Pause points were being stored with source video timestamps instead of
rendered video timeline coordinates. This caused misalignment between
the pause point markers and freeze frame segments in the timeline UI.
Now pause points are calculated from the freeze frame segment start
positions in the rendered timeline, ensuring they align correctly
with the AD audio segments.
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>
The previous implementation incorrectly used _get_video_duration which
in Cloud Run mode uses the cached source video URI instead of actually
measuring the freeze segment files. This caused all freeze segments to
report the source video duration (~78s) instead of their actual duration.
Changed to use _get_video_duration_local directly since freeze segments
are local files and need to be measured directly via ffprobe.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
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>
Replace sequential browser-based bulk download with server-side zip
generation. When users select "Download All Files" from bulk actions,
the system now creates a single organized .zip file containing all
job assets.
Changes:
- Add POST /jobs/bulk/download endpoint that streams zip to client
- Add BulkDownloadRequest schema for the new endpoint
- Create zip_download.py service with streaming zip generation
- Update frontend to call new endpoint and download single zip file
- Organize files in zip by job title and language subdirectories
Zip structure:
accessible_video_YYYYMMDD_HHMMSS.zip
└── {job_title}/
├── source.mp4
└── {lang}/
├── captions.vtt
├── ad.vtt
├── ad.mp3
├── accessible_video.mp4
└── accessible_captions.vtt
🤖 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>
Use context manager for AsyncClient instead of caching on singleton.
Each asyncio.run() creates a new event loop, so cached clients bound
to previous event loops fail when reused across jobs.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Changed from httpx.Client (sync) to httpx.AsyncClient so that
asyncio.gather() actually executes HTTP calls in parallel instead
of blocking the event loop sequentially.
Before: ~5 min for 18 segments (serial HTTP calls despite gather)
After: ~30 sec for 18 segments (truly parallel HTTP calls)
Changes:
- _http_client: httpx.Client -> httpx.AsyncClient
- _call_cloud_run_probe: sync -> async
- _call_cloud_run_endpoint: sync -> async
- Added await to all Cloud Run HTTP calls
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Refactored _render_pause_insert to execute FFmpeg operations in parallel
phases instead of sequentially:
Phase 1: Parallel extraction
- Generate shared silence (once, reused by all)
- Extract ALL video segments simultaneously
- Extract ALL freeze frames simultaneously
- Extract final segment
Phase 2: Parallel audio concatenation
- Concatenate ALL audio tracks (silence + AD + silence) simultaneously
Phase 3: Parallel freeze segment creation
- Create ALL freeze segments simultaneously
Phase 4: Assemble segments in correct order for final concatenation
This reduces render time from ~3 minutes (serial) to ~30 seconds (parallel)
for an 8-cue video when using Cloud Run FFmpeg service.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The /run-ffmpeg Cloud Run endpoint expects command_template field with
ffmpeg command placeholders, not ffmpeg_args. This fixes 422 validation
errors when generating silence audio via Cloud Run.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The /probe endpoint expects 'gcs_uri' but we were sending 'source_gcs_uri'.
Fixed to match the ProbeRequest model in ffmpeg_http_service.py.
🤖 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 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>
Add comprehensive error handling for TTS synthesis failures:
Backend:
- Add TTS_FAILED status to JobStatus enum for failed synthesis jobs
- Add TTSSynthesisError exception with cue index and context tracking
- Improve null-safe error handling in Gemini TTS response parsing
- Add _synthesize_cue_with_retry() with exponential backoff (3 attempts)
- Enhanced error logging with text preview and model context
Frontend:
- Add TTS_FAILED status styling (red badge) in StatusBadge component
- Add tts_failed to JobStatus TypeScript type
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The VTT retimer had two bugs causing subtitles to display during freeze
periods and become out of sync:
1. Same offset applied to both start and end times (should differ when
pause falls between them)
2. Cues spanning pause points weren't split (causing captions during freeze)
Changes:
- Add _offset_at() for timestamps AT or AFTER pause points
- Add _offset_before() for timestamps STRICTLY BEFORE pause points
- Add _retime_cue() to split cues at pause points into multiple segments
- Add _filter_short_segments() to remove <100ms segments after splitting
- Rewrite retime_for_pause_insert() to use new helper methods
Example fix for cue 8s-12s with pause at 10s (4s freeze):
- Before: 8s-12s (displayed during freeze!)
