docker-compose-cuda-gguf.yml

version: '3.6'

services:
  llama-gpt-api-cuda-gguf:
    build:
      context: ./cuda
      dockerfile: gguf.Dockerfile
    restart: on-failure
    volumes:
      - './models:/models'
      - './cuda:/cuda'
    ports:
      - 3001:8000
    environment:
      MODEL: '/models/${MODEL_NAME:-code-llama-2-7b-chat.gguf}'
      MODEL_DOWNLOAD_URL: '${MODEL_DOWNLOAD_URL:-https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-GGUF/resolve/main/codellama-7b-instruct.Q4_K_M.gguf}'
      N_GQA: '${N_GQA:-1}'
      USE_MLOCK: 1
    cap_add:
      - IPC_LOCK
      - SYS_RESOURCE
    command: '/bin/sh /cuda/run.sh'
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]

  llama-gpt-ui:
    # TODO: Use this image instead of building from source after the next release
    # image: 'ghcr.io/getumbrel/llama-gpt-ui:latest'
    build:
      context: ./ui
      dockerfile: Dockerfile
    ports:
      - 3000:3000
    restart: on-failure
    environment:
      - 'OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXX'
      - 'OPENAI_API_HOST=http://llama-gpt-api-cuda-gguf:8000'
      - 'DEFAULT_MODEL=/models/${MODEL_NAME:-code-llama-2-7b-chat.gguf}'
      - 'NEXT_PUBLIC_DEFAULT_SYSTEM_PROMPT=${DEFAULT_SYSTEM_PROMPT:-"You are a helpful and friendly AI assistant. Respond very concisely."}'
      - 'WAIT_HOSTS=llama-gpt-api-cuda-gguf:8000'
      - 'WAIT_TIMEOUT=${WAIT_TIMEOUT:-3600}'