = 42
-
-# 更多插件特定配置可以在此添加...
-# custom_parameter = "some_value"