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docker-compose.yml
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77 lines (73 loc) · 2.06 KB
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version: '3.8'
# QueryGym Docker Compose - Uses pre-built images from GitHub Container Registry
# No building required - just pull and run!
services:
# GPU-enabled version (default)
querygym:
image: ghcr.io/ls3-lab/querygym:latest
container_name: querygym
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
environment:
- NVIDIA_VISIBLE_DEVICES=all
- OPENAI_API_KEY=${OPENAI_API_KEY}
- OPENAI_BASE_URL=${OPENAI_BASE_URL:-https://api.openai.com/v1}
volumes:
- ./data:/workspace/data
- ./outputs:/workspace/outputs
- ./notebooks:/workspace/notebooks
ports:
- "8888:8888"
stdin_open: true
tty: true
command: /bin/bash
# CPU-only version (lightweight) - Uncomment if you don't have GPU
# querygym-cpu:
# image: ghcr.io/ls3-lab/querygym:cpu
# container_name: querygym-cpu
# environment:
# - OPENAI_API_KEY=${OPENAI_API_KEY}
# - OPENAI_BASE_URL=${OPENAI_BASE_URL:-https://api.openai.com/v1}
# volumes:
# - ./data:/workspace/data
# - ./outputs:/workspace/outputs
# - ./notebooks:/workspace/notebooks
# ports:
# - "8889:8888"
# stdin_open: true
# tty: true
# command: /bin/bash
# Jupyter notebook server (GPU-enabled)
jupyter:
image: ghcr.io/ls3-lab/querygym:latest
container_name: querygym-jupyter
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
environment:
- NVIDIA_VISIBLE_DEVICES=all
- OPENAI_API_KEY=${OPENAI_API_KEY}
- OPENAI_BASE_URL=${OPENAI_BASE_URL:-https://api.openai.com/v1}
volumes:
- ./data:/workspace/data
- ./outputs:/workspace/outputs
- ./notebooks:/workspace/notebooks
ports:
- "8888:8888"
command: >
jupyter notebook
--ip=0.0.0.0
--port=8888
--no-browser
--allow-root
--NotebookApp.token=''
--NotebookApp.password=''