yau-plant-assistant/compose/ai-compose.yml

# =============================================================================
# ai-compose.yml  ->  deployed to ~/ai-compose.yml on yau-sls-poc-lin001
#
# House style, inherited from ~/docker-compose.yml (host brief section 7):
#   - restart: unless-stopped on everything
#   - log rotation 10 MB x 3 on everything
#   - NO published host ports: reach services through Caddy on the proxy network
#   - secrets in 0600 env files under ~/ai/, never here and never in Git
#
# Orphan-container warnings are expected (shared Compose project name) - ignore.
#
#   docker compose -f ~/ai-compose.yml up -d
# =============================================================================

services:

  # ---------------------------------------------------------------------------
  # pg-ai - pgvector, reference data, Cube pre-aggregations.
  # Deliberately NOT on proxy: no UI, nothing outside the AI stack reaches it.
  # Pinned image - do NOT add to Watchtower's update list.
  # ---------------------------------------------------------------------------
  pg-ai:
    image: pgvector/pgvector:pg16
    container_name: pg-ai
    restart: unless-stopped
    networks: [ai-internal]
    env_file:
      - /home/azureuser/ai/pg-ai.env      # 0600, not in Git
    environment:
      POSTGRES_DB: plant
      POSTGRES_USER: postgres
      PGDATA: /var/lib/postgresql/data/pgdata
    volumes:
      - /datadisk/pg-ai:/var/lib/postgresql/data
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U postgres -d plant"]
      interval: 10s
      timeout: 5s
      retries: 5
    logging:
      driver: json-file
      options: { max-size: "10m", max-file: "3" }

  # ---------------------------------------------------------------------------
  # cubestore - Cube's own store. Queue, cache and pre-aggregations. Deployed
  # because Cube v1 does not run without it, not because we wanted another
  # container. Version pinned in lockstep with cube: a mismatched pair is a
  # documented Cube failure mode. Do NOT add either to Watchtower's list.
  #
  # Data goes on /datadisk. It grows with the pre-aggregations, and / is 62 GB
  # and has hit 100% on this host before.
  #   sudo install -d -o 1000 -g 1000 /datadisk/cubestore
  # No ports, ai-internal only: nothing outside the AI stack talks to it, and
  # it has no authentication of its own.
  # ---------------------------------------------------------------------------
  cubestore:
    image: cubejs/cubestore:v1.1.7
    container_name: cubestore
    restart: unless-stopped
    networks: [ai-internal]
    environment:
      CUBESTORE_DATA_DIR: /cube/data
    volumes:
      - /datadisk/cubestore:/cube/data
    logging:
      driver: json-file
      options: { max-size: "10m", max-file: "3" }

  # ---------------------------------------------------------------------------
  # cube - semantic layer. Reads imh over TDS/1433 with the read-only login, or
  # the fixture tables in pg-ai while USE_FIXTURES=true. Pinned - not in
  # Watchtower's list.
  #
  # PRE-AGGREGATIONS LIVE IN CUBE STORE, NOT pg-ai. This is a deviation from
  # the build spec, forced by the pinned version and found on lin001 deploying
  # Phase 5, not in review. Cube v1 will not materialise pre-aggregations into
  # Postgres - Cube Store is the only supported external store - so naming
  # Postgres as CUBEJS_EXT_DB_TYPE fails every query with
  #   "It`s not possible to use Cube Store as queue/cache driver without using
  #    it as external"
  # Cube Store is also the queue and cache driver, and it is not optional:
  # CUBEJS_CACHE_AND_QUEUE_DRIVER=memory does not fall back, it hangs /readyz
  # and every query forever, with nothing in the log at level warn.
  # So `cubestore` below is a hard dependency of cube, not an optimisation.
  # cube_preagg in pg-ai and its grants in db/003_roles.sql are now unused;
  # they are left in place rather than dropped, because nothing else changes if
  # a future Cube version restores Postgres as an external store.
  # ---------------------------------------------------------------------------
  cube:
    image: cubejs/cube:v1.1.7
    container_name: cube
    restart: unless-stopped
    depends_on:
      pg-ai:
        condition: service_healthy
      cubestore:
        condition: service_started
    networks: [ai-internal, proxy]
    env_file:
      - /home/azureuser/ai/api.env        # 0600, not in Git
    environment:
      CUBEJS_DEV_MODE: "false"
      CUBEJS_LOG_LEVEL: warn
      # Queue, cache and pre-aggregation store. Mandatory - see the note above.
      CUBEJS_CUBESTORE_HOST: cubestore
      CUBEJS_CUBESTORE_PORT: "3030"
      # Without this NOTHING builds the pre-aggregations, and every query that
      # matches one fails with "No pre-aggregation partitions were built yet"
      # rather than falling back to the source. Single node, so the API
      # instance is also the refresh worker.
      CUBEJS_REFRESH_WORKER: "true"
      # CUBEJS_DB_* and CUBEJS_API_SECRET come from api.env.
    volumes:
      - /home/azureuser/ai/cube/model:/cube/conf/model:ro
    healthcheck:
      # The image has neither wget nor curl - the original wget healthcheck
      # marked a perfectly healthy cube unhealthy on every deploy. node is
      # what it does have.
      test: ["CMD", "node", "-e", "require('http').get('http://localhost:4000/readyz', r => process.exit(r.statusCode === 200 ? 0 : 1)).on('error', () => process.exit(1))"]
      interval: 30s
      timeout: 5s
      retries: 3
    logging:
      driver: json-file
      options: { max-size: "10m", max-file: "3" }

