Files
silo-server/internal/ai/jobrunner/runner.go
39ba284c9d feat(ai): shared AI core — metadata translation, Whisper ASR, per-profile language, on-view translation (#127)
* docs: design + plan for shared AI core, metadata translation, Whisper ASR

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* refactor(ai): shared LLM client, segment translator, and job runner packages

internal/ai/llm: OpenAI-compatible chat client moved out of subtitles/ai,
plus /v1/audio/transcriptions (verbose_json) for the ASR work; one shared
retry/backoff loop for both. internal/ai/translate: the batched indexed-JSON
translation protocol generalized to text segments. internal/ai/jobrunner:
dispatch/heartbeat/reaper/cancel lifecycle extracted behind a minimal store
interface, with a semaphore shareable across job services.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* refactor(subtitles): consume shared AI core

LLMTranslator becomes a thin cue<->segment adapter over aitranslate; the
service delegates dispatch/heartbeat/reaper/cancel to jobrunner; the local
OpenAI client is gone in favor of internal/ai/llm. Behavior (prompts, wire
protocol, job rows, recovery semantics) is unchanged. NewService now takes
the dispatch semaphore so all AI job services can share one bound.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(config): shared ai.* settings, metadata translation job table, localization provenance columns

ai.* connection keys (chat + optional separate ASR endpoint) load with a
fallback to the legacy subtitle_ai.* rows — those are never renamed in SQL
because encrypted values are GCM-bound to their setting key. New toggles:
subtitle_ai.transcribe_enabled, metadata_ai.enabled. Migration adds
metadata_translation_jobs, per-field provenance (provider|ai|manual) on the
localization tables, and media_folders.auto_translate_metadata.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(catalog): localization field provenance with provider/ai/manual precedence

Provider upserts keep manual values and never blank a field with an empty
incoming value; new UpsertAITranslation/UpsertAIOverview methods write AI
fields only over empty or ai-sourced values (force adds provider, never
manual) — all enforced in single-statement SQL. Serving now merges only
non-empty localized fields onto the base item, since localization rows are
legitimately partial (AI rows carry no titles/artwork).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(metadata): AI translation service, refresh auto-fallback, and admin API

internal/metadata/translation: job service over the shared AI core that
expands an item to its season/episode overviews, skips already-localized
fields (zero model calls on repeat runs), batches paragraphs through the
generic translator, and persists per batch with provenance-aware upserts.
MetadataService gains an AutoTranslator seam invoked after each refresh for
libraries with auto_translate_metadata. Admin endpoints under the metadata
curation guard: enqueue, list (poll), cancel; plus a status probe.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(subtitles): Whisper ASR transcribe and transcribe_translate jobs

New WhisperTranscriber: one ffmpeg pass extracts the audio track to 10-min
16kHz mono WAV chunks (temp dir cleaned on every exit path), each chunk goes
to the OpenAI-compatible /v1/audio/transcriptions endpoint (verbose_json,
per-request timeout sized to 3x chunk duration), segment timestamps are
offset and built into wrapped cues. Chunks process playhead-first and stream
live to the requesting session. The transcript is stored as an ordinary
downloaded subtitle (provider 'transcribed'); transcribe_translate chains
the existing translator and stores the translated track as the job result.
Enqueue accepts an optional kind; status reports transcribe_enabled.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(web): AI services settings, metadata translate action, library auto-translate, generate-from-audio

New AI Services admin page hosts the shared endpoint config (reads fall back
to legacy subtitle_ai.* values, writes target ai.*) and the three feature
toggles; the AI card moves out of Subtitles settings. The metadata editor
gains a Translate-with-AI panel with job polling and force/re-translate. The
library form gains the auto-translate toggle (threaded through the libraries
API). The player translate modal gains a From-audio mode that lists audio
tracks and submits transcribe / transcribe_translate jobs.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* style: gofmt import grouping in router and translation tests

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(catalog): per-profile metadata language and viewer-triggered description translation

user_profiles.preferred_metadata_language threads through the access scope
into catalog serving: presentation language now resolves explicit param ->
profile preference -> library metadata language (native API and jellycompat).
ItemDetail gains pending_translation_language when the viewer's language is
missing a localized overview. New metadata_ai.on_view setting (off|button|
auto) gates POST /items/{id}/translate-description: any profile with item
access may request its language, with in-flight dedup and a 15-minute
failure cooldown so page views never hammer a broken endpoint.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(web): on-view description translation with per-profile metadata language

Profile playback settings gain a Metadata language picker (library default
inherit). Detail pages: when the server reports pending_translation_language
and metadata_ai.on_view is 'auto', the description translates on view with a
pulse animation until the refetched detail comes back localized (45s
timeout); in 'button' mode a small Translate chip triggers the same flow.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix(web): expose metadata_ai.on_view in AI Services settings

The on-view translation mode had no UI control, so it could only ever be
'off' — viewers got neither the auto translation nor the fallback button.
Adds the off/button/auto selector to the Features card, and the config
loader now warns and falls back to 'off' on a bad row instead of refusing
to start.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix(ai): clear configuration hint when the transcription endpoint is chat-only

A blank Transcription base URL falls back to the chat endpoint; chat-only
gateways reject the multipart upload with an opaque 400 that reads like a
pipeline bug. 400/404/405 transcription failures now carry a hint to set a
Whisper-compatible endpoint in AI Services.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix(subtitles): wrap ASR cue text by rune count, not bytes

Arabic/Cyrillic/Greek text is 2+ bytes per character in UTF-8, so byte-based
wrapping broke lines at roughly half the intended visual width.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* docs(web): steer transcription base URL hint away from chat-only gateways

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(ai): block chat-only gateways for transcription, add endpoint presets

llm.IsChatOnlyGateway (OpenRouter et al — no timestamped transcription API)
is enforced in three layers: the settings API rejects ai.asr_base_url values
pointing at one, the router disables ASR with a warning when the blank-URL
fallback would land on one, and llm.Transcribe refuses outright. The AI
Services page gains one-click transcription presets (Groq turbo/accurate,
OpenAI, self-hosted speaches) plus the mirrored client-side check, and the
settings API now also validates metadata_ai.on_view.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix(subtitles): tighten ASR subtitle sync

Three systematic timing-error sources addressed: cue offsets now use the
segment muxer's exact per-chunk start times (segment_list CSV) instead of
assuming index*chunk_seconds; the audio stream's start delay relative to the
container timeline (common in TS remuxes) is probed via ffprobe and added to
every cue; and the chunk length is now operator-tunable via
subtitle_ai.asr_chunk_seconds (60-600s, default 600) since shorter chunks
bound Whisper's within-chunk timestamp drift. Playhead-first ordering now
pivots on real chunk starts, and a beyond-end playhead starts at the final
chunk instead of restarting from zero.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix(ai): tolerate base URLs that already include the /v1 segment

Providers like DeepInfra expose their OpenAI-compatible API under a base
that contains the version segment (api.deepinfra.com/v1/openai); always
appending /v1/... mangled those. endpointURL now appends bare paths when
the base already carries /v1.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(web): prefer self-hosted transcription in presets and hints

Preset order becomes self-hosted (recommended) -> Groq turbo -> Groq
large-v3 -> OpenAI, and the settings hint plus the job-error hint lead with
the self-hosted option. The self-hosted preset now fills the turbo CT2 model
to match the recommended speaches setup.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix(subtitles): request VAD and word timestamps for ASR cue accuracy

Without vad_filter, faster-whisper servers report wall-to-wall segment
times: cues linger on screen through silence (verified up to 91s) and
paragraph-length segments become single 400+ char cues. Request
vad_filter=true (skipped for hosted providers that reject non-OpenAI
fields and run VAD server-side) plus timestamp_granularities word+segment,
and rebuild cues from word timings: split at speech pauses, sentence ends,
text capacity, and a 7s max duration; cap word-less segments instead of
trusting their reported end; stretch sub-second cues to a readable minimum.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
2026-06-10 14:58:54 -04:00

