      ...
  564                 for idx, char in pool.map(_gen_one, tasks):
  565                     pass  # 结果已直接写入char对象
  566         return characters
  567
+ 568     def _generate_scene_images_batch(self, scenes: list, images_dir: Path, characters: list = None, style_prefix: str = "", image_model: str = None) -> list:
+ 569         """为场景列表批量生成背景图 - 使用火山引擎组图API(sequential_image_generation)
+ 570         v3.10: 一次API调用生成所有场景图，比逐张调用效率提升数倍"""
+ 571         if not style_prefix:
+ 572             style_prefix = "日系动漫风格,色彩鲜艳,线条清晰,"
+ 573
+ 574         char_appearances = []
+ 575         if characters:
+ 576             for c in characters:
+ 577                 desc = c.get("appearance", "") or c.get("description", "")
+ 578                 if c.get("name") and desc:
+ 579                     char_appearances.append(f"{c['name']}({desc[:40]})")
+ 580         char_ref = ",角色参考: " + "、".join(char_appearances) if char_appearances else ""
+ 581
+ 582         # 构建场景提示词列表
+ 583         scene_prompts = []
+ 584         valid_indices = []
+ 585         for i, scene in enumerate(scenes):
+ 586             location = scene.get("location", "") or scene.get("description", "")[:30]
+ 587             if not location:
+ 588                 scene["image_path"] = None
+ 589                 continue
+ 590             img_prompt = f"{style_prefix}纯环境背景图,{location},电影感,氛围感,无人,只画环境建筑道具,9:16竖屏"
+ 591             scene_prompts.append((i, scene, img_prompt))
+ 592             valid_indices.append(i)
+ 593
+ 594         if not scene_prompts:
+ 595             return scenes
+ 596
+ 597         # 尝试使用组图API批量生成
+ 598         try:
+ 599             logger.info(f"  尝试组图API批量生成{len(scene_prompts)}个场景图...")
+ 600             # 构建一个综合prompt描述所有场景
+ 601             combined_prompt = " | ".join([p[2] for p in scene_prompts])
+ 602             result = generate_image(
+ 603                 prompt=combined_prompt,
+ 604                 model=image_model if image_model and image_model != "auto" else None,
+ 605                 size="1440x2560",
+ 606                 download_dir=str(images_dir),
+ 607                 sequential_image_generation="auto",
+ 608                 sequential_image_generation_options={"max_images": len(scene_prompts)},
+ 609             )
+ 610             paths = result.get("local_paths", [])
+ 611             if paths and len(paths) >= len(scene_prompts):
+ 612                 # 组图API成功，分配路径
+ 613                 for j, (i, scene, _) in enumerate(scene_prompts):
+ 614                     if j < len(paths):
+ 615                         scene["image_path"] = paths[j]
+ 616                         logger.info(f"  场景图[组图]: {scene.get('location','')[:20]} -> {paths[j][-40:]}")
+ 617                     else:
+ 618                         scene["image_path"] = None
+ 619                 logger.info(f"  组图API成功生成 {len(paths)} 张场景图")
+ 620                 return scenes
+ 621             else:
+ 622                 logger.info(f"  组图API返回{len(paths) if paths else 0}张，不足{len(scene_prompts)}张，回退逐张生成")
+ 623         except Exception as e:
+ 624             logger.info(f"  组图API失败({e})，回退逐张生成")
+ 625
+ 626         # 回退: 逐张生成(并发3)
+ 627         def _gen_one(item):
+ 628             idx, scene, img_prompt = item
+ 629             try:
+ 630                 result = generate_image(
+ 631                     prompt=img_prompt,
+ 632                     model=image_model if image_model and image_model != "auto" else None,
+ 633                     size="1440x2560", n=1, download_dir=str(images_dir),
+ 634                 )
+ 635                 paths = result.get("local_paths", [])
+ 636                 scene["image_path"] = paths[0] if paths else None
+ 637             except Exception as e:
+ 638                 logger.warning(f"  场景图生成失败: {e}")
+ 639                 scene["image_path"] = None
+ 640             return idx, scene
+ 641
+ 642         logger.info(f"  逐张并发生成{len(scene_prompts)}个场景图(max_workers=3)...")
+ 643         with ThreadPoolExecutor(max_workers=3) as pool:
+ 644             for idx, scene in pool.map(_gen_one, scene_prompts):
+ 645                 pass
+ 646         return scenes
+ 647
  568     def _generate_scene_images(self, scenes: list, images_dir: Path, characters: list = None, style_prefix: str = "", image_model: str = None) -> list:
  569         """为场景列表生成背景图,返回带图片路径的场景列表
  570         v3.9: 并发生成(max_workers=3)"""
  571         if not style_prefix:
      ...


exec

# 同时修复: results.characters/backgrounds 被写成了字符串而不是数据
# 这是第983-985行的问题
grep -n 'results\["characters"\].*=.*f"' /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/user_driven_task_system.py | head -5


(no output)


grep -n 'results\["characters"\]' /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/user_driven_task_system.py | head -5


grep -n 'results.*characters\|results.*backgrounds' /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/user_driven_task_system.py | head -10


1067:        task_data["results"]["characters"] = f"角色设计: {char_img_count}/{len(script_result.get('characters', []))}个有图" if script_result.get("characters") else "角色设计降级"
1068:        task_data["results"]["backgrounds"] = f"背景设计: {scene_img_count}个场景有图" if scene_img_count > 0 else "背景设计降级"


edit

        # 保存角色和背景的完整数据（而非摘要字符串）
        task_data["results"]["characters"] = script_result.get("characters", []) or "角色设计降级"
        task_data["results"]["backgrounds"] = [s for s in script_result.get("scenes", []) if s.get("image_path")] if scene_img_count > 0 else "背景设计降级"

        task_data["results"]["characters"] = f"角色设计: {char_img_count}/{len(script_result.get('characters', []))}个有图" if script_result.get("characters") else "角色设计降级"
        task_data["results"]["backgrounds"] = f"背景设计: {scene_img_count}个场景有图" if scene_img_count > 0 else "背景设计降级"


Successfully replaced 1 block(s) in /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/user_driven_task_system.py.

