jarvis-home/compose.yaml

x-skill-worker-env: &skill-worker-env
  JARVIS_MASTER_URL: http://jarvis:8080
  JARVIS_ENROLLMENT_TOKEN: ${JARVIS_MESH_ENROLLMENT_TOKEN:-change-this-enrollment-token}
  JARVIS_WORKER_ADDR: :8090
  JARVIS_SKILLS_DIR: /skills
  JARVIS_WORKER_WORK_DIR: /work
  JARVIS_WORKER_ALLOW_SYSTEM_EXEC: "true"
  JARVIS_WORKER_MAX_OUTPUT_KB: 1024
  TZ: Europe/Berlin

services:
  jarvis:
    build:
      context: .
      dockerfile: Dockerfile
    ports:
      - "8080:8080"
    volumes:
      - ./data:/app/data
      - ./models:/models:ro
      - ./local-tools:/tools:ro
      - ./skills:/app/skills:ro
      # Docker Engine control. This socket grants host-level Docker control;
      # JARVIS only exposes start/stop/restart for explicitly labelled containers.
      - /var/run/docker.sock:/var/run/docker.sock
    environment:
      JARVIS_ADDR: :8080
      JARVIS_DATA: /app/data/store.json
      JARVIS_RAG_DATA: /app/data/rag.json
      JARVIS_WAKE_WORD: jarvis
      JARVIS_TIMEZONE: Europe/Berlin
      JARVIS_SKILLS_DIR: /app/skills
      JARVIS_SKILLS_ENABLED: "true"
      # External runtime code belongs in Skill Mesh workers by default.
      JARVIS_SKILL_PROCESS_ENABLED: "false"
      JARVIS_SKILL_ALLOW_SYSTEM_EXEC: "false"
      JARVIS_SKILL_MAX_TIMEOUT_MS: 30000
      JARVIS_SKILL_MAX_OUTPUT_KB: 1024
      JARVIS_MESH_ENABLED: "true"
      JARVIS_MESH_ENROLLMENT_TOKEN: ${JARVIS_MESH_ENROLLMENT_TOKEN:-change-this-enrollment-token}
      JARVIS_MESH_LEASE_SECONDS: 30
      JARVIS_MESH_INVOKE_TIMEOUT_MS: 30000
      JARVIS_DOCKER_CONTROLLER_ENABLED: "true"
      JARVIS_DOCKER_SOCKET: /var/run/docker.sock
      JARVIS_DOCKER_SKILL_LABEL: com.jarvis.skill-service
      JARVIS_DOCKER_SKILL_LABEL_VALUE: "true"
      TZ: Europe/Berlin
      OLLAMA_URL: http://ollama:11434
      OLLAMA_MODEL: auto
      OLLAMA_EMBED_MODEL: auto
      TASK_SCOUT_INTERVAL: 2m
      HOME_AUTOMATION_INTERVAL: 1m
      KANBAN_AI_INTERVAL: 5m
      JARVIS_DEBUG_TRACE: "true"
      JARVIS_DEBUG_DIR: /app/data/debug
      JARVIS_DEBUG_MAX_MB: 25
      JARVIS_DEBUG_KEEP_FILES: 4
      VOICE_FFMPEG_BIN: ffmpeg
      VOICE_WHISPER_BIN: /usr/local/bin/whisper-cli
      VOICE_WHISPER_MODEL: /models/ggml-small.bin
      VOICE_LANGUAGE: de
      VOICE_PIPER_BIN: /tools/piper
      VOICE_PIPER_MODEL: /models/de_DE-thorsten-medium.onnx
      LD_LIBRARY_PATH: /tools:/tools/lib
    depends_on:
      - ollama

  ollama:
    image: ollama/ollama:latest
    ports:
      - "11434:11434"
    volumes:
      - ollama-data:/root/.ollama

  skill-python:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.python
    profiles: ["skill-workers"]
    depends_on: [jarvis]
    volumes: ["./skills/python:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: python-main
      JARVIS_WORKER_RUNTIME: python
      JARVIS_WORKER_RUNTIME_VERSION: "3.13"
      JARVIS_WORKER_PUBLIC_URL: http://skill-python:8090
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: python
      com.jarvis.worker-name: python-main

