Files
esh-pfi-infrastructure/services/lora-training-worker/.gitignore
T
vh 888ba6a714 feat(lora-worker): stand up in-arbo LoRA training worker on irv-ml1 (arbo Phase 1 §4.1)
Host service (runs as llmuser, owns /opt/fluxgym + GPU access) that runs
sd-scripts SDXL LoRA training on demand for arbo — the infra-ops half of the
in-arbo LoRA training Phase 1 ownership split (vh/arbo
docs/contracts/in-arbo-lora-training-phase1.contract.md §4.1/§2).

- Fixed-invocation only (INV-T7): bounded params -> one sd-scripts command
  shape; every param range/allowlist/path-containment checked before spawn;
  bad request = 422, never a silent downgrade. 14 unit tests green.
- Thin supervisor: never imports torch; subprocesses the fluxgym venv's
  accelerate. 1-job-at-a-time (arbo lease is the serializer, 409 is backstop).
  Durable job records + boot reconciliation (§4.3).
- API: POST /train, GET /train/{id}[/log], POST /train/{id}/cancel,
  GET /gpu-status (per-device VRAM + tts_on_3090 co-OOM signal), GET /healthz.
- Wire-shape (§7 resolved with comfy-dev): shared /worktank/arbo/train handoff
  (group arbotrain, setgid 2770); worker binds 0.0.0.0:8203, arbo reaches via
  host.docker.internal:host-gateway (reachability proven on 172.20.0.1:8203);
  device-aware TTS steering via /gpu-status.

Deployed to irv-ml1 via playbooks/deploy-lora-training-worker.yaml (elway,
idempotent); systemd unit active; /healthz + /gpu-status verified live.
2026-07-06 18:28:04 -07:00

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.venv/
__pycache__/
*.egg-info/
*.pyc
state/
logs/