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sbdh11/fraudwatch

sourceHugging Faceupdated 5mo agoView on Hugging Face
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docker-compose.yml75 linesDownload Raw Back to root
1name: fraud-detection2 3services:4  db:5    image: postgres:16-alpine6    environment:7      POSTGRES_USER: ${DB_USER:-app}8      POSTGRES_PASSWORD: ${DB_PASSWORD:-app}9      POSTGRES_DB: ${DB_NAME:-frauddetect}10    volumes:11      - pgdata:/var/lib/postgresql/data12    healthcheck:13      test: ["CMD-SHELL", "pg_isready -U ${DB_USER:-app} -d ${DB_NAME:-frauddetect}"]14      interval: 5s15      timeout: 5s16      retries: 2017    ports:18      - "${DB_PORT:-5544}:5432"19 20  mlflow:21    image: ghcr.io/mlflow/mlflow:v2.16.222    command: >23      mlflow server24      --host 0.0.0.0 --port 500025      --backend-store-uri sqlite:////mlruns/mlflow.db26      --default-artifact-root /mlruns/artifacts27    volumes:28      - mlruns:/mlruns29    healthcheck:30      test: ["CMD-SHELL", "python -c \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:5000/health').status==200 else 1)\""]31      interval: 10s32      timeout: 5s33      retries: 2034      start_period: 20s35    ports:36      - "${MLFLOW_PORT:-5500}:5000"37 38  backend:39    build: ./backend40    environment:41      DATABASE_URL: postgresql+asyncpg://${DB_USER:-app}:${DB_PASSWORD:-app}@db:5432/${DB_NAME:-frauddetect}42      MLFLOW_TRACKING_URI: http://mlflow:500043      MLFLOW_EXPERIMENT: fraud-detection44      SIM_ENABLED: "true"45      SIM_INTERVAL_SECONDS: "1.5"46      TRAIN_ON_STARTUP: "true"47      TRAIN_ROWS: "30000"48      CORS_ORIGINS: "*"49    depends_on:50      db:51        condition: service_healthy52      mlflow:53        condition: service_started54    volumes:55      - artifacts:/app/app/ml/artifacts56    ports:57      - "${BACKEND_PORT:-8008}:8000"58 59  frontend:60    build:61      context: ./frontend62      args:63        NEXT_PUBLIC_API_BASE: "http://localhost:${BACKEND_PORT:-8008}/api"64    environment:65      NEXT_PUBLIC_API_BASE: "http://localhost:${BACKEND_PORT:-8008}/api"66    depends_on:67      - backend68    ports:69      - "${FRONTEND_PORT:-3030}:3000"70 71volumes:72  pgdata:73  mlruns:74  artifacts:75