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🤖 自动格式化代码 [skip ci]

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github-actions[bot]
2025-04-25 14:59:23 +00:00
parent be1ba83319
commit 8bfff8efe2
9 changed files with 203 additions and 214 deletions
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24
src/plugins/emoji_system/emoji_manager.py
View File

@@ -29,10 +29,11 @@ EMOJI_DIR = os.path.join(BASE_DIR, "emoji") # 表情包存储目录
EMOJI_REGISTED_DIR = os.path.join(BASE_DIR, "emoji_registed") # 已注册的表情包注册目录
'''
"""
还没经过测试，有些地方数据库和内存数据同步可能不完全
'''
"""
class MaiEmoji:
"""定义一个表情包"""
@@ -258,7 +259,7 @@ class EmojiManager:
if emoji.hash == hash:
emoji.usage_count += 1
break
except Exception as e:
logger.error(f"记录表情使用失败: {str(e)}")
@@ -316,7 +317,9 @@ class EmojiManager:
time_end = time.time()
logger.info(f"找到[{text_emotion}]表情包,用时:{time_end - time_start:.2f}秒: {selected_emoji.description} (相似度: {similarity:.4f})")
logger.info(
f"找到[{text_emotion}]表情包,用时:{time_end - time_start:.2f}秒: {selected_emoji.description} (相似度: {similarity:.4f})"
)
return selected_emoji.path, f"[ {selected_emoji.description} ]"
except Exception as e:
@@ -784,16 +787,15 @@ class EmojiManager:
logger.error(f"[错误] 注册表情包失败: {str(e)}")
logger.error(traceback.format_exc())
return False
async def clear_temp_emoji(self):
"""每天清理临时表情包
清理/data/emoji和/data/image目录下的所有文件
当目录中文件数超过50时，会全部删除
"""
logger.info("[清理] 开始清理临时表情包...")
# 清理emoji目录
emoji_dir = os.path.join(BASE_DIR, "emoji")
if os.path.exists(emoji_dir):
@@ -805,7 +807,7 @@ class EmojiManager:
if os.path.isfile(file_path):
os.remove(file_path)
logger.debug(f"[清理] 删除表情包文件: {filename}")
# 清理image目录
image_dir = os.path.join(BASE_DIR, "image")
if os.path.exists(image_dir):
@@ -817,10 +819,8 @@ class EmojiManager:
if os.path.isfile(file_path):
os.remove(file_path)
logger.debug(f"[清理] 删除图片文件: {filename}")
logger.success("[清理] 临时文件清理完成")
# 创建全局单例

281
src/plugins/heartFC_chat/heartFC_chat.py
View File

@@ -38,31 +38,28 @@ logger = get_module_logger("HeartFCLoop", config=interest_log_config) # Logger
# 默认动作定义
DEFAULT_ACTIONS = {
"no_reply": "不回复",
"text_reply": "文本回复, 可选附带表情",
"emoji_reply": "仅表情回复"
}
DEFAULT_ACTIONS = {"no_reply": "不回复", "text_reply": "文本回复, 可选附带表情", "emoji_reply": "仅表情回复"}
class ActionManager:
"""动作管理器：控制每次决策可以使用的动作"""
def __init__(self):
# 初始化为默认动作集
self._available_actions: Dict[str, str] = DEFAULT_ACTIONS.copy()
def get_available_actions(self) -> Dict[str, str]:
"""获取当前可用的动作集"""
return self._available_actions
def add_action(self, action_name: str, description: str) -> bool:
"""
添加新的动作
参数:
action_name: 动作名称
description: 动作描述
返回:
bool: 是否添加成功
"""
@@ -70,14 +67,14 @@ class ActionManager:
return False
self._available_actions[action_name] = description
return True
def remove_action(self, action_name: str) -> bool:
"""
移除指定动作
参数:
action_name: 动作名称
返回:
bool: 是否移除成功
"""
@@ -85,63 +82,73 @@ class ActionManager:
return False
del self._available_actions[action_name]
return True
def clear_actions(self):
"""清空所有动作"""
self._available_actions.clear()
def reset_to_default(self):
"""重置为默认动作集"""
self._available_actions = DEFAULT_ACTIONS.copy()
def get_planner_tool_definition(self) -> List[Dict[str, Any]]:
"""获取当前动作集对应的规划器工具定义"""
return [{
"type": "function",
"function": {
"name": "decide_reply_action",
"description": "根据当前聊天内容和上下文，决定机器人是否应该回复以及如何回复。",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": list(self._available_actions.keys()),
"description": "决定采取的行动：" +
", ".join([f"'{k}'({v})" for k, v in self._available_actions.items()]),
},
"reasoning": {"type": "string", "description": "做出此决定的简要理由。"},
"emoji_query": {
"type": "string",
"description": "如果行动是'emoji_reply'，指定表情的主题或概念。如果行动是'text_reply'且希望在文本后追加表情，也在此指定表情主题。",
return [
{
"type": "function",
"function": {
"name": "decide_reply_action",
"description": "根据当前聊天内容和上下文，决定机器人是否应该回复以及如何回复。",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": list(self._available_actions.keys()),
"description": "决定采取的行动："
+ ", ".join([f"'{k}'({v})" for k, v in self._available_actions.items()]),
},
"reasoning": {"type": "string", "description": "做出此决定的简要理由。"},
"emoji_query": {
"type": "string",
"description": "如果行动是'emoji_reply'，指定表情的主题或概念。如果行动是'text_reply'且希望在文本后追加表情，也在此指定表情主题。",
},
},
"required": ["action", "reasoning"],
},
"required": ["action", "reasoning"],
},
},
}]
}
]
# 在文件开头添加自定义异常类
class HeartFCError(Exception):
"""麦麦聊天系统基础异常类"""
pass
class PlannerError(HeartFCError):
"""规划器异常"""
pass
class ReplierError(HeartFCError):
"""回复器异常"""
pass
class SenderError(HeartFCError):
"""发送器异常"""
pass
class CycleInfo:
"""循环信息记录类"""
def __init__(self, cycle_id: int):
self.cycle_id = cycle_id
self.start_time = time.time()
@@ -151,16 +158,16 @@ class CycleInfo:
self.reasoning = ""
self.timers: Dict[str, float] = {}
self.thinking_id = ""
# 添加响应信息相关字段
self.response_info: Dict[str, Any] = {
"response_text": [], # 回复的文本列表
"emoji_info": "", # 表情信息
"emoji_info": "", # 表情信息
"anchor_message_id": "", # 锚点消息ID
"reply_message_ids": [], # 回复消息ID列表
"sub_mind_thinking": "", # 子思维思考内容
}
def to_dict(self) -> Dict[str, Any]:
"""将循环信息转换为字典格式"""
return {
@@ -172,29 +179,31 @@ class CycleInfo:
"reasoning": self.reasoning,
"timers": self.timers,
"thinking_id": self.thinking_id,
"response_info": self.response_info
"response_info": self.response_info,
}
def complete_cycle(self):
"""完成循环，记录结束时间"""
self.end_time = time.time()
def set_action_info(self, action_type: str, reasoning: str, action_taken: bool):
"""设置动作信息"""
self.action_type = action_type
self.reasoning = reasoning
self.action_taken = action_taken
def set_thinking_id(self, thinking_id: str):
"""设置思考消息ID"""
self.thinking_id = thinking_id
def set_response_info(self,
response_text: Optional[List[str]] = None,
emoji_info: Optional[str] = None,
anchor_message_id: Optional[str] = None,
reply_message_ids: Optional[List[str]] = None,
sub_mind_thinking: Optional[str] = None):
def set_response_info(
self,
response_text: Optional[List[str]] = None,
emoji_info: Optional[str] = None,
anchor_message_id: Optional[str] = None,
reply_message_ids: Optional[List[str]] = None,
sub_mind_thinking: Optional[str] = None,
):
"""设置响应信息"""
if response_text is not None:
self.response_info["response_text"] = response_text
@@ -227,7 +236,7 @@ class HeartFChatting:
self.chat_stream: Optional[ChatStream] = None # 关联的聊天流
