fix(ports): docker 默认对外8502并修复空DB连接串回退
This commit is contained in:
Tony Zhang
37
Dockerfile
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37
Dockerfile
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# Video Flow - Python 后端 Dockerfile
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FROM python:3.11-slim
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# 安装系统依赖
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RUN apt-get update && apt-get install -y --no-install-recommends \
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ffmpeg \
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libsm6 \
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libxext6 \
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libgl1 \
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fonts-noto-cjk \
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fonts-wqy-zenhei \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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# 设置工作目录
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WORKDIR /app
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# 复制依赖文件
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COPY requirements.txt .
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# 安装 Python 依赖
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RUN pip install --no-cache-dir -r requirements.txt
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# 复制应用代码
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COPY . .
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# 创建必要的目录
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RUN mkdir -p /app/output /app/temp /app/assets
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# 暴露端口
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# - 8000: FastAPI
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# - 8503: Streamlit（docker-compose.yml 中运行在 8503；8502 是历史 runtime 标识）
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EXPOSE 8000 8503
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# 默认命令
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CMD ["uvicorn", "api.main:app", "--host", "0.0.0.0", "--port", "8000"]
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138
api/main.py
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138
api/main.py
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"""
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Video Flow API - FastAPI Backend
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前后端分离架构的后端服务
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端口：8000（与 Streamlit 8503 共存；8502 为历史 runtime/素材目录标识）
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"""
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import os
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import sys
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import logging
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from pathlib import Path
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from contextlib import asynccontextmanager
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.staticfiles import StaticFiles
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# 确保项目根目录在 path 中
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PROJECT_ROOT = Path(__file__).parent.parent
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sys.path.insert(0, str(PROJECT_ROOT))
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import config
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from api.routes import projects, editor, assets, compose
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# 配置日志
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger(__name__)
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""应用生命周期管理"""
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logger.info("Video Flow API 启动中...")
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logger.info(f"项目根目录: {PROJECT_ROOT}")
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logger.info(f"输出目录: {config.OUTPUT_DIR}")
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logger.info(f"临时目录: {config.TEMP_DIR}")
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yield
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logger.info("Video Flow API 关闭中...")
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# 创建 FastAPI 应用
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app = FastAPI(
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title="Video Flow API",
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description="视频工作流后端 API - 支持项目管理、素材处理、视频编辑与合成",
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version="1.0.0",
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lifespan=lifespan,
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docs_url="/api/docs",
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redoc_url="/api/redoc",
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openapi_url="/api/openapi.json"
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)
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# CORS 配置 - 允许 React 前端访问
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app.add_middleware(
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CORSMiddleware,
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allow_origins=[
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"http://localhost:3000", # React dev server
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"http://localhost:5173", # Vite dev server
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"http://127.0.0.1:3000",
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"http://127.0.0.1:5173",
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],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# 挂载静态文件目录（用于访问生成的视频/图片）
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app.mount("/static/output", StaticFiles(directory=str(config.OUTPUT_DIR)), name="output")
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app.mount("/static/temp", StaticFiles(directory=str(config.TEMP_DIR)), name="temp")
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app.mount("/static/assets", StaticFiles(directory=str(config.ASSETS_DIR)), name="assets")
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# Legacy mounts（8502 runtime 产物，宿主机目录通过 docker-compose 挂载到容器内）
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try:
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app.mount("/static/legacy-temp", StaticFiles(directory="/legacy/temp"), name="legacy-temp")
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app.mount("/static/legacy-output", StaticFiles(directory="/legacy/output"), name="legacy-output")
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except Exception:
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# 本地非 docker 环境可能不存在这些目录
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pass
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# 注册路由
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app.include_router(projects.router, prefix="/api/projects", tags=["Projects"])
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app.include_router(editor.router, prefix="/api/editor", tags=["Editor"])
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app.include_router(assets.router, prefix="/api/assets", tags=["Assets"])
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app.include_router(compose.router, prefix="/api/compose", tags=["Compose"])
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@app.get("/api/health")
