- Navbar: add WebSocket connection dot (green/yellow/red/gray) from GlobalWebSocketContext
- Profile page: /profile route shows email, full_name, role, auth_provider, languages
- JobResponse: expose failure and error fields (were stored in MongoDB but not returned)
so frontend now shows actual render error message instead of generic fallback
- render_accessible_video: write JOB_TASK_FAILED audit log entry on render failure
with language, error detail, step=render
- rerender_accessible_video: same audit log on re-render failure, step=rerender
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- NewBrief: use useAllProjects() (was useProjects('') which never fired)
- NewBrief: expand languages from 12 to 52 options with region variants
- NewBrief: add Assign To dropdown from org members
- Backend: add GET /clients/all-projects endpoint for cross-client project listing
- Backend: add assignee_id to JobBriefCreate/JobBriefResponse models + routes
- notify.py: send completion email to PMs (pm_client_ids) not client user — fixes email never arriving (was looking up users._id by client entity ID)
- Downloads: add Download All button that fetches all files sequentially
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- translate_and_synthesize.py: fetch job_doc from DB right before the combined
MP3 upload so gcs_path() has the gcs_prefix needed for newer jobs; removes the
duplicate fetch that existed later in the same function
- migration_2026-04-30-000001: add 'cancelled' to MongoDB $jsonSchema validator
enum so cancel_job writes no longer fail Document validation
- Dashboard.tsx: include all active processing statuses in the Processing counter
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
When a reviewer saves the source language VTT during QC and confirms
the re-translate dialog, all target languages are re-translated via
Celery. Job transitions to `translating` and returns to `pending_qc`
when done. Existing polling in useJob covers progress display.
- schemas/job.py: add `retranslate_languages: bool` to VttUpdateRequest
- audit_log.py: add VTT_RETRANSLATE audit action
- translate_and_synthesize_task: accept languages/retranslate params,
filter to specified languages, skip video render, return to PENDING_QC
- routes_jobs.py: add _trigger_retranslation helper, call after VTT save
- types/api.ts: add retranslate_languages to VttUpdateRequest
- useJob.ts: invalidate all lang VTTs on retranslate
- QCDetail.tsx: confirmation dialog when saving source VTT with targets
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Heavy pipeline tasks (ingest, translate, render, rerender) now dispatch
to a Cloud Run Job (va-worker) instead of local Celery workers. optical-dev
runs only api + lightweight worker (notify/embed) within its 2-CPU budget.
- backend/app/tasks/runner.py — Cloud Run Job entrypoint
- backend/app/services/cloud_run_dispatch.py — replaces .delay() for heavy tasks
- backend/Dockerfile.cloudrun — Cloud Run worker image (ffmpeg included)
- docker-compose.optical-dev.yml — 2-CPU safe overrides, disables heavy workers
- cloudbuild.yaml — builds va-worker image and updates Cloud Run Job
- deploy-dev.sh — uses 3-file compose, builds only api+worker locally
- routes_jobs, routes_admin_production, ingest_and_ai, translate_and_synthesize
— all dispatch sites updated to use cloud_run_dispatch.dispatch()
USE_CELERY_FALLBACK=true in .env.local to use Celery locally during dev.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
ingest_and_ai: exception handler now sets status=PROCESSING_FAILED and
writes Job.failure{step, type, message, retriable, occurred_at} instead
of leaving status unchanged (was silent failure).
translate_and_synthesize: replace the blanket TTS_FAILED status (even for
translation failures) with PROCESSING_FAILED + failure.step="translation"|
"tts" based on current job status at failure time.
render_accessible_video: add failure{step="render"} alongside existing
RENDER_FAILED status for UI consumption.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Changes:
- Dashboard: add project_manager case (final review / QC counts / new job widgets)
and production case (AI pipeline / failures widgets)
- Sidebar: add project_manager to Final Review and Audit Log nav items;
live badge counts for QC Queue (pending_qc) and Final Review (pending_final_review)
- App.tsx: add project_manager to Final Review and Audit Log RoleGates (W-10, PM-18)
- Login: role-based redirect after login — linguist/reviewer → /qc/queue, others → /
- language_qc._assert_can_approve: enforce two-stage QC; remove linguist self-approve
fallback; require reviewer assignment + submitted_for_review_at (W-6)
- routes_jobs.complete_job: allow project_manager to complete jobs (W-9)
- notify.py: re-enable email notifications (W-7)
- Fix 400 on cue save: treat empty-string audio_description_vtt/captions_vtt as absent
both in backend (truthy check) and frontend (|| undefined) — root cause was adVtt
initialising to '' when job has no AD track
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Two-stage QC workflow: linguist edits + submits → reviewer approves/rejects per language.