self.sub_mind: SubMind = sub_mind # 关联的子思维
self.observations: List[Observation] = observations # 关联的观察列表，用于监控聊天流状态
# 日志前缀
self.log_prefix: str = f"[{chat_manager.get_stream_name(chat_id) or chat_id}]"
@@ -274,7 +283,7 @@ class HeartFChatting:
# 更新日志前缀（以防流名称发生变化）
self.log_prefix = f"[{chat_manager.get_stream_name(self.stream_id) or self.stream_id}]"
self._initialized = True
logger.info(f"麦麦感觉到了，可以开始激情水群{self.log_prefix} ")
return True
@@ -333,52 +342,50 @@ class HeartFChatting:
self._processing_lock.release()
async def _hfc_loop(self):
"""主循环，持续进行计划并可能回复消息，直到被外部取消。"""
"""主循环，持续进行计划并可能回复消息，直到被外部取消。"""
try:
while True: # 主循环
# 创建新的循环信息
self._cycle_counter += 1
self._current_cycle = CycleInfo(self._cycle_counter)
# 初始化周期状态
cycle_timers = {}
loop_cycle_start_time = time.monotonic()
# 执行规划和处理阶段
async with self._get_cycle_context() as acquired_lock:
if not acquired_lock:
continue
# 记录规划开始时间点
planner_start_db_time = time.time()
# 执行规划阶段
action_taken, thinking_id = await self._think_plan_execute_loop(
cycle_timers, planner_start_db_time
)
# 执行规划阶段
action_taken, thinking_id = await self._think_plan_execute_loop(cycle_timers, planner_start_db_time)
# 更新循环信息
self._current_cycle.set_thinking_id(thinking_id)
self._current_cycle.timers = cycle_timers
# 防止循环过快消耗资源
await self._handle_cycle_delay(action_taken, loop_cycle_start_time, self.log_prefix)
# 等待直到所有消息都发送完成
with Timer("发送消息", cycle_timers):
while await self._should_skip_cycle(thinking_id):
await asyncio.sleep(0.2)
# 完成当前循环并保存历史
self._current_cycle.complete_cycle()
self._cycle_history.append(self._current_cycle)
# 记录循环信息和计时器结果
timer_strings = []
for name, elapsed in cycle_timers.items():
formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒"
timer_strings.append(f"{name}: {formatted_time}")
logger.debug(
f"{self.log_prefix} 第 #{self._current_cycle.cycle_id}次思考完成,"
f"耗时: {self._current_cycle.end_time - self._current_cycle.start_time:.2f}秒, "
@@ -396,7 +403,7 @@ class HeartFChatting:
async def _get_cycle_context(self):
"""
循环周期的上下文管理器
用于确保资源的正确获取和释放：
1. 获取处理锁
2. 执行操作
@@ -414,10 +421,10 @@ class HeartFChatting:
async def _check_new_messages(self, start_time: float) -> bool:
"""
检查从指定时间点后是否有新消息
参数:
start_time: 开始检查的时间点
返回:
bool: 是否有新消息
"""
@@ -431,9 +438,7 @@ class HeartFChatting:
logger.error(f"{self.log_prefix} 检查新消息时出错: {e}")
return False
async def _think_plan_execute_loop(
self, cycle_timers: dict, planner_start_db_time: float
) -> tuple[bool, str]:
async def _think_plan_execute_loop(self, cycle_timers: dict, planner_start_db_time: float) -> tuple[bool, str]:
"""执行规划阶段"""
try:
# 获取子思维思考结果
@@ -443,34 +448,36 @@ class HeartFChatting:
# 记录子思维思考内容
if self._current_cycle:
self._current_cycle.set_response_info(sub_mind_thinking=current_mind)
# 执行规划
with Timer("决策", cycle_timers):
planner_result = await self._planner(current_mind, cycle_timers)
# 在获取规划结果后检查新消息
if await self._check_new_messages(planner_start_db_time):
# 更新循环信息
logger.info(f"{self.log_prefix} 思考到一半，检测到新消息，重新思考")
self._current_cycle.set_action_info("new_messages", "检测到新消息", False)
return False, "new_messages"
# 解析规划结果
action = planner_result.get("action", "error")
reasoning = planner_result.get("reasoning", "未提供理由")
# 更新循环信息
self._current_cycle.set_action_info(action, reasoning, True)
# 处理LLM错误
if planner_result.get("llm_error"):
logger.error(f"{self.log_prefix} LLM失败: {reasoning}")
return False, ""
# 根据动作类型执行对应处理
with Timer("执行", cycle_timers):
return await self._handle_action(action, reasoning, planner_result.get("emoji_query", ""), cycle_timers, planner_start_db_time)
return await self._handle_action(
action, reasoning, planner_result.get("emoji_query", ""), cycle_timers, planner_start_db_time
)
except PlannerError as e:
logger.error(f"{self.log_prefix} 规划错误: {e}")
# 更新循环信息
@@ -478,37 +485,32 @@ class HeartFChatting:
return False, ""
async def _handle_action(
self,
action: str,
reasoning: str,
emoji_query: str,
cycle_timers: dict,
planner_start_db_time: float
self, action: str, reasoning: str, emoji_query: str, cycle_timers: dict, planner_start_db_time: float
) -> tuple[bool, str]:
"""
处理规划动作
参数:
action: 动作类型
reasoning: 决策理由
emoji_query: 表情查询
cycle_timers: 计时器字典
planner_start_db_time: 规划开始时间
返回:
tuple[bool, str]: (是否执行了动作, 思考消息ID)
"""
action_handlers = {
"text_reply": self._handle_text_reply,
"emoji_reply": self._handle_emoji_reply,
"no_reply": self._handle_no_reply
"no_reply": self._handle_no_reply,
}
handler = action_handlers.get(action)
if not handler:
logger.warning(f"{self.log_prefix} 未知动作: {action}, 原因: {reasoning}")
return False, ""
try:
if action == "text_reply":
return await handler(reasoning, emoji_query, cycle_timers)
@@ -520,37 +522,35 @@ class HeartFChatting:
logger.error(f"{self.log_prefix} 处理{action}时出错: {e}")
return False, ""
async def _handle_text_reply(
self, reasoning: str, emoji_query: str, cycle_timers: dict
) -> tuple[bool, str]:
async def _handle_text_reply(self, reasoning: str, emoji_query: str, cycle_timers: dict) -> tuple[bool, str]:
"""
处理文本回复
工作流程：
1. 获取锚点消息
2. 创建思考消息
3. 生成回复
4. 发送消息
参数:
reasoning: 回复原因
emoji_query: 表情查询
cycle_timers: 计时器字典
返回:
tuple[bool, str]: (是否回复成功, 思考消息ID)
"""
# 获取锚点消息
anchor_message = await self._get_anchor_message()
if not anchor_message:
raise PlannerError("无法获取锚点消息")
# 创建思考消息
thinking_id = await self._create_thinking_message(anchor_message)
if not thinking_id:
raise PlannerError("无法创建思考消息")
try:
# 生成回复
with Timer("Replier", cycle_timers):
@@ -559,10 +559,10 @@ class HeartFChatting:
thinking_id=thinking_id,
reason=reasoning,
)
if not reply:
raise ReplierError("回复生成失败")
# 发送消息
with Timer("Sender", cycle_timers):
await self._sender(
@@ -571,9 +571,9 @@ class HeartFChatting:
response_set=reply,
send_emoji=emoji_query,
)
return True, thinking_id
except (ReplierError, SenderError) as e:
logger.error(f"{self.log_prefix} 回复失败: {e}")
return True, thinking_id # 仍然返回thinking_id以便跟踪
@@ -581,72 +581,68 @@ class HeartFChatting:
async def _handle_emoji_reply(self, reasoning: str, emoji_query: str) -> bool:
"""
处理表情回复
工作流程：
1. 获取锚点消息
2. 发送表情
参数:
reasoning: 回复原因
emoji_query: 表情查询
返回:
bool: 是否发送成功
"""
logger.info(f"{self.log_prefix} 决定回复表情({emoji_query}): {reasoning}")
try:
anchor = await self._get_anchor_message()
if not anchor:
raise PlannerError("无法获取锚点消息")
await self._handle_emoji(anchor, [], emoji_query)
return True
except Exception as e:
