# Scriberr — self-hosted audio/video transcription with speaker diarization.
# Upstream: https://github.com/rishikanthc/Scriberr  (Go + SvelteKit, SQLite).
#
# Transcription runs locally via WhisperX (Whisper + pyannote diarization);
# NVIDIA Parakeet / Canary models are also selectable in the UI. Optional
# summarisation / transcript chat talks to any OpenAI-compatible endpoint —
# point it at the LiteLLM gateway rather than a paid API (see README).
#
# ── IMAGE: BUILT LOCALLY, ON PURPOSE ──────────────────────────────────────
# fv-ml1's RTX PRO 6000 Blackwell cards are **sm_120**. Upstream publishes
# `scriberr-cuda` (built for sm_61…sm_89 — no sm_120 kernels) and documents a
# `scriberr-cuda-blackwell` image that **has never actually been published**
# (GHCR returns no tags for it, checked 2026-08-23). The sm_120 path upstream
# ships is `Dockerfile.cuda.12.9` (CUDA 12.9.1 + cu128 torch), built locally.
# Do NOT "simplify" this to the published `scriberr-cuda` image — it will
# fail on these cards or silently fall back to CPU.
#   Rebuild: see README "Rebuilding" — checkout lives at
#   /tank/scriberr/src/Scriberr on fv-ml1.
#
# ── GPU PINNING ───────────────────────────────────────────────────────────
# Pinned to **GPU1** via explicit device_ids, per the house convention and
# because GPU0 is fully committed to the `gen` seat. GPU1 shares space with
# the `sec` seat, so this stack is a guest there — keep an eye on VRAM.
# NOTE: do NOT add `NVIDIA_VISIBLE_DEVICES=all` (as upstream's compose does).
# It overrides the device_ids reservation and exposes both cards.
#
# All tunables live in .env — edit that, not this file.

services:
  scriberr:
    image: ${SCRIBERR_IMAGE:-scriberr:local-blackwell}
    container_name: scriberr
    restart: unless-stopped
    ports:
      - "${SCRIBERR_BIND:-0.0.0.0}:${SCRIBERR_PORT}:8080"
    volumes:
      # Bind mounts rather than named volumes: /var/lib/docker on fv-ml1
      # lives on zroot with limited headroom, while /tank has terabytes.
      # Model weights (Whisper, pyannote, NeMo) land in whisperx-env and are
      # multi-GB — they must not go anywhere near the root pool.
      - ${SCRIBERR_DATA_DIR}:/app/data
      - ${SCRIBERR_ENV_DIR}:/app/whisperx-env
    environment:
      # ⚠ 10001, NOT the fleet-usual 1000 — this is load-bearing.
      # Dockerfile.cuda.12.9 creates `appuser` at uid 10001 (Ubuntu 24.04's
      # base image already owns uid 1000 as `ubuntu`, so upstream moved it) and
      # chowns /app to 10001. The entrypoint's PUID remapping only chowns
      # /app/data + /app/whisperx-env, not /app itself, so running as 1000
      # leaves the app unable to open its SQLite DB and it crash-loops with
      # `unable to open database file: out of memory (14)` — which is
      # SQLITE_CANTOPEN wearing a misleading message, not a real OOM.
      # The host bind-mount dirs are therefore chowned to 10001:10001 too.
      # Verified 2026-08-23: PUID=1000 crash-loops, PUID=10001 starts clean.
      - PUID=${SCRIBERR_PUID:-10001}
      - PGID=${SCRIBERR_PGID:-10001}
      - APP_ENV=production
      # Served over plain HTTP on the LAN. Left at the production default of
      # `true`, the session cookie is marked Secure and the browser silently
      # drops it — you log in, get bounced back to the login page, and the
      # logs show nothing wrong. This must stay false while access is HTTP.
      - SECURE_COOKIES=${SCRIBERR_SECURE_COOKIES:-false}
      # Upstream defaults to localhost origins only, which fails CORS when
      # reached by host IP. Keep this in sync with how the app is reached.
      - ALLOWED_ORIGINS=${SCRIBERR_ALLOWED_ORIGINS}
      - NVIDIA_DRIVER_CAPABILITIES=compute,utility
      # Scriberr builds each model backend's Python env with `uv` at runtime.
      # uv's default link mode reflink/hardlinks out of its cache, which fails
      # on this overlayfs+ZFS combination with a misleading
      #   "Failed to clone ... Resource temporarily unavailable (os error 11)"
      # and takes out the Parakeet + Sortformer backends (WhisperX survives).
      # `copy` trades a little disk and time for it actually working.
      - UV_LINK_MODE=${SCRIBERR_UV_LINK_MODE:-copy}
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              device_ids: ["${SCRIBERR_GPU_ID:-1}"]
              capabilities: [gpu]
    healthcheck:
      # 127.0.0.1 rather than localhost — the IPv6-first resolution trap has
      # bitten news-digest and chatterbox in this fleet before.
      # start_period is generous: first boot builds a Python env and pulls
      # several GB of model weights before the port answers.
      test: ["CMD-SHELL", "curl -fsS http://127.0.0.1:8080/ >/dev/null || exit 1"]
      interval: 30s
      timeout: 5s
      retries: 3
      start_period: 600s
    networks:
      - tnet
    labels:
      # ⚠ The group name MUST match a key in the dashboard's settings.yaml
      # `layout:` block. A group that appears nowhere in that block gets no
      # `tab:` assignment, and Homepage renders an untabbed group on EVERY tab.
      # This label read `AI Systems` — a group that existed nowhere — from
      # 2026-08-23 until it was caught on 2026-08-24.
      # `AI - Studios` and not one of the ASR groups because Scriberr is a
      # transcription UI you open and work in, which is what Studios collects;
      # the bare ASR endpoints (Parakeet, Speaches) live in the collapsed
      # `AI - Audio Tools` group instead.
      - homepage.group=AI - Studios
      - homepage.name=Scriberr
      - homepage.icon=mdi-microphone-message
      - homepage.description=Audio/video transcription + diarization (fv-ml1, GPU1)
      - homepage.href=http://10.251.50.54:${SCRIBERR_PORT}

networks:
  tnet:
    name: traefik-net
    external: true