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refactor: 日志打印优化（终于改完了，爽了

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This commit is contained in:
AL76
2025-03-10 02:25:03 +08:00
parent 8d99592b32
commit 052e67b576
15 changed files with 431 additions and 412 deletions
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114
src/plugins/chat/emoji_manager.py
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@@ -21,24 +21,25 @@ config = driver.config
class EmojiManager:
_instance = None
EMOJI_DIR = "data/emoji" # 表情包存储目录
def __new__(cls):
if cls._instance is None:
cls._instance = super().__new__(cls)
cls._instance.db = None
cls._instance._initialized = False
return cls._instance
def __init__(self):
self.db = Database.get_instance()
self._scan_task = None
self.vlm = LLM_request(model=global_config.vlm, temperature=0.3, max_tokens=1000)
self.llm_emotion_judge = LLM_request(model=global_config.llm_normal_minor, max_tokens=60,temperature=0.8) #更高的温度，更少的token（后续可以根据情绪来调整温度）
self.llm_emotion_judge = LLM_request(model=global_config.llm_normal_minor, max_tokens=60,
temperature=0.8) # 更高的温度，更少的token（后续可以根据情绪来调整温度）
def _ensure_emoji_dir(self):
"""确保表情存储目录存在"""
os.makedirs(self.EMOJI_DIR, exist_ok=True)
def initialize(self):
"""初始化数据库连接和表情目录"""
if not self._initialized:
@@ -50,15 +51,15 @@ class EmojiManager:
# 启动时执行一次完整性检查
self.check_emoji_file_integrity()
except Exception as e:
logger.error(f"初始化表情管理器失败: {str(e)}")
logger.exception(f"初始化表情管理器失败")
def _ensure_db(self):
"""确保数据库已初始化"""
if not self._initialized:
self.initialize()
if not self._initialized:
raise RuntimeError("EmojiManager not initialized")
def _ensure_emoji_collection(self):
"""确保emoji集合存在并创建索引
@@ -76,7 +77,7 @@ class EmojiManager:
self.db.db.emoji.create_index([('embedding', '2dsphere')])
self.db.db.emoji.create_index([('tags', 1)])
self.db.db.emoji.create_index([('filename', 1)], unique=True)
def record_usage(self, emoji_id: str):
"""记录表情使用次数"""
try:
@@ -86,8 +87,8 @@ class EmojiManager:
{'$inc': {'usage_count': 1}}
)
except Exception as e:
logger.error(f"记录表情使用失败: {str(e)}")
logger.exception(f"记录表情使用失败")
async def get_emoji_for_text(self, text: str) -> Optional[str]:
"""根据文本内容获取相关表情包
Args:
@@ -102,9 +103,9 @@ class EmojiManager:
"""
try:
self._ensure_db()
# 获取文本的embedding
text_for_search= await self._get_kimoji_for_text(text)
text_for_search = await self._get_kimoji_for_text(text)
if not text_for_search:
logger.error("无法获取文本的情绪")
return None
@@ -112,15 +113,15 @@ class EmojiManager:
if not text_embedding:
logger.error("无法获取文本的embedding")
return None
try:
# 获取所有表情包
all_emojis = list(self.db.db.emoji.find({}, {'_id': 1, 'path': 1, 'embedding': 1, 'discription': 1}))
if not all_emojis:
logger.warning("数据库中没有任何表情包")
return None
# 计算余弦相似度并排序
def cosine_similarity(v1, v2):
if not v1 or not v2:
@@ -131,42 +132,43 @@ class EmojiManager:
if norm_v1 == 0 or norm_v2 == 0:
return 0
return dot_product / (norm_v1 * norm_v2)
# 计算所有表情包与输入文本的相似度
emoji_similarities = [
(emoji, cosine_similarity(text_embedding, emoji.get('embedding', [])))
for emoji in all_emojis
]
# 按相似度降序排序
emoji_similarities.sort(key=lambda x: x[1], reverse=True)
# 获取前3个最相似的表情包
top_3_emojis = emoji_similarities[:3]
if not top_3_emojis:
logger.warning("未找到匹配的表情包")
return None
# 从前3个中随机选择一个
selected_emoji, similarity = random.choice(top_3_emojis)
if selected_emoji and 'path' in selected_emoji:
# 更新使用次数
self.db.db.emoji.update_one(
{'_id': selected_emoji['_id']},
{'$inc': {'usage_count': 1}}
)
logger.success(f"找到匹配的表情包: {selected_emoji.get('discription', '无描述')} (相似度: {similarity:.4f})")
logger.success(
f"找到匹配的表情包: {selected_emoji.get('discription', '无描述')} (相似度: {similarity:.4f})")
# 稍微改一下文本描述，不然容易产生幻觉，描述已经包含 表情包 了
return selected_emoji['path'],"[ %s ]" % selected_emoji.get('discription', '无描述')
return selected_emoji['path'], "[ %s ]" % selected_emoji.get('discription', '无描述')
except Exception as search_error:
logger.error(f"搜索表情包失败: {str(search_error)}")
return None
return None
