Add 3 major improvements:

1. Fix frontend freeze - ensure proper gr.Request handling
2. Add temp file cleanup documentation (Gradio auto-cleans, S3 uses memory)
3. Add history tab - users can view their past generations

Features:
- New history tab with HTML display of user's past evaluations
- get_user_history() method to fetch records from HF Dataset
- Refresh button to load history on demand
- Each history entry shows: timestamp, prompt, scores, video URLs
- Updated README with new features

Technical:
- Fixed UI tab structure and indentation
- Added get_history_html() function for rendering
- History data fetched from evaluations/*.json files in Dataset
- Limit to 10 most recent records

README.md

@@ -17,10 +17,12 @@ hf_oauth: true
 ## ✨ 功能
 
 - 🔐 强制登录（HF OAuth）
-- 📊 次数限制（每天 4 次）
+- 📊 次数限制（每天 4 次，持久化到 HF Private Dataset，完全免费）
 - 🚀 4 个模型同时生成（Sora 2 pro, Seedance Pro, Veo 3.1, Kling 2.6）
 - 💾 评分数据保存到 Private Dataset
 - ☁️ 图片和视频自动上传到 S3
+- 📜 历史记录查看（用户可查看自己之前的生成记录）
+- 🧹 自动清理（Gradio自动清理上传临时文件，S3上传使用内存操作无本地临时文件）
 
 ## 📋 环境变量配置
 

app.py

@@ -173,6 +173,72 @@ class DatasetManager:
             logger.error(f"更新用户调用次数失败: {e}")
             return False
     
+    def get_user_history(self, username: str, limit: int = 10) -> List[Dict]:
+        """
+        获取用户的历史评分记录
+        
+        Args:
+            username: Hugging Face 用户名
+            limit: 返回记录数量限制
+            
+        Returns:
+            历史记录列表
+        """
+        if not self.api or not self.repo_id:
+            logger.warning("Dataset API 未配置，无法获取历史记录")
+            return []
+            
+        try:
+            # 列出评分文件
+            files = self.api.list_repo_files(
+                repo_id=self.repo_id,
+                repo_type="dataset",
+                token=self.hf_token
+            )
+            
+            # 筛选该用户的评分文件
+            user_files = [f for f in files if f.startswith(f"evaluations/") and f.endswith('.json')]
+            
+            # 按时间倒序排序（文件名包含时间戳）
+            user_files.sort(reverse=True)
+            
+            history = []
+            for file_path in user_files[:limit * 2]:  # 多读一些，因为有些可能不是该用户的
+                try:
+                    # 下载文件
+                    local_path = self.api.hf_hub_download(
+                        repo_id=self.repo_id,
+                        filename=file_path,
+                        repo_type="dataset",
+                        token=self.hf_token
+                    )
+                    
+                    # 读取数据
+                    with open(local_path, 'r', encoding='utf-8') as f:
+                        data = json.load(f)
+                        
+                        # 只返回该用户的记录
+                        if data.get('user') == username:
+                            history.append({
+                                'timestamp': data.get('timestamp'),
+                                'prompt': data.get('prompt', ''),
+                                'scores': data.get('scores', {}),
+                                'video_urls': data.get('video_urls', {})
+                            })
+                            
+                            if len(history) >= limit:
+                                break
+                                
+                except Exception as e:
+                    logger.warning(f"读取历史记录失败 {file_path}: {e}")
+                    continue
+            
+            return history
+            
+        except Exception as e:
+            logger.error(f"获取用户历史记录失败: {e}")
+            return []
+    
     def save_evaluation(
         self,
         username: str,
@@ -532,6 +598,65 @@ def get_user_info(request: gr.Request = None) -> str:
     return f"{status_icon} 用户: {username}\n📊 今日已用: {calls_today}/{MAX_DAILY_CALLS}\n✨ 剩余次数: {remaining}"
 
 
+def get_history_html(request: gr.Request = None) -> str:
+    """获取用户历史记录的HTML"""
+    if not request:
+        return "<p>⏳ 正在加载...</p>"
+    
+    username, _ = check_user_access(request)
+    
+    if not username:
+        return "<p>❌ 请先登录 Hugging Face 账户</p>"
+    
+    if not dataset_manager:
+        return "<p>❌ Dataset 未配置</p>"
+    
+    try:
+        history = dataset_manager.get_user_history(username, limit=10)
+        
+        if not history:
+            return f"<p>📭 暂无历史记录（用户: {username}）</p>"
+        
+        html = f"<h3>用户: {username} 的历史记录</h3>"
+        html += f"<p>共 {len(history)} 条记录</p>"
+        html += "<div style='max-height: 600px; overflow-y: auto;'>"
+        
+        for i, record in enumerate(history, 1):
+            timestamp = record.get('timestamp', '未知时间')
+            prompt = record.get('prompt', '')
+            scores = record.get('scores', {})
+            video_urls = record.get('video_urls', {})
+            
+            html += f"""
+            <div style='border: 1px solid #ddd; padding: 15px; margin: 10px 0; border-radius: 8px; background: #f9f9f9;'>
+                <h4>📝 记录 #{i} - {timestamp}</h4>
+                <p><strong>提示词:</strong> {prompt[:100]}{'...' if len(prompt) > 100 else ''}</p>
+                <p><strong>评分:</strong></p>
+                <ul>
+            """
+            
+            for model, score in scores.items():
+                display_name = MODEL_DISPLAY_NAMES.get(model, model)
+                html += f"<li>{display_name}: {score} 分</li>"
+            
+            html += "</ul>"
+            
+            if video_urls:
+                html += "<p><strong>生成的视频:</strong></p>"
+                for model, url in video_urls.items():
+                    display_name = MODEL_DISPLAY_NAMES.get(model, model)
+                    html += f'<p>🎬 <a href="{url}" target="_blank">{display_name}</a></p>'
+            
+            html += "</div>"
+        
+        html += "</div>"
+        return html
+        
+    except Exception as e:
+        logger.error(f"获取历史记录失败: {e}")
+        return f"<p>❌ 获取历史记录失败: {str(e)}</p>"
+
+
 # 创建 Gradio 界面
 with gr.Blocks(title="Video Model Evaluator") as demo:
     gr.Markdown("""
@@ -569,60 +694,72 @@ with gr.Blocks(title="Video Model Evaluator") as demo:
         )
         refresh_user_btn = gr.Button("🔄 刷新", size="sm", scale=1)
     