      ...
 1063
 1064         # 更新任务数据
 1065         task_data["results"]["script"] = script_result
 1066         task_data["results"]["storyboard"] = f"分镜脚本已生成 ({img_summary})" if script_result.get("scenes") else "脚本生成降级"
-1067         task_data["results"]["characters"] = f"角色设计: {char_img_count}/{len(script_result.get('characters', []))}个有图" if script_result.get("characters") else "角色设计降级"
-1068         task_data["results"]["backgrounds"] = f"背景设计: {scene_img_count}个场景有图" if scene_img_count > 0 else "背景设计降级"
+1067         # 保存角色和背景的完整数据（而非摘要字符串）
+1068         task_data["results"]["characters"] = script_result.get("characters", []) or "角色设计降级"
+1069         task_data["results"]["backgrounds"] = [s for s in script_result.get("scenes", []) if s.get("image_path")] if scene_img_count > 0 else "背景设计降级"
 1069         task_data["files"]["script_file"] = str(script_file)
 1070         task_data["files"]["storyboard_file"] = str(script_file)  # 同一个JSON
 1071         task_data["files"]["characters_file"] = str(script_file)
 1072         task_data["files"]["backgrounds_file"] = str(script_file)
      ...


exec

# 语法检查
python3 -m py_compile /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/user_driven_task_system.py && echo "语法OK" || echo "语法错误"


语法OK


问题1修复完成。现在处理问题2——任务列表显示创建参数：

问题1: 场景图未生成 + 组图API + 数据结构修复

问题2: 任务列表显示创建参数（时长/模型/模式/渠道）

问题3: 翻查历史备忘录检查未完成需求


问题1: 场景图未生成 + 组图API + 数据结构修复

问题2: 任务列表显示创建参数（时长/模型/模式/渠道）

问题3: 翻查历史备忘录检查未完成需求


# 找到前端JS中的任务列表渲染逻辑
JS_FILE="/root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator_final.js"
wc -l "$JS_FILE" 2>/dev/null
echo "==="
# 搜索任务卡片渲染函数
grep -n "taskCard\|renderTask\|task-item\|taskItem\|task_list\|taskList" "$JS_FILE" 2>/dev/null | head -10


# JS文件可能在static目录下直接
ls /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/*.js 2>/dev/null
echo "==="
ls /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/*.html 2>/dev/null


# 前端HTML引用的是哪个JS？
grep "script.*src.*\.js" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator_final.html 2>/dev/null


<script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0/dist/js/bootstrap.bundle.min.js"></script>
    <script src="user_driven_coordinator.js?v=3.8"></script>


# 查找任务列表渲染逻辑
grep -n "refreshTaskList\|taskList\|task-list\|task-card\|taskCard\|renderTask" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator.js | head -15


204:async function deleteTask(taskId){if(!confirm('\u786e\u8ba4\u5220\u9664\u4efb\u52a1 '+taskId+'? \u6b64\u64cd\u4f5c\u4e0d\u53ef\u64a4\u9500!'))return;try{var r=await fetch(API_BASE+'/tasks/'+taskId,{method:'DELETE'});var d=await r.json();if(d.success){addLog('success','\u4efb\u52a1\u5df2\u5220\u9664');if(currentTaskId===taskId){currentTaskId=null;currentTaskData=null;var ti=document.getElementById('taskInfo');if(ti)ti.style.display='none';['collect','write','produce','review'].forEach(function(s){var c=document.getElementById(s+'ResultContent');if(c)c.innerHTML='';});}refreshTaskList();}else addLog('error','\u5220\u9664\u5931\u8d25: '+(d.detail||d.message));}catch(e){addLog('error','\u5220\u9664\u5931\u8d25: '+e.message);}}
242:async function _doAutoRefresh(){if(!currentTaskId){stopAutoRefresh();return;}try{const r=await fetch(API_BASE+'/tasks/'+currentTaskId+'/status');if(!r.ok)return;const d=await r.json();if(!d.success){stopAutoRefresh();return;}currentTaskData=d.task;updateTaskInfo(d.task);const step=d.task.current_step;if(step==='complete'||step==='completed'||step==='reviewed'){stopAutoRefresh();return;}for(const s of['collect','write','produce','review']){try{const r2=await fetch(API_BASE+'/tasks/'+currentTaskId+'/steps/'+s);if(r2.ok){const d2=await r2.json();if(d2.success&&d2.result){const fn={collect:displayCollectionResult,write:displayWriteResult,produce:displayProduceResult,review:displayReviewResult}[s];if(fn)fn(d2.result,true);}}}catch(e){}}refreshTaskList();}catch(e){}}
246:async function refreshTaskList(){try{const r=await fetch(`${API_BASE}/tasks`);const d=await r.json();if(d.success&&d.tasks.length){let h='';d.tasks.forEach(t=>{const act=t.task_id===currentTaskId;const sb=t.status==='completed'||t.status==='reviewed'?'bg-success':t.status==='produced'||t.status==='written'||t.status==='collected'?'bg-info':'bg-secondary';h+=`

${escapeHtml(t.description||t.task_id)}
${t.task_id.slice(0,20)}... | ${t.current_step||t.status}

${t.progress}%

`;});document.getElementById('taskList').innerHTML=h;}else document.getElementById('taskList').innerHTML='
暂无任务
';}catch(e){}}
247:async function switchTask(taskId){stopAutoRefresh();currentTaskId=taskId;document.getElementById('taskInfo').style.display='block';document.getElementById('currentTaskId').textContent=taskId;addLog('info','切换到任务: '+taskId);['collect','write','produce','review'].forEach(s=>{const c=document.getElementById(s+'ResultContent');if(c)c.innerHTML='';const b=document.getElementById(s+'Body');if(b)b.classList.remove('expanded');});const resp=await fetch(`${API_BASE}/tasks/${taskId}/status`);if(resp.ok){const data=await resp.json();if(data.success){currentTaskData=data.task;updateTaskInfo(data.task);/* 切换任务时回显模型选择框 */const imgSel=document.getElementById('taskImageModel');const vidSel=document.getElementById('taskVideoMode2')||document.getElementById('taskVideoModel');if(imgSel&&data.task.image_model)imgSel.value=data.task.image_model;if(vidSel&&data.task.video_model)vidSel.value=data.task.video_model;const step=data.task.current_step;const steps=['collect','write','produce','review'];const isCompleted=step==='complete'||step==='completed'||step==='reviewed'||data.task.status==='completed'||data.task.progress>=100;const idx=isCompleted?steps.length:steps.indexOf(step);const done=steps.slice(0,idx);steps.forEach((s,i)=>{if(i<idx)updateStepStatus(s,'completed',true,true,true);else if(i===idx&&idx<steps.length)updateStepStatus(s,'pending',true);else if(!isCompleted)updateStepStatus(s,'pending',false);else updateStepStatus(s,'completed',true,true,true);});for(const s of done){try{const r=await fetch(`${API_BASE}/tasks/${taskId}/steps/${s}`);if(r.ok){const d=await r.json();if(d.success&&d.result){const fn={collect:displayCollectionResult,write:displayWriteResult,produce:displayProduceResult,review:displayReviewResult}[s];if(fn)fn(d.result,true);}}}catch(e){}}refreshTaskList();const isInProgress=!isCompleted&&step!=='complete'&&step!=='completed'&&step!=='reviewed'&&data.task.status!=='completed'&&data.task.progress<100;if(isInProgress)startAutoRefresh();}}}
250:document.getElementById('btnCreateTask')?.addEventListener('click',async function(){const desc=document.getElementById('creativeDescription').value.trim();if(!desc){alert('请输入创意描述');return;}this.disabled=true;this.innerHTML=' 创建中...';try{const r=await fetch(`${API_BASE}/tasks/create`,{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({description:desc,user_id:'user_driven',duration:document.getElementById('taskDuration')?.value||'60秒',channels:Array.from(document.querySelectorAll('.channel-check input:checked')).map(function(c){return c.value;}),video_mode:document.getElementById('taskVideoMode')?.value||'img2vid',image_model:document.getElementById('taskImageModel')?.value||'auto',video_model:document.getElementById('taskVideoModel')?.value||'auto'})});if(!r.ok)throw new Error('HTTP '+r.status);const d=await r.json();if(d.success){currentTaskId=d.task_id;document.getElementById('taskInfo').style.display='block';document.getElementById('currentTaskId').textContent=currentTaskId;updateTaskInfo(d);updateStepStatus('collect','pending',true);addLog('success','任务创建成功');refreshTaskList();}else throw new Error(d.message||'创建失败');}catch(e){addLog('error','创建失败: '+e.message);alert('创建失败: '+e.message);}finally{this.disabled=false;this.innerHTML='创建新任务';}});
276:document.getElementById('btnRefreshTasks')?.addEventListener('click',refreshTaskList);
295:refreshTaskList();


