video-transcoding/docker-compose.yml at main · vector17002/video-transcoding · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
services:
  # ── Redis ────────────────────────────────────────────────
  redis:
    image: redis:7-alpine
    ports:
      - "6379:6379"
    volumes:
      - redis_data:/data
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 5s
      timeout: 3s
      retries: 5

  # ── API Server ───────────────────────────────────────────
  api:
    build:
      context: ./server
      dockerfile: Dockerfile
      target: api
    ports:
      - "${PORT:-8080}:${PORT:-8080}"
    env_file:
      - ./server/.env
    environment:
      - IOREDIS_URL=redis://redis:6379
    depends_on:
      redis:
        condition: service_healthy
    restart: unless-stopped

  # ── Transcode Worker (FFmpeg — HLS + thumbnails) ─────────
  worker:
    build:
      context: ./server
      dockerfile: Dockerfile
      target: worker
    env_file:
      - ./server/.env
    environment:
      - IOREDIS_URL=redis://redis:6379
    depends_on:
      redis:
        condition: service_healthy
    restart: unless-stopped
    deploy:
      resources:
        limits:
          memory: 2G

  # ── AI Worker (Whisper transcription & Gemini summarization) ───
  ai-worker:
    build:
      context: ./server
      dockerfile: Dockerfile
      target: ai-worker
      args:
        # Change to tiny/small/medium/large as needed
        WHISPER_MODEL: base
    env_file:
      - ./server/.env
    environment:
      - IOREDIS_URL=redis://redis:6379
    depends_on:
      redis:
        condition: service_healthy
    restart: unless-stopped
    deploy:
      resources:
        limits:
          # faster-whisper base model needs ~1 GB; bump for larger models
          memory: 2G


volumes:
  redis_data: