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

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This commit is contained in:
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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2
bot.py
View File

@@ -59,7 +59,7 @@ def init_env():
# 检测.env.dev文件是否存在，不存在的话直接复制生产环境配置 # 检测.env.dev文件是否存在，不存在的话直接复制生产环境配置
if not os.path.exists(".env.dev"): if not os.path.exists(".env.dev"):
logger.error("检测到.env.dev文件不存在") logger.error("检测到.env.dev文件不存在")
shutil.copy(".env.prod", "./.env.dev") shutil.copy("template.env", "./.env.dev")
# 首先加载基础环境变量.env # 首先加载基础环境变量.env
if os.path.exists(".env"): if os.path.exists(".env"):

91
src/plugins/chat/bot.py
View File

@@ -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 .willing_manager import willing_manager # 导入意愿管理器
from .message_base import UserInfo, GroupInfo, Seg from .message_base import UserInfo, GroupInfo, Seg
class ChatBot: class ChatBot:
def __init__(self): def __init__(self):
self.storage = MessageStorage() self.storage = MessageStorage()
@@ -46,8 +47,13 @@ class ChatBot:
self.bot = bot # 更新 bot 实例 self.bot = bot # 更新 bot 实例
# group_info = await bot.get_group_info(group_id=event.group_id) try:
# sender_info = await bot.get_group_member_info(group_id=event.group_id, user_id=event.user_id, no_cache=True) 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 # 白名单设定由nontbot侧完成
# 消息过滤，涉及到config有待更新 # 消息过滤，涉及到config有待更新
@@ -61,21 +67,22 @@ class ChatBot:
user_id=event.user_id, user_id=event.user_id,
user_nickname=event.sender.nickname, user_nickname=event.sender.nickname,
user_cardname=event.sender.card or None, user_cardname=event.sender.card or None,
platform='qq' platform="qq",
) )
group_info = GroupInfo( group_info = GroupInfo(
group_id=event.group_id, group_id=event.group_id,
group_name=None, group_name=group_name, # 使用获取到的群名称或None
platform='qq' platform="qq",
) )
message_cq = MessageRecvCQ( message_cq = MessageRecvCQ(
message_id=event.message_id, message_id=event.message_id,
user_info=user_info, user_info=user_info,
raw_message=str(event.original_message), raw_message=str(event.original_message),
group_info=group_info, group_info=group_info,
reply_message=event.reply, reply_message=event.reply,
platform='qq' platform="qq",
) )
message_json = message_cq.to_dict() message_json = message_cq.to_dict()
@@ -86,19 +93,22 @@ class ChatBot:
userinfo = message.message_info.user_info userinfo = message.message_info.user_info
messageinfo = message.message_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(
chat = await chat_manager.get_or_create_stream(platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo) platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo
)
message.update_chat_stream(chat) message.update_chat_stream(chat)
await relationship_manager.update_relationship(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_value(chat_stream=chat, relationship_value=0.5)
await message.process() await message.process()
# 过滤词 # 过滤词
for word in global_config.ban_words: for word in global_config.ban_words:
if word in message.processed_plain_text: if word in message.processed_plain_text:
logger.info( logger.info(f"[群{groupinfo.group_id}]{userinfo.user_nickname}:{message.processed_plain_text}")
f"[{groupinfo.group_name}]{userinfo.user_nickname}:{message.processed_plain_text}")
logger.info(f"[过滤词识别]消息中含有{word}，filtered") logger.info(f"[过滤词识别]消息中含有{word}，filtered")
return return
@@ -106,20 +116,18 @@ class ChatBot:
for pattern in global_config.ban_msgs_regex: for pattern in global_config.ban_msgs_regex:
if re.search(pattern, message.raw_message): if re.search(pattern, message.raw_message):
logger.info( 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") logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
return return
current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(messageinfo.time)) 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=await topic_identifier.identify_topic_llm(message.processed_plain_text)
topic = '' topic = ""
interested_rate = 0 interested_rate = 0
interested_rate = await hippocampus.memory_activate_value(message.processed_plain_text) / 100 interested_rate = await hippocampus.memory_activate_value(message.processed_plain_text) / 100
logger.debug(f"对{message.processed_plain_text}" logger.debug(f"对{message.processed_plain_text}的激活度:{interested_rate}")