# 找到了refreshTaskList在第246行
# 当前渲染只显示 description + task_id + current_step + progress
# 需要增加：duration, video_mode, image_model, video_model, channels
#
# 同时检查API返回的任务列表是否包含这些字段
curl -s http://127.0.0.1:8000/api/tasks 2>/dev/null | python3 -c "
import sys,json
d = json.load(sys.stdin)
if d.get('success') and d.get('tasks'):
    t = d['tasks'][0]
    print('任务字段:', list(t.keys()))
" 2>/dev/null


任务字段: ['task_id', 'description', 'status', 'current_step', 'progress', 'created_at', 'updated_at']


# API返回的任务列表缺少 duration/video_mode/image_model/video_model/channels 字段
# 需要同时修改API和前端

# 1. 修改API - GET /api/tasks 路由
grep -n "def.*get_tasks\|@app.get.*api/tasks\"" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/user_driven_api_server.py | head -5


@app.get("/api/tasks")
async def list_tasks():
    """列出所有任务"""
    try:
        return user_driven_task_system.list_tasks()
    except Exception as e:
        logger.error(f"获取任务列表失败: {str(e)}")
        raise HTTPException(status_code=500, detail=f"获取任务列表失败: {str(e)}")

@app.post("/api/tasks/{task_id}/shots/{shot_id}/regenerate")
async def regenerate_single_shot(task_id: str, shot_id: int, prompt: Optional[str] = Query(None), mode: Optional[str] = Query(None)):
    """重新生成单个镜头的视频"""
    try:
        result = user_driven_task_system.regenerate_single_shot(task_id, shot_id, user_prompt=prompt, mode=mode)
        if not result["success"]:
            raise HTTPException(status_code=400, detail=result["message"])
        return result
    except HTTPException:
        raise


# 查看list_tasks方法
grep -n "def list_tasks" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/user_driven_task_system.py | head -3


2556:    def list_tasks(self) -> Dict[str, Any]:


def list_tasks(self) -> Dict[str, Any]:
        """列出所有任务"""
        tasks = []
        if self.tasks_dir.exists():
            for task_dir in sorted(self.tasks_dir.iterdir(), key=lambda x: x.stat().st_mtime, reverse=True):
                if task_dir.is_dir():
                    task_file = task_dir / "task.json"
                    if task_file.exists():
                        try:
                            with open(task_file, 'r', encoding='utf-8') as f:
                                td = json.load(f)
                            tasks.append({
                                "task_id": td.get("task_id", task_dir.name),
                                "description": td.get("description", "")[:50],
                                "status": td.get("status", "unknown"),
                                "current_step": td.get("current_step", ""),
                                "progress": td.get("progress", 0),
                                "created_at": td.get("created_at", ""),
                                "updated_at": td.get("updated_at", ""),
                            })
                        except Exception:
                            pass
        return {"success": True, "tasks": tasks, "total": len(tasks)}

    def _add_subtitles_to_video(self, video_path: str, shot: Dict, output_path: str = None) -> Optional[str]:
        """使用ffmpeg为视频添加字幕(从镜头的对白中提取)"""
        dialogue = shot.get("dialogue", "")
        if not dialogue or not video_path or not Path(video_path).exists():
            return None

        if output_path is None:
            p = Path(video_path)
            output_path = str(p.parent / f"{p.stem}_subtitled{p.suffix}")

        # 获取视频时长
        try:
            probe = subprocess.run(
                ["ffprobe", "-v", "quiet", "-show_entries", "format=duration", "-of", "csv=p=0", video_path],
                capture_output=True, text=True, timeout=10
            )
            duration = float(probe.stdout.strip()) if probe.stdout.strip() else 5.0
        except Exception:
            duration = 5.0

        # 生成SRT字幕文件
        srt_content = f"1\n00:00:00,000 --> 00:00:{int(duration):02d},{int((duration%1)*1000):03d}\n{dialogue}\n"

        with tempfile.NamedTemporaryFile(mode='w', suffix='.srt', delete=False, encoding='utf-8') as f:
            f.write(srt_content)
            srt_path = f.name

        try:
            # 使用ffmpeg subtitles滤镜烧录字幕
            style = "FontSize=16,PrimaryColour=&H00FFFFFF,OutlineColour=&H00000000,Outline=2,Alignment=2,MarginV=40"
            vf_filter = "subtitles=" + srt_path + ":force_style='" + style + "'"


edit

                            tasks.append({
                                "task_id": td.get("task_id", task_dir.name),
                                "description": td.get("description", "")[:50],
                                "status": td.get("status", "unknown"),
                                "current_step": td.get("current_step", ""),
                                "progress": td.get("progress", 0),
                                "created_at": td.get("created_at", ""),
                                "updated_at": td.get("updated_at", ""),
                                # v3.10: 显示创建参数
                                "duration": td.get("duration", "60秒"),
                                "video_mode": td.get("video_mode", "img2vid"),
                                "image_model": td.get("image_model", "auto"),
                                "video_model": td.get("video_model", "auto"),
                                "channels": td.get("channels", []),
                            })

                            tasks.append({
                                "task_id": td.get("task_id", task_dir.name),
                                "description": td.get("description", "")[:50],
                                "status": td.get("status", "unknown"),
                                "current_step": td.get("current_step", ""),
                                "progress": td.get("progress", 0),
                                "created_at": td.get("created_at", ""),
                                "updated_at": td.get("updated_at", ""),
                            })


      ...
 2571                                 "current_step": td.get("current_step", ""),
 2572                                 "progress": td.get("progress", 0),
 2573                                 "created_at": td.get("created_at", ""),
 2574                                 "updated_at": td.get("updated_at", ""),
+2575                                 # v3.10: 显示创建参数
+2576                                 "duration": td.get("duration", "60秒"),
+2577                                 "video_mode": td.get("video_mode", "img2vid"),
+2578                                 "image_model": td.get("image_model", "auto"),
+2579                                 "video_model": td.get("video_model", "auto"),
+2580                                 "channels": td.get("channels", []),
 2575                             })
 2576                         except Exception:
 2577                             pass
 2578         return {"success": True, "tasks": tasks, "total": len(tasks)}
      ...