- After: 8s-10s + 14s-16s (gap during AD)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Replace complex overlap/catch-up logic with simpler approach:
- Snap pause points to midpoint between sentences (not sentence boundaries)
- Add 500ms silence before AND after AD audio during freeze frame
- Resume playback from same midpoint (no overlap, no visual jump-back)
This eliminates audio/visual anomalies caused by the previous algorithm's
complexity around sentence boundary snapping and audio catch-up.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Get video duration BEFORE the render loop (not after)
- Clamp pause_point to 100ms before video end if it exceeds duration
- Add validation in _extract_frame() to verify frame was created
- Add debug logging for frame extraction timestamps
This prevents "Frame file not found" errors when pause points
calculated by Whisper refinement exceed the source video duration.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
When a pause point falls between two sentences, the previous algorithm
created a visual jump-back where the video rewound to resume_from after
the AD played. This was distracting to viewers.
New behavior:
- Video plays normally to pause_point
- Freeze frame shows + AD audio plays
- Freeze frame CONTINUES while source audio from [resume_from, pause_point]
plays (the "catch-up" audio)
- Video resumes smoothly from pause_point (no visual jump)
The audio from the overlap region plays twice (once during video, once
during freeze extension) but this is acceptable as it's typically <1s
and provides natural audio context around the AD.
Implementation:
- Add _extract_audio_segment() to extract catch-up audio from source
- Add _concatenate_audio() to join AD + catch-up audio
- Modify render loop to create extended freeze segments with combined audio
- Resume video from pause_point instead of resume_from
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Show last 1500 chars of stderr instead of first 500 to capture actual
error messages (FFmpeg writes version banner first, errors at end)
- Add validation for freeze segment creation:
- Check duration > 0
- Verify frame and audio files exist
- Add debug logging for parameters
This helps diagnose FFmpeg failures that were previously showing only
version/configuration info instead of the actual error.
🤖 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>
Previously, all consolidated cues shared the same pause_point AND
resume_from, which caused the overlap video segment to play between
each AD cue in a consolidated group.
Now consolidated cues are treated as a single AD segment:
- All cues in a group share the same pause_point (front buffer once)
- Only the LAST cue keeps resume_from (back buffer once)
- Other cues have resume_from = pause_point (no video between ADs)
This ensures consolidated ADs play seamlessly back-to-back:
- Video plays up to pause_point (front buffer)
- AD_1 plays
- AD_2 plays immediately (no video)
- AD_n plays immediately (no video)
- Video resumes from resume_from (back buffer)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
When the Whisper analysis detects no speech near a Gemini-recommended
pause point, skip the full-gap-overlap algorithm and use the exact
pause point with no overlap (pause_point == resume_from).
This handles cases where Gemini chose a pause point in a silent or
music-only section of the video - there's no dialogue to buffer
around, so we simply pause and resume at the exact same point.
Three outcomes now in snap_pause_point():
1. No speech nearby → exact pause point, no overlap, no warning
2. Speech but no sentence break → warning (existing behavior)
3. Sentence break found → full-gap-overlap (existing behavior)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Changes pause point calculation to use the entire gap between sentences
as a buffer on BOTH sides of the audio description:
- pause_point: Just BEFORE next sentence starts (gap.end - 50ms)
- resume_from: Just AFTER previous sentence ends (gap.start + 50ms)
This means a small portion of video plays twice (the gap duration), but
creates a much more natural listening experience by maximizing the
breathing room around audio descriptions.
Changes:
- whisper_service.py: snap_pause_point() now returns (pause_point, resume_from)
- video_renderer.py: Uses resume_from for current_time after freeze segment
- vtt_retimer.py: Calculates effective_offset including overlap duration
- accessible_video.py: Added resume_from field to ADPlacementCue schema
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Logs pause point placements, segment creation, and final segment
calculation to help diagnose the 30s black footage issue.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Instead of a fixed 175ms buffer, the pause point is now placed
halfway between the end of the sentence and the start of the
next word. If the half-gap exceeds 2 seconds, uses 500ms instead.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Dynamically detects CPU count with os.cpu_count() instead of
hardcoded 4 threads. Falls back to 4 if detection fails.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Log model name explicitly when loading and transcribing
- Log model load time
- Log transcription processing time
- Helps verify correct model is being used
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
If consecutive AD cues have pause points within 5 seconds, they now
play back-to-back at the same pause point. This prevents AD from being
inserted mid-sentence when cues are close together.
Adds _consolidate_close_cues() method and consolidation_threshold
parameter to refine_all_pause_points().
