better：优化了图片展示形式

src/chat/utils/utils_image.py

@@ -2,10 +2,12 @@ import base64
 import os
 import time
 import hashlib
-from typing import Optional
+import uuid
+from typing import Optional, Tuple
 from PIL import Image
 import io
 import numpy as np
+import asyncio
 
 
 from src.common.database.database import db
@@ -360,6 +362,125 @@ class ImageManager:
             logger.error(f"GIF转换失败: {str(e)}", exc_info=True)  # 记录详细错误信息
             return None  # 其他错误也返回None
 
+    async def process_image(self, image_base64: str) -> Tuple[str, str]:
+        """处理图片并返回图片ID和描述
+
+        Args:
+            image_base64: 图片的base64编码
+
+        Returns:
+            Tuple[str, str]: (图片ID, 描述)
+        """
+        try:
+            # 生成图片ID            
+            # 计算图片哈希
+            image_bytes = base64.b64decode(image_base64)
+            image_hash = hashlib.md5(image_bytes).hexdigest()
+            
+            # 检查图片是否已存在
+            existing_image = Images.get_or_none(Images.emoji_hash == image_hash)
+            
+            if existing_image:
+                # print(f"图片已存在: {existing_image.image_id}")
+                # print(f"图片描述: {existing_image.description}")
+                # print(f"图片计数: {existing_image.count}")
+                # 更新计数
+                existing_image.count += 1
+                existing_image.save()
+                return existing_image.image_id, f"[picid:{existing_image.image_id}]"
+            else:
+                # print(f"图片不存在: {image_hash}")
+                image_id = str(uuid.uuid4())
+            
+            # 保存新图片
+            current_timestamp = time.time()
+            image_dir = os.path.join(self.IMAGE_DIR, "images")
+            os.makedirs(image_dir, exist_ok=True)
+            filename = f"{image_id}.png"
+            file_path = os.path.join(image_dir, filename)
+            
+            # 保存文件
+            with open(file_path, "wb") as f:
+                f.write(image_bytes)
+            
+            # 保存到数据库
+            Images.create(
+                image_id=image_id,
+                emoji_hash=image_hash,
+                path=file_path,
+                base64=image_base64,
+                type="image",
+                timestamp=current_timestamp,
+                vlm_processed=False
+            )
+            
+            # 启动异步VLM处理
+            asyncio.create_task(self._process_image_with_vlm(image_id, image_base64))
+            
+            return image_id, f"[picid:{image_id}]"
+            
+        except Exception as e:
+            logger.error(f"处理图片失败: {str(e)}")
+            return "", "[图片]"
+
+    async def _process_image_with_vlm(self, image_id: str, image_base64: str) -> None:
+        """使用VLM处理图片并更新数据库
+
+        Args:
+            image_id: 图片ID
+            image_base64: 图片的base64编码
+        """
+        try:
+            # 计算图片哈希
+            image_bytes = base64.b64decode(image_base64)
+            image_hash = hashlib.md5(image_bytes).hexdigest()
+            
+            # 先检查缓存的描述
+            cached_description = self._get_description_from_db(image_hash, "image")
+            if cached_description:
+                logger.debug(f"VLM处理时发现缓存描述: {cached_description}")
+                # 更新数据库
+                image = Images.get(Images.image_id == image_id)
+                image.description = cached_description
+                image.vlm_processed = True
+                image.save()
+                return
+            
+            # 获取图片格式
+            image_format = Image.open(io.BytesIO(image_bytes)).format.lower()
+            
+            # 构建prompt
+            prompt = """请用中文描述这张图片的内容。如果有文字，请把文字描述概括出来，请留意其主题，直观感受，输出为一段平文本，最多50字"""
+            
+            # 获取VLM描述
+            description, _ = await self._llm.generate_response_for_image(
+                prompt, 
+                image_base64,
+                image_format
+            )
+            
+            if description is None:
+                logger.warning("VLM未能生成图片描述")
+                description = "无法生成描述"
+            
+            # 再次检查缓存，防止并发写入时重复生成
+            cached_description = self._get_description_from_db(image_hash, "image")
+            if cached_description:
+                logger.warning(f"虽然生成了描述，但是找到缓存图片描述: {cached_description}")
+                description = cached_description
+            
+            # 更新数据库
+            image = Images.get(Images.image_id == image_id)
+            image.description = description
+            image.vlm_processed = True
+            image.save()
+            
+            # 保存描述到ImageDescriptions表
+            self._save_description_to_db(image_hash, description, "image")
+            
+        except Exception as e:
+            logger.error(f"VLM处理图片失败: {str(e)}")
+
 
 # 创建全局单例
 image_manager = None