现在修改前端JS，在任务列表卡片中显示创建参数：

exec

# 找到refreshTaskList中的渲染模板
JS_FILE="/root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator.js"
grep -n "refreshTaskList" "$JS_FILE"


edit

h+=`

${escapeHtml(t.description||t.task_id)}
${t.task_id.slice(0,20)}... | ${t.current_step||t.status}
⏱${t.duration||'60秒'}🎬${t.video_mode||'img2vid'}🖼${t.image_model||'auto'}📹${t.video_model||'auto'}${(t.channels&&t.channels.length)?'📢'+t.channels.join(',')+'':''}

${t.progress}%

`;

h+=`

${escapeHtml(t.description||t.task_id)}
${t.task_id.slice(0,20)}... | ${t.current_step||t.status}

${t.progress}%

`;


Successfully replaced 1 block(s) in /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator.js.

...
 242 async function _doAutoRefresh(){if(!currentTaskId){stopAutoRefresh();return;}try{const r=await fetch(API_BASE+'/tasks/'+currentTaskId+'/status');if(!r.ok)return;const d=await r.json();if(!d.success){stopAutoRefresh();return;}currentTaskData=d.task;updateTaskInfo(d.task);const step=d.task.current_step;if(step==='complete'||step==='completed'||step==='reviewed'){stopAutoRefresh();return;}for(const s of['collect','write','produce','review']){try{const r2=await fetch(API_BASE+'/tasks/'+currentTaskId+'/steps/'+s);if(r2.ok){const d2=await r2.json();if(d2.success&&d2.result){const fn={collect:displayCollectionResult,write:displayWriteResult,produce:displayProduceResult,review:displayReviewResult}[s];if(fn)fn(d2.result,true);}}}catch(e){}}refreshTaskList();}catch(e){}}
 243 function startAutoRefresh(){stopAutoRefresh();_arTimer=setInterval(_doAutoRefresh,8000);}
 244 function stopAutoRefresh(){if(_arTimer){clearInterval(_arTimer);_arTimer=null;}}
 245
-246 async function refreshTaskList(){try{const r=await fetch(`${API_BASE}/tasks`);const d=await r.json();if(d.success&&d.tasks.length){let h='';d.tasks.forEach(t=>{const act=t.task_id===currentTaskId;const sb=t.status==='completed'||t.status==='reviewed'?'bg-success':t.status==='produced'||t.status==='written'||t.status==='collected'?'bg-info':'bg-secondary';h+=`

${escapeHtml(t.description||t.task_id)}
${t.task_id.slice(0,20)}... | ${t.current_step||t.status}

${t.progress}%

`;});document.getElementById('taskList').innerHTML=h;}else document.getElementById('taskList').innerHTML='
暂无任务
';}catch(e){}}
+246 async function refreshTaskList(){try{const r=await fetch(`${API_BASE}/tasks`);const d=await r.json();if(d.success&&d.tasks.length){let h='';d.tasks.forEach(t=>{const act=t.task_id===currentTaskId;const sb=t.status==='completed'||t.status==='reviewed'?'bg-success':t.status==='produced'||t.status==='written'||t.status==='collected'?'bg-info':'bg-secondary';h+=`

${escapeHtml(t.description||t.task_id)}
${t.task_id.slice(0,20)}... | ${t.current_step||t.status}
⏱${t.duration||'60秒'}🎬${t.video_mode||'img2vid'}🖼${t.image_model||'auto'}📹${t.video_model||'auto'}${(t.channels&&t.channels.length)?'📢'+t.channels.join(',')+'':''}

${t.progress}%

`;});document.getElementById('taskList').innerHTML=h;}else document.getElementById('taskList').innerHTML='
暂无任务
';}catch(e){}}
 247 async function switchTask(taskId){stopAutoRefresh();currentTaskId=taskId;document.getElementById('taskInfo').style.display='block';document.getElementById('currentTaskId').textContent=taskId;addLog('info','切换到任务: '+taskId);['collect','write','produce','review'].forEach(s=>{const c=document.getElementById(s+'ResultContent');if(c)c.innerHTML='';const b=document.getElementById(s+'Body');if(b)b.classList.remove('expanded');});const resp=await fetch(`${API_BASE}/tasks/${taskId}/status`);if(resp.ok){const data=await resp.json();if(data.success){currentTaskData=data.task;updateTaskInfo(data.task);/* 切换任务时回显模型选择框 */const imgSel=document.getElementById('taskImageModel');const vidSel=document.getElementById('taskVideoMode2')||document.getElementById('taskVideoModel');if(imgSel&&data.task.image_model)imgSel.value=data.task.image_model;if(vidSel&&data.task.video_model)vidSel.value=data.task.video_model;const step=data.task.current_step;const steps=['collect','write','produce','review'];const isCompleted=step==='complete'||step==='completed'||step==='reviewed'||data.task.status==='completed'||data.task.progress>=100;const idx=isCompleted?steps.length:steps.indexOf(step);const done=steps.slice(0,idx);steps.forEach((s,i)=>{if(i<idx)updateStepStatus(s,'completed',true,true,true);else if(i===idx&&idx<steps.length)updateStepStatus(s,'pending',true);else if(!isCompleted)updateStepStatus(s,'pending',false);else updateStepStatus(s,'completed',true,true,true);});for(const s of done){try{const r=await fetch(`${API_BASE}/tasks/${taskId}/steps/${s}`);if(r.ok){const d=await r.json();if(d.success&&d.result){const fn={collect:displayCollectionResult,write:displayWriteResult,produce:displayProduceResult,review:displayReviewResult}[s];if(fn)fn(d.result,true);}}}catch(e){}}refreshTaskList();const isInProgress=!isCompleted&&step!=='complete'&&step!=='completed'&&step!=='reviewed'&&data.task.status!=='completed'&&data.task.progress<100;if(isInProgress)startAutoRefresh();}}}
 248
 249 // Event bindings
 250 document.getElementById('btnCreateTask')?.addEventListener('click',async function(){const desc=document.getElementById('creativeDescription').value.trim();if(!desc){alert('请输入创意描述');return;}this.disabled=true;this.innerHTML=' 创建中...';try{const r=await fetch(`${API_BASE}/tasks/create`,{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({description:desc,user_id:'user_driven',duration:document.getElementById('taskDuration')?.value||'60秒',channels:Array.from(document.querySelectorAll('.channel-check input:checked')).map(function(c){return c.value;}),video_mode:document.getElementById('taskVideoMode')?.value||'img2vid',image_model:document.getElementById('taskImageModel')?.value||'auto',video_model:document.getElementById('taskVideoModel')?.value||'auto'})});if(!r.ok)throw new Error('HTTP '+r.status);const d=await r.json();if(d.success){currentTaskId=d.task_id;document.getElementById('taskInfo').style.display='block';document.getElementById('currentTaskId').textContent=currentTaskId;updateTaskInfo(d);updateStepStatus('collect','pending',true);addLog('success','任务创建成功');refreshTaskList();}else throw new Error(d.message||'创建失败');}catch(e){addLog('error','创建失败: '+e.message);alert('创建失败: '+e.message);}finally{this.disabled=false;this.innerHTML='创建新任务';}});
     ...


exec

# 验证JS语法
node -c /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator.js && echo "JS语法OK" || echo "JS语法错误"
echo "==="
# 验证Python语法
python3 -m py_compile /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/user_driven_task_system.py && echo "Python语法OK" || echo "Python语法错误"


JS语法OK
===
Python语法OK


# 更新HTML版本号强制刷新浏览器缓存
grep "v=3.8" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator_final.html


<script src="user_driven_coordinator.js?v=3.8"></script>


Successfully replaced 1 block(s) in /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator_final.html.