New statuses: in_progress, pending_review, in_review. New service functions: submit_for_review,
open_review, assign_reviewer, reassign_reviewer, add_comment. Linguist and reviewer deadlines.
- Reject now resets language to in_progress so linguist can iterate without full re-assignment.
- QC comment threads per language (append-only), visible to all assignees.
- Email notifications via Mailgun on: assignment, submit-for-review, comment, approve, reject.
Best-effort (failures do not roll back QC actions). asyncio.gather for parallel fan-out.
- New audit actions: LANGUAGE_QC_REVIEWER_ASSIGN/REASSIGN, LANGUAGE_QC_SUBMIT,
LANGUAGE_QC_OPEN_REVIEW, LANGUAGE_QC_COMMENT.
- Inline project picker in NewJob: "＋ Create new project…" option with name, default
languages, default linguist, default reviewer. Pre-fills languages on the new job.
- Project model extended with default_languages, default_linguist_id, default_reviewer_id.
- RBAC: CLIENT org-members can now create projects (backend guard relaxed).
- LinguistQueue: role toggle "As linguist / As reviewer" + new status tabs.
- QCDetail: two-slot assignment cards (linguist + reviewer), deadline display, role-aware
action buttons, comments panel with optimistic insert and 15s refetch.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
The function was copy-pasted identically in ingest_and_ai.py and
translate_and_synthesize.py. Extracted to tasks/_websocket_bridge.py
as the single definition; all four task modules now import from there.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- New services/cost_tracker.py: sync httpx preflight()/record() + async wrappers;
BudgetExceeded exception; no-op when COST_TRACKER_BASE_URL is empty
- Preflight budget check added before ingestion (Gemini), per-language translation
(video-native + traditional), and per-language TTS dispatch
- _record_gemini_usage and _record_tts_cost now call cost_tracker directly;
removes broken asyncio.get_event_loop() hack from sync Celery worker
- Fix: _cost_ctx now threaded into extract_accessibility_targeted (video-native path)
- Fix: user_id/cost_project_id now propagated through dispatch_language_tts →
synthesize_cue_task.s() and the rerender_accessible_video.py re-render path
- Remove oliver-cost-tracker SDK dependency (was commented-out/never installed)
- Drop cost_tracker_outbox_path setting and get_cost_tracker() factory
- Update COST_TRACKER_BASE_URL default to optical-dev.oliver.solutions in
.env.prod.example, docker-compose.yml, and all Cloud Run service yamls
- Cloud Run yamls use Secret Manager ref (cost-tracker-api-key) for the API key
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Rewrote VTT translation to two-step (text-only → Gemini → apply to original timestamps) preventing caption timing desync
- Added polling fallback for all processing states and Safari visibilitychange WebSocket reconnect
- Added 11 new TTS languages (cs, da, fi, hu, no, sk, sv, es-419, pt-BR, fr-CA)
- Updated caption/AD prompts to DCMP Captioning Key & Description Key standards (line splitting, ♪ music notation, italic tags, caption positioning, ethics guidelines)
- Added descriptive transcript generation (WCAG 2.1 §1.2.1) combining captions + AD into plain text
- Fixed amix normalize=0 to prevent audio loss in rendered videos
- Fixed AD re-timing double-count when source_ms is None
- Fixed cue block numbering to be 1-based in VttEditor and Timeline Preview
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
**BUG-1 & BUG-2 — Wrong audio plays after re-render / MP3 doesn't match text**
Root cause: audio files were named by index (cue_0.mp3, cue_1.mp3). When a cue
was inserted or deleted, all following indices shifted but old MP3 files kept
their original names, so re-render would play the wrong audio for the wrong cue.
Fix: renamed files to cue_N_CONTENTHASH.mp3 and introduced an ad_cue_manifest
stored in the job document that maps each cue index to its correct GCS URI.
Re-render now reads from the manifest instead of guessing by filename.
Also: editing AD cue text in the VTT editor now automatically queues TTS
regeneration for changed cues — no more silent mismatches.
**BUG-3 — App crash / state desync when uploading VTT or clearing TTS queue**
Fixed handleVttFileUpload to only update local editor state after the server
confirms the save — previously local state was updated first, so a network
error left the UI showing content that wasn't actually saved.