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async def health_check():
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"""健康检查"""
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return {
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"status": "ok",
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"service": "video-flow-api",
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"version": "1.0.0"
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}
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@app.get("/api/config")
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async def get_config():
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"""获取前端所需的配置信息"""
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return {
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"video_settings": config.VIDEO_SETTINGS,
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"available_voices": [
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{"id": config.VOLC_TTS_DEFAULT_VOICE, "name": "三通永 (默认)"},
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{"id": "zh_female_meilinvyou_saturn_bigtts", "name": "美丽女友"},
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],
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"available_bgm": _list_bgm_files(),
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}
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def _list_bgm_files():
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"""列出可用的 BGM 文件"""
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bgm_dir = config.ASSETS_DIR / "bgm"
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if not bgm_dir.exists():
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return []
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bgm_files = []
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for f in bgm_dir.iterdir():
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if f.suffix.lower() in ['.mp3', '.mp4', '.m4a', '.wav']:
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bgm_files.append({
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"id": f.name,
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"name": f.stem,
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"path": f"/static/assets/bgm/{f.name}"
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})
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return bgm_files
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(
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"api.main:app",
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host="0.0.0.0",
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port=8000,
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reload=True,
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log_level="info"
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)
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10
config.py
10
config.py
@@ -15,9 +15,13 @@ load_dotenv()
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VOLC_API_KEY = os.getenv("VOLC_API_KEY", "05aed9c1-f5e6-487b-9273-fe7d6be51957")
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VOLC_BASE_URL = os.getenv("VOLC_BASE_URL", "https://ark.cn-beijing.volces.com/api/v3")
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# OpenAI (for GPT models)
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
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OPENAI_BASE_URL = os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1")
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# Models (Updated with User-Provided Endpoint IDs)
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# LLM: Doubao Pro 1.5 (Using provided brain/vision endpoint)
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BRAIN_MODEL_ID = os.getenv("BRAIN_MODEL_ID", "ep-20251203231055-dpsp7")
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BRAIN_MODEL_ID = os.getenv("BRAIN_MODEL_ID", "ep-20251203231055-dpsp7")
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# Vision: Doubao Vision Pro 1.5
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VISION_MODEL_ID = os.getenv("VISION_MODEL_ID", "ep-20251203232121-xjt2s")
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# Image: Doubao Image (Updated to user provided model)
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@@ -115,8 +119,8 @@ FONTS_DIR.mkdir(exist_ok=True)
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# Database Configuration
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# ============================================================
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# Format: postgresql://user:password@host:port/dbname
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# Default to SQLite if not provided
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DB_CONNECTION_STRING = os.getenv("DB_CONNECTION_STRING", f"sqlite:///{BASE_DIR}/video_flow.db")
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# Default to SQLite if not provided OR provided as empty string
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DB_CONNECTION_STRING = os.getenv("DB_CONNECTION_STRING") or f"sqlite:///{BASE_DIR}/video_flow.db"
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# ============================================================
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# Font Settings (字体配置)
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149
docker-compose.yml
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149
docker-compose.yml
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version: '3.8'
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# Video Flow - Docker Compose 配置
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# 支持水平扩展的视频处理服务
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services:
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# ============================================================
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# Redis - 消息队列和缓存
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# ============================================================
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redis:
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image: redis:7-alpine
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ports:
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- "6379:6379"
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volumes:
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- redis_data:/data
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command: redis-server --appendonly yes
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healthcheck:
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test: ["CMD", "redis-cli", "ping"]
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interval: 10s
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timeout: 5s
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retries: 5
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restart: unless-stopped
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# ============================================================
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# FastAPI Backend - API 服务
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# ============================================================
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api:
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build:
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context: .
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dockerfile: Dockerfile
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ports:
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- "8000:8000"
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volumes:
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- ./modules:/app/modules:ro
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- ./api:/app/api:ro
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- ./config.py:/app/config.py:ro
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- ./assets:/app/assets
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- ./output:/app/output
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- ./temp:/app/temp
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- ./video_flow.db:/app/video_flow.db
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# 方案A：通过 Unix Socket 连接宿主机 Postgres（不暴露 5432）
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- /var/run/postgresql:/var/run/postgresql
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# 复用 8502（/root/video-flow）生成的历史素材
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- /root/video-flow/temp:/legacy/temp:ro
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- /root/video-flow/output:/legacy/output:ro
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environment:
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- REDIS_URL=redis://redis:6379/0
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- PYTHONUNBUFFERED=1
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# 8503 读写 8502 的 Postgres（从 .env 注入，避免写死密码）
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- DB_CONNECTION_STRING=${VIDEO_FLOW_DB_CONNECTION_STRING}
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depends_on:
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redis:
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condition: service_healthy
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command: uvicorn api.main:app --host 0.0.0.0 --port 8000
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8000/api/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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restart: unless-stopped
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# ============================================================
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# Celery Worker - 视频处理 Worker
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# 可以通过 docker-compose scale worker=N 水平扩展
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# ============================================================
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worker:
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build:
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context: .
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dockerfile: Dockerfile
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volumes:
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- ./modules:/app/modules:ro
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- ./api:/app/api:ro
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- ./config.py:/app/config.py:ro
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- ./bin:/app/bin:ro
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- ./assets:/app/assets
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- ./output:/app/output
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- ./temp:/app/temp
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- ./video_flow.db:/app/video_flow.db
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- /var/run/postgresql:/var/run/postgresql
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- /root/video-flow/temp:/legacy/temp:ro
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- /root/video-flow/output:/legacy/output:ro
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environment:
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- REDIS_URL=redis://redis:6379/0
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- PYTHONUNBUFFERED=1
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- C_FORCE_ROOT=1
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- DB_CONNECTION_STRING=${VIDEO_FLOW_DB_CONNECTION_STRING}
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depends_on:
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redis:
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condition: service_healthy
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command: celery -A api.celery_app worker --loglevel=info --concurrency=2 -Q default,video,audio
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restart: unless-stopped
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deploy:
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# 生产环境可以增加副本数
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replicas: 1
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resources:
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limits:
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cpus: '2'
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memory: 4G
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# ============================================================
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# React Frontend - 前端服务 (生产环境)
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# ============================================================
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web:
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build:
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context: ./web
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dockerfile: Dockerfile
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ports:
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- "3000:80"
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depends_on:
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- api
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restart: unless-stopped
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# ============================================================
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# Streamlit - 原有调试界面 (保留在 8503)
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# 连接到 8502 的数据目录，复用历史素材
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# ============================================================
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streamlit:
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build:
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context: .
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dockerfile: Dockerfile
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ports:
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# 默认对外保持 8502（兼容历史入口）；容器内仍运行在 8503
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- "${STREAMLIT_PORT:-8502}:8503"
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volumes:
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- ./app.py:/app/app.py:ro
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- ./modules:/app/modules:ro
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- ./config.py:/app/config.py:ro
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- ./assets:/app/assets
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- ./output:/app/output
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# 挂载 8502 服务的 temp 目录，复用历史项目数据
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- /opt/gloda-factory/temp:/app/temp
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- ./video_flow.db:/app/video_flow.db
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- /var/run/postgresql:/var/run/postgresql
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- /root/video-flow/temp:/legacy/temp:ro
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- /root/video-flow/output:/legacy/output:ro
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environment:
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- PYTHONUNBUFFERED=1
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- DB_CONNECTION_STRING=${VIDEO_FLOW_DB_CONNECTION_STRING}
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- WEB_BASE_URL=${WEB_BASE_URL}
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command: streamlit run app.py --server.port 8503 --server.address 0.0.0.0
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restart: unless-stopped
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volumes:
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redis_data:
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networks:
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default:
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name: video-flow-network
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@@ -21,7 +21,8 @@ echo ""
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echo "📌 访问地址："
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echo " - 视频编辑器: http://localhost:3000"
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echo " - API 文档: http://localhost:8000/api/docs"
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echo " - 工作流控制台: http://localhost:8503"
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STREAMLIT_PORT="${STREAMLIT_PORT:-8502}"
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echo " - 工作流控制台: http://localhost:${STREAMLIT_PORT}"
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echo ""
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echo "📊 查看日志: docker-compose logs -f"
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echo "🔧 扩展 Worker: docker-compose scale worker=3"
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