logger.error(f"{self.log_prefix} 表情发送失败: {e}")
return False
async def _handle_no_reply(
self, reasoning: str, planner_start_db_time: float, cycle_timers: dict
) -> bool:
async def _handle_no_reply(self, reasoning: str, planner_start_db_time: float, cycle_timers: dict) -> bool:
"""
处理不回复的情况
工作流程：
1. 等待新消息
2. 超时或收到新消息时返回
参数:
reasoning: 不回复的原因
planner_start_db_time: 规划开始时间
cycle_timers: 计时器字典
返回:
bool: 是否成功处理
"""
logger.info(f"{self.log_prefix} 决定不回复: {reasoning}")
observation = self.observations[0] if self.observations else None
try:
with Timer("Wait New Msg", cycle_timers):
return await self._wait_for_new_message(observation, planner_start_db_time, self.log_prefix)
except asyncio.CancelledError:
logger.info(f"{self.log_prefix} 等待被中断")
raise
async def _wait_for_new_message(
self, observation, planner_start_db_time: float, log_prefix: str
) -> bool:
async def _wait_for_new_message(self, observation, planner_start_db_time: float, log_prefix: str) -> bool:
"""
等待新消息
参数:
observation: 观察实例
planner_start_db_time: 开始等待的时间
log_prefix: 日志前缀
返回:
bool: 是否检测到新消息
"""
@@ -655,11 +651,11 @@ class HeartFChatting:
if await observation.has_new_messages_since(planner_start_db_time):
logger.info(f"{log_prefix} 检测到新消息")
return True
if time.monotonic() - wait_start_time > 60:
logger.warning(f"{log_prefix} 等待超时(60秒)")
return False
await asyncio.sleep(1.5)
async def _should_skip_cycle(self, thinking_id: str) -> bool:
@@ -677,13 +673,11 @@ class HeartFChatting:
if timer_strings:
logger.debug(f"{log_prefix} 该次决策耗时: {'; '.join(timer_strings)}")
async def _handle_cycle_delay(
self, action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str
):
async def _handle_cycle_delay(self, action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str):
"""处理循环延迟"""
cycle_duration = time.monotonic() - cycle_start_time
# if cycle_duration > 0.1:
# logger.debug(f"{log_prefix} HeartFChatting: 周期耗时 {cycle_duration:.2f}s.")
# logger.debug(f"{log_prefix} HeartFChatting: 周期耗时 {cycle_duration:.2f}s.")
try:
sleep_duration = 0.0
@@ -702,7 +696,7 @@ class HeartFChatting:
async def _get_submind_thinking(self) -> str:
"""
获取子思维的思考结果
返回:
str: 思考结果，如果思考失败则返回错误信息
"""
@@ -719,7 +713,7 @@ class HeartFChatting:
async def _planner(self, current_mind: str, cycle_timers: dict) -> Dict[str, Any]:
"""
规划器 (Planner): 使用LLM根据上下文决定是否和如何回复。
参数:
current_mind: 子思维的当前思考结果
"""
@@ -779,7 +773,9 @@ class HeartFChatting:
action = arguments.get("action", "no_reply")
# 验证动作是否在可用动作集中
if action not in self.action_manager.get_available_actions():
logger.warning(f"{self.log_prefix}[Planner] LLM返回了未授权的动作: {action}，使用默认动作no_reply")
logger.warning(
f"{self.log_prefix}[Planner] LLM返回了未授权的动作: {action}，使用默认动作no_reply"
)
action = "no_reply"
reasoning = f"LLM返回了未授权的动作: {action}"
else:
@@ -787,7 +783,9 @@ class HeartFChatting:
emoji_query = arguments.get("emoji_query", "")
# 记录决策结果
logger.debug(f"{self.log_prefix}[要做什么]\nPrompt:\n{prompt}\n\n决策结果: {action}, 理由: {reasoning}, 表情查询: '{emoji_query}'")
logger.debug(
f"{self.log_prefix}[要做什么]\nPrompt:\n{prompt}\n\n决策结果: {action}, 理由: {reasoning}, 表情查询: '{emoji_query}'"
)
else:
# 处理工具调用失败
logger.warning(f"{self.log_prefix}[Planner] {error_msg}")
@@ -960,9 +958,6 @@ class HeartFChatting:
message=anchor_message, # Pass anchor_message positionally (matches 'message' parameter)
thinking_id=thinking_id, # Pass thinking_id positionally
)
if not response_set:
logger.warning(f"{self.log_prefix}[Replier-{thinking_id}] LLM生成了一个空回复集。")
@@ -1014,8 +1009,7 @@ class HeartFChatting:
# 记录锚点消息ID
if self._current_cycle and anchor_message:
self._current_cycle.set_response_info(
response_text=response_set,
anchor_message_id=anchor_message.message_info.message_id
response_text=response_set, anchor_message_id=anchor_message.message_info.message_id
)
chat = anchor_message.chat_stream
@@ -1090,9 +1084,7 @@ class HeartFChatting:
emoji_path, description = emoji_raw
# 记录表情信息
if self._current_cycle:
self._current_cycle.set_response_info(
emoji_info=f"表情: {description}, 路径: {emoji_path}"
)
self._current_cycle.set_response_info(emoji_info=f"表情: {description}, 路径: {emoji_path}")
emoji_cq = image_path_to_base64(emoji_path)
thinking_time_point = round(time.time(), 2)
@@ -1117,10 +1109,10 @@ class HeartFChatting:
def get_cycle_history(self, last_n: Optional[int] = None) -> List[Dict[str, Any]]:
"""获取循环历史记录
参数:
last_n: 获取最近n个循环的信息，如果为None则获取所有历史记录
返回:
List[Dict[str, Any]]: 循环历史记录列表
"""
@@ -1134,4 +1126,3 @@ class HeartFChatting:
if self._cycle_history:
return self._cycle_history[-1].to_dict()
return None

61
src/plugins/heartFC_chat/heartflow_processor.py
View File

@@ -24,14 +24,14 @@ logger = get_module_logger("heartflow_processor", config=processor_config)
class HeartFCProcessor:
"""心流处理器，负责处理接收到的消息并计算兴趣度"""
def __init__(self):
"""初始化心流处理器，创建消息存储实例"""
self.storage = MessageStorage()
async def _handle_error(self, error: Exception, context: str, message: Optional[MessageRecv] = None) -> None:
"""统一的错误处理函数
Args:
error: 捕获到的异常
context: 错误发生的上下文描述
@@ -39,12 +39,12 @@ class HeartFCProcessor:
"""
logger.error(f"{context}: {error}")
logger.error(traceback.format_exc())
if message and hasattr(message, 'raw_message'):
if message and hasattr(message, "raw_message"):
logger.error(f"相关消息原始内容: {message.raw_message}")
async def _process_relationship(self, message: MessageRecv) -> None:
"""处理用户关系逻辑
Args:
message: 消息对象，包含用户信息
"""
@@ -54,24 +54,20 @@ class HeartFCProcessor:
cardname = message.message_info.user_info.user_cardname or nickname
is_known = await relationship_manager.is_known_some_one(platform, user_id)
if not is_known:
logger.info(f"首次认识用户: {nickname}")
await relationship_manager.first_knowing_some_one(
platform, user_id, nickname, cardname, ""
)
await relationship_manager.first_knowing_some_one(platform, user_id, nickname, cardname, "")
elif not await relationship_manager.is_qved_name(platform, user_id):
logger.info(f"给用户({nickname},{cardname})取名: {nickname}")
await relationship_manager.first_knowing_some_one(
platform, user_id, nickname, cardname, ""
)
await relationship_manager.first_knowing_some_one(platform, user_id, nickname, cardname, "")
async def _calculate_interest(self, message: MessageRecv) -> Tuple[float, bool]:
"""计算消息的兴趣度
Args:
message: 待处理的消息对象
Returns:
Tuple[float, bool]: (兴趣度, 是否被提及)
"""
@@ -93,33 +89,35 @@ class HeartFCProcessor:
