esh-pfi-infrastructure/stacks/voices-seat/compose.yaml

# voices-seat — one base carrier, N author LoRA adapters, hot-swappable. fv-ml1 GPU 0, :8027.
#
# NAMING: adapters are `lv-<author>` — lv for lang-voice (operator, 2026-09-16, retiring the
# `baby*` prefix: it read fine for one experiment and invites confusion across a family).
# The adapter NAME is the request's `model` field, so this string is the public API of a voice.
#
# WHY LORA AND NOT MERGE (operator decision 2026-09-16, after measurement): the R49 line
# produces a FAMILY of author voices — lv-bronte, lv-yarros (shipped), lv-hemingway (in
# build) — and Skaldsong switches between them per request. Merging bakes each 264 MB adapter
# into a fresh 7.6 GB model:
#
#     3 authors   LoRA  7.6 GB + 3x264 MB ~ 8.4 GB      merged ~23 GB
#     6 authors   LoRA  7.6 GB + 6x264 MB ~ 9.2 GB      merged ~46 GB
#
# On a box where GPU 1 has 5.7 GB free, GPU 2 has 2.4 GB and GPU 3 is a held reserve, that
# is the whole argument. A new author becomes a directory drop, not a VRAM negotiation.
#
# ⚠ SUPPORT WAS CHECKED, NOT ASSUMED. The training-throughput playbook records a LoRA refusal
# on a Qwen3 *MoE* arch ("get_expert_mapping must be implemented") and its lesson is that
# feature support is per-architecture, not per-family. Verified on the fleet's own engine
# before committing: vllm/model_executor/models/qwen3.py:271 declares Qwen3ForCausalLM with
# SupportsLoRA, plus packed_modules_mapping and embedding_modules. Dense Qwen3 is fine; do NOT
# transplant this compose onto an MoE carrier without re-running that grep.
#
# ⚠ KV IS PINNED IN BYTES, deliberately, following gen-small-seat's note. On THIS box
# `--gpu-memory-utilization` has been measured wrong in both directions — cyberprev at 0.40
# holds 47.1 GB (8 GB over its fraction), gen-small at 0.48 holds 36.9 (10 GB under) — so a
# fraction cannot be used to place a seat beside live co-tenants. GPU 0 already carries
# cyberprev, gen-small and the Parakeet STT seat; an explicit KV budget makes this seat's
# footprint deterministic instead of negotiated.
#
# ⚠ ADAPTERS ARE MOUNTED READ-ONLY and named explicitly. A request selects a voice by putting
# the adapter name in the `model` field — switching voices is a field, not a deployment.
#
# MEASURED on this seat, 2026-09-16, rather than taken from docs:
#   POST /v1/load_lora_adapter   {"lora_name","lora_path"}   -> 200 in 0.24 s
#   POST /v1/unload_lora_adapter {"lora_name"}               -> 200 in 0.003 s
#   VRAM unchanged across the swap; container stayed healthy; no restart, no reload.
# ⚠ Anything added that way is GONE on `compose up -d` unless it is ALSO listed in
# --lora-modules below. Runtime load is for trying a voice; this list is what survives.
#
# MEASURED LORA COST on this seat (n=30 per arm, interleaved, A-vs-A floor 0.1%):
#   base            median 143.0 tok/s
#   lv-yarros       median 108.2 tok/s   -> -24.3%, far outside the floor.
# Accepted deliberately: the seat is for prose, not a latency path, and 24% buys every future
# author for 264 MB instead of 7.6 GB. If a voice ever lands on a hot path, merge THAT one.
#
# MEASURED RESIDENCY: 10,740 MiB, against a requested 0.11 x 94.97 GiB = 10,700 MiB — a 40 MiB
# miss on a box where the util fraction has been wrong by 8-10 GB in BOTH directions. Pinning
# --kv-cache-memory in bytes is what makes the fraction predictive; do not remove it.
name: voices-seat

services:
  vllm-voices:
    image: ${VOICES_IMAGE:-vllm/vllm-openai:nightly-e9d1398d9edfd90fcc1cf783805240e3effec013}
    container_name: ${VOICES_CONTAINER_NAME:-vllm-voices}
    restart: unless-stopped
    ipc: host
    ports:
      - "${VOICES_PORT:-8027}:8000"
    volumes:
      - /tank/aimodels/huggingface:/hfcache
      - ${VOICES_MODEL:-/tank/aimodels/Qwen3-4B-Instruct}:/model:ro
      - /tank/aimodels/voice-adapters:/adapters:ro
    environment:
      - VLLM_API_KEY=${API_KEY:-}
      - VLLM_ALLOW_RUNTIME_LORA_UPDATING=${VOICES_RUNTIME_LORA:-1}
    command:
      - /model
      - --served-model-name
      - ${VOICES_SERVED_NAME:-voices-base}
      - --host
      - 0.0.0.0
      - --port
      - "8000"
      - --gpu-memory-utilization
      - "${VOICES_GPU_MEM_UTIL:-0.12}"
      - --kv-cache-memory
      - "${VOICES_KV_CACHE_MEMORY:-2147483648}"
      - --max-model-len
      - "${VOICES_MAX_MODEL_LEN:-8192}"
      - --max-num-seqs
      - "${VOICES_MAX_NUM_SEQS:-8}"
      - --dtype
      - auto
      - --enable-prefix-caching
      - --enable-lora
      - --max-loras
      - "${VOICES_MAX_LORAS:-4}"
      - --max-lora-rank
      - "${VOICES_MAX_LORA_RANK:-32}"
      - --lora-modules
      - lv-yarros=/adapters/lv-yarros-4b-v1
      # ⚠ lv-bronte did NOT pass its voice gate: +0.193 delta_cb toward held-out
      # Brontë against a 0.251 measured noise floor. Shipped anyway because it is
      # additive, reversible, and clean on the safety axis (8-gram overlap 0.00,
      # identical to the never-saw-it control). The effect is underpowered, not
      # absent — it closed 48% of the achievable span and beat base on every seed.
      # Do not cite it as evidence pair-SFT works for this author.
      # See /adapters/lv-bronte-4b-v1/README.md and
      # persistent-memory.d/2026-09-17-lv-bronte-gate.md
      - lv-bronte=/adapters/lv-bronte-4b-v1
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              device_ids:
                - "${VOICES_GPU_ID:-0}"
              capabilities: [gpu]
    healthcheck:
      test: ["CMD-SHELL", "curl -fsS http://localhost:8000/health || exit 1"]
      interval: 30s
      timeout: 5s
      retries: 20
      start_period: 300s
    labels:
      - homepage.group=AI - Inference
      - homepage.name=Voices
      - homepage.icon=mdi-account-voice
      - homepage.description=Author voice adapters (LoRA) on Qwen3-4B
      - homepage.href=http://10.251.50.54:8027/docs
    networks: [tnet]

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