  skill-node:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.node
    profiles: ["skill-workers"]
    depends_on: [jarvis]
    volumes: ["./skills/node:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: node-main
      JARVIS_WORKER_RUNTIME: node
      JARVIS_WORKER_RUNTIME_VERSION: "22"
      JARVIS_WORKER_PUBLIC_URL: http://skill-node:8090
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: node
      com.jarvis.worker-name: node-main

  skill-go:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.golang
    profiles: ["skill-workers"]
    depends_on: [jarvis]
    volumes: ["./skills/go:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: go-main
      JARVIS_WORKER_RUNTIME: go
      JARVIS_WORKER_RUNTIME_VERSION: "1.23"
      JARVIS_WORKER_PUBLIC_URL: http://skill-go:8090
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: go
      com.jarvis.worker-name: go-main

  skill-rust:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.rust
    profiles: ["skill-workers"]
    depends_on: [jarvis]
    volumes: ["./skills/rust:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: rust-main
      JARVIS_WORKER_RUNTIME: rust
      JARVIS_WORKER_RUNTIME_VERSION: stable
      JARVIS_WORKER_PUBLIC_URL: http://skill-rust:8090
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: rust
      com.jarvis.worker-name: rust-main

  skill-c:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.c
    profiles: ["skill-workers"]
    depends_on: [jarvis]
    volumes: ["./skills/c:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: c-main
      JARVIS_WORKER_RUNTIME: c
      JARVIS_WORKER_RUNTIME_VERSION: gcc
      JARVIS_WORKER_PUBLIC_URL: http://skill-c:8090
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: c
      com.jarvis.worker-name: c-main

  skill-cpp:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.cpp
    profiles: ["skill-workers"]
    depends_on: [jarvis]
    volumes: ["./skills/cpp:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: cpp-main
      JARVIS_WORKER_RUNTIME: cpp
      JARVIS_WORKER_RUNTIME_VERSION: g++
      JARVIS_WORKER_PUBLIC_URL: http://skill-cpp:8090
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: cpp
      com.jarvis.worker-name: cpp-main

  skill-csharp:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.csharp
    profiles: ["skill-workers"]
    depends_on: [jarvis]
    volumes: ["./skills/csharp:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: csharp-main
      JARVIS_WORKER_RUNTIME: csharp
      JARVIS_WORKER_RUNTIME_VERSION: ".NET 8"
      JARVIS_WORKER_PUBLIC_URL: http://skill-csharp:8090
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: csharp
      com.jarvis.worker-name: csharp-main


  # --- Home Control integration workers (1 container = 1 integration) ---
  # Start all with: docker compose --profile home-skills up -d --build
  skill-hue:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.python
    profiles: ["home-skills"]
    depends_on: [jarvis]
    volumes: ["./skills/python/philips-hue:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: hue
      JARVIS_WORKER_RUNTIME: python
      JARVIS_WORKER_RUNTIME_VERSION: "3.13"
      JARVIS_WORKER_PUBLIC_URL: http://skill-hue:8090
      HUE_BRIDGE_URL: ${HUE_BRIDGE_URL:-}
      HUE_APP_KEY: ${HUE_APP_KEY:-}
      HUE_VERIFY_TLS: ${HUE_VERIFY_TLS:-false}
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: python
      com.jarvis.worker-name: hue
      com.jarvis.integration: philips-hue

  skill-unifi-network:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.python
    profiles: ["home-skills"]
    depends_on: [jarvis]
    volumes: ["./skills/python/unifi-network:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: unifi-network
      JARVIS_WORKER_RUNTIME: python
      JARVIS_WORKER_RUNTIME_VERSION: "3.13"
      JARVIS_WORKER_PUBLIC_URL: http://skill-unifi-network:8090
      UNIFI_NETWORK_URL: ${UNIFI_NETWORK_URL:-}
      UNIFI_API_KEY: ${UNIFI_API_KEY:-}
      UNIFI_VERIFY_TLS: ${UNIFI_VERIFY_TLS:-false}
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: python
      com.jarvis.worker-name: unifi-network
      com.jarvis.integration: unifi-network

