Fix: 完美的图片压缩 @sourcery-ai (#54)

* fix: logger三合一

* fix: emoji压缩功能正常使用

* fix: 提高压缩率

* fix: 0.8MB

src/plugins/chat/bot.py

@@ -16,6 +16,7 @@ from .relationship_manager import relationship_manager
 from .willing_manager import willing_manager  # 导入意愿管理器
 from .utils import is_mentioned_bot_in_txt, calculate_typing_time
 from ..memory_system.memory import memory_graph
+from loguru import logger
 
 class ChatBot:
     def __init__(self):
@@ -61,8 +62,8 @@ class ChatBot:
         # 过滤词
         for word in global_config.ban_words:
             if word in message.detailed_plain_text:
-                print(f"\033[1;32m[{message.group_name}]{message.user_nickname}:\033[0m {message.processed_plain_text}")
+                logger.info(f"\033[1;32m[{message.group_name}]{message.user_nickname}:\033[0m {message.processed_plain_text}")
-                print(f"\033[1;32m[过滤词识别]\033[0m 消息中含有{word}，filtered")
+                logger.info(f"\033[1;32m[过滤词识别]\033[0m 消息中含有{word}，filtered")
                 return
         
         current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(message.time))
@@ -77,8 +78,7 @@ class ChatBot:
         # topic1 = topic_identifier.identify_topic_jieba(message.processed_plain_text)
         # topic2 = await topic_identifier.identify_topic_llm(message.processed_plain_text)
         # topic3 = topic_identifier.identify_topic_snownlp(message.processed_plain_text)
-        print(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}")
-
         
         all_num = 0
         interested_num = 0

src/plugins/chat/config.py

@@ -1,8 +1,6 @@
 from dataclasses import dataclass, field
 from typing import Dict, Any, Optional, Set
 import os
-from nonebot.log import logger, default_format
-import logging
 import configparser
 import tomli
 import sys
@@ -85,9 +83,9 @@ class BotConfig:
                 personality_config=toml_dict['personality']
                 personality=personality_config.get('prompt_personality')
                 if len(personality) >= 2:
-                    print(f"载入自定义人格:{personality}")
+                    logger.info(f"载入自定义人格:{personality}")
                     config.PROMPT_PERSONALITY=personality_config.get('prompt_personality',config.PROMPT_PERSONALITY)
-                print(f"载入自定义日程prompt:{personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)}")
+                logger.info(f"载入自定义日程prompt:{personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)}")
                 config.PROMPT_SCHEDULE_GEN=personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)
 
             if "emoji" in toml_dict:
@@ -141,10 +139,10 @@ class BotConfig:
                 topic_config=toml_dict['topic']
                 if 'topic_extract' in topic_config:
                     config.topic_extract=topic_config.get('topic_extract',config.topic_extract)
-                    print(f"载入自定义主题提取为{config.topic_extract}")
+                    logger.info(f"载入自定义主题提取为{config.topic_extract}")
                 if config.topic_extract=='llm' and 'llm_topic' in topic_config:
                     config.llm_topic_extract=topic_config['llm_topic']
-                    print(f"载入自定义主题提取模型为{config.llm_topic_extract['name']}")
+                    logger.info(f"载入自定义主题提取模型为{config.llm_topic_extract['name']}")
                 
             # 消息配置
             if "message" in toml_dict:

src/plugins/chat/emoji_manager.py

@@ -12,6 +12,8 @@ import base64
 import shutil
 import asyncio
 import time
+from PIL import Image
+import io
 
 from nonebot import get_driver
 from ..chat.config import global_config
@@ -240,36 +242,97 @@ class EmojiManager:
         print(f"\033[1;32m[调试信息]\033[0m 使用默认标签: neutral")
         return "skip"  # 默认标签
 
