fix: 增强情感标签生成的鲁棒性

src/plugins/chat/llm_generator.py

@@ -138,9 +138,12 @@ class ResponseGenerator:
             内容：{content}
             输出：
             '''
-            
             content, _ = await self.model_v3.generate_response(prompt)
-            return [content.strip()] if content else ["neutral"]
+            content=content.strip()
+            if content in ['happy','angry','sad','surprised','disgusted','fearful','neutral']:
+                return [content]
+            else:
+                return ["neutral"]
             
         except Exception as e:
             print(f"获取情感标签时出错: {e}")

src/plugins/chat/utils_image.py

@@ -257,71 +257,3 @@ def compress_base64_image_by_scale(base64_data: str, scale: float = 0.5) -> str:
         print(traceback.format_exc())
         return base64_data 
     
-async def compress_image( image_path: str, target_size: int = 0.8 * 1024 * 1024):
-    """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