* 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>
159 lines
3.7 KiB
Go
159 lines
3.7 KiB
Go
package jobrunner
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import (
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"context"
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"sync"
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"sync/atomic"
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"testing"
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"time"
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)
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type fakeStore struct {
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mu sync.Mutex
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heartbeats int
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resets int
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lastBefore time.Time
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}
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func (s *fakeStore) Heartbeat(context.Context, int64) error {
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s.mu.Lock()
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defer s.mu.Unlock()
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s.heartbeats++
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return nil
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}
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func (s *fakeStore) ResetStaleJobs(_ context.Context, before time.Time, _ string) (int64, error) {
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s.mu.Lock()
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defer s.mu.Unlock()
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s.resets++
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s.lastBefore = before
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return 0, nil
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}
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func (s *fakeStore) snapshot() (int, time.Time) {
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s.mu.Lock()
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defer s.mu.Unlock()
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return s.resets, s.lastBefore
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}
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func TestRecoverReapsImmediatelyWithStaleCutoff(t *testing.T) {
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store := &fakeStore{}
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ctx, cancel := context.WithCancel(context.Background())
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defer cancel()
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approxNow := time.Now()
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New(ctx, nil, store, "test", nil).Recover()
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resets, before := store.snapshot()
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if resets < 1 {
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t.Fatalf("Recover did not reap immediately: resets=%d", resets)
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}
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want := approxNow.Add(-StaleJobThreshold)
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if diff := before.Sub(want); diff > 2*time.Second || diff < -2*time.Second {
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t.Errorf("stale cutoff = %v, want ~%v", before, want)
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}
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}
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// One shared semaphore bounds jobs across BOTH runners: with size 1, the
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// second runner's job must not start until the first runner's job finishes.
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func TestSharedSemaphoreBoundsAcrossRunners(t *testing.T) {
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ctx, cancel := context.WithCancel(context.Background())
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defer cancel()
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sem := NewSemaphore(1)
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r1 := New(ctx, sem, &fakeStore{}, "one", nil)
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r2 := New(ctx, sem, &fakeStore{}, "two", nil)
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release := make(chan struct{})
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aStarted := make(chan struct{})
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var bStarted atomic.Bool
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bDone := make(chan struct{})
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r1.Dispatch(1, func(context.Context) {
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close(aStarted)
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<-release
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}, nil)
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<-aStarted
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r2.Dispatch(2, func(context.Context) {
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bStarted.Store(true)
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close(bDone)
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}, nil)
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time.Sleep(50 * time.Millisecond)
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if bStarted.Load() {
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t.Fatal("job B ran while job A held the only slot")
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}
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close(release)
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select {
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case <-bDone:
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case <-time.After(2 * time.Second):
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t.Fatal("job B never ran after the slot freed")
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}
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}
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// Cancelling a job that is queued behind the semaphore aborts it without
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// running it, via the onAbort callback.
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func TestCancelWhileQueuedCallsOnAbort(t *testing.T) {
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ctx, cancel := context.WithCancel(context.Background())
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defer cancel()
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sem := NewSemaphore(1)
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r := New(ctx, sem, &fakeStore{}, "test", nil)
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release := make(chan struct{})
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defer close(release)
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started := make(chan struct{})
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r.Dispatch(1, func(context.Context) {
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close(started)
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<-release
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}, nil)
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<-started
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var ran atomic.Bool
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aborted := make(chan struct{})
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r.Dispatch(2, func(context.Context) {
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ran.Store(true)
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}, func(context.Context) {
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close(aborted)
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})
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if !r.Cancel(2) {
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t.Fatal("Cancel(2) found no in-flight goroutine")
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}
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select {
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case <-aborted:
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case <-time.After(2 * time.Second):
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t.Fatal("onAbort never ran")
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}
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if ran.Load() {
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t.Fatal("cancelled queued job still ran")
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}
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}
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func TestCancelUnknownJobReturnsFalse(t *testing.T) {
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r := New(context.Background(), nil, &fakeStore{}, "test", nil)
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if r.Cancel(99) {
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t.Fatal("Cancel(99) = true for unknown job")
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}
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}
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// The run context is cancelled by Cancel(id) so an in-flight job can stop.
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func TestCancelRunningJobCancelsContext(t *testing.T) {
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r := New(context.Background(), NewSemaphore(1), &fakeStore{}, "test", nil)
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started := make(chan struct{})
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stopped := make(chan struct{})
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r.Dispatch(7, func(ctx context.Context) {
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close(started)
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<-ctx.Done()
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close(stopped)
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}, nil)
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<-started
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if !r.Cancel(7) {
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t.Fatal("Cancel(7) found no in-flight goroutine")
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}
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select {
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case <-stopped:
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case <-time.After(2 * time.Second):
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t.Fatal("running job did not observe cancellation")
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}
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}
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