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docker-compose-gpu.yml
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docker-compose-gpu.yml
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version: '2.3'
services:
michaniki_client:
build:
context: ./src
dockerfile: Dockerfile-gpu
runtime: nvidia
ports:
- "3031:3031"
environment:
- PORT=3031
- FLAS_APP=app/__init__.py
- FLASK_DEBUG=1
- REDIS_URL="redis://redis"
- REDIS_PORT=6379
- AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}
- AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}
volumes:
- ./src:/opt/src
command: ./entryPoint.sh
depends_on:
- redis
networks:
- michaniki
inference_server:
build:
context: ./src
dockerfile: Dockerfile-gpu
runtime: nvidia
environment:
- REDIS_URL="redis://redis"
- REDIS_PORT=6379
- AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}
- AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}
command: ['python', 'app/models/InceptionV3/inception_inference_server.py']
volumes:
- ./src:/opt/src
networks:
- michaniki
depends_on:
- michaniki_client
- redis
sentiment_inference_server:
build:
context: ./src
dockerfile: Dockerfile-sentiment
runtime: nvidia
environment:
- REDIS_URL="redis://redis"
- REDIS_PORT=6379
- AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}
- AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}
command: ['python', 'app/models/SentimentV1/sentiment_infer_server.py']
volumes:
- ./src:/opt/src
networks:
- michaniki
depends_on:
- michaniki_client
- redis
celery_worker:
build:
context: ./src
dockerfile: Dockerfile-gpu
runtime: nvidia
command: ['celery', '-A', 'app.celeryapp:michaniki_celery_app', 'worker', '-l', 'info']
volumes:
- ./src:/opt/src
networks:
- michaniki
depends_on:
- michaniki_client
environment:
- AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}
- AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}
- DB_HOST=db
- DB_USERNAME=root
- DB_PASSWORD=michaniki
- DB_NAME=michanikidb
- BROKER_URL=redis://redis:6379/0
redis:
image: redis:4.0.5-alpine
command: ["redis-server", "--appendonly", "yes"]
hostname: redis
networks:
- michaniki
networks:
michaniki: