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Merge branch 'dev' of https://github.com/MaiM-with-u/MaiBot into dev

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This commit is contained in:
tcmofashi
2025-04-17 15:53:26 +08:00
parent 89ff064f41 dcebdb7a35
commit 585fe50f57
52 changed files with 299 additions and 336 deletions
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6
src/plugins/chat_module/only_process/only_message_process.py
View File

@@ -13,7 +13,8 @@ class MessageProcessor:
def __init__(self):
self.storage = MessageStorage()
def _check_ban_words(self, text: str, chat, userinfo) -> bool:
@staticmethod
def _check_ban_words(text: str, chat, userinfo) -> bool:
"""检查消息中是否包含过滤词"""
for word in global_config.ban_words:
if word in text:
@@ -24,7 +25,8 @@ class MessageProcessor:
return True
return False
def _check_ban_regex(self, text: str, chat, userinfo) -> bool:
@staticmethod
def _check_ban_regex(text: str, chat, userinfo) -> bool:
"""检查消息是否匹配过滤正则表达式"""
for pattern in global_config.ban_msgs_regex:
if pattern.search(text):

27
src/plugins/chat_module/reasoning_chat/reasoning_chat.py
View File

@@ -37,7 +37,8 @@ class ReasoningChat:
self.mood_manager = MoodManager.get_instance()
self.mood_manager.start_mood_update()
async def _create_thinking_message(self, message, chat, userinfo, messageinfo):
@staticmethod
async def _create_thinking_message(message, chat, userinfo, messageinfo):
"""创建思考消息"""
bot_user_info = UserInfo(
user_id=global_config.BOT_QQ,
@@ -59,7 +60,8 @@ class ReasoningChat:
return thinking_id
async def _send_response_messages(self, message, chat, response_set: List[str], thinking_id) -> MessageSending:
@staticmethod
async def _send_response_messages(message, chat, response_set: List[str], thinking_id) -> MessageSending:
"""发送回复消息"""
container = message_manager.get_container(chat.stream_id)
thinking_message = None
@@ -104,7 +106,8 @@ class ReasoningChat:
return first_bot_msg
async def _handle_emoji(self, message, chat, response):
@staticmethod
async def _handle_emoji(message, chat, response):
"""处理表情包"""
if random() < global_config.emoji_chance:
emoji_raw = await emoji_manager.get_emoji_for_text(response)
@@ -192,21 +195,21 @@ class ReasoningChat:
if not buffer_result:
await willing_manager.bombing_buffer_message_handle(message.message_info.message_id)
willing_manager.delete(message.message_info.message_id)
F_type = "seglist"
f_type = "seglist"
if message.message_segment.type != "seglist":
F_type = message.message_segment.type
f_type = message.message_segment.type
else:
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
):
F_type = message.message_segment.data[0].type
if F_type == "text":
f_type = message.message_segment.data[0].type
if f_type == "text":
logger.info(f"触发缓冲，已炸飞消息：{message.processed_plain_text}")
elif F_type == "image":
elif f_type == "image":
logger.info("触发缓冲，已炸飞表情包/图片")
elif F_type == "seglist":
elif f_type == "seglist":
logger.info("触发缓冲，已炸飞消息列")
return
@@ -291,7 +294,8 @@ class ReasoningChat:
# 意愿管理器：注销当前message信息
willing_manager.delete(message.message_info.message_id)
def _check_ban_words(self, text: str, chat, userinfo) -> bool:
@staticmethod
def _check_ban_words(text: str, chat, userinfo) -> bool:
"""检查消息中是否包含过滤词"""
for word in global_config.ban_words:
if word in text:
@@ -302,7 +306,8 @@ class ReasoningChat:
return True
return False
def _check_ban_regex(self, text: str, chat, userinfo) -> bool:
@staticmethod
def _check_ban_regex(text: str, chat, userinfo) -> bool:
"""检查消息是否匹配过滤正则表达式"""
for pattern in global_config.ban_msgs_regex:
if pattern.search(text):

5
src/plugins/chat_module/reasoning_chat/reasoning_generator.py
View File

@@ -69,8 +69,6 @@ class ResponseGenerator:
return None
async def _generate_response_with_model(self, message: MessageThinking, model: LLMRequest, thinking_id: str):
sender_name = ""
info_catcher = info_catcher_manager.get_info_catcher(thinking_id)
if message.chat_stream.user_info.user_cardname and message.chat_stream.user_info.user_nickname:
@@ -188,7 +186,8 @@ class ResponseGenerator:
logger.debug(f"获取情感标签时出错: {e}")
return "中立", "平静" # 出错时返回默认值
async def _process_response(self, content: str) -> Tuple[List[str], List[str]]:
@staticmethod
async def _process_response(content: str) -> Tuple[List[str], List[str]]:
"""处理响应内容，返回处理后的内容和情感标签"""
if not content:
return None, []

8
src/plugins/chat_module/reasoning_chat/reasoning_prompt_builder.py
View File

@@ -101,16 +101,14 @@ class PromptBuilder:
related_memory = await HippocampusManager.get_instance().get_memory_from_text(
text=message_txt, max_memory_num=2, max_memory_length=2, max_depth=3, fast_retrieval=False
)
related_memory_info = ""
if related_memory:
related_memory_info = ""
for memory in related_memory:
related_memory_info += memory[1]
# memory_prompt = f"你想起你之前见过的事情：{related_memory_info}。\n以上是你的回忆，不一定是目前聊天里的人说的，也不一定是现在发生的事情，请记住。\n"
memory_prompt = await global_prompt_manager.format_prompt(
"memory_prompt", related_memory_info=related_memory_info
)
else:
related_memory_info = ""
# print(f"相关记忆：{related_memory_info}")
@@ -162,7 +160,6 @@ class PromptBuilder:
# 知识构建
start_time = time.time()
prompt_info = ""
prompt_info = await self.get_prompt_info(message_txt, threshold=0.38)
if prompt_info:
# prompt_info = f"""\n你有以下这些**知识**：\n{prompt_info}\n请你**记住上面的知识**，之后可能会用到。\n"""
@@ -373,8 +370,9 @@ class PromptBuilder:
logger.info(f"知识库检索总耗时: {time.time() - start_time:.3f}秒")
return related_info
@staticmethod
def get_info_from_db(
self, query_embedding: list, limit: int = 1, threshold: float = 0.5, return_raw: bool = False
query_embedding: list, limit: int = 1, threshold: float = 0.5, return_raw: bool = False
) -> Union[str, list]:
if not query_embedding:
return "" if not return_raw else []

27
src/plugins/chat_module/think_flow_chat/think_flow_chat.py
View File

@@ -40,7 +40,8 @@ class ThinkFlowChat:
self.mood_manager.start_mood_update()
self.tool_user = ToolUser()
async def _create_thinking_message(self, message, chat, userinfo, messageinfo):
@staticmethod
async def _create_thinking_message(message, chat, userinfo, messageinfo):
"""创建思考消息"""
bot_user_info = UserInfo(
user_id=global_config.BOT_QQ,
@@ -62,7 +63,8 @@ class ThinkFlowChat:
return thinking_id
async def _send_response_messages(self, message, chat, response_set: List[str], thinking_id) -> MessageSending:
@staticmethod
async def _send_response_messages(message, chat, response_set: List[str], thinking_id) -> MessageSending:
"""发送回复消息"""
container = message_manager.get_container(chat.stream_id)
thinking_message = None
@@ -108,7 +110,8 @@ class ThinkFlowChat:
message_manager.add_message(message_set)
return first_bot_msg
async def _handle_emoji(self, message, chat, response, send_emoji=""):
@staticmethod
async def _handle_emoji(message, chat, response, send_emoji=""):
"""处理表情包"""
if send_emoji:
emoji_raw = await emoji_manager.get_emoji_for_text(send_emoji)
@@ -204,21 +207,21 @@ class ThinkFlowChat:
if not buffer_result:
await willing_manager.bombing_buffer_message_handle(message.message_info.message_id)
willing_manager.delete(message.message_info.message_id)
F_type = "seglist"
f_type = "seglist"
if message.message_segment.type != "seglist":
F_type = message.message_segment.type
f_type = message.message_segment.type
else:
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
):
F_type = message.message_segment.data[0].type
if F_type == "text":
f_type = message.message_segment.data[0].type
if f_type == "text":
logger.info(f"触发缓冲，已炸飞消息：{message.processed_plain_text}")
elif F_type == "image":
elif f_type == "image":
logger.info("触发缓冲，已炸飞表情包/图片")
elif F_type == "seglist":
elif f_type == "seglist":
logger.info("触发缓冲，已炸飞消息列")
return
@@ -461,7 +464,8 @@ class ThinkFlowChat:
# 意愿管理器：注销当前message信息
willing_manager.delete(message.message_info.message_id)
def _check_ban_words(self, text: str, chat, userinfo) -> bool:
@staticmethod
def _check_ban_words(text: str, chat, userinfo) -> bool:
"""检查消息中是否包含过滤词"""
for word in global_config.ban_words:
if word in text:
@@ -472,7 +476,8 @@ class ThinkFlowChat:
return True
return False
def _check_ban_regex(self, text: str, chat, userinfo) -> bool:
@staticmethod
def _check_ban_regex(text: str, chat, userinfo) -> bool:
"""检查消息是否匹配过滤正则表达式"""
for pattern in global_config.ban_msgs_regex:
if pattern.search(text):

3
src/plugins/chat_module/think_flow_chat/think_flow_generator.py
View File

@@ -236,7 +236,8 @@ class ResponseGenerator:
logger.debug(f"获取情感标签时出错: {e}")
return "中立", "平静" # 出错时返回默认值
async def _process_response(self, content: str) -> List[str]:
@staticmethod
async def _process_response(content: str) -> List[str]:
"""处理响应内容，返回处理后的内容和情感标签"""
if not content:
return None

8
src/plugins/chat_module/think_flow_chat/think_flow_prompt_builder.py
View File

@@ -64,8 +64,9 @@ class PromptBuilder:
self.prompt_built = ""
self.activate_messages = ""
@staticmethod
async def _build_prompt(
self, chat_stream, message_txt: str, sender_name: str = "某人", stream_id: Optional[int] = None
chat_stream, message_txt: str, sender_name: str = "某人", stream_id: Optional[int] = None
) -> tuple[str, str]:
current_mind_info = heartflow.get_subheartflow(stream_id).current_mind
@@ -168,8 +169,9 @@ class PromptBuilder:
return prompt
@staticmethod
async def _build_prompt_simple(
self, chat_stream, message_txt: str, sender_name: str = "某人", stream_id: Optional[int] = None
chat_stream, message_txt: str, sender_name: str = "某人", stream_id: Optional[int] = None
) -> tuple[str, str]:
current_mind_info = heartflow.get_subheartflow(stream_id).current_mind
@@ -237,8 +239,8 @@ class PromptBuilder:
logger.info(f"生成回复的prompt: {prompt}")
return prompt
@staticmethod
async def _build_prompt_check_response(
self,
chat_stream,
message_txt: str,
sender_name: str = "某人",