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🤖 自动格式化代码 [skip ci]

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github-actions[bot]
2025-04-18 03:37:20 +00:00
parent c0dcd578c9
commit dfe788c65c
12 changed files with 610 additions and 487 deletions
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147
src/plugins/chat_module/heartFC_chat/heartFC_chat.py
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@@ -33,15 +33,16 @@ logger = get_module_logger("heartFC_chat", config=chat_config)
# 新增常量
INTEREST_MONITOR_INTERVAL_SECONDS = 1
class HeartFC_Chat:
_instance = None # For potential singleton access if needed by MessageManager
_instance = None # For potential singleton access if needed by MessageManager
def __init__(self):
# --- Updated Init ---
if HeartFC_Chat._instance is not None:
# Prevent re-initialization if used as a singleton
return
self.logger = logger # Make logger accessible via self
self.logger = logger # Make logger accessible via self
self.gpt = ResponseGenerator()
self.mood_manager = MoodManager.get_instance()
self.mood_manager.start_mood_update()
@@ -52,13 +53,14 @@ class HeartFC_Chat:
self.pf_chatting_instances: Dict[str, PFChatting] = {}
self._pf_chatting_lock = Lock()
# --- End New PFChatting Management ---
HeartFC_Chat._instance = self # Register instance
HeartFC_Chat._instance = self # Register instance
# --- End Updated Init ---
# --- Added Class Method for Singleton Access ---
@classmethod
def get_instance(cls):
return cls._instance
# --- End Added Class Method ---
async def start(self):
@@ -76,8 +78,8 @@ class HeartFC_Chat:
self._interest_monitor_task = loop.create_task(self._interest_monitor_loop())
logger.info(f"兴趣监控任务已创建。监控间隔: {INTEREST_MONITOR_INTERVAL_SECONDS}秒。")
except RuntimeError:
logger.error("创建兴趣监控任务失败：没有运行中的事件循环。")
raise
logger.error("创建兴趣监控任务失败：没有运行中的事件循环。")
raise
else:
logger.warning("跳过兴趣监控任务创建：任务已存在或正在运行。")
@@ -95,6 +97,7 @@ class HeartFC_Chat:
return None
self.pf_chatting_instances[stream_id] = instance
return self.pf_chatting_instances[stream_id]
# --- End Added PFChatting Instance Manager ---
async def _interest_monitor_loop(self):
@@ -107,7 +110,7 @@ class HeartFC_Chat:
# logger.trace(f"检查 {len(active_stream_ids)} 个活跃流是否足以开启心流对话...") # 调试日志
for stream_id in active_stream_ids:
stream_name = chat_manager.get_stream_name(stream_id) or stream_id # 获取流名称
stream_name = chat_manager.get_stream_name(stream_id) or stream_id # 获取流名称
sub_hf = heartflow.get_subheartflow(stream_id)
if not sub_hf:
logger.warning(f"监控循环: 无法获取活跃流 {stream_name} 的 sub_hf")
@@ -121,7 +124,9 @@ class HeartFC_Chat:
# if should_trigger:
# logger.info(f"[{stream_name}] 基于兴趣概率决定启动交流模式 (概率: {interest_chatting.current_reply_probability:.4f})。")
else:
logger.trace(f"[{stream_name}] 没有找到对应的 InterestChatting 实例，跳过基于兴趣的触发检查。")
logger.trace(
f"[{stream_name}] 没有找到对应的 InterestChatting 实例，跳过基于兴趣的触发检查。"
)
except Exception as e:
logger.error(f"检查兴趣触发器时出错 流 {stream_name}: {e}")
logger.error(traceback.format_exc())
@@ -140,7 +145,7 @@ class HeartFC_Chat:
except Exception as e:
logger.error(f"兴趣监控循环错误: {e}")
logger.error(traceback.format_exc())
await asyncio.sleep(5) # 发生错误时等待
await asyncio.sleep(5) # 发生错误时等待
async def _create_thinking_message(self, anchor_message: Optional[MessageRecv]):
"""创建思考消息 (尝试锚定到 anchor_message)"""
@@ -162,14 +167,16 @@ class HeartFC_Chat:
message_id=thinking_id,
chat_stream=chat,
bot_user_info=bot_user_info,
reply=anchor_message, # 回复的是锚点消息
reply=anchor_message, # 回复的是锚点消息
thinking_start_time=thinking_time_point,
)
MessageManager().add_message(thinking_message)
return thinking_id
async def _send_response_messages(self, anchor_message: Optional[MessageRecv], response_set: List[str], thinking_id) -> Optional[MessageSending]:
async def _send_response_messages(
self, anchor_message: Optional[MessageRecv], response_set: List[str], thinking_id
) -> Optional[MessageSending]:
"""发送回复消息 (尝试锚定到 anchor_message)"""
if not anchor_message or not anchor_message.chat_stream:
logger.error("无法发送回复，缺少有效的锚点消息或聊天流。")
@@ -184,7 +191,7 @@ class HeartFC_Chat:
container.messages.remove(msg)
break
if not thinking_message:
stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id # 获取流名称
stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id # 获取流名称
logger.warning(f"[{stream_name}] 未找到对应的思考消息 {thinking_id}，可能已超时被移除")
return None
@@ -195,16 +202,16 @@ class HeartFC_Chat:
for msg_text in response_set:
message_segment = Seg(type="text", data=msg_text)
bot_message = MessageSending(
message_id=thinking_id, # 使用 thinking_id 作为批次标识
message_id=thinking_id, # 使用 thinking_id 作为批次标识
chat_stream=chat,
bot_user_info=UserInfo(
user_id=global_config.BOT_QQ,
user_nickname=global_config.BOT_NICKNAME,
platform=anchor_message.message_info.platform,
),
sender_info=anchor_message.message_info.user_info, # 发送给锚点消息的用户
sender_info=anchor_message.message_info.user_info, # 发送给锚点消息的用户
message_segment=message_segment,
reply=anchor_message, # 回复锚点消息
reply=anchor_message, # 回复锚点消息
is_head=not mark_head,
is_emoji=False,
thinking_start_time=thinking_start_time,
@@ -214,19 +221,19 @@ class HeartFC_Chat:
first_bot_msg = bot_message
message_set.add_message(bot_message)
if message_set.messages: # 确保有消息才添加
if message_set.messages: # 确保有消息才添加
MessageManager().add_message(message_set)
return first_bot_msg
else:
stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id # 获取流名称
stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id # 获取流名称
logger.warning(f"[{stream_name}] 没有生成有效的回复消息集，无法发送。")
return None
async def _handle_emoji(self, anchor_message: Optional[MessageRecv], response_set, send_emoji=""):
"""处理表情包 (尝试锚定到 anchor_message)"""
if not anchor_message or not anchor_message.chat_stream:
logger.error("无法处理表情包，缺少有效的锚点消息或聊天流。")
return
logger.error("无法处理表情包，缺少有效的锚点消息或聊天流。")
return
chat = anchor_message.chat_stream
if send_emoji:
@@ -242,7 +249,7 @@ class HeartFC_Chat:
thinking_time_point = round(time.time(), 2)
message_segment = Seg(type="emoji", data=emoji_cq)
bot_message = MessageSending(
message_id="me" + str(thinking_time_point), # 使用不同的 ID 前缀?
message_id="me" + str(thinking_time_point), # 使用不同的 ID 前缀?
chat_stream=chat,
bot_user_info=UserInfo(
user_id=global_config.BOT_QQ,
@@ -251,7 +258,7 @@ class HeartFC_Chat:
),
sender_info=anchor_message.message_info.user_info,
message_segment=message_segment,
reply=anchor_message, # 回复锚点消息
reply=anchor_message, # 回复锚点消息
is_head=False,
is_emoji=True,
)
@@ -260,8 +267,8 @@ class HeartFC_Chat:
async def _update_relationship(self, anchor_message: Optional[MessageRecv], response_set):
"""更新关系情绪 (尝试基于 anchor_message)"""
if not anchor_message or not anchor_message.chat_stream:
logger.error("无法更新关系情绪，缺少有效的锚点消息或聊天流。")
return
logger.error("无法更新关系情绪，缺少有效的锚点消息或聊天流。")
return
# 关系更新依赖于理解回复是针对谁的，以及原始消息的上下文
# 这里的实现可能需要调整，取决于关系管理器如何工作
@@ -269,18 +276,18 @@ class HeartFC_Chat:
# 注意：anchor_message.processed_plain_text 是锚点消息的文本，不一定是思考的全部上下文
stance, emotion = await self.gpt._get_emotion_tags(ori_response, anchor_message.processed_plain_text)
await relationship_manager.calculate_update_relationship_value(
chat_stream=anchor_message.chat_stream, # 使用锚点消息的流
chat_stream=anchor_message.chat_stream, # 使用锚点消息的流
label=emotion,
stance=stance
stance=stance,
)
self.mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor)
async def trigger_reply_generation(self, stream_id: str, observed_messages: List[dict]):
"""根据 SubHeartflow 的触发信号生成回复 (基于观察)"""
stream_name = chat_manager.get_stream_name(stream_id) or stream_id # <--- 在开始时获取名称
stream_name = chat_manager.get_stream_name(stream_id) or stream_id # <--- 在开始时获取名称
chat = None
sub_hf = None
anchor_message: Optional[MessageRecv] = None # <--- 重命名，用于锚定回复的消息对象
anchor_message: Optional[MessageRecv] = None # <--- 重命名，用于锚定回复的消息对象
userinfo: Optional[UserInfo] = None
messageinfo: Optional[BaseMessageInfo] = None
@@ -303,9 +310,9 @@ class HeartFC_Chat:
logger.error(f"[{stream_name}] 无法找到子心流对象，无法生成回复。")
return
except Exception as e:
logger.error(f"[{stream_name}] 获取 ChatStream 或 SubHeartflow 时出错: {e}")
logger.error(traceback.format_exc())
return
logger.error(f"[{stream_name}] 获取 ChatStream 或 SubHeartflow 时出错: {e}")
logger.error(traceback.format_exc())
return
# --- 2. 尝试从 observed_messages 重建最后一条消息作为锚点, 失败则创建占位符 --- #
try:
@@ -314,36 +321,49 @@ class HeartFC_Chat:
if observed_messages:
try:
last_msg_dict = observed_messages[-1]
logger.debug(f"[{stream_name}] Attempting to reconstruct MessageRecv from last observed message.")
