# docker version version: "3" services: keycloak: image: quay.io/keycloak/keycloak:${KEYCLOAK_VERSION-22.0.0} command: ["start-dev", "--import-realm", "--http-port", "8088"] environment: KC_DB: postgres KC_DB_URL_HOST: keycloak_postgres KC_DB_URL_DATABASE: ${POSTGRES_DB_NAME:-keycloak} KC_DB_PASSWORD: ${POSTGRES_PASSWORD:-postgres} KC_DB_USERNAME: ${POSTGRES_USERNAME:-postgres} KC_DB_SCHEMA: ${KC_DB_SCHEMA:-public} KC_HEALTH_ENABLED: 'true' KEYCLOAK_ADMIN: ${KEYCLOAK_ADMIN-admin} KEYCLOAK_ADMIN_PASSWORD: ${KEYCLOAK_ADMIN_PASSWORD-admin} volumes: - ./conf/keycloak_conf:/opt/keycloak/data/import ports: - "8088:8088" depends_on: keycloak_postgres: condition: service_healthy networks: jan_community: ipv4_address: 172.20.0.9 keycloak_postgres: image: postgres:15 command: postgres -c 'max_connections=200' && postgres -c 'shared_buffers=24MB' environment: # Environment Variables expecially for Postgres POSTGRES_DB: ${POSTGRES_DB_NAME:-keycloak} POSTGRES_USER: ${POSTGRES_USERNAME:-postgres} POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-postgres} PGDATA: /data/postgres PGPORT: ${POSTGRES_PORT:-5432} healthcheck: test: "exit 0" ports: - ${POSTGRES_PORT:-5432}:${POSTGRES_PORT:-5432} networks: jan_community: ipv4_address: 172.20.0.10 postgres: image: postgres:15 restart: always env_file: - conf/sample.env_app-backend-postgres networks: jan_community: ipv4_address: 172.20.0.11 graphql-engine: image: hasura/graphql-engine:v2.31.0.cli-migrations-v3 ports: - "8080:8080" restart: always env_file: - conf/sample.env_app-backend volumes: - ./app-backend/hasura/migrations:/migrations - ./app-backend/hasura/metadata:/metadata depends_on: data-connector-agent: condition: service_healthy healthcheck: test: ["CMD", "curl", "-f", "http://localhost:8080/healthz"] interval: 30s timeout: 10s retries: 10 networks: jan_community: ipv4_address: 172.20.0.12 hasura-seed-apply: image: hasura/graphql-engine:v2.31.0.cli-migrations-v3 entrypoint: [""] command: ["/bin/sh", "-c", "hasura-cli seed apply --all-databases"] env_file: - conf/sample.env_app-backend volumes: - ./app-backend/hasura/config.yaml:/config.yaml - ./app-backend/hasura/seeds:/seeds depends_on: graphql-engine: condition: service_healthy extra_hosts: - "localhost:172.20.0.12" networks: jan_community: worker: build: context: ./app-backend/worker dockerfile: ./Dockerfile restart: always environment: - "NODE_ENV=development" volumes: - ./app-backend/worker:/worker ports: - "8787:8787" networks: jan_community: ipv4_address: 172.20.0.13 data-connector-agent: image: hasura/graphql-data-connector:v2.31.0 restart: always ports: - 8081:8081 environment: QUARKUS_LOG_LEVEL: ERROR # FATAL, ERROR, WARN, INFO, DEBUG, TRACE ## https://quarkus.io/guides/opentelemetry#configuration-reference QUARKUS_OPENTELEMETRY_ENABLED: "false" ## QUARKUS_OPENTELEMETRY_TRACER_EXPORTER_OTLP_ENDPOINT: http://jaeger:4317 healthcheck: test: ["CMD", "curl", "-f", "http://localhost:8081/api/v1/athena/health"] interval: 5s timeout: 10s retries: 5 start_period: 5s networks: jan_community: ipv4_address: 172.20.0.14 web: build: context: ./web-client dockerfile: ./dev.Dockerfile container_name: jan_web restart: always volumes: - ./web-client/:/app - /app/node_modules - /app/.next env_file: - conf/sample.env_web-client ports: - "3000:3000" environment: NODE_ENV: development extra_hosts: - "localhost:172.20.0.9" networks: jan_community: ipv4_address: 172.20.0.15 # Service to run the Llama web application. llm: image: ghcr.io/abetlen/llama-cpp-python@sha256:b6d21ff8c4d9baad65e1fa741a0f8c898d68735fff3f3cd777e3f0c6a1839dd4 # Mount the directory that contains the downloaded model. volumes: - ./jan-inference/llm/models:/models ports: - 8000:8000 environment: # Specify the path to the model for the web application. MODEL: /models/${LLM_MODEL_FILE} PYTHONUNBUFFERED: 1 # Restart policy configuration restart: on-failure # Specifies that this service should start only after wait-for-downloader has completed successfully. networks: jan_community: ipv4_address: 172.20.0.18 sd-downloader: build: context: ./jan-inference/sd/ dockerfile: compile.Dockerfile # The command extracts the model filename from MODEL_URL and downloads it if it doesn't exist. command: /bin/sh -c "if [ ! -f /models/*.bin ]; then python /sd.cpp/sd_cpp/models/convert.py --out_type q4_0 --out_file /models/${SD_MODEL_FILE}.q4_0.bin /models/${SD_MODEL_FILE}; fi" # Mount a local directory to store the downloaded model. volumes: - ./jan-inference/sd/models:/models networks: jan_community: ipv4_address: 172.20.0.19 # Service to run the SD web application. sd: build: context: ./jan-inference/sd/ dockerfile: inference.Dockerfile # Mount the directory that contains the downloaded model. volumes: - ./jan-inference/sd/models:/models - ./jan-inference/sd/output/:/serving/output command: /bin/bash -c "python -m uvicorn main:app --proxy-headers --host 0.0.0.0 --port 8000" environment: # Specify the path to the model for the web application. BASE_URL: http://0.0.0.0:8000 MODEL_NAME: ${SD_MODEL_FILE}.q4_0.bin MODEL_DIR: "/models" SD_PATH: "/sd" PYTHONUNBUFFERED: 1 ports: - 8001:8000 # Restart policy configuration restart: on-failure # Specifies that this service should start only after wait-for-downloader has completed successfully. depends_on: sd-downloader: condition: service_completed_successfully networks: jan_community: ipv4_address: 172.20.0.21 # Service for Traefik, a modern HTTP reverse proxy and load balancer. # traefik: # image: traefik:v2.10 # ports: # # Map port 80 in the container to port 80 on the host. # - "80:80" # # Map port 8080 in the container (Traefik's dashboard) to port 8080 on the host. # - "8080:8080" # # Mount the Docker socket to allow Traefik to listen to Docker's API. # volumes: # - /var/run/docker.sock:/var/run/docker.sock:ro # - ./traefik/traefik.yml:/traefik.yml:ro # - ./traefik/config.yml:/config.yml:ro # networks: # jan_community: # ipv4_address: 172.20.0.22 networks: jan_community: driver: bridge ipam: driver: default config: - subnet: 172.20.0.0/16