f"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}") # 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)
@@ -131,12 +139,12 @@ class ChatBot:
is_mentioned_bot=is_mentioned, is_mentioned_bot=is_mentioned,
config=global_config, config=global_config,
is_emoji=message.is_emoji, is_emoji=message.is_emoji,
interested_rate=interested_rate interested_rate=interested_rate,
) )
current_willing = willing_manager.get_willing(chat_stream=chat) current_willing = willing_manager.get_willing(chat_stream=chat)
logger.info( 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}%]" f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]"
) )
@@ -144,17 +152,12 @@ class ChatBot:
if random() < reply_probability: if random() < reply_probability:
bot_user_info = UserInfo( bot_user_info = UserInfo(
user_id=global_config.BOT_QQ, user_id=global_config.BOT_QQ, user_nickname=global_config.BOT_NICKNAME, platform=messageinfo.platform
user_nickname=global_config.BOT_NICKNAME,
platform=messageinfo.platform
) )
tinking_time_point = round(time.time(), 2) thinking_time_point = round(time.time(), 2)
think_id = 'mt' + str(tinking_time_point) think_id = "mt" + str(thinking_time_point)
thinking_message = MessageThinking( thinking_message = MessageThinking(
message_id=think_id, message_id=think_id, chat_stream=chat, bot_user_info=bot_user_info, reply=message
chat_stream=chat,
bot_user_info=bot_user_info,
reply=message
) )
message_manager.add_message(thinking_message) message_manager.add_message(thinking_message)
@@ -195,8 +198,8 @@ class ChatBot:
typing_time = calculate_typing_time(msg) typing_time = calculate_typing_time(msg)
print(f"typing_time: {typing_time}") print(f"typing_time: {typing_time}")
accu_typing_time += typing_time accu_typing_time += typing_time
timepoint = tinking_time_point + accu_typing_time timepoint = thinking_time_point + accu_typing_time
message_segment = Seg(type='text', data=msg) message_segment = Seg(type="text", data=msg)
print(f"message_segment: {message_segment}") print(f"message_segment: {message_segment}")
bot_message = MessageSending( bot_message = MessageSending(
message_id=think_id, message_id=think_id,
@@ -205,7 +208,7 @@ class ChatBot:
message_segment=message_segment, message_segment=message_segment,
reply=message, reply=message,
is_head=not mark_head, is_head=not mark_head,
is_emoji=False is_emoji=False,
) )
print(f"bot_message: {bot_message}") print(f"bot_message: {bot_message}")
if not mark_head: if not mark_head:
@@ -218,7 +221,7 @@ class ChatBot:
print(f"添加message_set到message_manager") print(f"添加message_set到message_manager")
message_manager.add_message(message_set) message_manager.add_message(message_set)
bot_response_time = tinking_time_point bot_response_time = thinking_time_point
if random() < global_config.emoji_chance: if random() < global_config.emoji_chance:
emoji_raw = await emoji_manager.get_emoji_for_text(response) emoji_raw = await emoji_manager.get_emoji_for_text(response)
@@ -230,11 +233,11 @@ class ChatBot:
emoji_cq = image_path_to_base64(emoji_path) emoji_cq = image_path_to_base64(emoji_path)
if random() < 0.5: if random() < 0.5:
bot_response_time = tinking_time_point - 1 bot_response_time = thinking_time_point - 1
else: else:
bot_response_time = bot_response_time + 1 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( bot_message = MessageSending(
message_id=think_id, message_id=think_id,
chat_stream=chat, chat_stream=chat,
@@ -242,22 +245,24 @@ class ChatBot:
message_segment=message_segment, message_segment=message_segment,
reply=message, reply=message,
is_head=False, is_head=False,
is_emoji=True is_emoji=True,
) )
message_manager.add_message(bot_message) message_manager.add_message(bot_message)
emotion = await self.gpt._get_emotion_tags(raw_content) emotion = await self.gpt._get_emotion_tags(raw_content)
logger.debug(f"为 '{response}' 获取到的情感标签为：{emotion}") logger.debug(f"为 '{response}' 获取到的情感标签为：{emotion}")
valuedict = { valuedict = {
'happy': 0.5, "happy": 0.5,
'angry': -1, "angry": -1,
'sad': -0.5, "sad": -0.5,
'surprised': 0.2, "surprised": 0.2,
'disgusted': -1.5, "disgusted": -1.5,
'fearful': -0.7, "fearful": -0.7,
'neutral': 0.1 "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 # 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) self.mood_manager.update_mood_from_emotion(emotion[0], global_config.mood_intensity_factor)