+    async def _compress_image(self, image_path: str, target_size: int = 0.8 * 1024 * 1024) -> Optional[str]:
+        """压缩图片并返回base64编码
+        Args:
+            image_path: 图片文件路径
+            target_size: 目标文件大小（字节），默认0.8MB
+        Returns:
+            Optional[str]: 成功返回base64编码的图片数据，失败返回None
+        """
+        try:
+            file_size = os.path.getsize(image_path)
+            if file_size <= target_size:
+                # 如果文件已经小于目标大小，直接读取并返回base64
+                with open(image_path, 'rb') as f:
+                    return base64.b64encode(f.read()).decode('utf-8')
+            
+            # 打开图片
+            with Image.open(image_path) as img:
+                # 获取原始尺寸
+                original_width, original_height = img.size
+                
+                # 计算缩放比例
+                scale = min(1.0, (target_size / file_size) ** 0.5)
+                
+                # 计算新的尺寸
+                new_width = int(original_width * scale)
+                new_height = int(original_height * scale)
+                
+                # 创建内存缓冲区
+                output_buffer = io.BytesIO()
+                
+                # 如果是GIF，处理所有帧
+                if getattr(img, "is_animated", False):
+                    frames = []
+                    for frame_idx in range(img.n_frames):
+                        img.seek(frame_idx)
+                        new_frame = img.copy()
+                        new_frame = new_frame.resize((new_width, new_height), Image.Resampling.LANCZOS)
+                        frames.append(new_frame)
+                    
+                    # 保存到缓冲区
+                    frames[0].save(
+                        output_buffer,
+                        format='GIF',
+                        save_all=True,
+                        append_images=frames[1:],
+                        optimize=True,
+                        duration=img.info.get('duration', 100),
+                        loop=img.info.get('loop', 0)
+                    )
+                else:
+                    # 处理静态图片
+                    resized_img = img.resize((new_width, new_height), Image.Resampling.LANCZOS)
+                    
+                    # 保存到缓冲区，保持原始格式
+                    if img.format == 'PNG' and img.mode in ('RGBA', 'LA'):
+                        resized_img.save(output_buffer, format='PNG', optimize=True)
+                    else:
+                        resized_img.save(output_buffer, format='JPEG', quality=95, optimize=True)
+                
+                # 获取压缩后的数据并转换为base64
+                compressed_data = output_buffer.getvalue()
+                print(f"\033[1;32m[成功]\033[0m 压缩图片: {os.path.basename(image_path)} ({original_width}x{original_height} -> {new_width}x{new_height})")
+                
+                return base64.b64encode(compressed_data).decode('utf-8')
+                
+        except Exception as e:
+            print(f"\033[1;31m[错误]\033[0m 压缩图片失败: {os.path.basename(image_path)}, 错误: {str(e)}")
+            return None
+            
     async def scan_new_emojis(self):
         """扫描新的表情包"""
         try:
             emoji_dir = "data/emoji"
             os.makedirs(emoji_dir, exist_ok=True)
 
-            # 获取所有jpg文件
+            # 获取所有支持的图片文件
-            files_to_process = [f for f in os.listdir(emoji_dir) if f.endswith('.jpg')]
+            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)
                 
-                # 检查文件大小
-                file_size = os.path.getsize(image_path)
-                if file_size > 5 * 1024 * 1024:  # 5MB
-                    print(f"\033[1;33m[警告]\033[0m 表情包文件过大 ({file_size/1024/1024:.2f}MB)，删除: {filename}")
-                    os.remove(image_path)
-                    continue
-                
                 # 检查是否已经注册过
                 existing_emoji = self.db.db['emoji'].find_one({'filename': filename})
                 if existing_emoji:
                     continue
                 
-                # 读取图片数据
+                # 压缩图片并获取base64编码
-                with open(image_path, 'rb') as f:
+                image_base64 = await self._compress_image(image_path)
-                    image_data = f.read()
+                if image_base64 is None:
-                
+                    os.remove(image_path)
-                # 将图片转换为base64
+                    continue
-                image_base64 = base64.b64encode(image_data).decode('utf-8')
                 
                 # 获取表情包的情感标签
                 tag = await self._get_emoji_tag(image_base64)
@@ -289,7 +352,6 @@ class EmojiManager:
                 else:
                     print(f"\033[1;33m[警告]\033[0m 跳过表情包: {filename}")
                 
-                
         except Exception as e:
             print(f"\033[1;31m[错误]\033[0m 扫描表情包失败: {str(e)}")
             import traceback