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refactor: 重构配置模块

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This commit is contained in:
Oct-autumn
2025-05-16 16:50:53 +08:00
parent 5d5033452d
commit 021e7f1a97
52 changed files with 902 additions and 1102 deletions
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8
src/chat/utils/chat_message_builder.py
View File

@@ -190,8 +190,8 @@ async def _build_readable_messages_internal(
person_id = person_info_manager.get_person_id(platform, user_id)
# 根据 replace_bot_name 参数决定是否替换机器人名称
if replace_bot_name and user_id == global_config.BOT_QQ:
person_name = f"{global_config.BOT_NICKNAME}(你)"
if replace_bot_name and user_id == global_config.bot.qq_account:
person_name = f"{global_config.bot.nickname}(你)"
else:
person_name = await person_info_manager.get_value(person_id, "person_name")
@@ -427,7 +427,7 @@ async def build_anonymous_messages(messages: List[Dict[str, Any]]) -> str:
output_lines = []
def get_anon_name(platform, user_id):
if user_id == global_config.BOT_QQ:
if user_id == global_config.bot.qq_account:
return "SELF"
person_id = person_info_manager.get_person_id(platform, user_id)
if person_id not in person_map:
@@ -501,7 +501,7 @@ async def get_person_id_list(messages: List[Dict[str, Any]]) -> List[str]:
user_id = user_info.get("user_id")
# 检查必要信息是否存在 且 不是机器人自己
if not all([platform, user_id]) or user_id == global_config.BOT_QQ:
if not all([platform, user_id]) or user_id == global_config.bot.qq_account:
continue
person_id = person_info_manager.get_person_id(platform, user_id)

3
src/chat/utils/info_catcher.py
View File

@@ -9,7 +9,6 @@ from typing import List
class InfoCatcher:
def __init__(self):
self.chat_history = [] # 聊天历史，长度为三倍使用的上下文喵~
self.context_length = global_config.observation_context_size
self.chat_history_in_thinking = [] # 思考期间的聊天内容喵~
self.chat_history_after_response = [] # 回复后的聊天内容，长度为一倍上下文喵~
@@ -143,7 +142,7 @@ class InfoCatcher:
messages_before = (
db.messages.find({"chat_id": chat_id, "message_id": {"$lt": message_id}})
.sort("time", -1)
.limit(self.context_length * 3)
.limit(global_config.chat.observation_context_size * 3)
) # 获取更多历史信息
return list(messages_before)

