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Merge remote-tracking branch 'upstream/debug' into refractor

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tcmofashi
2025-03-11 19:51:03 +08:00
parent aa41f0d1d8 bd64e72f55
commit b19902919e
5 changed files with 121 additions and 92 deletions
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151
src/plugins/chat/bot.py
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@@ -7,7 +7,7 @@ from nonebot.adapters.onebot.v11 import Bot, GroupMessageEvent
from ..memory_system.memory import hippocampus
from ..moods.moods import MoodManager # 导入情绪管理器
from .config import global_config
from .cq_code import CQCode,cq_code_tool # 导入CQCode模块
from .cq_code import CQCode, cq_code_tool # 导入CQCode模块
from .emoji_manager import emoji_manager # 导入表情包管理器
from .llm_generator import ResponseGenerator
from .message import MessageSending, MessageRecv, MessageThinking, MessageSet
@@ -24,6 +24,7 @@ from .utils_image import image_path_to_base64
from .willing_manager import willing_manager # 导入意愿管理器
from .message_base import UserInfo, GroupInfo, Seg
class ChatBot:
def __init__(self):
self.storage = MessageStorage()
@@ -46,8 +47,13 @@ class ChatBot:
self.bot = bot # 更新 bot 实例
# group_info = await bot.get_group_info(group_id=event.group_id)
# sender_info = await bot.get_group_member_info(group_id=event.group_id, user_id=event.user_id, no_cache=True)
try:
group_info_api = await bot.get_group_info(group_id=event.group_id)
logger.info(f"成功获取群信息: {group_info_api}")
group_name = group_info_api["group_name"]
except Exception as e:
logger.error(f"获取群信息失败: {str(e)}")
group_name = None
# 白名单设定由nontbot侧完成
# 消息过滤，涉及到config有待更新
@@ -56,49 +62,53 @@ class ChatBot:
return
if event.user_id in global_config.ban_user_id:
return
user_info=UserInfo(
user_info = UserInfo(
user_id=event.user_id,
user_nickname=event.sender.nickname,
user_cardname=event.sender.card or None,
platform='qq'
platform="qq",
)
group_info=GroupInfo(
group_info = GroupInfo(
group_id=event.group_id,
group_name=None,
platform='qq'
group_name=group_name, # 使用获取到的群名称或None
platform="qq",
)
message_cq=MessageRecvCQ(
message_cq = MessageRecvCQ(
message_id=event.message_id,
user_info=user_info,
raw_message=str(event.original_message),
group_info=group_info,
reply_message=event.reply,
platform='qq'
platform="qq",
)
message_json=message_cq.to_dict()
message_json = message_cq.to_dict()
# 进入maimbot
message=MessageRecv(message_json)
groupinfo=message.message_info.group_info
userinfo=message.message_info.user_info
messageinfo=message.message_info
message = MessageRecv(message_json)
chat = await chat_manager.get_or_create_stream(platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo)
groupinfo = message.message_info.group_info
userinfo = message.message_info.user_info
messageinfo = message.message_info
# 消息过滤，涉及到config有待更新
chat = await chat_manager.get_or_create_stream(
platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo
)
message.update_chat_stream(chat)
await relationship_manager.update_relationship(chat_stream=chat,)
await relationship_manager.update_relationship_value(chat_stream=chat, relationship_value = 0.5)
await relationship_manager.update_relationship(
chat_stream=chat,
)
await relationship_manager.update_relationship_value(chat_stream=chat, relationship_value=0.5)
await message.process()
# 过滤词
for word in global_config.ban_words:
if word in message.processed_plain_text:
logger.info(
f"[{groupinfo.group_name}]{userinfo.user_nickname}:{message.processed_plain_text}")
logger.info(f"[群{groupinfo.group_id}]{userinfo.user_nickname}:{message.processed_plain_text}")
logger.info(f"[过滤词识别]消息中含有{word}，filtered")
return
@@ -106,23 +116,21 @@ class ChatBot:
for pattern in global_config.ban_msgs_regex:
if re.search(pattern, message.raw_message):
logger.info(
f"[{message.group_name}]{message.user_nickname}:{message.raw_message}")
f"[群{message.message_info.group_info.group_id}]{message.user_nickname}:{message.raw_message}"
)
logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
return
current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(messageinfo.time))
# topic=await topic_identifier.identify_topic_llm(message.processed_plain_text)
topic = ''
topic = ""
interested_rate = 0
interested_rate = await hippocampus.memory_activate_value(message.processed_plain_text) / 100
logger.debug(f"对{message.processed_plain_text}"
f"的激活度:{interested_rate}")
logger.debug(f"对{message.processed_plain_text}的激活度:{interested_rate}")
# logger.info(f"\033[1;32m[主题识别]\033[0m 使用{global_config.topic_extract}主题: {topic}")
await self.storage.store_message(message,chat, topic[0] if topic else None)
await self.storage.store_message(message, chat, topic[0] if topic else None)
is_mentioned = is_mentioned_bot_in_message(message)
reply_probability = await willing_manager.change_reply_willing_received(
@@ -131,38 +139,33 @@ class ChatBot:
is_mentioned_bot=is_mentioned,
config=global_config,
is_emoji=message.is_emoji,
interested_rate=interested_rate
interested_rate=interested_rate,
)
current_willing = willing_manager.get_willing(chat_stream=chat)
logger.info(
f"[{current_time}][{chat.group_info.group_name}]{chat.user_info.user_nickname}:"
f"[{current_time}][群{chat.group_info.group_id}]{chat.user_info.user_nickname}:"
f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]"
)
response = None
if random() < reply_probability:
bot_user_info=UserInfo(
user_id=global_config.BOT_QQ,
user_nickname=global_config.BOT_NICKNAME,
platform=messageinfo.platform
bot_user_info = UserInfo(
user_id=global_config.BOT_QQ, user_nickname=global_config.BOT_NICKNAME, platform=messageinfo.platform
)
tinking_time_point = round(time.time(), 2)
think_id = 'mt' + str(tinking_time_point)
thinking_time_point = round(time.time(), 2)
think_id = "mt" + str(thinking_time_point)
thinking_message = MessageThinking(
message_id=think_id,
chat_stream=chat,
bot_user_info=bot_user_info,
reply=message
message_id=think_id, chat_stream=chat, bot_user_info=bot_user_info, reply=message
)
message_manager.add_message(thinking_message)
willing_manager.change_reply_willing_sent(chat)
response,raw_content = await self.gpt.generate_response(message)
response, raw_content = await self.gpt.generate_response(message)
# print(f"response: {response}")
if response:
# print(f"有response: {response}")
@@ -185,9 +188,9 @@ class ChatBot:
# 记录开始思考的时间，避免从思考到回复的时间太久
thinking_start_time = thinking_message.thinking_start_time
message_set = MessageSet(chat, think_id)
#计算打字时间，1是为了模拟打字，2是避免多条回复乱序
# 计算打字时间，1是为了模拟打字，2是避免多条回复乱序
accu_typing_time = 0
mark_head = False
for msg in response:
# print(f"\033[1;32m[回复内容]\033[0m {msg}")
@@ -195,8 +198,8 @@ class ChatBot:
typing_time = calculate_typing_time(msg)
print(f"typing_time: {typing_time}")
accu_typing_time += typing_time
timepoint = tinking_time_point + accu_typing_time
message_segment = Seg(type='text', data=msg)
timepoint = thinking_time_point + accu_typing_time
message_segment = Seg(type="text", data=msg)
print(f"message_segment: {message_segment}")
bot_message = MessageSending(
message_id=think_id,
@@ -205,7 +208,7 @@ class ChatBot:
message_segment=message_segment,
reply=message,
is_head=not mark_head,
is_emoji=False
is_emoji=False,
)
print(f"bot_message: {bot_message}")
if not mark_head:
@@ -218,7 +221,7 @@ class ChatBot:
print(f"添加message_set到message_manager")
message_manager.add_message(message_set)
bot_response_time = tinking_time_point
bot_response_time = thinking_time_point
if random() < global_config.emoji_chance:
emoji_raw = await emoji_manager.get_emoji_for_text(response)
@@ -227,14 +230,14 @@ class ChatBot:
if emoji_raw != None:
emoji_path, description = emoji_raw
emoji_cq = image_path_to_base64(emoji_path)
emoji_cq = image_path_to_base64(emoji_path)
if random() < 0.5:
bot_response_time = tinking_time_point - 1
bot_response_time = thinking_time_point - 1
else:
bot_response_time = bot_response_time + 1
message_segment = Seg(type='emoji', data=emoji_cq)
message_segment = Seg(type="emoji", data=emoji_cq)
bot_message = MessageSending(
message_id=think_id,
chat_stream=chat,
@@ -242,25 +245,27 @@ class ChatBot:
message_segment=message_segment,
reply=message,
is_head=False,
is_emoji=True
is_emoji=True,
)
message_manager.add_message(bot_message)
emotion = await self.gpt._get_emotion_tags(raw_content)
logger.debug(f"为 '{response}' 获取到的情感标签为：{emotion}")
valuedict = {
'happy': 0.5,
'angry': -1,
'sad': -0.5,
'surprised': 0.2,
'disgusted': -1.5,
'fearful': -0.7,
'neutral': 0.1
"happy": 0.5,
"angry": -1,
"sad": -0.5,
"surprised": 0.2,
"disgusted": -1.5,
"fearful": -0.7,
"neutral": 0.1,
}
await relationship_manager.update_relationship_value(chat_stream=chat, relationship_value=valuedict[emotion[0]])
await relationship_manager.update_relationship_value(
chat_stream=chat, relationship_value=valuedict[emotion[0]]
)
# 使用情绪管理器更新情绪
self.mood_manager.update_mood_from_emotion(emotion[0], global_config.mood_intensity_factor)
# willing_manager.change_reply_willing_after_sent(
# chat_stream=chat
# )