-    with gr.Row():
-        with gr.Column(scale=1):
-            
-            prompt_input = gr.Textbox(
-                label="提示词 (Prompt)",
-                placeholder="输入视频生成的提示词...",
-                lines=3
-            )
-            
-            input_image = gr.Image(
-                label="输入图片 (可选，用于图生视频 i2v)",
-                type="filepath",
-                sources=["upload"]
-            )
-            
-            generate_btn = gr.Button("🚀 生成视频", variant="primary", size="lg")
-            
-            status_output = gr.Textbox(
-                label="生成状态",
-                interactive=False,
-                lines=5
-            )
-        
-        with gr.Column(scale=1):
-            # 视频展示区域
-            gr.Markdown("### 🎬 生成的视频")
-            
-            # 动态创建视频和评分组件
-            video_components = {}
-            score_components = {}
-            
-            for model_name in MODELS_TO_CALL:
-                display_name = MODEL_DISPLAY_NAMES.get(model_name, model_name)
-                video_components[model_name] = gr.Video(
-                    label=display_name,
-                    visible=False
-                )
-                score_components[model_name] = gr.Slider(
-                    label=f"{display_name} 评分",
-                    minimum=0,
-                    maximum=10,
-                    step=0.1,
-                    value=5.0,
-                    visible=False
-                )
+    with gr.Tabs():
+        with gr.Tab("🎬 生成视频"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    prompt_input = gr.Textbox(
+                        label="提示词 (Prompt)",
+                        placeholder="输入视频生成的提示词...",
+                        lines=3
+                    )
+                    
+                    input_image = gr.Image(
+                        label="输入图片 (可选，用于图生视频 i2v)",
+                        type="filepath",
+                        sources=["upload"]
+                    )
+                    
+                    generate_btn = gr.Button("🚀 生成视频", variant="primary", size="lg")
+                    
+                    status_output = gr.Textbox(
+                        label="生成状态",
+                        interactive=False,
+                        lines=5
+                    )
+                
+                with gr.Column(scale=1):
+                    # 视频展示区域
+                    gr.Markdown("### 🎬 生成的视频")
+                    
+                    # 动态创建视频和评分组件
+                    video_components = {}
+                    score_components = {}
+                    
+                    for model_name in MODELS_TO_CALL:
+                        display_name = MODEL_DISPLAY_NAMES.get(model_name, model_name)
+                        video_components[model_name] = gr.Video(
+                            label=display_name,
+                            visible=False
+                        )
+                        score_components[model_name] = gr.Slider(
+                            label=f"{display_name} 评分",
+                            minimum=0,
+                            maximum=10,
+                            step=0.1,
+                            value=5.0,
+                            visible=False
+                        )
+                    
+                    # 评分区域
+                    gr.Markdown("### 📊 评分 (0-10分)")
+                    
+                    submit_btn = gr.Button("💾 提交评分", variant="secondary", visible=False)
+                    submit_status = gr.Textbox(
+                        label="提交状态",
+                        interactive=False
+                    )
+    
+        # 历史记录Tab
+        with gr.Tab("📜 历史记录"):
+            gr.Markdown("""
+            ### 📜 我的生成历史
             
-            # 评分区域
-            gr.Markdown("### 📊 评分 (0-10分)")
+            这里显示您最近的视频生成记录（最多10条）
+            """)
             
-            submit_btn = gr.Button("💾 提交评分", variant="secondary", visible=False)
-            submit_status = gr.Textbox(
-                label="提交状态",
-                interactive=False
-            )
+            history_refresh_btn = gr.Button("🔄 刷新历史记录", variant="primary")
+            history_output = gr.HTML(label="历史记录", value="<p>点击刷新按钮加载历史记录</p>")
     
     # 存储中间数据
     model_results_state = gr.State({})
@@ -694,6 +831,8 @@ with gr.Blocks(title="Video Model Evaluator") as demo:
         outputs=[submit_status]
     )
     
+    # 注意: gr.Request 会被 Gradio 自动注入到 on_submit 的 request 参数
+    
     # 刷新用户信息按钮
     refresh_user_btn.click(
         fn=get_user_info,
@@ -701,6 +840,13 @@ with gr.Blocks(title="Video Model Evaluator") as demo:
         outputs=[user_info]
     )
     
+    # 刷新历史记录按钮
+    history_refresh_btn.click(
+        fn=get_history_html,
+        inputs=None,
+        outputs=[history_output]
+    )
+    
     # 页面加载时显示初始提示（不绑定函数，避免 "no backend method" 错误）
     # 用户信息会在用户操作时更新