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Increases the search window from ±10s to ±20s to maximize the chance
of finding a proper sentence ending and avoid falling back to Gemini's
potentially imprecise pause points.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
When the first AD cue (index 0) cannot find a sentence boundary within
the ±10s search window, insert the AD at T=0:00 instead of using the
potentially mid-sentence Gemini pause point.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Update Gemini prompt to require transcription with precise timestamps
- Add sentence_boundaries output field for validation
- Add pause_point_rationale field to explain each pause point choice
- Emphasize terminal punctuation only (., ?, !) - never commas
- Expand Whisper search window from ±5s to ±10s
- Increase post-pause buffer from 50ms to 175ms
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Updated pause point algorithm:
- Search range: 5 seconds BEFORE to 5 seconds AFTER Gemini pause point
- ONLY considers sentence breaks (after periods, !, ?) - not phrase breaks
- Chooses the closest sentence break to the Gemini pause point
This ensures audio descriptions are inserted at natural sentence
boundaries, not in the middle of sentences after commas.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The pause point algorithm was snapping to gap.end (start of next word),
which caused the first word after the pause to be cut off. Changed to
snap to gap.start (end of previous word) instead.
Now the video pauses right after a word finishes, the AD plays during
the silence gap, and the next word plays in full when video resumes.
🤖 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>
Celery doesn't allow calling result.get() within a task by default to
prevent deadlocks. Use allow_join_result() context manager since we've
already confirmed the task is complete via ready() polling.
🤖 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>
- Add validation for accessible_video_gcs (file exists, size 0.1MB-5GB)
- Add validation for retimed_captions_vtt_gcs when accessible video exists
- Add AD Videos count to asset validation panel
- Include retimed captions in VTT file count
- Remove AI confidence from validation panel and backend checks
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Update _get_video_properties() to extract audio sample_rate, channels,
and pix_fmt in addition to video properties
- Add _extract_segment_reencoded() for frame-accurate cuts using
re-encoding instead of stream copy (fixes keyframe-only cut limitation)
- Add _create_freeze_segment_matched() to enforce source audio property
matching (fixes silent pauses caused by sample rate mismatch)
- Update _render_pause_insert_method() to use new methods with uniform
encoding parameters
- Add -video_track_timescale 90000 for consistent timebase across segments
Root causes fixed:
1. -c copy could only cut at keyframes, causing audio dropouts
2. Sample rate mismatch (48kHz source vs 44.1kHz MP3) caused silent
freeze-frame segments when concatenated
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add new deliverable type that renders video with audio descriptions embedded.
Supports two AI-determined methods:
- Direct Overlay: ducks original audio and overlays AD TTS (for minimal dialogue)
- Pause-Insert: freeze-frame video, insert AD, re-time subtitles (for significant dialogue)
Backend:
- Add Pydantic schemas for Gemini analysis response
- Add Gemini prompt and analyze_accessible_video_placement() method
- Add video_renderer.py service using FFmpeg for both rendering methods
- Add vtt_retimer.py service for pause-insert subtitle adjustment
- Add render_accessible_video.py Celery task
- Modify TTS service to return individual per-cue segments
- Update translate_and_synthesize.py to save segments and trigger rendering
- Update download endpoint to include accessible video outputs
Frontend:
- Add accessible_video_mp4 checkbox to NewJob form
- Update TypeScript types for new deliverable
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add model selection (flash vs pro) for quality control
- Add speed slider (0.5x - 2.0x) for pacing adjustment
- Add style presets (neutral, calm, energetic, professional, warm, documentary)
- Add custom style prompt option for advanced customization
- New /tts/options endpoint returns available TTS options
- Voice preview now tests all settings so users hear exact output
- Backward compatible: all new fields have sensible defaults
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add Gemini TTS service with 30 voices and 24 languages
- Add TTS API endpoints for voice listing and preview
- Add per-language voice selection in job creation form
- Add voice override at QC approval stage
- Add VoiceSelector and VoicePreviewButton components
- Update TTSPreferences model with provider and voice mapping
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Change model from gemini-2.5-pro to gemini-3-pro-preview
- Upgrade google-genai package from ^1.31.0 to ^1.56.0
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Upload form now has "English / Different language" radio with optional language hint
- Gemini auto-detects language and saves outputs to outputs.{detected_language}
- QC review dynamically loads/saves VTT for source language
- New APPROVED_SOURCE status for non-English videos (APPROVED_ENGLISH kept for backwards compat)
- Translation pipeline reads from source language and passes source_language to Google Translate
- All existing English jobs continue to work unchanged
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