9
src/plugins/chat/config.py
View File

@@ -1,4 +1,5 @@
import os import os
import sys
from dataclasses import dataclass, field from dataclasses import dataclass, field
from typing import Dict, List, Optional from typing import Dict, List, Optional
@@ -67,6 +68,7 @@ class BotConfig:
enable_advance_output: bool = False # 是否启用高级输出 enable_advance_output: bool = False # 是否启用高级输出
enable_kuuki_read: bool = True # 是否启用读空气功能 enable_kuuki_read: bool = True # 是否启用读空气功能
enable_debug_output: bool = False # 是否启用调试输出
mood_update_interval: float = 1.0 # 情绪更新间隔 单位秒 mood_update_interval: float = 1.0 # 情绪更新间隔 单位秒
mood_decay_rate: float = 0.95 # 情绪衰减率 mood_decay_rate: float = 0.95 # 情绪衰减率
@@ -325,6 +327,7 @@ class BotConfig:
others_config = parent["others"] others_config = parent["others"]
config.enable_advance_output = others_config.get("enable_advance_output", config.enable_advance_output) config.enable_advance_output = others_config.get("enable_advance_output", config.enable_advance_output)
config.enable_kuuki_read = others_config.get("enable_kuuki_read", config.enable_kuuki_read) config.enable_kuuki_read = others_config.get("enable_kuuki_read", config.enable_kuuki_read)
config.enable_debug_output = others_config.get("enable_debug_output", config.enable_debug_output)
# 版本表达式：>=1.0.0,<2.0.0 # 版本表达式：>=1.0.0,<2.0.0
# 允许字段：func: method, support: str, notice: str, necessary: bool # 允许字段：func: method, support: str, notice: str, necessary: bool
@@ -419,4 +422,8 @@ global_config = BotConfig.load_config(config_path=bot_config_path)
if not global_config.enable_advance_output: if not global_config.enable_advance_output:
logger.remove() logger.remove()
pass
# 调试输出功能
if global_config.enable_debug_output:
logger.remove()
logger.add(sys.stdout, level="DEBUG")