logger.debug(
f"[{stream_name}] Attempting to reconstruct MessageRecv from last observed message."
)
anchor_message = MessageRecv(last_msg_dict, chat_stream=chat)
if not (anchor_message and anchor_message.message_info and anchor_message.message_info.message_id and anchor_message.message_info.user_info):
if not (
anchor_message
and anchor_message.message_info
and anchor_message.message_info.message_id
and anchor_message.message_info.user_info
):
raise ValueError("Reconstructed MessageRecv missing essential info.")
userinfo = anchor_message.message_info.user_info
messageinfo = anchor_message.message_info
logger.debug(f"[{stream_name}] Successfully reconstructed anchor message: ID={messageinfo.message_id}, Sender={userinfo.user_nickname}")
logger.debug(
f"[{stream_name}] Successfully reconstructed anchor message: ID={messageinfo.message_id}, Sender={userinfo.user_nickname}"
)
except Exception as e_reconstruct:
logger.warning(f"[{stream_name}] Reconstructing MessageRecv from observed message failed: {e_reconstruct}. Will create placeholder.")
logger.warning(
f"[{stream_name}] Reconstructing MessageRecv from observed message failed: {e_reconstruct}. Will create placeholder."
)
reconstruction_failed = True
else:
logger.warning(f"[{stream_name}] observed_messages is empty. Will create placeholder anchor message.")
reconstruction_failed = True # Treat empty observed_messages as a failure to reconstruct
logger.warning(
f"[{stream_name}] observed_messages is empty. Will create placeholder anchor message."
)
reconstruction_failed = True # Treat empty observed_messages as a failure to reconstruct
# 如果重建失败或 observed_messages 为空，创建占位符
if reconstruction_failed:
placeholder_id = f"mid_{int(time.time() * 1000)}" # 使用毫秒时间戳增加唯一性
placeholder_id = f"mid_{int(time.time() * 1000)}" # 使用毫秒时间戳增加唯一性
placeholder_user = UserInfo(user_id="system_trigger", user_nickname="系统触发")
placeholder_msg_info = BaseMessageInfo(
message_id=placeholder_id,
platform=chat.platform,
group_info=chat.group_info,
user_info=placeholder_user,
time=time.time()
time=time.time(),
# 其他 BaseMessageInfo 可能需要的字段设为默认值或 None
)
# 创建 MessageRecv 实例，注意它需要消息字典结构，我们创建一个最小化的
placeholder_msg_dict = {
"message_info": placeholder_msg_info.to_dict(),
"processed_plain_text": "", # 提供空文本
"processed_plain_text": "", # 提供空文本
"raw_message": "",
"time": placeholder_msg_info.time,
}
@@ -353,18 +373,20 @@ class HeartFC_Chat:
anchor_message.update_chat_stream(chat)
userinfo = anchor_message.message_info.user_info
messageinfo = anchor_message.message_info
logger.info(f"[{stream_name}] Created placeholder anchor message: ID={messageinfo.message_id}, Sender={userinfo.user_nickname}")
logger.info(
f"[{stream_name}] Created placeholder anchor message: ID={messageinfo.message_id}, Sender={userinfo.user_nickname}"
)
except Exception as e:
logger.error(f"[{stream_name}] 获取或创建锚点消息时出错: {e}")
logger.error(traceback.format_exc())
anchor_message = None # 确保出错时 anchor_message 为 None
anchor_message = None # 确保出错时 anchor_message 为 None
# --- 4. 检查并发思考限制 (使用 anchor_message 简化获取) ---
try:
container = MessageManager().get_container(chat.stream_id)
thinking_count = container.count_thinking_messages()
max_thinking_messages = getattr(global_config, 'max_concurrent_thinking_messages', 3)
max_thinking_messages = getattr(global_config, "max_concurrent_thinking_messages", 3)
if thinking_count >= max_thinking_messages:
logger.warning(f"聊天流 {stream_name} 已有 {thinking_count} 条思考消息，取消回复。")
return
@@ -393,7 +415,7 @@ class HeartFC_Chat:
get_mid_memory_id = []
tool_result_info = {}
send_emoji = ""
observation_context_text = "" # 从 observation 获取上下文文本
observation_context_text = "" # 从 observation 获取上下文文本
try:
# --- 使用传入的 observed_messages 构建上下文文本 --- #
if observed_messages:
@@ -403,20 +425,22 @@ class HeartFC_Chat:
for msg_dict in observed_messages:
# 假设 detailed_plain_text 字段包含所需文本
# 你可能需要更复杂的逻辑来格式化，例如添加发送者和时间
text = msg_dict.get('detailed_plain_text', '')
if text:
text = msg_dict.get("detailed_plain_text", "")
if text:
context_texts.append(text)
observation_context_text = "\n".join(context_texts)
logger.debug(f"[{stream_name}] Context for tools:\n{observation_context_text[-200:]}...") # 打印部分上下文
logger.debug(
f"[{stream_name}] Context for tools:\n{observation_context_text[-200:]}..."