  # ---------------------------------------------------------------------------
  # ai-api - FastAPI. Classifier, agent, contracts, guardrails.
  # ---------------------------------------------------------------------------
  ai-api:
    build:
      context: /home/azureuser/ai/api
      dockerfile: Dockerfile
    image: yau/ai-api:local
    container_name: ai-api
    restart: unless-stopped
    depends_on:
      pg-ai:
        condition: service_healthy
    networks: [ai-internal, proxy]
    env_file:
      - /home/azureuser/ai/api.env        # 0600, not in Git
    # Phase 9 - the upload inbox, and the ONLY writable path this container
    # gets. Deliberately not /datadisk/ai-docs: a file that has been uploaded
    # but not yet approved must not be visible to `ai-ingest --all`.
    #
    # COMMENTED OUT UNTIL PHASE 9, on the same principle as caddy/ai-routes.caddy:
    # add each piece at the phase that needs it. Docker creates a missing bind
    # source as a ROOT-OWNED directory, and ai-api does not run as root - so
    # deploying this before the directory exists gives you an inbox the API
    # cannot write to, on the growing disk of a live shared host.
    # Create it first, then uncomment:
    #   sudo install -d -o 10002 -g 10002 /datadisk/ai-docs-inbox
    # volumes:
    #   - /datadisk/ai-docs-inbox:/inbox
    healthcheck:
      test: ["CMD", "python", "-m", "app_healthcheck"]
      interval: 30s
      timeout: 5s
      retries: 3
    logging:
      driver: json-file
      options: { max-size: "10m", max-file: "3" }

  # ---------------------------------------------------------------------------
  # ai-web - React/Vite build served by nginx. proxy only; the browser talks to
  # the API through its public hostname, so it needs nothing on ai-internal.
  # ---------------------------------------------------------------------------
  ai-web:
    build:
      context: /home/azureuser/ai/web
      dockerfile: Dockerfile
      args:
        # Empty in a real deployment: the browser reaches the API at its own
        # public hostname through Caddy. Set only for a tunnelled demo build,
        # which has no Caddy and no Authelia in front of it.
        VITE_API_BASE: "${VITE_API_BASE:-}"
    image: yau/ai-web:local
    container_name: ai-web
    restart: unless-stopped
    networks: [proxy]
    logging:
      driver: json-file
      options: { max-size: "10m", max-file: "3" }

  # ---------------------------------------------------------------------------
  # ai-ingest - on demand, not a service. Docling -> chunk -> embed -> pg-ai.
  #   docker compose -f ~/ai-compose.yml run --rm ai-ingest --all
  # The profile keeps it out of `up -d`.
  # ---------------------------------------------------------------------------
  ai-ingest:
    build:
      context: /home/azureuser/ai/ingest
      dockerfile: Dockerfile
    image: yau/ai-ingest:local
    container_name: ai-ingest
    profiles: [ingest]
    restart: "no"
    networks: [ai-internal]
    env_file:
      - /home/azureuser/ai/api.env        # 0600, not in Git
    volumes:
      - /datadisk/ai-docs:/docs:ro
    logging:
      driver: json-file
      options: { max-size: "10m", max-file: "3" }

  # ---------------------------------------------------------------------------
  # ai-docs-worker - Phase 9. The ai-ingest IMAGE with worker.py as entrypoint,
  # so an uploaded document is parsed and chunked by exactly the same code as a
  # file ingested from the command line - by construction, not by discipline.
  #
  # Two jobs: pre-scan `uploaded` rows for a header proposal, and publish
  # `approved` ones. It is the only container that can write doc_chunks
  # (ingest_rw), and it has no HTTP surface and no place on the proxy network.
  #
  # /docs is READ-WRITE here, unlike the ai-ingest CLI service above, because
  # publishing moves the approved file into the folder that determines its
  # doc_type. That is the one write, and it happens only after a human has
  # confirmed the header.
  #
  # Both mounts must be writable by the image's uid 10002 (ingestuser):
  #   sudo install -d -o 10002 -g 10002 /datadisk/ai-docs-inbox
  #   sudo chown -R 10002:10002 /datadisk/ai-docs
  # ai-api writes the inbox as its own non-root uid - give the inbox group
  # write and put both uids in the group rather than making it world-writable.
  # ---------------------------------------------------------------------------
  ai-docs-worker:
    build:
      context: /home/azureuser/ai/ingest
      dockerfile: Dockerfile
    image: yau/ai-ingest:local
    container_name: ai-docs-worker
    # Kept out of `up -d` by the profile, exactly as ai-ingest is. worker.py
    # does not exist yet, so an unguarded service here would crash-loop on a
    # live shared host. Drop the profile in the same commit that adds the file.
    #   docker compose -f ~/ai-compose.yml --profile worker up -d ai-docs-worker
    profiles: [worker]
    restart: unless-stopped
    depends_on:
      pg-ai:
        condition: service_healthy
    networks: [ai-internal]
    env_file:
      - /home/azureuser/ai/api.env        # 0600, not in Git
    entrypoint: ["python", "worker.py"]
    command: []
    volumes:
      - /datadisk/ai-docs-inbox:/inbox
      - /datadisk/ai-docs:/docs           # rw - see above
      # Withdrawn documents are MOVED here, not deleted. It is outside the four
      # doc_type folders on purpose: ingest_file() inserts every chunk with
      # superseded = FALSE, so a withdrawn file left in /docs comes back LIVE on
      # the next `ai-ingest --all`.
      - /datadisk/ai-docs-withdrawn:/withdrawn
    logging:
      driver: json-file
      options: { max-size: "10m", max-file: "3" }

networks:
  ai-internal:
    driver: bridge
  proxy:
    external: true