Fixed handleClearRegenerationQueue to only remove items from local state if
the server removal succeeded — previously all items were cleared regardless.
**BUG-4 — AI generates different audio descriptions every time**
Added GenerateContentConfig(temperature=0.2, top_p=0.8, top_k=40) to the
Gemini API call so output is more consistent across runs.
**BUG-5 — On-screen text inconsistently described**
Strengthened the AI prompt rule from a vague suggestion to a mandatory
requirement with an explicit format: "Text on screen reads: [exact text]".
Applied to both gemini_ingestion.md and gemini_ingestion_targeted.md.
**BUG-6 — No notification when re-render finishes**
Added rendering_qc toast notification and a dismissible green banner that
appears in QCDetail when re-render transitions to pending_qc. The banner
auto-dismisses after 10 seconds. Also increased WebSocket reconnect attempts
from 5 to 15 and capped backoff at 60s to prevent falling back to manual refresh.
**BUG-7 — Timeline preview looks accurate but isn't after edits**
Added isStale prop to TimelinePreview. The timeline now shows an amber tint
and "Preview may be outdated" label whenever there are unsaved pause point
changes, pending TTS regenerations, or a new VTT has been uploaded.
**BUG-8 — ElevenLabs API errors break TTS with no fallback**
Added try/except fallback chain in _synthesize_single_cue: if the configured
provider fails, it automatically retries with google, then gemini.
**BUG-9 — Concurrent re-render requests cause race conditions**
Made the PENDING_QC → RENDERING_QC status transition conditional (only
succeeds if the job is still in PENDING_QC). Returns HTTP 409 if a re-render
is already in progress. The completion transition back to PENDING_QC is also
conditional so a cancelled/overridden render doesn't corrupt job state.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
SDH captions extend standard VTT with speaker identification labels,
sound effects [PHONE RINGS], music notation ♪, and off-screen indicators.
- Add sdh_vtt flag to RequestedOutputs model and frontend form
- Add sdh_captions_vtt_gcs field to LangOutput model
- Inject SDH generation instructions into both Gemini prompts via
{SDH_FIELD} and {SDH_GUIDELINES} placeholders when requested
- Upload sdh_captions.vtt to GCS in ingest task
- Pass SDH through video_native translation (Gemini generates it directly)
and traditional translation (translate source SDH VTT via Gemini)
- Expose sdh_captions_vtt in downloads endpoint and bulk zip export
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add brand_context field (job model, API, frontend form) so clients can
list brand names present in their video; Gemini uses these names instead
of generic descriptors (e.g. "Sellotape" not "sticky tape")
- Add ethical guidelines section to both Gemini prompts covering
person-first language, consistent race/gender description only when
plot-relevant, no guessing at unconfirmed identity
- Revamp audio description rules: priority ordering (essential →
high-priority → time-permitting), pre-teaching placement, no cinematic
jargon, succinct style replacing the former "20% longer" instruction
- Thread brand_context through full stack: routes → job doc → ingest
task → translate task → both Gemini prompt templates
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Old pause_points in edit_state always overrode new VTT cue timings
during re-render, making AD VTT upload for timing adjustments
non-functional. Clear pause_points and video_segments on AD VTT
upload so re-render falls back to the new cue start times.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add dynamic ElevenLabs voice catalog with provider toggle in the UI,
allowing users to browse ElevenLabs voices, configure stability and
similarity boost settings, and preview/synthesize with ElevenLabs TTS.
Backend:
- New elevenlabs_voices.py service with 1-hour cached API fetching
- TTS routes support ?provider= query param for voices and options
- Preview endpoint routes to ElevenLabs or Gemini based on provider
- stability/similarity_boost params flow through TTS synthesis pipeline
- TTSPreferences model extended with ElevenLabs-specific fields
- Deprecated hardcoded elevenlabs_voices config (now fetched dynamically)
Frontend:
- Provider toggle (Gemini/ElevenLabs) in VoiceSelector
- ElevenLabsSettingsPanel with stability and similarity boost sliders
- VoicePreviewButton supports provider-specific preview parameters
- API client passes provider param to voices, options, and preview endpoints
- New VoiceInfo, ProviderVoicesResponse, ProviderOptionsResponse types
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Whisper's snap_pause_point() finds the nearest sentence boundary
independently per cue, which can move a later cue's pause_point before
an earlier cue's. The renderer then sorts by pause_point, producing
non-sequential cue indices in the timeline.