30
src/plugins/models/utils_model.py
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@@ -184,18 +184,21 @@ class LLM_request:
elif response.status in policy["abort_codes"]: elif response.status in policy["abort_codes"]:
logger.error(f"错误码: {response.status} - {error_code_mapping.get(response.status)}") logger.error(f"错误码: {response.status} - {error_code_mapping.get(response.status)}")
if response.status == 403: if response.status == 403:
# 尝试降级Pro模型 #只针对硅基流动的V3和R1进行降级处理
if self.model_name.startswith( if self.model_name.startswith(
"Pro/") and self.base_url == "https://api.siliconflow.cn/v1/": "Pro/deepseek-ai") and self.base_url == "https://api.siliconflow.cn/v1/":
old_model_name = self.model_name old_model_name = self.model_name
self.model_name = self.model_name[4:] # 移除"Pro/"前缀 self.model_name = self.model_name[4:] # 移除"Pro/"前缀
logger.warning(f"检测到403错误，模型从 {old_model_name} 降级为 {self.model_name}") logger.warning(f"检测到403错误，模型从 {old_model_name} 降级为 {self.model_name}")
# 对全局配置进行更新 # 对全局配置进行更新
if hasattr(global_config, 'llm_normal') and global_config.llm_normal.get( if global_config.llm_normal.get('name') == old_model_name:
'name') == old_model_name:
global_config.llm_normal['name'] = self.model_name global_config.llm_normal['name'] = self.model_name
logger.warning("已将全局配置中的 llm_normal 模型降级") logger.warning(f"将全局配置中的 llm_normal 模型临时降级至{self.model_name}")
if global_config.llm_reasoning.get('name') == old_model_name:
global_config.llm_reasoning['name'] = self.model_name
logger.warning(f"将全局配置中的 llm_reasoning 模型临时降级至{self.model_name}")
# 更新payload中的模型名 # 更新payload中的模型名
if payload and 'model' in payload: if payload and 'model' in payload:
@@ -211,6 +214,7 @@ class LLM_request:
# 将流式输出转化为非流式输出 # 将流式输出转化为非流式输出
if stream_mode: if stream_mode:
flag_delta_content_finished = False
accumulated_content = "" accumulated_content = ""
async for line_bytes in response.content: async for line_bytes in response.content:
line = line_bytes.decode("utf-8").strip() line = line_bytes.decode("utf-8").strip()
@@ -222,13 +226,25 @@ class LLM_request:
break break
try: try:
chunk = json.loads(data_str) chunk = json.loads(data_str)
if flag_delta_content_finished:
usage = chunk.get("usage", None) # 获取tokn用量
else:
delta = chunk["choices"][0]["delta"] delta = chunk["choices"][0]["delta"]
delta_content = delta.get("content") delta_content = delta.get("content")
if delta_content is None: if delta_content is None:
delta_content = "" delta_content = ""
accumulated_content += delta_content accumulated_content += delta_content
# 检测流式输出文本是否结束
finish_reason = chunk["choices"][0]["finish_reason"]
if finish_reason == "stop":
usage = chunk.get("usage", None)
if usage:
break
# 部分平台在文本输出结束前不会返回token用量，此时需要再获取一次chunk
flag_delta_content_finished = True
except Exception: except Exception:
logger.exception("解析流式输出错") logger.exception("解析流式输出错误")
content = accumulated_content content = accumulated_content
reasoning_content = "" reasoning_content = ""
think_match = re.search(r'<think>(.*?)</think>', content, re.DOTALL) think_match = re.search(r'<think>(.*?)</think>', content, re.DOTALL)
@@ -237,7 +253,7 @@ class LLM_request:
content = re.sub(r'<think>.*?</think>', '', content, flags=re.DOTALL).strip() content = re.sub(r'<think>.*?</think>', '', content, flags=re.DOTALL).strip()
# 构造一个伪result以便调用自定义响应处理器或默认处理器 # 构造一个伪result以便调用自定义响应处理器或默认处理器
result = { result = {
"choices": [{"message": {"content": content, "reasoning_content": reasoning_content}}]} "choices": [{"message": {"content": content, "reasoning_content": reasoning_content}}], "usage": usage}
return response_handler(result) if response_handler else self._default_response_handler( return response_handler(result) if response_handler else self._default_response_handler(
result, user_id, request_type, endpoint) result, user_id, request_type, endpoint)
else: else:

1
template/bot_config_template.toml
View File

@@ -100,6 +100,7 @@ word_replace_rate=0.006 # 整词替换概率
[others] [others]
enable_advance_output = true # 是否启用高级输出 enable_advance_output = true # 是否启用高级输出
enable_kuuki_read = true # 是否启用读空气功能 enable_kuuki_read = true # 是否启用读空气功能
enable_debug_output = false # 是否启用调试输出
[groups] [groups]
talk_allowed = [ talk_allowed = [