feat: 支持多图上传和智能解析产品参数

- 新增 /api/parse-images API 预览解析结果
- 智能添加支持多张图片上传和粘贴
- 支持一次解析出多个产品参数
- 所有类别（模型/GPU/CPU/动态分类）都支持图片解析
- 添加 vision_model 配置支持视觉模型

app.py

@@ -1,7 +1,7 @@
 """
 ParamHub - 参数百科
 AI大模型与硬件参数速查平台
-v1.4.0 - 新增图片上传功能
+v1.5.0 - 支持多图上传和智能解析产品参数
 """
 
 from flask import Flask, render_template, jsonify, request
@@ -46,6 +46,7 @@ LLM_CONFIG = {
     'base_url': 'http://192.168.2.17:19007/v1',
     'api_key': 'xxxx',
     'model': 'auto',
+    'vision_model': 'gpt-4-vision-preview',  # 视觉模型（解析图片）
 }
 
 # 默认网站配置
@@ -81,9 +82,10 @@ def save_data(file_path, data):
 
 # ============ 大模型智能解析 ============
 
-def parse_with_llm(text, category_type):
+def parse_with_llm(text, category_type, images=None):
     """
-    使用大模型解析文本，提取结构化数据
+    使用大模型解析文本/图片，提取结构化数据
+    支持多张图片输入，可能解析出多个产品
     """
     
     # 根据类型定义字段模板
@@ -139,7 +141,62 @@ def parse_with_llm(text, category_type):
     
     fields = field_templates.get(category_type, field_templates['dynamic'])
     
-    prompt = f"""请解析以下文本，提取结构化数据。
+    # 构建消息内容
+    content_parts = []
+    
+    # 如果有图片，添加图片内容
+    if images and len(images) > 0:
+        content_parts.append({
+            "type": "text",
+            "text": f"""请分析图片中的产品参数信息，提取结构化数据。
+
+需要提取的字段：
+{json.dumps(fields, ensure_ascii=False, indent=2)}
+
+重要要求：
+1. 图片中可能包含1个或多个产品，请识别所有产品
+2. 如果是多张图片，请综合分析所有图片内容
+3. 数字字段只返回数字，不带单位
+4. 如果某字段没有提及，返回null
+5. 返回格式：如果识别到多个产品，返回数组 [{"name": ...}, {"name": ...}]; 如果只有一个产品，返回单个对象 {"name": ...}
+6. 只返回JSON数据，不要其他内容"""
+        })
+        
+        # 添加每张图片（支持URL或base64）
+        for img in images:
+            if isinstance(img, str):
+                if img.startswith('http'):
+                    # URL图片
+                    content_parts.append({
+                        "type": "image_url",
+                        "image_url": {"url": img}
+                    })
+                elif img.startswith('data:'):
+                    # base64图片
+                    content_parts.append({
+                        "type": "image_url",
+                        "image_url": {"url": img}
+                    })
+                else:
+                    # 本地路径，读取并转为base64
+                    try:
+                        img_path = IMAGES_DIR / img.replace('/static/uploads/', '')
+                        if img_path.exists():
+                            with open(img_path, 'rb') as f:
+                                img_data = base64.b64encode(f.read()).decode()
+                            ext = img_path.suffix.lower()
+                            mime_type = f'image/{ext if ext != "jpg" else "jpeg"}'
+                            content_parts.append({
+                                "type": "image_url",
+                                "image_url": {"url": f"data:{mime_type};base64,{img_data}"}
+                            })
+                    except Exception as e:
+                        print(f"读取图片失败: {e}")
+    else:
+        # 纯文本解析
+        content_parts.append({
+            "type": "text",
+            "text": f"""请解析以下文本，提取结构化数据。
 
 文本内容：
 {text}
@@ -154,8 +211,12 @@ def parse_with_llm(text, category_type):
 4. 返回JSON格式，不要包含任何其他内容
 
 请直接返回JSON数据："""
-
+        })
+    
     try:
+        # 使用视觉模型解析
+        model = LLM_CONFIG.get('vision_model', 'gpt-4-vision-preview') if images else LLM_CONFIG['model']
+        
         response = requests.post(
             f"{LLM_CONFIG['base_url']}/chat/completions",
             headers={
@@ -163,15 +224,15 @@ def parse_with_llm(text, category_type):
                 "Authorization": f"Bearer {LLM_CONFIG['api_key']}"
             },
             json={
-                "model": LLM_CONFIG['model'],
+                "model": model,
                 "messages": [
-                    {"role": "system", "content": "你是一个数据提取助手，负责从文本中提取结构化数据。只返回JSON，不要其他内容。"},
-                    {"role": "user", "content": prompt}
+                    {"role": "system", "content": "你是一个产品参数提取助手，负责从文本和图片中提取结构化的产品参数数据。只返回JSON，不要其他内容。如果图片中包含多个产品，返回数组。"},
+                    {"role": "user", "content": content_parts}
                 ],
-                "max_tokens": 1000,
+                "max_tokens": 2000,
                 "temperature": 0.1
             },
-            timeout=30
+            timeout=60
         )
         
         if response.status_code == 200:
@@ -186,28 +247,38 @@ def parse_with_llm(text, category_type):
             # 解析JSON
             parsed = json.loads(content)
             
-            # 清理null值
-            cleaned = {}
-            for k, v in parsed.items():
-                if v is not None and v != '' and v != 'null':
-                    # 尝试转换数字
-                    if isinstance(v, str):
-                        try:
-                            if '.' in v:
-                                cleaned[k] = float(v)
-                            else:
-                                cleaned[k] = int(v)
-                        except:
-                            cleaned[k] = v
-                    else:
-                        cleaned[k] = v
+            # 处理结果（可能是数组或单个对象）
+            results = []
+            if isinstance(parsed, list):
+                results = parsed
+            else:
+                results = [parsed]
             
-            return cleaned
+            # 清理每个结果的null值
+            cleaned_results = []
+            for item in results:
+                cleaned = {}
+                for k, v in item.items():
+                    if v is not None and v != '' and v != 'null':
+                        # 尝试转换数字
+                        if isinstance(v, str):
+                            try:
+                                if '.' in v:
+                                    cleaned[k] = float(v)
+                                else:
+                                    cleaned[k] = int(v)
+                            except:
+                                cleaned[k] = v
+                        else:
+                            cleaned[k] = v
+                cleaned_results.append(cleaned)
+            
+            return cleaned_results
     except Exception as e:
         print(f"LLM解析失败: {e}")
     
     # 降级处理：返回基本结构
-    return {'name': text[:50], 'description': text}
+    return [{'name': text[:50] if text else '未命名产品', 'description': text}]
 
 # ============ 页面路由 ============
 
@@ -393,109 +464,171 @@ def api_toggle_model_visible(model_id):
     
     return jsonify({'success': True, 'visible': model['visible']})
 
+# ============ 图片解析API（预览） ============
+
+@app.route('/api/parse-images', methods=['POST'])
+def api_parse_images():
+    """
+    解析图片中的产品参数（预览模式，不保存）
+    支持多张图片，可能返回多个产品
+    """
+    data = request.get_json()
+    text = data.get('text', '')
+    images = data.get('images', [])
+    category_type = data.get('category_type', 'dynamic')
+    
+    if not text and not images:
+        return jsonify({'error': '文本或图片不能都为空'}), 400
+    
+    if not images:
+        return jsonify({'error': '请上传至少一张图片'}), 400
+    
+    # 调用大模型解析
+    parsed_list = parse_with_llm(text, category_type, images)
+    
+    return jsonify({
+        'success': True,
+        'count': len(parsed_list),
+        'products': parsed_list,
+        'raw_text': text,
+        'images': images
+    })
+
 # ============ 智能添加API ============
 
 @app.route('/api/models/smart-add', methods=['POST'])
 def api_smart_add_model():
-    """智能添加模型（粘贴文本解析）"""
+    """智能添加模型（支持文本和多图解析，可能添加多个产品）"""
     data = request.get_json()
     text = data.get('text', '')
+    images = data.get('images', [])
     
-    if not text:
-        return jsonify({'error': '文本不能为空'}), 400
+    if not text and not images:
+        return jsonify({'error': '文本或图片不能都为空'}), 400
     
-    # 大模型解析
-    parsed = parse_with_llm(text, 'model')
+    # 大模型解析（支持多图）
+    parsed_list = parse_with_llm(text, 'model', images)
     
-    # 补充必要字段
-    parsed['id'] = uuid.uuid4().hex[:12]
-    parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    parsed['visible'] = True
-    parsed['raw_text'] = text  # 保存原始文本
-    parsed['publish_date'] = parsed.get('publish_date', '')  # 发布日期
-    parsed['views'] = 0  # 热度初始化为0
-    parsed['is_pinned'] = False  # 置顶初始化为False
-    
-    # 保存
+    # 处理多个产品
+    results = []
     models = load_data(MODELS_FILE)
-    models.append(parsed)
+    
+    for parsed in parsed_list:
+        # 补充必要字段
+        parsed['id'] = uuid.uuid4().hex[:12]
+        parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+        parsed['visible'] = True
+        parsed['raw_text'] = text  # 保存原始文本
+        parsed['images'] = images  # 保存图片
+        parsed['publish_date'] = parsed.get('publish_date', '')
+        parsed['views'] = 0
+        parsed['is_pinned'] = False
+        
+        models.append(parsed)
+        results.append(parsed)
+    
     save_data(MODELS_FILE, models)
     
-    return jsonify(parsed)
+    # 返回添加的产品列表
+    return jsonify({'success': True, 'count': len(results), 'products': results})
 
 @app.route('/api/gpus/smart-add', methods=['POST'])
 def api_smart_add_gpu():
-    """智能添加GPU"""
+    """智能添加GPU（支持文本和多图解析）"""
     data = request.get_json()
     text = data.get('text', '')
+    images = data.get('images', [])
     
-    if not text:
-        return jsonify({'error': '文本不能为空'}), 400
+    if not text and not images:
+        return jsonify({'error': '文本或图片不能都为空'}), 400
     
-    parsed = parse_with_llm(text, 'gpu')
-    parsed['id'] = uuid.uuid4().hex[:12]
-    parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    parsed['visible'] = True
-    parsed['raw_text'] = text
-    parsed['publish_date'] = parsed.get('publish_date', '')
-    parsed['views'] = 0
-    parsed['is_pinned'] = False
+    parsed_list = parse_with_llm(text, 'gpu', images)
     
+    results = []
     gpus = load_data(GPUS_FILE)
-    gpus.append(parsed)
+    
+    for parsed in parsed_list:
+        parsed['id'] = uuid.uuid4().hex[:12]
+        parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+        parsed['visible'] = True
+        parsed['raw_text'] = text
+        parsed['images'] = images
+        parsed['publish_date'] = parsed.get('publish_date', '')
+        parsed['views'] = 0
+        parsed['is_pinned'] = False
+        
+        gpus.append(parsed)
+        results.append(parsed)
+    
     save_data(GPUS_FILE, gpus)
     
-    return jsonify(parsed)
+    return jsonify({'success': True, 'count': len(results), 'products': results})
 
 @app.route('/api/cpus/smart-add', methods=['POST'])
 def api_smart_add_cpu():
-    """智能添加CPU"""
+    """智能添加CPU（支持文本和多图解析）"""
     data = request.get_json()
     text = data.get('text', '')
+    images = data.get('images', [])
     
-    if not text:
-        return jsonify({'error': '文本不能为空'}), 400
+    if not text and not images:
+        return jsonify({'error': '文本或图片不能都为空'}), 400
     
-    parsed = parse_with_llm(text, 'cpu')
-    parsed['id'] = uuid.uuid4().hex[:12]
-    parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    parsed['visible'] = True
-    parsed['raw_text'] = text
-    parsed['publish_date'] = parsed.get('publish_date', '')
-    parsed['views'] = 0
-    parsed['is_pinned'] = False
+    parsed_list = parse_with_llm(text, 'cpu', images)
     
+    results = []
     cpus = load_data(CPUS_FILE)
-    cpus.append(parsed)
+    
+    for parsed in parsed_list:
+        parsed['id'] = uuid.uuid4().hex[:12]
+        parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+        parsed['visible'] = True
+        parsed['raw_text'] = text
+        parsed['images'] = images
+        parsed['publish_date'] = parsed.get('publish_date', '')
+        parsed['views'] = 0
+        parsed['is_pinned'] = False
+        
+        cpus.append(parsed)
+        results.append(parsed)
+    
     save_data(CPUS_FILE, cpus)
     
-    return jsonify(parsed)
+    return jsonify({'success': True, 'count': len(results), 'products': results})
 
 @app.route('/api/items/<category_id>/smart-add', methods=['POST'])
 def api_smart_add_item(category_id):
-    """智能添加动态分类数据"""
+    """智能添加动态分类数据（支持文本和多图解析）"""
     data = request.get_json()
     text = data.get('text', '')
+    images = data.get('images', [])
     
-    if not text:
-        return jsonify({'error': '文本不能为空'}), 400
+    if not text and not images:
+        return jsonify({'error': '文本或图片不能都为空'}), 400
     
-    parsed = parse_with_llm(text, 'dynamic')
-    parsed['id'] = uuid.uuid4().hex[:12]
-    parsed['category_id'] = category_id
-    parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    parsed['visible'] = True
-    parsed['raw_text'] = text
-    parsed['publish_date'] = parsed.get('publish_date', '')
-    parsed['views'] = 0
-    parsed['is_pinned'] = False
+    parsed_list = parse_with_llm(text, 'dynamic', images)
     
+    results = []
     items_file = DATA_DIR / f'items_{category_id}.json'
     items = load_data(items_file)
-    items.append(parsed)
+    
+    for parsed in parsed_list:
+        parsed['id'] = uuid.uuid4().hex[:12]
+        parsed['category_id'] = category_id
+        parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+        parsed['visible'] = True
+        parsed['raw_text'] = text
+        parsed['images'] = images
+        parsed['publish_date'] = parsed.get('publish_date', '')
+        parsed['views'] = 0
+        parsed['is_pinned'] = False
+        
+        items.append(parsed)
+        results.append(parsed)
+    
     save_data(items_file, items)
     
-    return jsonify(parsed)
+    return jsonify({'success': True, 'count': len(results), 'products': results})
 
 # ============ GPU API ============
 

templates/admin.html

@@ -277,25 +277,52 @@
 
     <!-- 智能添加弹窗 -->
     <div id="smartAddModal" class="fixed inset-0 bg-black/50 z-50 hidden flex items-center justify-center">
-        <div class="bg-white rounded-xl max-w-3xl w-full mx-4 max-h-[90vh] overflow-auto">
+        <div class="bg-white rounded-xl max-w-4xl w-full mx-4 max-h-[90vh] overflow-auto">
             <div class="p-6 border-b flex justify-between items-center sticky top-0 bg-white z-10">
-                <h2 class="text-xl font-bold text-gray-800"><i class="ri-magic-line mr-2 text-orange-600"></i>智能添加</h2>
+                <h2 class="text-xl font-bold text-gray-800"><i class="ri-magic-line mr-2 text-orange-600"></i>智能添加（支持多图解析）</h2>
                 <button onclick="closeSmartAddModal()" class="text-gray-400 hover:text-gray-600"><i class="ri-close-line text-2xl"></i></button>
             </div>
             <div class="p-6">
-                <p class="text-sm text-gray-500 mb-4">粘贴产品信息文本，AI将自动解析并提取结构化数据。支持各种格式的产品介绍、规格参数、价格信息等。</p>
-                <textarea id="smartAddText" rows="8" class="w-full p-4 border border-gray-200 rounded-lg focus:outline-none focus:border-orange-400 text-gray-700" placeholder="粘贴产品信息文本...
-
-示例：
-GPT-4是OpenAI发布的大语言模型，参数量约1.8万亿，支持128K上下文，MMLU分数86.4，输入价格$0.03/1K tokens，输出价格$0.06/1K tokens，商业许可。"></textarea>
+                <div class="mb-6">
+                    <p class="text-sm text-gray-500 mb-3">上传产品图片，AI将自动识别并解析参数。支持一次上传多张图片，可识别多个产品。</p>
+                    <div class="flex flex-wrap gap-3 mb-3" id="smartImagePreviewArea">
+                        <!-- 图片预览区 -->
+                    </div>
+                    <div class="flex gap-3">
+                        <input type="file" id="smartImageInput" accept="image/*" multiple class="hidden" onchange="handleSmartImageUpload(event)">
+                        <button onclick="document.getElementById('smartImageInput').click()" class="px-4 py-2 bg-orange-100 text-orange-600 rounded-lg hover:bg-orange-200 text-sm">
+                            <i class="ri-image-add-line mr-1"></i>选择图片（支持多选）
+                        </button>
+                        <button onclick="pasteSmartImageFromClipboard()" class="px-4 py-2 bg-gray-100 text-gray-600 rounded-lg hover:bg-gray-200 text-sm">
+                            <i class="ri-clipboard-line mr-1"></i>粘贴图片
+                        </button>
+                        <button onclick="clearSmartImages()" class="px-4 py-2 bg-gray-100 text-gray-600 rounded-lg hover:bg-gray-200 text-sm">
+                            <i class="ri-delete-bin-line mr-1"></i>清空图片
+                        </button>
+                    </div>
+                    <div class="mt-3 text-xs text-gray-400">
+                        <i class="ri-information-line mr-1"></i>
+                        已选择 <span id="smartImageCount">0</span> 张图片
+                    </div>
+                </div>
+                <div class="border-t pt-4">
+                    <label class="text-sm text-gray-600 mb-2 block">补充文本（可选）</label>
+                    <textarea id="smartAddText" rows="4" class="w-full p-4 border border-gray-200 rounded-lg focus:outline-none focus:border-orange-400 text-gray-700" placeholder="可粘贴补充信息文本，与图片一起解析..."></textarea>
+                </div>
                 <div id="smartAddPreview" class="mt-4 hidden">
-                    <h3 class="text-sm font-semibold text-gray-700 mb-2">解析结果预览：</h3>
-                    <div class="bg-gray-50 rounded-lg p-4 text-sm text-gray-600" id="smartAddResult"></div>
+                    <h3 class="text-sm font-semibold text-gray-700 mb-2"><i class="ri-checkbox-circle-line text-green-600 mr-1"></i>解析结果预览：</h3>
+                    <div class="bg-gray-50 rounded-lg p-4 text-sm text-gray-600" id="smartAddResult">
+                        <!-- 解析结果显示 -->
+                    </div>
+                    <div class="mt-3 flex gap-2" id="smartAddActions">
+                        <!-- 操作按钮 -->
+                    </div>
                 </div>
             </div>
             <div class="p-6 border-t flex justify-end gap-4 sticky bottom-0 bg-white">
                 <button onclick="closeSmartAddModal()" class="px-4 py-2 bg-gray-200 text-gray-600 rounded-lg hover:bg-gray-300">取消</button>
-                <button onclick="smartAddSubmit()" id="smartAddBtn" class="px-4 py-2 bg-orange-600 text-white rounded-lg hover:bg-orange-700"><i class="ri-magic-line mr-1"></i>智能解析并添加</button>
+                <button onclick="previewSmartParse()" id="previewBtn" class="px-4 py-2 bg-blue-600 text-white rounded-lg hover:bg-blue-700"><i class="ri-eye-line mr-1"></i>预览解析结果</button>
+                <button onclick="smartAddSubmit()" id="smartAddBtn" class="px-4 py-2 bg-orange-600 text-white rounded-lg hover:bg-orange-700"><i class="ri-magic-line mr-1"></i>解析并添加</button>
             </div>
         </div>
     </div>
@@ -1151,11 +1178,15 @@ GPT-4是OpenAI发布的大语言模型，参数量约1.8万亿，支持128K上
         // ============ 智能添加功能 ============
         
         let smartAddType = '';
+        let smartAddImages = []; // 智能添加的图片列表
         
         function openSmartAddModal(type) {
             smartAddType = type;
+            smartAddImages = [];
             document.getElementById('smartAddText').value = '';
             document.getElementById('smartAddPreview').classList.add('hidden');
+            document.getElementById('smartImagePreviewArea').innerHTML = '';
+            document.getElementById('smartImageCount').textContent = '0';
             document.getElementById('smartAddModal').classList.remove('hidden');
         }
         
@@ -1163,16 +1194,158 @@ GPT-4是OpenAI发布的大语言模型，参数量约1.8万亿，支持128K上
             document.getElementById('smartAddModal').classList.add('hidden');
         }
         
+        // 处理智能添加图片上传
+        async function handleSmartImageUpload(event) {
+            const files = event.target.files;
+            for (let file of files) {
+                const formData = new FormData();
+                formData.append('file', file);
+                
+                try {
+                    const res = await fetch('/api/upload/image', {
+                        method: 'POST',
+                        body: formData
+                    });
+                    const data = await res.json();
+                    if (data.success) {
+                        smartAddImages.push(data.url);
+                        updateSmartImagePreview();
+                    }
+                } catch (e) {
+                    alert('上传失败: ' + e.message);
+                }
+            }
+            event.target.value = '';
+        }
+        
+        // 从剪贴板粘贴图片
+        async function pasteSmartImageFromClipboard() {
+            try {
+                const clipboardItems = await navigator.clipboard.read();
+                for (const item of clipboardItems) {
+                    for (const type of item.types) {
+                        if (type.startsWith('image/')) {
+                            const blob = await item.getType(type);
+                            const reader = new FileReader();
+                            reader.onload = async (e) => {
+                                const base64 = e.target.result;
+                                const res = await fetch('/api/upload/image/base64', {
+                                    method: 'POST',
+                                    headers: { 'Content-Type': 'application/json' },
+                                    body: JSON.stringify({ image: base64 })
+                                });
+                                const data = await res.json();
+                                if (data.success) {
+                                    smartAddImages.push(data.url);
+                                    updateSmartImagePreview();
+                                }
+                            };
+                            reader.readAsDataURL(blob);
+                        }
+                    }
+                }
+            } catch (e) {
+                alert('无法从剪贴板获取图片，请使用文件选择');
+            }
+        }
+        
+        // 清空智能添加图片
+        function clearSmartImages() {
+            smartAddImages = [];
+            updateSmartImagePreview();
+        }
+        
+        // 移除单张图片
+        function removeSmartImage(index) {
+            smartAddImages.splice(index, 1);
+            updateSmartImagePreview();
+        }
+        
+        // 更新智能添加图片预览
+        function updateSmartImagePreview() {
+            const area = document.getElementById('smartImagePreviewArea');
+            const count = document.getElementById('smartImageCount');
+            
+            area.innerHTML = smartAddImages.map((url, idx) => `
+                <div class="relative w-24 h-24 border rounded-lg overflow-hidden group">
+                    <img src="${url}" class="w-full h-full object-cover">
+                    <button onclick="removeSmartImage(${idx})" class="absolute top-1 right-1 w-6 h-6 bg-red-500 text-white rounded-full opacity-0 group-hover:opacity-100 transition flex items-center justify-center">
+                        <i class="ri-close-line"></i>
+                    </button>
+                </div>
+            `).join('');
+            
+            count.textContent = smartAddImages.length;
+        }
+        
+        // 预览解析结果
+        async function previewSmartParse() {
+            const text = document.getElementById('smartAddText').value.trim();
+            
+            if (!text && smartAddImages.length === 0) {
+                alert('请上传图片或输入文本');
+                return;
+            }
+            
+            const btn = document.getElementById('previewBtn');
+            btn.disabled = true;
+            btn.innerHTML = '<i class="ri-loader-4-line animate-spin mr-1"></i>解析中...';
+            
+            try {
+                const res = await fetch('/api/parse-images', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({
+                        text: text,
+                        images: smartAddImages,
+                        category_type: smartAddType
+                    })
+                });
+                
+                const data = await res.json();
+                
+                if (data.error) {
+                    alert('解析失败: ' + data.error);
+                } else {
+                    // 显示解析结果
+                    document.getElementById('smartAddPreview').classList.remove('hidden');
+                    
+                    let html = `<div class="mb-2 text-green-600"><i class="ri-checkbox-circle-line mr-1"></i>识别到 ${data.count} 个产品</div>`;
+                    
+                    data.products.forEach((product, idx) => {
+                        html += `
+                            <div class="bg-white rounded-lg p-3 mb-2 border">
+                                <div class="font-medium text-gray-800 mb-2">产品 ${idx + 1}: ${product.name || '未命名'}</div>
+                                <div class="text-xs text-gray-600 grid grid-cols-2 gap-2">
+                                    ${Object.entries(product).map(([k, v]) => `
+                                        <div><span class="text-gray-400">${k}:</span> ${v || '-'}</div>
+                                    `).join('')}
+                                </div>
+                            </div>
+                        `;
+                    });
+                    
+                    document.getElementById('smartAddResult').innerHTML = html;
+                }
+            } catch (e) {
+                alert('请求失败: ' + e.message);
+            }
+            
+            btn.disabled = false;
+            btn.innerHTML = '<i class="ri-eye-line mr-1"></i>预览解析结果';
+        }
+        
         async function smartAddSubmit() {
             const text = document.getElementById('smartAddText').value.trim();
-            if (!text) {
-                alert('请粘贴产品信息文本');
+            
+            if (!text && smartAddImages.length === 0) {
+                alert('请上传图片或输入文本');
                 return;
             }
             
             const btn = document.getElementById('smartAddBtn');
             btn.disabled = true;
-            btn.innerHTML = '<i class="ri-loader-4-line animate-spin mr-1"></i>解析中...';
+            btn.innerHTML = '<i class="ri-loader-4-line animate-spin mr-1"></i>解析并保存中...';
             
             try {
                 let endpoint;
@@ -1184,7 +1357,10 @@ GPT-4是OpenAI发布的大语言模型，参数量约1.8万亿，支持128K上
                 const res = await fetch(endpoint, {
                     method: 'POST',
                     headers: { 'Content-Type': 'application/json' },
-                    body: JSON.stringify({ text })
+                    body: JSON.stringify({
+                        text: text,
+                        images: smartAddImages
+                    })
                 });
                 
                 const data = await res.json();
@@ -1194,26 +1370,38 @@ GPT-4是OpenAI发布的大语言模型，参数量约1.8万亿，支持128K上
                 } else {
                     // 显示解析结果
                     document.getElementById('smartAddPreview').classList.remove('hidden');
-                    document.getElementById('smartAddResult').innerHTML = `<pre>${JSON.stringify(data, null, 2)}</pre>`;
+                    
+                    let html = `<div class="mb-2 text-green-600"><i class="ri-checkbox-circle-fill mr-1"></i>成功添加 ${data.count} 个产品</div>`;
+                    
+                    data.products.forEach((product, idx) => {
+                        html += `
+                            <div class="bg-white rounded-lg p-3 mb-2 border border-green-200">
+                                <div class="font-medium text-gray-800 mb-2">产品 ${idx + 1}: ${product.name || '未命名'}</div>
+                                <div class="text-xs text-gray-500">ID: ${product.id}</div>
+                            </div>
+                        `;
+                    });
+                    
+                    document.getElementById('smartAddResult').innerHTML = html;
                     
                     // 关闭弹窗并刷新列表
-                    closeSmartAddModal();
-                    
-                    if (smartAddType === 'dynamic') showDynamicCategory(dynamicCategoryId);
-                    else {
-                        const loaders = {model: loadAdminModels, gpu: loadAdminGpus, cpu: loadAdminCpus};
-                        loaders[smartAddType]();
-                    }
-                    loadOverview();
-                    
-                    alert('智能添加成功！数据已自动解析并保存。');
+                    setTimeout(() => {
+                        closeSmartAddModal();
+                        
+                        if (smartAddType === 'dynamic') showDynamicCategory(dynamicCategoryId);
+                        else {
+                            const loaders = {model: loadAdminModels, gpu: loadAdminGpus, cpu: loadAdminCpus};
+                            loaders[smartAddType]();
+                        }
+                        loadOverview();
+                    }, 1500);
                 }
             } catch (e) {
                 alert('请求失败: ' + e.message);
             }
             
             btn.disabled = false;
-            btn.innerHTML = '<i class="ri-magic-line mr-1"></i>智能解析并添加';
+            btn.innerHTML = '<i class="ri-magic-line mr-1"></i>解析并添加';
         }
         
         // ============ 显示切换功能 ============