Add a forward monotonicity pass (clamp each pause_point >= previous) at
three layers for defense-in-depth:
- whisper_service: Phase 3 after consolidation
- video_renderer: before temporal sort in _render_pause_insert_method
- rerender_accessible_video: in _build_placements_with_adjustments
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When a new AD cue is inserted in the middle of existing cues, the system
now automatically queues TTS regeneration for the new cue AND all cues
that shifted positions. This ensures MP3 file indices stay synchronized
with VTT cue indices, preventing cues from being silently dropped during
re-render.
Changes:
- VttEditor: Add onCueInserted callback to notify parent of insertions
- QCDetail: Track insertion context and queue TTS for all shifted cues
- rerender_accessible_video: Add warning log when cue/MP3 count mismatch
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The re-render task was using pause point coordinates from the accessible
video timeline (which includes freeze frame durations) instead of the
original source video coordinates. This caused pause points to exceed
the source video duration and get clamped incorrectly.
Changes:
- Add source_ms field to PausePointData model to store source video cut point
- Update video_renderer.py to populate source_ms when building pause points
- Update rerender_accessible_video.py to use source_ms for placement calculations
- Apply user adjustments as relative offsets (delta-based adjustment)
- Update API responses and TypeScript types to include source_ms
- Add backward compatibility fallback for jobs without source_ms
Note: Existing jobs need to be re-processed from initial render to populate
the new source_ms field.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The task was created but not imported in the Celery task registry,
causing "Received unregistered task" error when triggering re-render.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Reorder workflow: translations now happen BEFORE QC Review step
- Add language tabs to switch between translated languages in QC
- Add video mode tabs (Original Video / Accessible Video)
- Add interactive timeline preview showing video segments and AD cues
- Enable pause point adjustment with millisecond precision
- Add TTS regeneration queue for selective cue re-synthesis
- Add re-render controls with optional Whisper refinement
- Persist video segments and TTS MP3s to GCS for editability
- Add new RENDERING_QC job status for re-render operations
- Create 5 new API endpoints for accessible video editing
- Add rerender_accessible_video.py Celery task
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Subtitles were appearing progressively out of sync (~1.0s early per AD)
because the VTT retimer calculated freeze durations theoretically
rather than using actual rendered segment durations.
Changes:
- video_renderer: Measure actual freeze segment duration after creation
- video_renderer: Return updated placements with actual_freeze_duration
- vtt_retimer: Prefer actual_freeze_duration over calculated values
- render_task: Pass actual durations to VTT retimer
This ensures subtitle timing matches the real video timeline regardless
of any FFmpeg encoding variations.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
When TTS synthesis fails after 3 retries, the system now:
- Sends problematic cue text to Gemini for TTS-safe rewriting
- Updates the VTT file in GCS with rewritten text
- Retries TTS synthesis with the new text
- Records successful rewrites in job.tts_rewrites field
UI changes:
- JobDetail shows amber caution box with original/rewritten text
- JobsList shows warning icon next to jobs with rewrites
- Error display clarifies text shown is "after rewrite attempt"
Files changed:
- backend/app/models/job.py: Add tts_rewrites field
- backend/app/prompts/gemini_tts_rewrite.md: New prompt template
- backend/app/services/gemini.py: Add rewrite_tts_cue method
- backend/app/tasks/tts_synthesis.py: Add VTT update utilities
- backend/app/tasks/translate_and_synthesize.py: Rewrite+retry logic
- frontend/src/types/api.ts: Add TTSRewriteItem type
- frontend/src/routes/jobs/JobDetail.tsx: Caution display
- frontend/src/routes/jobs/JobsList.tsx: Warning indicator
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The TTS error handling had a bug where failed jobs stayed in
'tts_generating' status instead of being set to 'tts_failed'.
Root cause: synthesize_cue_task used autoretry_for=(Exception,)
which raises the original exception after max retries, not
MaxRetriesExceededError. The exception handler never fired.
Changes:
- tts_synthesis.py: Replace autoretry_for with manual retry logic
that returns a failure dict on final failure instead of raising
- translate_and_synthesize.py: Add propagate=False to group.get()
to safely retrieve all results including failures
- translate_and_synthesize.py: Update outer exception handler to
set job status to tts_failed, store error details, and broadcast
status update via WebSocket
Now TTS failures will:
1. Set job status to 'tts_failed'
2. Store detailed error info (cue index, text, message)
3. Show error in UI with retry button
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Optimize the accessible video workflow by eliminating the dedicated
Gemini video analysis call for pause point estimation. Instead:
- Use AD VTT cue start times as initial pause points for Whisper refinement
- Add user-selectable accessible video method (pause_insert/overlay) at QC approval
- Add bulk approval API endpoint with method selection
- Add method selector UI to QCDetail page
- Add bulk approval modal to QCList for jobs with accessible video
Benefits:
- Eliminates expensive Gemini API call with video upload
- Faster workflow (~5-15 seconds saved per job)
- Cost savings on Gemini video analysis
- User control over accessible video integration method
Backend changes:
- Add accessible_video_method to RequestedOutputs and ApproveSourceRequest
- Add POST /jobs/bulk/approve endpoint
- Replace Gemini call with _build_placements_from_ad_vtt() helper
- Mark analyze_accessible_video_placement() as deprecated
Frontend changes:
- Add method selector radio buttons to QCDetail
- Add bulk approval modal with method selection to QCList
- Update API client and React Query hooks
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Cloud Run services are deployed with --no-allow-unauthenticated,
requiring an ID token in the Authorization header.
- Add _get_cloud_run_id_token() helper using google-auth library
- Update whisper_transcribe.py to include Bearer token in Cloud Run calls
- Update video_renderer.py to include Bearer token in FFmpeg Cloud Run calls
The ID token is fetched using the service account credentials
(GOOGLE_APPLICATION_CREDENTIALS) and targets the Cloud Run service URL.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Migrate CPU-intensive workloads to Cloud Run for autoscaling:
- Add Whisper HTTP service (FastAPI) with /transcribe endpoint
- Add FFmpeg HTTP service (FastAPI) with /encode, /probe, /extract-frame, etc.
- Add Dockerfiles for both services (8 vCPU, 32GB RAM, Gen2)
- Add Cloud Build config for CI/CD deployment
- Add Cloud Run service YAML configs with scale-to-zero
- Update whisper_transcribe.py to call Cloud Run when WHISPER_SERVICE_URL set
- Update video_renderer.py to call Cloud Run when FFMPEG_SERVICE_URL set
- Update whisper_service.py for Cloud Run compatibility (no settings dependency)
- Add ffmpeg_service_url and whisper_service_url to config.py
Services scale 0→N based on request load, falling back to local
execution when service URLs are not configured (hybrid mode).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add RENDER_FAILED job status for when video rendering fails
- Fix _check_accessible_video_completion to detect failures and transition
job status accordingly (was stuck in RENDERING_VIDEO forever)
- Store detailed error info in job.error including failed_languages array
- Call completion check after failures to properly update job status
- Broadcast WebSocket notification on render failures
Frontend:
- Add render_failed to JobStatus type and StatusBadge (red styling)
- Add tts_failed and render_failed to JobsList STATUS_LABELS
- Enhance JobDetail error display with:
- Warning icon and prominent styling
- Error type and message
- Failed languages list with per-language errors
- Timestamp of when error occurred
- Update ProgressIndicator to handle failed states with red dot
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Video-native translation mode now processes all target languages in parallel
using asyncio.gather() with a semaphore (max 3 concurrent) for rate limiting.
This significantly reduces total translation time when multiple languages
are selected.
- Add MAX_CONCURRENT_VIDEO_NATIVE constant for rate limiting
- Refactor video-native path to use parallel coroutines
- Keep traditional VTT translation mode sequential
- Handle per-language errors without stopping other translations
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add a new "Video Native Mode" translation option that re-processes the
video through Gemini for each target language, generating captions and
audio descriptions directly from visual context. This produces more
natural and culturally appropriate content compared to traditional VTT
text translation.
Changes:
- Add translation_mode field to RequestedOutputs (video_native | traditional)
- Create gemini_ingestion_targeted.md prompt for target language generation
- Add extract_accessibility_targeted() method to Gemini service
- Modify translate_and_synthesize task to handle both translation modes
- Add Translation Mode UI selector in NewJob screen (video_native is default)
- Remove transcreation UI (replaced by video_native mode)
- Remove Google Translate service (replaced by Gemini translation)
- Add LanguageSelector component with searchable dropdown
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Break out TTS synthesis into a dedicated Celery worker (tts queue) with
concurrency=8 for parallel processing. Each AD cue is now synthesized as
a separate task, enabling up to 8 cues to be processed simultaneously.