) # 打印部分上下文
else:
logger.warning(f"[{stream_name}] observed_messages 列表为空，无法为工具提供上下文。")
if observation_context_text:
with Timer("思考前使用工具", timing_results):
tool_result = await self.tool_user.use_tool(
message_txt=observation_context_text, # <--- 使用观察上下文
message_txt=observation_context_text, # <--- 使用观察上下文
chat_stream=chat,
sub_heartflow=sub_hf
sub_heartflow=sub_hf,
)
if tool_result.get("used_tools", False):
if "structured_info" in tool_result:
@@ -446,9 +470,9 @@ class HeartFC_Chat:
except Exception as e:
logger.error(f"[{stream_name}] SubHeartflow 思考失败: {e}")
logger.error(traceback.format_exc())
if info_catcher:
if info_catcher:
info_catcher.done_catch()
return # 思考失败则不继续
return # 思考失败则不继续
if info_catcher:
info_catcher.catch_afer_shf_step(timing_results.get("生成内心想法(SubHF)"), past_mind, current_mind)
@@ -458,16 +482,16 @@ class HeartFC_Chat:
# response_set = await self.gpt.generate_response(anchor_message, thinking_id, current_mind=current_mind)
response_set = await self.gpt.generate_response(anchor_message, thinking_id)
except Exception as e:
logger.error(f"[{stream_name}] GPT 生成回复失败: {e}")
logger.error(traceback.format_exc())
if info_catcher:
info_catcher.done_catch()
return
logger.error(f"[{stream_name}] GPT 生成回复失败: {e}")
logger.error(traceback.format_exc())
if info_catcher:
info_catcher.done_catch()
return
if info_catcher:
info_catcher.catch_after_generate_response(timing_results.get("生成最终回复(GPT)"))
if not response_set:
logger.info(f"[{stream_name}] 回复生成失败或为空。")
if info_catcher:
if info_catcher:
info_catcher.done_catch()
return
@@ -481,7 +505,7 @@ class HeartFC_Chat:
logger.error(traceback.format_exc())
if info_catcher:
info_catcher.catch_after_response(timing_results.get("发送消息"), response_set, first_bot_msg)
info_catcher.done_catch() # 完成捕捉
info_catcher.done_catch() # 完成捕捉
# --- 11. 处理表情包 (使用 anchor_message) ---
try:
@@ -496,10 +520,12 @@ class HeartFC_Chat:
# --- 12. 记录性能日志 --- #
timing_str = " | ".join([f"{step}: {duration:.2f}秒" for step, duration in timing_results.items()])
response_msg = " ".join(response_set) if response_set else "无回复"
logger.info(f"[{stream_name}] 回复任务完成 (Observation Triggered): | 思维消息: {response_msg[:30]}... | 性能计时: {timing_str}")
logger.info(
f"[{stream_name}] 回复任务完成 (Observation Triggered): | 思维消息: {response_msg[:30]}... | 性能计时: {timing_str}"
)
# --- 13. 更新关系情绪 (使用 anchor_message) ---
if first_bot_msg: # 仅在成功发送消息后
if first_bot_msg: # 仅在成功发送消息后
try:
with Timer("更新关系情绪", timing_results):
await self._update_relationship(anchor_message, response_set)
@@ -512,8 +538,9 @@ class HeartFC_Chat:
logger.error(traceback.format_exc())
finally:
# 可以在这里添加清理逻辑，如果有的话
pass
# 可以在这里添加清理逻辑，如果有的话
pass
# --- 结束重构 ---
# _create_thinking_message, _send_response_messages, _handle_emoji, _update_relationship