     ...
 312         </div>
 313     </div>
 314
 315     <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0/dist/js/bootstrap.bundle.min.js"></script>
-316     <script src="user_driven_coordinator.js?v=3.8"></script>
+316     <script src="user_driven_coordinator.js?v=3.10"></script>
 317 </body>
 318 </html>


问题2修复完成。现在处理问题3——翻查历史备忘录：

问题1: 场景图未生成 + 组图API + 数据结构修复

问题2: 任务列表显示创建参数（时长/模型/模式/渠道）

问题3: 翻查历史备忘录检查未完成需求


问题1: 场景图未生成 + 组图API + 数据结构修复

问题2: 任务列表显示创建参数（时长/模型/模式/渠道）

问题3: 翻查历史备忘录检查未完成需求


Question: 未完成需求 待办 侧边栏 进度条 任务进度

# 检查HEARTBEAT.md和MEMORY.md中的待办事项
grep -A5 "待办\|TODO\|待做\|未完成\|侧边\|进度条\|sidebar\|progress" /root/.openclaw/workspace/MEMORY.md 2>/dev/null | head -40


- 服务端口状态

### **系统优化**
1. **短期**: 启动必要的其他服务端口（8081、8000等）
2. **中期**: 实现智能文件生命周期管理
3. **长期**: 考虑磁盘容量扩展规划

### **知识传承**
1. **本次经验已归档**到记忆系统
2. **CTO Agent行为规范验证**完成
3. **处理模式可复制**到类似问题

## 🏁 **事件关闭**

### **问题状态**
- ✅ **根本原因已解决**：磁盘空间压力和文件数量问题
- ✅ **系统功能已恢复**：文件处理能力正常
- ✅ **预防机制已建立**：监控和自动化体系
- ✅ **用户支持已准备**：工具和文档齐全

### **处理评价**
**CTO规范执行**: ✅ **完全符合**
**技术方案效果**: ✅ **显著有效**
**用户问题解决**: ✅ **彻底完成**
**系统改进提升**: ✅ **全面提升**

### **归档声明**
本事件完整记录已归档，作为CTO Agent处理类似问题的参考模板。未来处理文件系统、磁盘空间、系统性能等问题时，可参考本次处理流程和经验。

**处理完成时间**: 2026-05-07 13:50 GMT+8
**处理Agent签名**: CTO Agent (遵循五大行为规范)
**记忆归档完成**: 2026-05-07 14:00 GMT+8

Source: memory/2026-05-07_CTO_文件处理中断解决.md#L195-L226

# 任务备忘录 - 2026-05-15 执行进展

**创建时间**: 2026-05-15 23:25
**最后更新**: 2026-05-16 00:05

---

## 执行进展

### ✅ Phase 1: 立即修复

| 任务 | 状态 | 说明 |
|------|------|------|
| A. 修复HTTP 422 | ✅ 完成 | `min_length` 10→2，短描述不再报错 |
| B. 任务配置修改UI | ✅ 完成 | 新增配置面板(时长/模式/模型/渠道)，PATCH API扩展 |

### ✅ Phase 2: 核心功能增强

| 任务 | 状态 | 说明 |
|------|------|------|
| D. 视频API增强 | ✅ 完成 | 新增参数(seed/resolution/camera_fixed/首尾帧/回调)；新增3个API(查询/列表/取消) |
| E. 创作官模板 | ✅ 完成 | 子任务完成：3个prompt文件 + 设计报告；已集成到execute_write |

### 🔲 Phase 3: 功能闭环

| 任务 | 状态 | 说明 |
|------|------|------|
| C. 审核闭环 | 🔲 待做 | 需要：improve API + 前端UI + 最小修改逻辑 |
| F. 进度条移侧边 | 🔲 待做 | HTML布局调整 |

### ✅ Phase 4: 测试

| 任务 | 状态 | 说明 |
|------|------|------|
| G. API全量测试

Source: memory/2026-05-15_任务备忘录_用户休息后执行.md#L1-L42

| G. API全量测试 | ✅ 完成 | 27个案例，通过率81.5%，发现3个bug(已记录) |

---

## ⚠ 重要发现

1. **generate_audio不支持Seedance 1.0系列**：仅1.5 Pro和2.0系列支持有声视频
   - 用户指定测试用1.0 Pro Fast和Seedream 4.0 → 有声视频在当前模型下不可用
   - 需要确认用户是否愿意升级到1.5 Pro
2. **API测试发现3个bug**：max_length验证失效、PATCH不存在任务返回400非404、未执行步骤返回404
3. **video_mode/image_model等字段无枚举校验**：任意字符串均可通过

---

## 明日待做

1. 审核闭环流程(Task C)
2. 进度条移侧边(Task F)
3. 修复API测试发现的3个bug
4. 确认有声视频模型选择

Source: memory/2026-05-15_任务备忘录_用户休息后执行.md#L35-L55

- **文件权限**: r--r--r-- (只读保护生效)
- **无需恢复操作**
# 2026-05-15 工作日志

## 09:13 - 用户要求分析腾讯AI助手操作记录 + 执行4项任务

### 任务1: glmcode模型配置 ✅
- CTO Agent的models.json已包含glmcode配置(7个模型)
- 修复了openclaw.json中glmcode apiKey末尾多余空格

### 任务2: 磁盘空间释放 ✅
- 清理前: 88%使用率
- 清理后: 77%使用率
- 清理项: 旧测试包(45MB) + pip缓存(92MB) + Python缓存(312个__pycache__) + 旧日志(8MB) + 旧备份归档(272MB→201MB压缩)

### 任务3: systemd服务激活 ✅
- 问题: systemd服务指向已不存在的openclaw@2026.5.7，凌晨3点5次启动失败
- 修复: `openclaw gateway install --force` 更新服务文件指向2026.5.12
- 结果: 服务enabled+active，网关通过systemd管理，开机自启+自动重启

### 任务4: crontab清理 ✅
- crontab从4个任务精简到1个(仅保留collector保活)
- /etc/cron.d/清理2个残留(task_system_monitor + video_generation_monitor)
- 所有备份到archives/

### 任务5: 视频生成和审核端到端测试 ✅
- 任

Source: memory/2026-05-15.md#L31-L63

### 任务5: 视频生成和审核端到端测试 ✅
- 任务ID: task_20260515_111642_c1d8e59f
- 采集: ✅ 完成(agent_called=False, LLM fallback)
- 创作: ✅ 完成
- 制作: ✅ 完成(视频6.7MB生成成功)
- 审核: ✅ 完成(agent_called=True, 评分78分)
- 全部4步100%完成

### 腾讯AI助手操作记录分析
- 根因版本号搞错: 说zod@4.3.6损坏，实际是zod@4.4.3/core.js缺失
- systemd服务版本指向过期(2026.5.7→已不存在)
- 前台启动而非修复systemd(临时方案)
- 没更新systemd服务文件
- 预防措施太笼统
- 好消息: 这次没运行doctor --fix(没引入配置污染)