37
src/chat/utils/utils.py
View File

@@ -43,8 +43,8 @@ def db_message_to_str(message_dict: dict) -> str:
def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, float]:
"""检查消息是否提到了机器人"""
keywords = [global_config.BOT_NICKNAME]
nicknames = global_config.BOT_ALIAS_NAMES
keywords = [global_config.bot.nickname]
nicknames = global_config.bot.alias_names
reply_probability = 0.0
is_at = False
is_mentioned = False
@@ -64,18 +64,18 @@ def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, float]:
)
# 判断是否被@
if re.search(f"@[\s\S]*?（id:{global_config.BOT_QQ}）", message.processed_plain_text):
if re.search(f"@[\s\S]*?（id:{global_config.bot.qq_account}）", message.processed_plain_text):
is_at = True
is_mentioned = True
if is_at and global_config.at_bot_inevitable_reply:
if is_at and global_config.normal_chat.at_bot_inevitable_reply:
reply_probability = 1.0
logger.info("被@，回复概率设置为100%")
else:
if not is_mentioned:
# 判断是否被回复
if re.match(
f"\[回复 [\s\S]*?\({str(global_config.BOT_QQ)}\)：[\s\S]*?]，说：", message.processed_plain_text
f"\[回复 [\s\S]*?\({str(global_config.bot.qq_account)}\)：[\s\S]*?]，说：", message.processed_plain_text
):
is_mentioned = True
else:
@@ -88,7 +88,7 @@ def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, float]:
for nickname in nicknames:
if nickname in message_content:
is_mentioned = True
if is_mentioned and global_config.mentioned_bot_inevitable_reply:
if is_mentioned and global_config.normal_chat.mentioned_bot_inevitable_reply:
reply_probability = 1.0
logger.info("被提及，回复概率设置为100%")
return is_mentioned, reply_probability
@@ -96,7 +96,8 @@ def is_mentioned_bot_in_message(message: MessageRecv) -> tuple[bool, float]:
async def get_embedding(text, request_type="embedding"):
"""获取文本的embedding向量"""
llm = LLMRequest(model=global_config.embedding, request_type=request_type)
# TODO: API-Adapter修改标记
llm = LLMRequest(model=global_config.model.embedding, request_type=request_type)
# return llm.get_embedding_sync(text)
try:
embedding = await llm.get_embedding(text)
@@ -163,7 +164,7 @@ def get_recent_group_speaker(chat_stream_id: int, sender, limit: int = 12) -> li
user_info = UserInfo.from_dict(msg_db_data["user_info"])
if (
(user_info.platform, user_info.user_id) != sender
and user_info.user_id != global_config.BOT_QQ
and user_info.user_id != global_config.bot.qq_account
and (user_info.platform, user_info.user_id, user_info.user_nickname) not in who_chat_in_group
and len(who_chat_in_group) < 5
): # 排除重复，排除消息发送者，排除bot，限制加载的关系数目
@@ -321,7 +322,7 @@ def random_remove_punctuation(text: str) -> str:
def process_llm_response(text: str) -> list[str]:
# 先保护颜文字
if global_config.enable_kaomoji_protection:
if global_config.response_splitter.enable_kaomoji_protection:
protected_text, kaomoji_mapping = protect_kaomoji(text)
logger.trace(f"保护颜文字后的文本: {protected_text}")
else:
@@ -340,8 +341,8 @@ def process_llm_response(text: str) -> list[str]:
logger.debug(f"{text}去除括号处理后的文本: {cleaned_text}")
# 对清理后的文本进行进一步处理
max_length = global_config.response_max_length * 2
max_sentence_num = global_config.response_max_sentence_num
max_length = global_config.response_splitter.max_length * 2
max_sentence_num = global_config.response_splitter.max_sentence_num
# 如果基本上是中文，则进行长度过滤
if get_western_ratio(cleaned_text) < 0.1:
if len(cleaned_text) > max_length:
@@ -349,20 +350,20 @@ def process_llm_response(text: str) -> list[str]:
return ["懒得说"]
typo_generator = ChineseTypoGenerator(
error_rate=global_config.chinese_typo_error_rate,
min_freq=global_config.chinese_typo_min_freq,
tone_error_rate=global_config.chinese_typo_tone_error_rate,
word_replace_rate=global_config.chinese_typo_word_replace_rate,
error_rate=global_config.chinese_typo.error_rate,
min_freq=global_config.chinese_typo.min_freq,
tone_error_rate=global_config.chinese_typo.tone_error_rate,
word_replace_rate=global_config.chinese_typo.word_replace_rate,
)
if global_config.enable_response_splitter:
if global_config.response_splitter.enable:
split_sentences = split_into_sentences_w_remove_punctuation(cleaned_text)
else:
split_sentences = [cleaned_text]
sentences = []
for sentence in split_sentences:
if global_config.chinese_typo_enable:
if global_config.chinese_typo.enable:
typoed_text, typo_corrections = typo_generator.create_typo_sentence(sentence)
sentences.append(typoed_text)
if typo_corrections:
@@ -372,7 +373,7 @@ def process_llm_response(text: str) -> list[str]:
if len(sentences) > max_sentence_num:
logger.warning(f"分割后消息数量过多 ({len(sentences)} 条)，返回默认回复")
return [f"{global_config.BOT_NICKNAME}不知道哦"]
return [f"{global_config.bot.nickname}不知道哦"]
# if extracted_contents:
# for content in extracted_contents:

6
src/chat/utils/utils_image.py
View File

@@ -36,7 +36,7 @@ class ImageManager:
self._ensure_description_collection()
self._ensure_image_dir()
self._initialized = True
self._llm = LLMRequest(model=global_config.vlm, temperature=0.4, max_tokens=300, request_type="image")
self._llm = LLMRequest(model=global_config.model.vlm, temperature=0.4, max_tokens=300, request_type="image")
def _ensure_image_dir(self):
"""确保图像存储目录存在"""
@@ -134,7 +134,7 @@ class ImageManager:
return f"[表情包，含义看起来是：{cached_description}]"
# 根据配置决定是否保存图片
if global_config.save_emoji:
if global_config.emoji.save_emoji:
# 生成文件名和路径
timestamp = int(time.time())
filename = f"{timestamp}_{image_hash[:8]}.{image_format}"
@@ -200,7 +200,7 @@ class ImageManager:
return "[图片]"
# 根据配置决定是否保存图片
if global_config.save_pic:
if global_config.emoji.save_pic:
# 生成文件名和路径
timestamp = int(time.time())
filename = f"{timestamp}_{image_hash[:8]}.{image_format}"