48f6f49f7be4610b2c7d2785d318862fa671d2ba
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Two-phase pipeline: worker renders and precomputes dedup metadata, but does
not create GeneratedVideo until user confirms cover in Step 5.
Domain
- Add GenerationTaskStatus.AWAITING_COVER (non-terminal)
- Add mark_awaiting_cover(): progress=100, clears error, leaves completed_at unset
- Transitions: running → {awaiting_cover, completed, failed, cancelled};
awaiting_cover → {completed, failed, cancelled}
- _missing_ aliases: waiting_cover/video_ready/rendered/pending_cover
- Keep running→completed for backward compat / legacy paths
Worker (apps/worker/worker_app/tasks/generation.py)
- Replace _record_video_and_dedup with _precompute_render_metadata:
calls compute_render_fingerprint_and_dedup, returns dict without DB writes
- Remove runtime batch-rerender decision (should_rerender_for_batch_dedup path);
dedup now happens at finalize time against all finished records
- Persist precomputed metadata into task.extra_meta['rendered_output']
- Final status: mark_awaiting_cover instead of mark_completed
Dedup helpers (apps/worker/video_processing/dedup_helpers.py)
- New compute_render_fingerprint_and_dedup(video_path,...): local fingerprint
+ historical dedup + batch dedup, returns fully serializable dict
(fingerprint_dict, fingerprint_chunks list, is_duplicate, duplicate_of, etc.)
- create_video_record_and_dedup() retained for compat/tests; now supports
pre_dedup_result to reuse worker-precomputed data without re-reading video
- VideoFingerprint.from_dict() added to reconstruct from serialized form
Application layer (packages/application/generated_video_finalize.py)
- RenderedOutput dataclass + from_dict() for deserializing worker output
- finalize_generated_video(): creates GeneratedVideo, bulk-inserts
VideoFingerprintChunk rows, commits; API-layer free
API service (apps/api/app/services/generation_finalize_service.py)
- GenerationFinalizeService.finalize_task(task_id, user_id, cover_url):
* permission / existence check
* idempotent: if GeneratedVideo already exists for this task, just ensure
task is marked completed and return (safe for double-click)
* status gate: only awaiting_cover (or legacy completed) accepted
* cover resolution: explicit cover_url arg > task.cover_url
* delegates to finalize_generated_video, marks task completed,
clears extra_meta['rendered_output']
API endpoint (apps/api/app/api/routes/generation_tasks.py)
- POST /api/v1/generation/tasks/{task_id}/finalize
- Body: { cover_url?: string }; returns video_id/cover_url/file_url/is_duplicate
- Adjust confirm_generation fast path: mark_confirmed keeps task in
awaiting_cover (don't auto-complete); historical 'completed' previews
migrated back to awaiting_cover
- Preview-reuse accepts awaiting_cover tasks
Preview / task center
- GET /preview/{task_id} constructs lightweight _PreviewVideo from
extra_meta.rendered_output when task is awaiting_cover
- Task center step map: awaiting_cover → 等待确认封面; status filter includes it
Tests
- tests/unit/test_finalize_generation.py: 13 new tests covering status
transitions, mark_awaiting_cover, RenderedOutput parsing, finalize use case
(success / missing metadata / cover fallback)
- test_generation_task.py updated for 6th status value
- Full suite: 15978 passed, 28 skipped (matches #2023 baseline, no regressions)
- black/isort/ruff clean
Out of scope (intentionally untouched)
- AI avatar pipeline uses separate AiAvatarRenderJob; finalize_job and
/{job_id}/finalize are unchanged
- PR #2023 subtitle font scaling files (ass_subtitle_builder,
video_filter_builder, subtitle_generator) not modified
- No DB migration: GenerationTaskModel.status is String(20) without CHECK
- Temp file cleanup: leave to existing periodic job
小虾 SaaS - 自动化视频剪辑平台
自动化视频剪辑 SaaS 平台,支持素材上传、AI 分类、智能剪辑计划生成、自动化视频合成与成片管理。
✨ 核心功能
🎬 视频剪辑主链路
- 素材上传(直传 OSS + 分片上传大文件,最大 2GB)
- AI 智能分类与质量评分
- 4 种剪辑模式:one_take / pip(画中画)/ voice_over(口播+B-roll)/ voice_pip
- 剪辑计划模板 + 智能生成
- 自动化视频合成任务(Celery 异步)
- 成片下载与审核管理
- 资产诊断(素材就绪度评估、缺口分析)
🔐 认证系统
- JWT Bearer Token 认证
- 邮箱注册 + 邮箱验证
- 密码重置(邮箱找回)
- bcrypt 密码加密
📋 项目管理
- 项目 CRUD + 共享
- 任务管理(创建/更新/状态流转/进度追踪)
- 里程碑管理
- 任务问题追踪
📊 素材库管理
- 素材库创建与管理
- 素材上传、审核状态流转(pending_review → approved/rejected)
- 素材诊断(就绪度评分、缺口分析、智能视图)
🚀 快速开始
方式 1: Docker Compose(推荐)
# 1. 克隆仓库
git clone https://git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas.git
cd xiaoxia-saas
# 2. 配置环境变量
cp .env.example .env
# 编辑 .env 填写数据库、Redis、OSS 等配置
# 3. 启动所有服务
docker-compose up -d
# 4. 访问 API 文档
open http://localhost:8000/docs
方式 2: 本地开发
# 1. 克隆仓库
git clone https://git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas.git
cd xiaoxia-saas
# 2. 创建虚拟环境
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
# 3. 安装依赖
pip install -r requirements.txt
# 4. 配置环境变量
cp .env.example .env
# 5. 启动 API 服务
uvicorn apps.api.main:app --reload
# 6. 访问 API 文档
open http://localhost:8000/docs
📚 API 文档
交互式文档
- Swagger UI: https://saas-api.xiaoxiajianji.com/docs
- OpenAPI Schema: https://saas-api.xiaoxiajianji.com/openapi.json
核心 API 路径
认证 (/api/v1/auth)
| 方法 | 路径 | 说明 |
|---|---|---|
| POST | /register |
用户注册 |
| POST | /login |
用户登录 |
| GET | /me |
获取当前用户信息 |
| POST | /password/forgot |
忘记密码 |
| POST | /password/reset |
重置密码 |
视频剪辑主链路
上传素材 → POST /api/v1/upload(直传)或 /api/v1/upload/chunk/init(分片)
↓
创建素材 → POST /api/v1/assets
↓
AI 分类 → POST /api/v1/classification-jobs
↓
生成剪辑计划 → POST /api/v1/projects/{id}/edit-plans/auto-generate
↓
创建生成任务 → POST /api/v1/generation/tasks/
↓
查询结果 → GET /api/v1/generation/tasks/{task_id}/results/
↓
获取成片 → GET /api/v1/generated-videos/{video_id}/download-url
项目管理 (/api/v1/project-management)
| 方法 | 路径 | 说明 |
|---|---|---|
| GET/POST | /tasks |
任务列表/创建 |
| PATCH | /tasks/{id} |
更新任务信息 |
| PATCH | /tasks/{id}/status |
更新任务状态 |
| PATCH | /tasks/{id}/progress |
更新任务进度 |
| GET/POST | /milestones |
里程碑列表/创建 |
| GET/POST | /issues |
问题列表/创建 |
| PATCH | /issues/{id}/resolve |
解决问题 |
素材与上传
| 方法 | 路径 | 说明 |
|---|---|---|
| POST | /api/v1/upload |
直传素材(multipart/form-data) |
| POST | /api/v1/upload/direct/prepare |
准备 OSS 直传签名 |
| POST | /api/v1/upload/direct/complete |
确认直传完成 |
| POST | /api/v1/upload/chunk/init |
初始化分片上传 |
| POST | /api/v1/upload/chunk/{id}/{index} |
上传分片 |
| POST | /api/v1/upload/chunk/{id}/complete |
完成分片上传 |
| GET | /api/v1/assets |
素材列表 |
| PATCH | /api/v1/assets/{id}/review |
更新素材审核状态 |
| GET | /api/v1/projects/{id}/asset-diagnosis |
资产诊断 |
成片管理 (/api/v1/generated-videos)
| 方法 | 路径 | 说明 |
|---|---|---|
| GET | / |
成片列表 |
| GET | /{video_id} |
成片详情 |
| GET | /{video_id}/download-url |
下载链接 |
| PATCH | /{video_id}/review |
审核状态 |
完整 API 列表请查看 API 主线清单
🏗️ 架构
小虾 SaaS
├── packages/ # 核心业务逻辑(Clean Architecture)
│ ├── domain/ # 领域模型(dataclass)
│ ├── application/ # 用例(Use Cases)
│ ├── ports/ # 接口定义(抽象端口)
│ └── adapters/ # 适配器实现(SQLAlchemy、Redis、SMTP 等)
├── apps/ # 应用层
│ ├── api/ # FastAPI 应用 + 路由 + Pydantic schemas
│ ├── web/ # React + Vite 前端
│ └── worker/ # Celery 异步任务(视频处理、分类等)
├── migrations/ # Alembic 数据库迁移
├── tests/ # 测试
│ ├── unit/ # 单元测试
│ ├── integration/ # 集成测试
│ └── e2e/ # 端到端测试
└── docs/ # 文档
设计模式:
- Clean Architecture(依赖方向:外层 → 内层)
- 依赖注入(FastAPI Depends)
- Repository 模式(通过 ports 抽象)
- Domain-Driven Design
🛠️ 技术栈
后端:
- Python 3.12 + FastAPI 0.115.0
- PostgreSQL 16(生产)
- Redis 7(缓存 + Celery Broker)
- Celery(异步任务:视频处理、素材导入、分类)
- 阿里云 OSS(文件存储)
前端:
- React 18 + TypeScript
- Vite(构建工具)
- Ant Design(UI 组件)
部署:
- Docker + Docker Compose
- Gitea + Gitea Actions(CI/CD)
- Nginx(反向代理)
🧪 测试
# 运行所有测试
pytest tests/ -v
# 运行单元测试
pytest tests/unit -v
# 运行集成测试
pytest tests/integration -v
# 生成覆盖率报告
pytest --cov=packages --cov-report=html
📊 当前状态
| 模块 | 状态 |
|---|---|
| 视频剪辑主链路(Phase 7) | ✅ 已完成 |
| 分片上传(最大 2GB) | ✅ 已完成 |
| 4 种剪辑模式 | ✅ 已完成 |
| 项目管理 + 任务追踪 | ✅ 已完成 |
| 资产诊断 | ✅ 已完成 |
| 认证系统(JWT) | ✅ 已完成 |
| CI/CD 流水线 | ✅ 运行中 |
| 前端界面(Vite) | ✅ 已完成 |
📄 更多文档
🤝 贡献
欢迎贡献!请查看 贡献指南
仓库地址: https://git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas
License: MIT
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