Key changes:
- Add tts_synthesis.py with synthesize_cue_task for per-cue synthesis
- Refactor translate_and_synthesize.py to dispatch cue tasks in parallel
- Add tts-worker service to docker-compose.yml (concurrency=8)
- Add Cloud Run service config for production deployment
Benefits:
- Parallel synthesis even for single jobs (e.g., 50 cues → 8 concurrent)
- Natural rate limiting across multiple concurrent jobs
- Fault tolerance with per-cue retries and GCS persistence
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Completely rewrites the Whisper-based pause point refinement to use
a two-phase approach with explicit ordering:
Phase 1 - Individual refinement:
1. Check if pause point is "during speaking" (words within ±2s)
- If NOT during speaking → use Gemini's exact point, no overlap
2. If during speaking, find nearest sentence boundary
3. Apply appropriate buffering based on context:
- Case A: First sentence → pause 500ms before sentence starts
- Case B: Last sentence → pause 500ms after sentence ends
- Case C: Between sentences → full double buffer (overlap)
Phase 2 - Consolidation (after all refinements):
- Consolidate cues within 5s of each other to play back-to-back
Key changes:
- Add SentenceBoundary dataclass for tracking boundaries with context
- Add _is_during_speaking() helper to detect speech proximity
- Add _find_sentence_boundaries() with longest-gap fallback
- Rewrite snap_pause_point() with new ordered algorithm
- Update refine_all_pause_points() to pass words and use two phases
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Remove the cached transcript lookup - always run a fresh Whisper
transcription for each accessible video render. This ensures we get
accurate word timestamps for the current video file.
The transcript is still saved to the job document for debugging and
auditing purposes, but it will never be read back for reuse.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Changed the Whisper transcription to run on dedicated whisper-worker
using the same dispatch pattern as FFmpeg:
1. apply_async() to dispatch to the whisper queue
2. Poll with ready() using async sleep to avoid blocking
3. Use allow_join_result() context manager
4. Get result only after task is ready
This ensures Whisper runs with concurrency=1 on a dedicated worker
to prevent memory overload while still allowing the render task
to wait for results without deadlocking.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Celery does not allow calling result.get() within a task as it causes
deadlocks. Changed the implementation to run Whisper transcription
directly using asyncio.to_thread() instead of dispatching to a separate
Celery queue.
The Whisper transcript is still cached in MongoDB for reuse across
language variants.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements word-level speech analysis using faster-whisper to refine
AD pause points. Gemini's timestamps are snapped to natural speech gaps
(sentence/phrase boundaries) to prevent pauses mid-word.
Key changes:
- Add WhisperService for transcription and gap detection
- Add dedicated Celery task routed to 'whisper' queue
- Integrate refinement into render_accessible_video task
- Cache Whisper transcripts in MongoDB for reuse across languages
- Add dedicated whisper-worker with concurrency=1 to prevent OOM
Configuration:
- Uses faster-whisper 'base' model (multilingual, ~145MB)
- 5-second search window after Gemini's recommended point
- Falls back to original timestamp if no gap found
Infrastructure:
- New Docker stage: whisper-worker
- New Cloud Run service: accessible-video-whisper-worker
- Updated docker-compose.yml with whisper-worker service
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Previously only the final pending_qc status was broadcast via WebSocket.
Now all intermediate status changes (ingesting, ai_processing) are also
broadcast so the frontend can update in real-time during reprocessing.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
When jobs with accessible video option enabled enter video rendering
phase, the status now transitions to 'rendering_video' so users can
see why processing is taking longer. This provides better visibility
into the video rendering pipeline.
Changes:
- Added RENDERING_VIDEO status to JobStatus enum
- Updated render_accessible_video task to set new status
- Added status display to StatusBadge, jobStatusMessages
- Included new status in JobsList Translation filter group
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Modified render_accessible_video.py to explicitly pass TMPDIR to
tempfile.TemporaryDirectory() so files are created in shared volume
- Updated docker-compose.yml to run containers as root initially,
chown /shared-tmp to app:app, then switch to app user for celery
- This ensures both worker containers can access the same temp files
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add a dedicated Celery queue (ffmpeg) with concurrency=1 to serialize
all FFmpeg operations. This prevents CPU spikes when multiple render
tasks run in parallel with multiple languages.
Changes:
- Add ffmpeg_operations.py with run_ffmpeg_command and run_ffprobe_command tasks
- Update VideoRendererService to dispatch ffmpeg commands via the queue
- Add ffmpeg-worker service to docker-compose with --concurrency=1
- Configure main worker to exclude the ffmpeg queue
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