def _get_message_type(self, message: MessageRecv) -> str:
"""获取消息类型
Args:
message: 消息对象
Returns:
str: 消息类型
"""
if message.message_segment.type != "seglist":
return message.message_segment.type
if (isinstance(message.message_segment.data, list)
if (
isinstance(message.message_segment.data, list)
and all(isinstance(x, Seg) for x in message.message_segment.data)
and len(message.message_segment.data) == 1):
and len(message.message_segment.data) == 1
):
return message.message_segment.data[0].type
return "seglist"
async def process_message(self, message_data: str) -> None:
"""处理接收到的原始消息数据
主要流程:
1. 消息解析与初始化
2. 消息缓冲处理
3. 过滤检查
4. 兴趣度计算
5. 关系处理
Args:
message_data: 原始消息字符串
"""
@@ -133,20 +131,21 @@ class HeartFCProcessor:
# 2. 消息缓冲与流程序化
await message_buffer.start_caching_messages(message)
chat = await chat_manager.get_or_create_stream(
platform=messageinfo.platform,
user_info=userinfo,
group_info=groupinfo,
)
subheartflow = await heartflow.create_subheartflow(chat.stream_id)
message.update_chat_stream(chat)
await message.process()
# 3. 过滤检查
if self._check_ban_words(message.processed_plain_text, chat, userinfo) or \
self._check_ban_regex(message.raw_message, chat, userinfo):
if self._check_ban_words(message.processed_plain_text, chat, userinfo) or self._check_ban_regex(
message.raw_message, chat, userinfo
):
return
# 4. 缓冲检查
@@ -156,7 +155,7 @@ class HeartFCProcessor:
type_messages = {
"text": f"触发缓冲，消息：{message.processed_plain_text}",
"image": "触发缓冲，表情包/图片等待中",
"seglist": "触发缓冲，消息列表等待中"
"seglist": "触发缓冲，消息列表等待中",
}
logger.debug(type_messages.get(msg_type, "触发未知类型缓冲"))
return
@@ -189,12 +188,12 @@ class HeartFCProcessor:
def _check_ban_words(self, text: str, chat, userinfo) -> bool:
"""检查消息是否包含过滤词
Args:
text: 待检查的文本
chat: 聊天对象
userinfo: 用户信息
Returns:
bool: 是否包含过滤词
"""
@@ -208,12 +207,12 @@ class HeartFCProcessor:
def _check_ban_regex(self, text: str, chat, userinfo) -> bool:
"""检查消息是否匹配过滤正则表达式
Args:
text: 待检查的文本
chat: 聊天对象
userinfo: 用户信息
Returns:
bool: 是否匹配过滤正则
"""

15
src/plugins/heartFC_chat/heartflow_prompt_builder.py
View File

@@ -37,12 +37,15 @@ def init_prompt():
{moderation_prompt}。注意：回复不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )。""",
"heart_flow_prompt",
)
Prompt("""
Prompt(
"""
你有以下信息可供参考：
{structured_info}
以上的消息是你获取到的消息，或许可以帮助你更好地回复。
""", "info_from_tools")
""",
"info_from_tools",
)
# Planner提示词
Prompt(
@@ -163,11 +166,11 @@ class PromptBuilder:
prompt_ger += "你喜欢用倒装句"
if random.random() < 0.02:
prompt_ger += "你喜欢用反问句"
if structured_info:
structured_info_prompt = await global_prompt_manager.format_prompt(
"info_from_tools",
structured_info = structured_info)
"info_from_tools", structured_info=structured_info
)
else:
structured_info_prompt = ""

4
src/plugins/utils/chat_message_builder.py
View File

@@ -303,9 +303,7 @@ async def build_readable_messages(
)
readable_read_mark = translate_timestamp_to_human_readable(read_mark, mode=timestamp_mode)
read_mark_line = (
f"\n\n--- 以上消息已读 (标记时间: {readable_read_mark}) ---\n--- 以下新消息未读---\n"
)
read_mark_line = f"\n\n--- 以上消息已读 (标记时间: {readable_read_mark}) ---\n--- 以下新消息未读---\n"
# 组合结果，确保空部分不引入多余的标记或换行
if formatted_before and formatted_after: