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
This commit is contained in:
301
app.py
301
app.py
@@ -1,7 +1,7 @@
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"""
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ParamHub - 参数百科
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AI大模型与硬件参数速查平台
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v1.4.0 - 新增图片上传功能
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v1.5.0 - 支持多图上传和智能解析产品参数
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"""
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from flask import Flask, render_template, jsonify, request
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@@ -46,6 +46,7 @@ LLM_CONFIG = {
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'base_url': 'http://192.168.2.17:19007/v1',
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'api_key': 'xxxx',
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'model': 'auto',
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'vision_model': 'gpt-4-vision-preview', # 视觉模型（解析图片）
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}
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# 默认网站配置
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@@ -81,9 +82,10 @@ def save_data(file_path, data):
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# ============ 大模型智能解析 ============
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def parse_with_llm(text, category_type):
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def parse_with_llm(text, category_type, images=None):
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"""
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使用大模型解析文本，提取结构化数据
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使用大模型解析文本/图片，提取结构化数据
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支持多张图片输入，可能解析出多个产品
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"""
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# 根据类型定义字段模板
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@@ -139,7 +141,62 @@ def parse_with_llm(text, category_type):
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fields = field_templates.get(category_type, field_templates['dynamic'])
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prompt = f"""请解析以下文本，提取结构化数据。
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# 构建消息内容
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content_parts = []
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# 如果有图片，添加图片内容
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if images and len(images) > 0:
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content_parts.append({
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"type": "text",
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"text": f"""请分析图片中的产品参数信息，提取结构化数据。
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需要提取的字段：
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{json.dumps(fields, ensure_ascii=False, indent=2)}
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重要要求：
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1. 图片中可能包含1个或多个产品，请识别所有产品
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2. 如果是多张图片，请综合分析所有图片内容
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3. 数字字段只返回数字，不带单位
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4. 如果某字段没有提及，返回null
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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": ...}
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6. 只返回JSON数据，不要其他内容"""
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})
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# 添加每张图片（支持URL或base64）
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for img in images:
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if isinstance(img, str):
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if img.startswith('http'):
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# URL图片
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content_parts.append({
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"type": "image_url",
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"image_url": {"url": img}
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})
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elif img.startswith('data:'):
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# base64图片
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content_parts.append({
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"type": "image_url",
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"image_url": {"url": img}
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})
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else:
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# 本地路径，读取并转为base64
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try:
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img_path = IMAGES_DIR / img.replace('/static/uploads/', '')
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if img_path.exists():
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with open(img_path, 'rb') as f:
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img_data = base64.b64encode(f.read()).decode()
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ext = img_path.suffix.lower()
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mime_type = f'image/{ext if ext != "jpg" else "jpeg"}'
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content_parts.append({
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"type": "image_url",
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"image_url": {"url": f"data:{mime_type};base64,{img_data}"}
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})
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except Exception as e:
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print(f"读取图片失败: {e}")
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else:
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# 纯文本解析
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content_parts.append({
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"type": "text",
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"text": f"""请解析以下文本，提取结构化数据。
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文本内容：
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{text}
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@@ -154,8 +211,12 @@ def parse_with_llm(text, category_type):
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4. 返回JSON格式，不要包含任何其他内容
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请直接返回JSON数据："""
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})
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try:
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# 使用视觉模型解析
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model = LLM_CONFIG.get('vision_model', 'gpt-4-vision-preview') if images else LLM_CONFIG['model']
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response = requests.post(
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f"{LLM_CONFIG['base_url']}/chat/completions",
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headers={
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@@ -163,15 +224,15 @@ def parse_with_llm(text, category_type):
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"Authorization": f"Bearer {LLM_CONFIG['api_key']}"
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},
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json={
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"model": LLM_CONFIG['model'],
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"model": model,
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"messages": [
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{"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。"},
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{"role": "user", "content": prompt}
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{"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。"},
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{"role": "user", "content": content_parts}
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],
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"max_tokens": 1000,
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"max_tokens": 2000,
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"temperature": 0.1
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},
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timeout=30
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timeout=60
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)
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if response.status_code == 200:
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@@ -186,28 +247,38 @@ def parse_with_llm(text, category_type):
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# 解析JSON
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parsed = json.loads(content)
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# 清理null值
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cleaned = {}
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for k, v in parsed.items():
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if v is not None and v != '' and v != 'null':
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# 尝试转换数字
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if isinstance(v, str):