except Exception as e:
logger.error(f"获取表情包失败: {str(e)}")
return None
@@ -175,39 +177,39 @@ class EmojiManager:
"""获取表情包的标签"""
try:
prompt = '这是一个表情包，使用中文简洁的描述一下表情包的内容和表情包所表达的情感'
content, _ = await self.vlm.generate_response_for_image(prompt, image_base64)
logger.debug(f"输出描述: {content}")
return content
except Exception as e:
logger.error(f"获取标签失败: {str(e)}")
return None
async def _check_emoji(self, image_base64: str) -> str:
try:
prompt = f'这是一个表情包，请回答这个表情包是否满足\"{global_config.EMOJI_CHECK_PROMPT}\"的要求，是则回答是，否则回答否，不要出现任何其他内容'
content, _ = await self.vlm.generate_response_for_image(prompt, image_base64)
logger.debug(f"输出描述: {content}")
return content
except Exception as e:
logger.error(f"获取标签失败: {str(e)}")
return None
async def _get_kimoji_for_text(self, text:str):
async def _get_kimoji_for_text(self, text: str):
try:
prompt = f'这是{global_config.BOT_NICKNAME}将要发送的消息内容:\n{text}\n若要为其配上表情包，请你输出这个表情包应该表达怎样的情感，应该给人什么样的感觉，不要太简洁也不要太长，注意不要输出任何对消息内容的分析内容，只输出\"一种什么样的感觉\"中间的形容词部分。'
content, _ = await self.llm_emotion_judge.generate_response_async(prompt)
logger.info(f"输出描述: {content}")
return content
except Exception as e:
logger.error(f"获取标签失败: {str(e)}")
return None
async def scan_new_emojis(self):
"""扫描新的表情包"""
try:
@@ -215,22 +217,23 @@ class EmojiManager:
os.makedirs(emoji_dir, exist_ok=True)
# 获取所有支持的图片文件
files_to_process = [f for f in os.listdir(emoji_dir) if f.lower().endswith(('.jpg', '.jpeg', '.png', '.gif'))]
files_to_process = [f for f in os.listdir(emoji_dir) if
f.lower().endswith(('.jpg', '.jpeg', '.png', '.gif'))]
for filename in files_to_process:
image_path = os.path.join(emoji_dir, filename)
# 检查是否已经注册过
existing_emoji = self.db.db['emoji'].find_one({'filename': filename})
if existing_emoji:
continue
# 压缩图片并获取base64编码
image_base64 = image_path_to_base64(image_path)
if image_base64 is None:
os.remove(image_path)
continue
# 获取表情包的描述
discription = await self._get_emoji_discription(image_base64)
if global_config.EMOJI_CHECK:
@@ -247,30 +250,28 @@ class EmojiManager:
emoji_record = {
'filename': filename,
'path': image_path,
'embedding':embedding,
'embedding': embedding,
'discription': discription,
'timestamp': int(time.time())
}
# 保存到数据库
self.db.db['emoji'].insert_one(emoji_record)
logger.success(f"注册新表情包: {filename}")
logger.info(f"描述: {discription}")
else:
logger.warning(f"跳过表情包: {filename}")
except Exception as e:
logger.error(f"扫描表情包失败: {str(e)}")
logger.error(traceback.format_exc())
logger.exception(f"扫描表情包失败")
async def _periodic_scan(self, interval_MINS: int = 10):
"""定期扫描新表情包"""
while True:
print("\033[1;36m[表情包]\033[0m 开始扫描新表情包...")
logger.info("开始扫描新表情包...")
await self.scan_new_emojis()
await asyncio.sleep(interval_MINS * 60) # 每600秒扫描一次
def check_emoji_file_integrity(self):
"""检查表情包文件完整性
如果文件已被删除，则从数据库中移除对应记录
@@ -281,7 +282,7 @@ class EmojiManager:
all_emojis = list(self.db.db.emoji.find())
removed_count = 0
total_count = len(all_emojis)
for emoji in all_emojis:
try:
if 'path' not in emoji:
@@ -289,13 +290,13 @@ class EmojiManager:
self.db.db.emoji.delete_one({'_id': emoji['_id']})
removed_count += 1
continue
if 'embedding' not in emoji:
logger.warning(f"发现过时记录（缺少embedding字段），ID: {emoji.get('_id', 'unknown')}")
self.db.db.emoji.delete_one({'_id': emoji['_id']})
removed_count += 1
continue
# 检查文件是否存在
if not os.path.exists(emoji['path']):
logger.warning(f"表情包文件已被删除: {emoji['path']}")
@@ -309,7 +310,7 @@ class EmojiManager:
except Exception as item_error:
logger.error(f"处理表情包记录时出错: {str(item_error)}")
continue
# 验证清理结果
remaining_count = self.db.db.emoji.count_documents({})
if removed_count > 0:
@@ -317,7 +318,7 @@ class EmojiManager:
logger.info(f"清理前总数: {total_count} | 清理后总数: {remaining_count}")
else:
logger.info(f"已检查 {total_count} 个表情包记录")
except Exception as e:
logger.error(f"检查表情包完整性失败: {str(e)}")
logger.error(traceback.format_exc())
@@ -328,6 +329,5 @@ class EmojiManager:
await asyncio.sleep(interval_MINS * 60)
# 创建全局单例
emoji_manager = EmojiManager()
emoji_manager = EmojiManager()