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// Package jobrunner owns the lifecycle mechanics shared by Silo's AI job
// services (subtitle translation/ASR, metadata translation): bounded dispatch
// off a semaphore shared across services, a heartbeat loop that keeps a row
// alive even while the job is queued, a stale-job reaper for rows orphaned by
// a crashed worker, and a per-job cancel registry. The services keep their own
// job tables, validation, and run logic; this package keeps them honest about
// concurrency and crash recovery without copy-pasting the trickiest code.
package jobrunner
import (
"context"
"log/slog"
"sync"
"time"
)
const (
// A running job refreshes its heartbeat every HeartbeatInterval; one whose
// heartbeat has not advanced for StaleJobThreshold is treated as orphaned
// by a crashed worker and reaped. The margin over HeartbeatInterval avoids
// reaping a job that is merely midLLM-call.
HeartbeatInterval = 30 * time.Second
StaleJobThreshold = 2 * time.Minute
// How often the background reaper scans for orphaned jobs.
ReaperInterval = time.Minute
)
// Store is the minimal persistence surface the runner needs. Both AI job
// repositories satisfy it.
type Store interface {
Heartbeat(ctx context.Context, id int64) error
// ResetStaleJobs marks pending/running jobs whose heartbeat predates
// `before` as failed with the given message. Returns rows reset.
ResetStaleJobs(ctx context.Context, before time.Time, message string) (int64, error)
}
// NewSemaphore builds the dispatch semaphore shared across runners, so the
// configured endpoint sees one global bound regardless of job mix. size <= 0
// falls back to 2.
func NewSemaphore(size int) chan struct{} {
if size <= 0 {
size = 2
}
return make(chan struct{}, size)
}
// Runner executes jobs with bounded concurrency, heartbeats, cancellation,
// and crash recovery. One Runner per job table; the semaphore may be shared
// across Runners.
type Runner struct {
// baseCtx is the application context; dispatched jobs and the reaper
// derive from it so they stop when the server shuts down.
baseCtx context.Context
sem chan struct{}
store Store
// label names the job family in log lines ("subtitle ai", "metadata translation").
label string
logger *slog.Logger
mu sync.Mutex
cancels map[int64]context.CancelFunc
wg sync.WaitGroup
}
// New wires a runner. A nil appCtx falls back to context.Background(); a nil
// sem gets a private default-size semaphore (used by tests; production passes
// the shared one).
func New(appCtx context.Context, sem chan struct{}, store Store, label string, logger *slog.Logger) *Runner {
if appCtx == nil {
appCtx = context.Background()
}
if sem == nil {
sem = NewSemaphore(0)
}
if logger == nil {
logger = slog.Default()
}
return &Runner{
baseCtx: appCtx,
sem: sem,
store: store,
label: label,
logger: logger,
cancels: make(map[int64]context.CancelFunc),
}
}
// Recover clears jobs orphaned by a crashed worker and starts a background
// reaper that keeps doing so. Reaping is heartbeat-based (not "every active
// job"), so it is safe when multiple instances share one database: a job
// still being heartbeat-updated by a live worker is never reset. Call once at
// startup; jobs and the reaper derive from the application context, so they
// stop on shutdown.
func (r *Runner) Recover() {
r.reapStaleJobs()
go r.reaperLoop()
}
func (r *Runner) reaperLoop() {
ticker := time.NewTicker(ReaperInterval)
defer ticker.Stop()
for {
select {
case <-r.baseCtx.Done():
return
case <-ticker.C:
r.reapStaleJobs()
}
}
}
func (r *Runner) reapStaleJobs() {
before := time.Now().Add(-StaleJobThreshold)
n, err := r.store.ResetStaleJobs(context.WithoutCancel(r.baseCtx), before, "interrupted by server restart")
if err != nil {
r.logger.Warn("failed to reset stale jobs", "jobs", r.label, "error", err)
return
}
if n > 0 {
r.logger.Info("reset stale jobs", "jobs", r.label, "count", n)
}
}
// Dispatch launches a bounded background goroutine for job id. run executes
// once a semaphore slot is acquired; onAbort runs instead if the job is
// cancelled (user cancel or shutdown) while still waiting for a slot. Both
// receive a context derived from the application context that is cancelled by
// Cancel(id) or server shutdown.
func (r *Runner) Dispatch(id int64, run func(ctx context.Context), onAbort func(ctx context.Context)) {
runCtx, cancel := context.WithCancel(r.baseCtx)
r.mu.Lock()
r.cancels[id] = cancel
r.mu.Unlock()
r.wg.Add(1)
go func() {
defer r.wg.Done()
defer func() {
r.mu.Lock()
delete(r.cancels, id)
r.mu.Unlock()
cancel()
}()
// Heartbeat for the whole lifetime — crucially including while queued
// behind the semaphore — so the stale-job reaper never reaps a job that
// is alive but merely waiting for a slot (which would otherwise mark it
// failed and let it resurrect itself on acquire, or admit a duplicate).
stopHeartbeat := make(chan struct{})
defer close(stopHeartbeat)
go r.heartbeatLoop(runCtx, id, stopHeartbeat)
select {
case r.sem <- struct{}{}:
case <-runCtx.Done():
if onAbort != nil {
onAbort(context.WithoutCancel(runCtx))
}
return
}
defer func() { <-r.sem }()
run(runCtx)
}()
}
// Cancel cancels the in-flight goroutine for id, returning false when none is
// registered (job on another node, or never dispatched) so the caller can
// fall back to a best-effort terminal transition in the database.
func (r *Runner) Cancel(id int64) bool {
r.mu.Lock()
cancel := r.cancels[id]
r.mu.Unlock()
if cancel == nil {
return false
}
cancel()
return true
}
// heartbeatLoop keeps a job's heartbeat_at fresh until the job ends or the
// context is cancelled, so the stale-job reaper only ever reaps jobs orphaned
// by a crashed worker.
func (r *Runner) heartbeatLoop(ctx context.Context, jobID int64, stop <-chan struct{}) {
ticker := time.NewTicker(HeartbeatInterval)
defer ticker.Stop()
for {
select {
case <-stop:
return
case <-ctx.Done():
return
case <-ticker.C:
_ = r.store.Heartbeat(context.WithoutCancel(ctx), jobID)
}
}
}