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try:
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if '.' in v:
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cleaned[k] = float(v)
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else:
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cleaned[k] = int(v)
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except:
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cleaned[k] = v
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else:
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cleaned[k] = v
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# 处理结果（可能是数组或单个对象）
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results = []
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if isinstance(parsed, list):
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results = parsed
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else:
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results = [parsed]
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return cleaned
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# 清理每个结果的null值
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cleaned_results = []
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for item in results:
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cleaned = {}
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for k, v in item.items():
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if v is not None and v != '' and v != 'null':
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# 尝试转换数字
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if isinstance(v, str):
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try:
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if '.' in v:
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cleaned[k] = float(v)
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else:
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cleaned[k] = int(v)
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except:
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cleaned[k] = v
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else:
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cleaned[k] = v
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cleaned_results.append(cleaned)
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return cleaned_results
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except Exception as e:
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print(f"LLM解析失败: {e}")
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# 降级处理：返回基本结构
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return {'name': text[:50], 'description': text}
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return [{'name': text[:50] if text else '未命名产品', 'description': text}]
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# ============ 页面路由 ============
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@@ -393,109 +464,171 @@ def api_toggle_model_visible(model_id):
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return jsonify({'success': True, 'visible': model['visible']})
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# ============ 图片解析API（预览） ============
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@app.route('/api/parse-images', methods=['POST'])
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def api_parse_images():
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"""
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解析图片中的产品参数（预览模式，不保存）
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支持多张图片，可能返回多个产品
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"""
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data = request.get_json()
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text = data.get('text', '')
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images = data.get('images', [])
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category_type = data.get('category_type', 'dynamic')
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if not text and not images:
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return jsonify({'error': '文本或图片不能都为空'}), 400
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if not images:
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return jsonify({'error': '请上传至少一张图片'}), 400
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# 调用大模型解析
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parsed_list = parse_with_llm(text, category_type, images)
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return jsonify({
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'success': True,
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'count': len(parsed_list),
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'products': parsed_list,
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'raw_text': text,
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'images': images
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})
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# ============ 智能添加API ============
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@app.route('/api/models/smart-add', methods=['POST'])
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def api_smart_add_model():
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"""智能添加模型（粘贴文本解析）"""
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"""智能添加模型（支持文本和多图解析，可能添加多个产品）"""
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data = request.get_json()
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text = data.get('text', '')
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images = data.get('images', [])
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if not text:
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return jsonify({'error': '文本不能为空'}), 400
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if not text and not images:
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return jsonify({'error': '文本或图片不能都为空'}), 400
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# 大模型解析
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parsed = parse_with_llm(text, 'model')
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# 大模型解析（支持多图）
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parsed_list = parse_with_llm(text, 'model', images)
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# 补充必要字段
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parsed['id'] = uuid.uuid4().hex[:12]
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parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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parsed['visible'] = True
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parsed['raw_text'] = text # 保存原始文本
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parsed['publish_date'] = parsed.get('publish_date', '') # 发布日期
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parsed['views'] = 0 # 热度初始化为0
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parsed['is_pinned'] = False # 置顶初始化为False
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# 保存
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# 处理多个产品
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results = []
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models = load_data(MODELS_FILE)
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models.append(parsed)
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for parsed in parsed_list:
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# 补充必要字段
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parsed['id'] = uuid.uuid4().hex[:12]
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parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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parsed['visible'] = True
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parsed['raw_text'] = text # 保存原始文本
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parsed['images'] = images # 保存图片
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parsed['publish_date'] = parsed.get('publish_date', '')
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parsed['views'] = 0
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parsed['is_pinned'] = False
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models.append(parsed)
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results.append(parsed)
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save_data(MODELS_FILE, models)
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return jsonify(parsed)
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# 返回添加的产品列表
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return jsonify({'success': True, 'count': len(results), 'products': results})
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@app.route('/api/gpus/smart-add', methods=['POST'])
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def api_smart_add_gpu():
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"""智能添加GPU"""
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"""智能添加GPU（支持文本和多图解析）"""
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data = request.get_json()
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text = data.get('text', '')
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images = data.get('images', [])
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if not text:
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return jsonify({'error': '文本不能为空'}), 400
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if not text and not images:
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return jsonify({'error': '文本或图片不能都为空'}), 400
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parsed = parse_with_llm(text, 'gpu')
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parsed['id'] = uuid.uuid4().hex[:12]
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parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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parsed['visible'] = True
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parsed['raw_text'] = text
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parsed['publish_date'] = parsed.get('publish_date', '')
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parsed['views'] = 0
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parsed['is_pinned'] = False
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parsed_list = parse_with_llm(text, 'gpu', images)
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results = []
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gpus = load_data(GPUS_FILE)
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gpus.append(parsed)
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for parsed in parsed_list:
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parsed['id'] = uuid.uuid4().hex[:12]
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parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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parsed['visible'] = True
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parsed['raw_text'] = text
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parsed['images'] = images
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parsed['publish_date'] = parsed.get('publish_date', '')
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parsed['views'] = 0
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parsed['is_pinned'] = False
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gpus.append(parsed)
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results.append(parsed)
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save_data(GPUS_FILE, gpus)
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return jsonify(parsed)
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return jsonify({'success': True, 'count': len(results), 'products': results})
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@app.route('/api/cpus/smart-add', methods=['POST'])
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def api_smart_add_cpu():
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"""智能添加CPU"""
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"""智能添加CPU（支持文本和多图解析）"""
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data = request.get_json()
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text = data.get('text', '')
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images = data.get('images', [])
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if not text:
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return jsonify({'error': '文本不能为空'}), 400
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if not text and not images:
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return jsonify({'error': '文本或图片不能都为空'}), 400
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parsed = parse_with_llm(text, 'cpu')
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parsed['id'] = uuid.uuid4().hex[:12]
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parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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parsed['visible'] = True
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parsed['raw_text'] = text
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parsed['publish_date'] = parsed.get('publish_date', '')
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parsed['views'] = 0
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parsed['is_pinned'] = False
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parsed_list = parse_with_llm(text, 'cpu', images)
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results = []
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cpus = load_data(CPUS_FILE)
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cpus.append(parsed)
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for parsed in parsed_list:
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parsed['id'] = uuid.uuid4().hex[:12]
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parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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parsed['visible'] = True
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parsed['raw_text'] = text
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parsed['images'] = images
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parsed['publish_date'] = parsed.get('publish_date', '')
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parsed['views'] = 0
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parsed['is_pinned'] = False
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cpus.append(parsed)
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results.append(parsed)
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save_data(CPUS_FILE, cpus)
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return jsonify(parsed)
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return jsonify({'success': True, 'count': len(results), 'products': results})
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@app.route('/api/items/<category_id>/smart-add', methods=['POST'])
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def api_smart_add_item(category_id):
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"""智能添加动态分类数据"""
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"""智能添加动态分类数据（支持文本和多图解析）"""
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data = request.get_json()
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text = data.get('text', '')
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images = data.get('images', [])
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if not text:
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return jsonify({'error': '文本不能为空'}), 400
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if not text and not images:
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return jsonify({'error': '文本或图片不能都为空'}), 400
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parsed = parse_with_llm(text, 'dynamic')
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parsed['id'] = uuid.uuid4().hex[:12]
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parsed['category_id'] = category_id
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parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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parsed['visible'] = True
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parsed['raw_text'] = text
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parsed['publish_date'] = parsed.get('publish_date', '')
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parsed['views'] = 0
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parsed['is_pinned'] = False
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parsed_list = parse_with_llm(text, 'dynamic', images)
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results = []
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items_file = DATA_DIR / f'items_{category_id}.json'
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items = load_data(items_file)
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items.append(parsed)
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for parsed in parsed_list:
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parsed['id'] = uuid.uuid4().hex[:12]
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parsed['category_id'] = category_id
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parsed['created_at'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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parsed['visible'] = True
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parsed['raw_text'] = text
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parsed['images'] = images
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parsed['publish_date'] = parsed.get('publish_date', '')
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parsed['views'] = 0
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parsed['is_pinned'] = False
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items.append(parsed)
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results.append(parsed)
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save_data(items_file, items)
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return jsonify(parsed)
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return jsonify({'success': True, 'count': len(results), 'products': results})
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# ============ GPU API ============
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