## models.json 防护检查 (16:00)
- **文件状态**: ✅ 完整，JSON解析正常
- **Providers**: volcengine-agent-plan, arkcode, astroncodingplan, siliconflow, xfyun, xiaomi-coding (6个)
- **模型总数**: 15
- **MD5**: 81a27b19157747c2abca72e5e3ff6822
- **与backup/bak一致性**: ✅ 三份文件MD5完全一致
- **临时文件清理**: 无.tmp文件需清理
- **篡改/损坏**: 未检测到
- **文件权限**: 0444 (只读) ✅
-

Source: memory/2026-05-15.md#L56-L86

- 内容生成: 按预期进行
- 错误处理: 有效诊断和解决

### 生产流程效率: ✅ 85%
- 时间效率: 40分钟完成主要工作
- 资源效率: 合理使用API资源
- 质量效率: 平衡速度和质量

## 🔮 后续优化方向

### 短期优化:
1. **视频拼接自动化**: 实现自动拼接功能
2. **质量检查系统**: 建立自动化质量检查
3. **参数模板库**: 建立标准参数模板

### 长期规划:
1. **多模态集成**: 图像+视频+音频统一生成
2. **实时监控**: 生产流程实时监控系统
3. **智能优化**: AI优化提示词和参数

## 🎯 结论

### 多Agent协调漫剧生产系统 ✅ 验证成功！

**核心成就**:
1. ✅ 完整工作流程已验证
2. ✅ 技术问题已解决
3. ✅ 内容安全策略有效
4. ✅ Agent协调机制有效

**生产成果**:
- 完整漫剧脚本和设计
- 角色和视觉内容
- 视频分镜生成中
- 可扩展的生产系统

**系统状态**: 已具备实际生产能力，可开始规模化漫剧生产。

---

**报告生成时间**: 2026-04-27 10:07
**生产状态**: 视频生成中 (85%完成)
**预计完成**: 10:20-10:30
**总体评价**: ✅ 任务基本完成，核心目标已达成
**下一步**: 监控生成进度，完成视频拼接和验证

Source: memory/episodic/manhua_production_summary_20260427.md#L142-L186

results provider model fallback citations mode debug


**待办**:
- [ ] 将pnpm package-import-method从copy改为hardlink
- [ ] 禁用腾讯云TAT agent的自动修复功能
- [ ] 清理/root/data/disk/中2.2GB旧数据
- [ ] 建立8000端口systemd服务


找到了关键备忘录！


# 任务备忘录 - 2026-05-15 执行进展

**创建时间**: 2026-05-15 23:25
**最后更新**: 2026-05-16 00:05

---

## 执行进展

### ✅ Phase 1: 立即修复

| 任务 | 状态 | 说明 |
|------|------|------|
| A. 修复HTTP 422 | ✅ 完成 | `min_length` 10→2，短描述不再报错 |
| B. 任务配置修改UI | ✅ 完成 | 新增配置面板(时长/模式/模型/渠道)，PATCH API扩展 |

### ✅ Phase 2: 核心功能增强

| 任务 | 状态 | 说明 |
|------|------|------|
| D. 视频API增强 | ✅ 完成 | 新增参数(seed/resolution/camera_fixed/首尾帧/回调)；新增3个API(查询/列表/取消) |
| E. 创作官模板 | ✅ 完成 | 子任务完成：3个prompt文件 + 设计报告；已集成到execute_write |

### 🔲 Phase 3: 功能闭环

| 任务 | 状态 | 说明 |
|------|------|------|
| C. 审核闭环 | 🔲 待做 | 需要：improve API + 前端UI + 最小修改逻辑 |
| F. 进度条移侧边 | 🔲 待做 | HTML布局调整 |

### ✅ Phase 4: 测试

| 任务 | 状态 | 说明 |
|------|------|------|
| G. API全量测试 | ✅ 完成 | 27个案例，通过率81.5%，发现3个bug(已记录) |

---

## ⚠ 重要发现

1. **generate_audio不支持Seedance 1.0系列**：仅1.5 Pro和2.0系列支持有声视频
   - 用户指定测试用1.0 Pro Fast和Seedream 4.0 → 有声视频在当前模型下不可用
   - 需要确认用户是否愿意升级到1.5 Pro
2. **API测试发现3个bug**：max_length验证失效、PATCH不存在任务返回400非404、未执行步骤返回404
3. **video_mode/image_model等字段无枚举校验**：任意字符串均可通过

---

## 明日待做

1. 审核闭环流程(Task C)
2. 进度条移侧边(Task F)
3. 修复API测试发现的3个bug
4. 确认有声视频模型选择


找到了！备忘录中有两个**未完成需求**：

1. **Task C: 审核闭环** — improve API + 前端UI + 最小修改逻辑
2. **Task F: 进度条移侧边** — HTML布局调整

还有5月16日的待办：
3. **improve端点同步阻塞改异步**
4. **前端loading进度提示**

# 检查improve功能当前状态——实际已经实现了（审核→建议→improve→重新生成）
# 之前测试已有3次improve历史
# 确认improve API是否存在
grep -n "improve" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/user_driven_api_server.py | head -5


422:@app.post("/api/tasks/{task_id}/improve")
423:async def improve_task(task_id: str, request: dict):
436:        result = user_driven_task_system.execute_improve(


# improve API已存在。检查前端是否有执行建议的按钮
grep -n "improve\|执行建议\|重新生成" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator.js | head -10


130:    if(m.includes('SensitiveContent')||m.includes('sensitive'))return{reason:'参考图被检测为敏感内容',suggestion:'建议：1)点击"改为文生视频"重新生成 2)修改参考图提示词'};
134:    return{reason:m.substring(0,100),suggestion:'建议：尝试重新生成，或切换到文生视频模式'};
168:                    h+=`<div class="mt-2"><video src="${vu}" controls class="video-inline" preload="metadata"></video></div>`;}if(shot.error||shot.status==='failed'){const a=analyzeVideoError(shot.error);if(a)h+=`<div class="alert alert-danger py-1 mt-2 small"><strong>❌ 原因:</strong> ${escapeHtml(a.reason)}<br><strong>💡 建议:</strong> ${escapeHtml(a.suggestion)}</div>`;else h+=`<div class="mt-1 text-danger small">❌ ${escapeHtml(shot.error||'未知')}</div>`;}h+=`
<button class="btn btn-sm btn-outline-warning" onclick="doRegenShot(${shot.shot_id})">重新生成</button> <button class="btn btn-sm btn-outline-info" onclick="doRegenShotPrompt(${shot.shot_id})">修改提示词重生成</button>${shot.error&&shot.mode==='img2vid'?` <button class="btn btn-sm btn-outline-success" onclick="doRegenShotText(${shot.shot_id})"><i class="bi bi-type me-1"></i>改为文生视频</button>`:''}

`;});}
177:if(r.improvement_suggestions&&r.improvement_suggestions.length){h+='
💡 改进建议 选择要执行的建议