  skill-unifi-protect:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.python
    profiles: ["home-skills"]
    depends_on: [jarvis]
    volumes: ["./skills/python/unifi-protect:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: unifi-protect
      JARVIS_WORKER_RUNTIME: python
      JARVIS_WORKER_RUNTIME_VERSION: "3.13"
      JARVIS_WORKER_PUBLIC_URL: http://skill-unifi-protect:8090
      UNIFI_PROTECT_URL: ${UNIFI_PROTECT_URL:-}
      UNIFI_API_KEY: ${UNIFI_API_KEY:-}
      UNIFI_VERIFY_TLS: ${UNIFI_VERIFY_TLS:-false}
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: python
      com.jarvis.worker-name: unifi-protect
      com.jarvis.integration: unifi-protect

  skill-proxmox:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.python
    profiles: ["home-skills"]
    depends_on: [jarvis]
    volumes: ["./skills/python/proxmox-ve:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: proxmox
      JARVIS_WORKER_RUNTIME: python
      JARVIS_WORKER_RUNTIME_VERSION: "3.13"
      JARVIS_WORKER_PUBLIC_URL: http://skill-proxmox:8090
      PROXMOX_BASE_URL: ${PROXMOX_BASE_URL:-}
      PROXMOX_TOKEN_ID: ${PROXMOX_TOKEN_ID:-}
      PROXMOX_TOKEN_SECRET: ${PROXMOX_TOKEN_SECRET:-}
      PROXMOX_VERIFY_TLS: ${PROXMOX_VERIFY_TLS:-false}
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: python
      com.jarvis.worker-name: proxmox
      com.jarvis.integration: proxmox

  skill-network-tools:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.python
    profiles: ["home-skills"]
    depends_on: [jarvis]
    volumes: ["./skills/python/network-tools:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: network-tools
      JARVIS_WORKER_RUNTIME: python
      JARVIS_WORKER_RUNTIME_VERSION: "3.13"
      JARVIS_WORKER_PUBLIC_URL: http://skill-network-tools:8090
      WOL_BROADCAST: ${WOL_BROADCAST:-255.255.255.255}
      WOL_PORT: ${WOL_PORT:-9}
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: python
      com.jarvis.worker-name: network-tools
      com.jarvis.integration: network-tools

  skill-ntfy:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.python
    profiles: ["home-skills"]
    depends_on: [jarvis]
    volumes: ["./skills/python/ntfy:/skills:ro"]
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: ntfy
      JARVIS_WORKER_RUNTIME: python
      JARVIS_WORKER_RUNTIME_VERSION: "3.13"
      JARVIS_WORKER_PUBLIC_URL: http://skill-ntfy:8090
      NTFY_BASE_URL: ${NTFY_BASE_URL:-https://ntfy.sh}
      NTFY_TOKEN: ${NTFY_TOKEN:-}
      NTFY_DEFAULT_TOPIC: ${NTFY_DEFAULT_TOPIC:-}
      NTFY_VERIFY_TLS: ${NTFY_VERIFY_TLS:-true}
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: python
      com.jarvis.worker-name: ntfy
      com.jarvis.integration: ntfy

  # Dockge upstream does not currently expose a stable authenticated management
  # API. This dedicated worker therefore operates on the same Compose stack
  # directory and Docker Engine. It is intentionally isolated from the master.
  skill-dockge:
    build:
      context: .
      dockerfile: workers/docker/Dockerfile.dockge
    profiles: ["home-skills"]
    depends_on: [jarvis]
    volumes:
      - ./skills/python/dockge-compose:/skills:ro
      - /var/run/docker.sock:/var/run/docker.sock
      - ${DOCKGE_STACKS_DIR:-/opt/stacks}:${DOCKGE_STACKS_DIR:-/opt/stacks}:ro
    environment:
      <<: *skill-worker-env
      JARVIS_WORKER_NAME: dockge
      JARVIS_WORKER_RUNTIME: python-docker
      JARVIS_WORKER_RUNTIME_VERSION: "3.13"
      JARVIS_WORKER_PUBLIC_URL: http://skill-dockge:8090
      DOCKGE_STACKS_DIR: ${DOCKGE_STACKS_DIR:-/opt/stacks}
      DOCKGE_ALLOWED_STACKS: ${DOCKGE_ALLOWED_STACKS:-}
    labels:
      com.jarvis.skill-service: "true"
      com.jarvis.skill-runtime: python-docker
      com.jarvis.worker-name: dockge
      com.jarvis.integration: dockge

volumes:
  ollama-data: