fix(core): 测试清单行24/28-39/46 — 流水线脚本&资产/消息页 + 单镜重跑后端接口

前端流水线(pipeline.tsx):脚本助手三选项指引(AI全生/一句话/自带脚本)+来源风格推荐; 风格/人物设定卡并持久化到 project.metadata;Enter发送/Shift+Enter换行;长文折叠10行; 生成进度流提示;分镜人物/场景标签可编辑并持久化+点击添加分镜;单镜重跑/删除即时反馈; 脚本助手记录按项目 localStorage 持久化;Stage2 基础资产补替换/重跑/可编辑提示词; 三视图采用弹窗+缺三视图气泡。消息页(messages):复用全站 .search-inline 搜索框、去掉小标题背景方块。视频项目(projects):列表按创建时间倒序,新建置顶。性能:action 改后台 hydrate,消除创建/确认后白等(行29/37)。后端(projects/ai):新增单镜 AI 重跑接口 POST /projects/{id}/rerun-script-segment/ (regenerate_script_segment 服务,复用 AITask+计费 reserve/charge/release;+2 单测)。前端 build 通过;后端 check 0/无新迁移/apps.projects 14 测试通过。 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-16 16:51:32 +08:00
parent f7a403ead3
commit 9be2042520
11 changed files with 703 additions and 60 deletions
@@ -236,6 +236,105 @@ def generate_project_script(*, project, user, user_prompt: str, selling_point_id
        raise


+def build_segment_rerun_prompt(*, project, segment, instruction: str = "") -> list[dict[str, str]]:
+    """单镜重跑提示词:带商品/卖点上下文 + 该镜当前内容 + 前后镜上下文(保连贯)+ 用户修改意见。
+    只重写这一镜,严格输出「旁白：…/画面：…」两行,供 parse_segment_fields 精确解析。"""
+    product = project.product
+    selling_points = product.selling_points.all()
+    selling_text = "\n".join(f"- {item.title}: {item.detail}" for item in selling_points)
+
+    script = segment.script_version
+    siblings = list(script.segments.order_by("sort_order"))
+    prev_seg = next((s for s in reversed(siblings) if s.sort_order < segment.sort_order), None)
+    next_seg = next((s for s in siblings if s.sort_order > segment.sort_order), None)
+
+    def _brief(seg) -> str:
+        narration = (seg.narration or "").strip()
+        visual = (seg.visual_prompt or "").strip()
+        return f"旁白：{narration or '无'}；画面：{visual or '无'}"
+
+    system = (
+        "你是电商短视频脚本导演。现在只需要**重写一条分镜**(其它分镜保持不变)。"
+        "结合商品卖点、该镜当前内容、前后镜上下文和用户的修改意见,重新生成这一镜的旁白口播与画面描述,"
+        "并保证与前后镜衔接连贯。严格按以下格式输出两行,不要输出镜头编号或任何其它内容：\n"
+        "旁白：这一镜要念出来的口播文案（一两句话）\n画面：这一镜的画面描述、商品露出方式和转场建议"
+    )
+    context_lines = [
+        f"商品标题：{product.title}",
+        f"品牌：{product.brand or '未填写'}",
+        f"类目：{product.category or '未填写'}",
+        f"目标人群：{product.target_audience or '未填写'}",
+        f"卖点：\n{selling_text or '未选择卖点，请根据商品信息自行提炼。'}",
+        "",
+        f"这是第 {segment.sort_order + 1} 镜(共 {len(siblings)} 镜),时长约 {segment.duration_seconds} 秒。",
+        f"该镜当前内容：{_brief(segment)}",
+    ]
+    if prev_seg is not None:
+        context_lines.append(f"上一镜(保持不变,用于衔接)：{_brief(prev_seg)}")
+    if next_seg is not None:
+        context_lines.append(f"下一镜(保持不变,用于衔接)：{_brief(next_seg)}")
+    context_lines.append("")
+    context_lines.append(f"用户的修改意见：{instruction.strip() or '让这一镜更有吸引力、表达更清晰，并与前后镜自然衔接。'}")
+    user = "\n".join(context_lines).strip()
+    return [{"role": "system", "content": system}, {"role": "user", "content": user}]
+
+
+def regenerate_script_segment(*, project, user, segment, instruction: str = "") -> ScriptVersion:
+    """单镜 AI 重跑:只重新生成该 ScriptSegment 的 narration + visual_prompt(其它镜不动),
+    沿用 generate_project_script 的 AITask + 计费(reserve/charge/release)闭环,同步调 LLM。
+    返回该 segment 所属的 ScriptVersion。"""
+    model_config = get_default_model(ModelConfig.Capability.TEXT)
+    if model_config is None:
+        raise ValueError("no active text model configured")
+
+    messages = build_segment_rerun_prompt(project=project, segment=segment, instruction=instruction)
+    payload = {
+        "model": model_config.name,
+        "endpoint": model_config.endpoint,
+        "messages": messages,
+        "script_segment": str(segment.id),
+    }
+    task = create_ai_task(
+        project=project,
+        user=user,
+        task_type=AITask.Type.SCRIPT_OPTIMIZATION,
+        model_config=model_config,
+        request_payload=payload,
+    )
+    reservation = task.credit_reservation
+
+    try:
+        task.status = AITask.Status.SUBMITTED
+        task.submitted_at = timezone.now()
+        task.save(update_fields=["status", "submitted_at", "updated_at"])
+
+        provider = VolcanoArkProvider(base_url=model_config.provider.base_url or None)
+        response = provider.chat_completion(model=model_config.name, endpoint=model_config.endpoint, messages=messages)
+        content = provider.extract_text(response)
+        narration, visual = parse_segment_fields(content)
+
+        with transaction.atomic():
+            task.status = AITask.Status.SUCCEEDED
+            task.response_payload = response
+            task.actual_cost = task.estimated_cost
+            task.completed_at = timezone.now()
+            task.save(update_fields=["status", "response_payload", "actual_cost", "completed_at", "updated_at"])
+            charge_reserved_credit(reservation=reservation, actual_amount=task.actual_cost)
+
+            segment.narration = narration
+            segment.visual_prompt = visual
+            segment.save(update_fields=["narration", "visual_prompt", "updated_at"])
+            return segment.script_version
+    except Exception as exc:
+        with transaction.atomic():
+            task.status = AITask.Status.FAILED
+            task.error_message = str(exc)
+            task.completed_at = timezone.now()
+            task.save(update_fields=["status", "error_message", "completed_at", "updated_at"])
+            release_credit(reservation=reservation, reason=str(exc))
+        raise
+
+
 def _generate_video_poster(*, video_bytes: bytes, team, project, asset_id) -> "StoredObject | None":
    """用 ffmpeg 抽视频首帧作为封面(poster)并上传 TOS。best-effort:任何失败都返回 None,不影响视频资产落地。"""
    if not video_bytes: