Add server-side AI subtitle translation backed by any OpenAI-compatible
chat endpoint (OpenAI, Groq, a local Ollama/llama.cpp server). A viewer
picks a source track and target language in the player; the server runs a
bounded, resumable job pipeline that translates SRT/VTT cues in batches and
streams them back over the realtime websocket so playback pauses, fills in
cues near the playhead, and resumes. The finished track is persisted as an
ordinary downloaded subtitle, so it reaches every client through the
existing subtitle pipeline with no client changes.
- Job lifecycle persisted in subtitle_ai_jobs (migration 168): enqueue with
idempotency, bounded concurrency, progress/heartbeat, cancellation, and
crash recovery.
- New realtime events (subtitle_ready + subtitle_translation_*) with a
per-session notifier; the player renders a synthetic "live" track fed by
websocket cues. Timestamps never leave the server, so timing can't drift.
- Admin settings card for endpoint / model / concurrency.
Player + lifecycle hardening (from the code review of this feature):
- Hand off from the live track to the persisted track on completion
(selected by downloaded-subtitle id) and on the subtitle_ready broadcast,
so the saved track survives a reload and a mid-stream socket drop.
- Never persist the synthetic live-track sentinel index as a subtitle
preference; restore the prior selection on failure; only auto-resume
playback if the viewer was actually playing.
- Resume promptly when the playhead is past the last cue; rebuild the live
track on a new job; O(batch) live-cue ingestion instead of O(n^2).
Reliability:
- Root translation jobs in the application context so shutdown cancels them.
- Heartbeat-based stale-job reaper (safe across multiple instances) replaces
the table-wide startup reset.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