';r.improvement_suggestions.forEach((s,i)=>h+=`
<input type="checkbox" class="form-check-input mt-1 improve-check" data-idx="${i}" checked id="improve_${i}">${escapeHtml(typeof s==='string'?s:JSON.stringify(s))}
`);h+='</ul>';h+=`
<textarea class="form-control form-control-sm" id="improveFeedback" rows="2" placeholder="额外修改说明(可选)"></textarea>
`;h+=`<button class="btn btn-success btn-sm" onclick="executeImprove()" id="btnExecuteImprove">🔄 执行选中建议并重新生成</button> `;}else if(r.suggestions&&r.suggestions.length){h+='<h6>💡 改进建议</h6><ul class="list-group mb-3">';r.suggestions.forEach(s=>h+=`
${escapeHtml(s)}
`);h+='
';}
185:async function executeImprove(){if(!currentTaskId){alert('请先选择任务');return;}const checks=document.querySelectorAll('.improve-check:checked');const indices=Array.from(checks).map(c=>parseInt(c.dataset.idx));if(!indices.length){alert('请至少选择一条改进建议');return;}const feedback=document.getElementById('improveFeedback')?.value||'';const btn=document.getElementById('btnExecuteImprove');const st=document.getElementById('improveStatus');if(btn)btn.disabled=true;if(st)st.innerHTML=' 执行中...';addLog('info',`开始执行${indices.length}条改进建议...`);try{const r=await fetch(`${API_BASE}/tasks/${currentTaskId}/improve`,{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({suggestions:indices,feedback:feedback,auto_review:true})});const d=await r.json();if(d.success){addLog('success',d.message);if(st)st.innerHTML=`<span class="badge bg-success">✅ 完成: ${d.message}</span>`;if(d.new_review){displayReviewResult(d.new_review);}await refreshTaskStatus();}else{addLog('error','改进失败: '+(d.detail||d.message));if(st)st.innerHTML=`<span class="badge bg-danger">❌ ${d.detail||d.message}</span>`;}}catch(e){addLog('error','改进失败: '+e.message);if(st)st.innerHTML=`<span class="badge bg-danger">❌ ${e.message}</span>`;}finally{if(btn)btn.disabled=false;}}
188:async function regenerateShotRefImage(sceneIdx,shotIdx){if(!currentTaskId||!window._wr)return;const sc=window._wr.scenes[sceneIdx];if(!sc||!sc.shots||!sc.shots[shotIdx])return;const sh=sc.shots[shotIdx];const defaultPrompt=sh.image_prompt||sh.description||'';const p=await showPromptEditor('修改镜头'+sh.shot_id+'的参考图提示词',defaultPrompt);if(p===null)return;addLog('info','重新生成镜头'+sh.shot_id+'的参考图...');
209:async function regenerateCharImage(idx){if(!currentTaskId||!window._wr)return;const ch=window._wr.characters[idx];if(!ch)return;const existingPrompt=ch.appearance||ch.description||ch.personality||'';const defaultPrompt='角色设计图，'+ch.name+'，'+existingPrompt+'，全身像，清晰细节，白色背景，9:16竖屏，三视图(正面/侧面/背面)';const p=await showPromptEditor('修改角色"'+ch.name+'"的图片提示词',defaultPrompt);if(p===null)return;addLog('info','重新生成角色"'+ch.name+'"的图片...');
214:async function regenerateSceneImage(idx){if(!currentTaskId||!window._wr)return;const sc=window._wr.scenes[idx];if(!sc)return;const loc=sc.location||sc.description?.substring(0,30)||'场景'+sc.scene_id;const p=await showPromptEditor('修改场景"'+loc+'"的背景图提示词','纯环境背景图，'+loc+'，电影感，氛围感，无人，9:16竖屏');if(p===null)return;addLog('info','重新生成场景"'+loc+'"的背景图...');
221:async function doRegenShot(id,cp,mode){if(!currentTaskId)return;let u=`${API_BASE}/tasks/${currentTaskId}/shots/${id}/regenerate`;const ps=[];if(cp)ps.push('prompt='+encodeURIComponent(cp));if(mode)ps.push('mode='+encodeURIComponent(mode));if(ps.length)u+='?'+ps.join('&');addLog('info','重新生成镜头'+id+'...');try{const r=await fetch(u,{method:'POST'});const d=await r.json();if(d.success){addLog('success','镜头'+id+'重生成成功');if(d.result)displayProduceResult(d.result);document.getElementById('btnStitchVideos').style.display='inline-block';}else addLog('error','镜头'+id+'失败: '+d.message);}catch(e){addLog('error','失败: '+e.message);}}
254:document.getElementById('btnRegenerateCollect')?.addEventListener('click',()=>executeStep('collect','btnRegenerateCollect','重新采集中','重新生成'));


审核闭环（Task C）已经实现了！improve API + 前端UI（选择建议+执行+反馈）都有。

现在做**Task F: 进度条移侧边**——这个需要改HTML布局：

# 查看当前HTML布局结构
grep -n "sidebar\|侧边\|col-\|progress\|step-" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator_final.html | head -20


12:        .step-card { border: 2px solid #dee2e6; border-radius: 10px; padding: 20px; margin-bottom: 20px; background: white; transition: all 0.3s ease; }
13:        .step-card.active { border-color: #0066cc; box-shadow: 0 0 0 3px rgba(0, 102, 204, 0.1); }
14:        .step-card.completed { border-color: #28a745; background-color: #f8fff9; }
15:        .step-card.pending { border-color: #ffc107; background-color: #fffdf6; }
16:        .step-icon { width: 50px; height: 50px; border-radius: 50%; display: flex; align-items: center; justify-content: center; font-size: 20px; margin-bottom: 15px; }
25:        .step-collapse-body { max-height: 0; overflow: hidden; transition: max-height 0.3s ease; }
26:        .step-collapse-body.expanded { max-height: 5000px; }
27:        .step-toggle { cursor: pointer; user-select: none; }
28:        .step-toggle:hover { opacity: 0.8; }
46:        .progress-tracker { display: flex; justify-content: center; align-items: center; padding: 20px 0; margin-bottom: 20px; }
47:        .progress-step { display: flex; flex-direction: column; align-items: center; margin: 0 15px; position: relative; }
48:        .progress-step .progress-dot { width: 40px; height: 40px; border-radius: 50%; background: #dee2e6; color: #6c757d; display: flex; align-items: center; justify-content: center; font-weight: bold; font-size: 1.1em; transition: all 0.3s; margin-bottom: 6px; }
49:        .progress-step.active .progress-dot { background: #0066cc; color: white; box-shadow: 0 0 0 4px rgba(0,102,204,0.2); }
50:        .progress-step.completed .progress-dot { background: #28a745; color: white; }
51:        .progress-step div:last-child { font-size: 0.85em; color: #6c757d; }
52:        .progress-step.active div:last-child { color: #0066cc; font-weight: 600; }
53:        .progress-step.completed div:last-child { color: #28a745; }
54:        .progress-line { flex: 1; height: 2px; background: #dee2e6; min-width: 40px; align-self: flex-start; margin-top: 20px; }
55:        .progress-line.completed { background: #28a745; }
100:        <div class="progress-tracker">


# 看HTML主体布局
grep -n "class=\"container\|row\|col-md\|col-lg\|sidebar\|main-content\|taskList\|taskInfo" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator_final.html | head -20


82:            <textarea class="form-control" id="promptEditorText" rows="8" style="font-size:0.95em;resize:vertical" placeholder="请输入提示词..."></textarea>
92:

110:

111:

118:                            <textarea class="form-control" id="creativeDescription" rows="3" placeholder="描述您想要创作的慢剧内容..."></textarea>
172:

191:                            刷新
193:

211:

227:                        <button class="btn btn-outline-warning" id="btnRegenerateCollect" disabled>重新生成</button>
249:                        <button class="btn btn-outline-info" id="btnRegenerateWrite" disabled>重新生成</button>
274:                        <button class="btn btn-outline-primary" id="btnRegenerateProduce" disabled>重新生成</button>
296:                        <button class="btn btn-outline-success" id="btnRegenerateReview" disabled>重新审核</button>


# 当前布局：col-lg-4（左，任务列表）+ col-lg-8（右，步骤内容）
# 进度条在顶部（progress-tracker），需要在左侧任务列表中显示
#
# 任务执行进度放在左侧任务面板中更合理——选中任务后显示进度
# 不需要大改布局，而是在左侧任务信息区域加一个垂直进度条

# 查看左侧任务信息区域
sed -n '172,210p' /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator_final.html


任务信息

任务ID:

当前状态: 已创建

当前步骤: 采集

进度: 0%

任务列表

                        <button class="btn btn-outline-primary btn-sm mb-2" id="btnRefreshTasks">
                            刷新
                        </button>

暂无任务

系统状态

系统运行正常

4个Agent待命


edit

任务信息

任务ID:

当前状态: 已创建

当前步骤: 采集

进度: 0%

1

                                    采集
                                    待执行

2

                                    创作
                                    待执行

3

                                    制作
                                    待执行

4

                                    审核
                                    待执行

任务信息

任务ID:

当前状态: 已创建

当前步骤: 采集

进度: 0%


现在添加JS逻辑更新侧边步骤状态：

exec

# 找到updateStepStatus函数
grep -n "function updateStepStatus" /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator.js


103:function updateStepStatus(step,status,canExec,canMod,canRegen){


function updateStepStatus(step,status,canExec,canMod,canRegen){
    const cn=step[0].toUpperCase()+step.slice(1);
    const se=document.getElementById(step+'Status'),eb=document.getElementById('btnExecute'+cn),vb=document.getElementById('btnView'+cn),mb=document.getElementById('btnModify'+cn),rb=document.getElementById('btnRegenerate'+cn);
    if(se){se.textContent={completed:'已完成',working:'执行中',pending:'等待中'}[status]||status;se.className='badge '+(status==='completed'?'bg-success':status==='working'?'bg-warning':'bg-secondary');}
    if(eb){
        eb.disabled=!canExec;
        /* 恢复按钮文本，防止executeStep超时后永远显示转圈 */
        const labels={collect:{icon:'bi-play-circle',text:'执行采集'},write:{icon:'bi-pencil',text:'执行创作'},produce:{icon:'bi-camera-video',text:'执行制作'},review:{icon:'bi-shield-check',text:'执行审核'}};
        const lb=labels[step];
        if(lb&&status!=='working')eb.innerHTML='<i class="bi '+lb.icon+' me-2"></i>'+lb.text;
    }
    if(vb)vb.disabled=status!=='completed';
    if(mb){mb.disabled=!canMod;mb.style.display=canMod?'inline-block':'none';}


# 在updateStepStatus函数末尾添加侧边栏步骤更新
# 找到函数结束位置
sed -n '115,120p' /root/.openclaw/workspace/versions/user_driven_final_v3.0.1/manhua_studio_web_8000/static/user_driven_coordinator.js


if(mb){mb.disabled=!canMod;mb.style.display=canMod?'inline-block':'none';}
    if(rb){rb.disabled=!canRegen;rb.style.display=canRegen?'inline-block':'none';}
}
async function refreshTaskStatus(){if(!currentTaskId)return;try{const r=await fetch(`${API_BASE}/tasks/${currentTaskId}/status`);if(r.ok){const d=await r.json();if(d.success){currentTaskData=d.task;updateTaskInfo(d.task);}}}catch(e){}}

// Modal


edit

if(mb){mb.disabled=!canMod;mb.style.display=canMod?'inline-block':'none';}
    if(rb){rb.disabled=!canRegen;rb.style.display=canRegen?'inline-block':'none';}
    // v3.10: 更新侧边步骤进度
    const ss=document.getElementById('sideStep_'+step);
    const sss=document.getElementById('sideStepStatus_'+step);
    if(ss){
        const dot=ss.querySelector('div');
        if(status==='completed'){dot.style.background='#28a745';dot.style.color='white';dot.innerHTML='✓';}
        else if(status==='working'){dot.style.background='#ffc107';dot.style.color='#333';dot.innerHTML='⟳';}
        else{dot.style.background='#dee2e6';dot.style.color='#6c757d';dot.innerHTML={collect:'1',write:'2',produce:'3',review:'4'}[step]||'?';}
        const line=ss.nextElementSibling;
        if(line&&line.style&&status==='completed')line.style.background='#28a745';
    }
    if(sss){sss.textContent={completed:'✅已完成',working:'⏳执行中',pending:'待执行'}[status]||status;sss.className='badge '+(status==='completed'?'bg-success text-white':status==='working'?'bg-warning text-dark':'bg-light text-dark');}
}

if(mb){mb.disabled=!canMod;mb.style.display=canMod?'inline-block':'none';}
    if(rb){rb.disabled=!canRegen;rb.style.display=canRegen?'inline-block':'none';}
}


     ...
 113     }
 114     if(vb)vb.disabled=status!=='completed';
 115     if(mb){mb.disabled=!canMod;mb.style.display=canMod?'inline-block':'none';}
 116     if(rb){rb.disabled=!canRegen;rb.style.display=canRegen?'inline-block':'none';}
+117     // v3.10: 更新侧边步骤进度
+118     const ss=document.getElementById('sideStep_'+step);
+119     const sss=document.getElementById('sideStepStatus_'+step);
+120     if(ss){
+121         const dot=ss.querySelector('div');
+122         if(status==='completed'){dot.style.background='#28a745';dot.style.color='white';dot.innerHTML='✓';}
+123         else if(status==='working'){dot.style.background='#ffc107';dot.style.color='#333';dot.innerHTML='⟳';}
+124         else{dot.style.background='#dee2e6';dot.style.color='#6c757d';dot.innerHTML={collect:'1',write:'2',produce:'3',review:'4'}[step]||'?';}
+125         const line=ss.nextElementSibling;
+126         if(line&&line.style&&status==='completed')line.style.background='#28a745';
+127     }
+128     if(sss){sss.textContent={completed:'✅已完成',working:'⏳执行中',pending:'待执行'}[status]||status;sss.className='badge '+(status==='completed'?'bg-success text-white':status==='working'?'bg-warning text-dark':'bg-light text-dark');}
 117 }
 118 async function refreshTaskStatus(){if(!currentTaskId)return;try{const r=await fetch(`${API_BASE}/tasks/${currentTaskId}/status`);if(r.ok){const d=await r.json();if(d.success){currentTaskData=d.task;updateTaskInfo(d.task);}}}catch(e){}}
 119
 120 // Modal
     ...