- Expanded runs now show horizontal stage tabs (Segment→Extract→Classify→Synthesize→Embed)
- Each tab has status indicator dot (idle/running/done/error) with pulse animation
- Clicking a tab shows that stage's events with summary stats (LLM calls, tokens, duration)
- Error events auto-expanded with monospace error detail block
- Auto-selects the error stage or latest active stage on expand
- Renamed 'stale pages' to 'orphaned pages' in admin header
Deletes all technique pages, versions, links, key moments, pipeline
events/runs, Qdrant vectors, and Redis cache while preserving creators,
videos, and transcript segments. Resets all video status to not_started.
Double-confirm dialog in the UI prevents accidental use.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Drops prompt iteration cycles from 20-30 min to under 5 min by enabling
stage-isolated re-runs and offline prompt testing against exported fixtures.
Phase 1: Offline prompt test harness
- export_fixture.py: export stage 5 inputs from DB to reusable JSON fixtures
- test_harness.py: run synthesis offline with any prompt, no Docker needed
- promote subcommand: deploy winning prompts with backup and optional git commit
Phase 2: Classification data persistence
- Dual-write classification to PostgreSQL + Redis (fixes 24hr TTL data loss)
- Clean retrigger now clears Redis cache keys (fixes stale data bug)
- Alembic migration 011: classification_data JSONB column + stage_rerun enum
Phase 3: Stage-isolated re-run
- run_single_stage Celery task with prerequisite validation and prompt overrides
- _load_prompt supports per-video Redis overrides for testing custom prompts
- POST /admin/pipeline/rerun-stage/{video_id}/{stage_name} endpoint
- Frontend: Re-run Stage modal with stage selector and prompt override textarea
Phase 4: Chunking inspector
- GET /admin/pipeline/chunking/{video_id} returns topic boundaries,
classifications, and synthesis group breakdowns
- Frontend: collapsible Chunking Inspector panel per video
Phase 5: Prompt deployment & stale data cleanup
- GET /admin/pipeline/stale-pages detects pages from older prompts
- POST /admin/pipeline/bulk-resynthesize re-runs a stage on all completed videos
- Frontend: stale pages indicator badge with one-click bulk re-synth
Phase 6: Automated iteration foundation
- Quality CLI --video-id flag auto-exports fixture from DB
- POST /admin/pipeline/optimize-prompt/{stage} dispatches optimization as Celery task
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- _make_llm_callback now accepts request_params dict
- All 6 LLM call sites pass max_tokens, model_override, modality, response_model, hard_limit
- request_params stored in payload JSONB on every llm_call event (always, not just debug mode)
- Frontend JSON export includes full payload + request_params at top level
- DebugPayloadViewer shows 'Request Params' section even with debug mode off
- Answers whether max_tokens is actually being sent on pipeline requests
In-progress stages now show:
- Live elapsed time (ticks every second) next to the active stage dot
- Run-level token count so far
Performance: wrapped StageTimeline, StatusFilter, WorkerStatus, and
RecentActivityFeed with React.memo. Memoized filteredVideos with useMemo.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Filters video list by filename or creator name as you type. Works
alongside the existing status and creator dropdown filters. Includes
a clear button when text is entered.
Stage 3 (extraction) LLM calls now show the topic group label (e.g.,
'Sound Design Basics') and Stage 5 (synthesis) calls show the category
name. Displayed as a cyan italic label in the event row between the
event type badge and model name. Helps admins understand why there are
multiple LLM calls per stage.
Data model:
- New pipeline_runs table (id, video_id, run_number, trigger, status,
started_at, finished_at, error_stage, total_tokens)
- pipeline_events gains run_id FK (nullable for backward compat)
- Alembic migration 010_add_pipeline_runs
Backend:
- run_pipeline() creates a PipelineRun, threads run_id through all stages
- _emit_event() and _make_llm_callback() accept and store run_id
- Stage 6 (final) calls _finish_run() to mark complete with token totals
- mark_pipeline_error marks run as error
- Revoke marks running runs as cancelled
- Trigger endpoints pass trigger type (manual, clean_reprocess)
- New GET /admin/pipeline/runs/{video_id} — lists runs with event counts
- GET /admin/pipeline/events supports ?run_id= filter
Frontend:
- Expanded video detail now shows RunList instead of flat EventLog
- Each run is a collapsible card showing: run number, trigger type,
status badge, timestamps, token count, event count
- Latest run auto-expands, older runs collapsed
- Legacy events (pre-run-tracking) shown as separate collapsible section
- Run cards color-coded: cyan border for running, red for error,
gray for cancelled
- EventLog accepts optional runId prop to scope events to a single run
Previously the event log only loaded once when the row was expanded,
so mid-pipeline videos only showed start events. Now the EventLog
component accepts a status prop and polls every 10s when the video is
processing or queued, silently updating without showing a loading spinner.
- Backend: Video list now includes active_stage, active_stage_status, and
stage_started_at fields via DISTINCT ON subquery
- Backend: New GET /admin/pipeline/recent-activity endpoint returns
latest stage completions/errors with video context
- Frontend: 15-second auto-refresh with change detection — video rows
flash when status changes
- Frontend: Stage timeline dots on processing/complete/error videos
showing progress through stages 2-5, active stage pulses
- Frontend: Collapsible Recent Activity feed at top showing last 8
stage completions/errors with duration and creator
- Frontend: Bulk operation scrollable log showing per-video results
as they complete
- Frontend: Auto-refresh checkbox toggle in header
- Backend: POST /admin/pipeline/clean-retrigger/{video_id} endpoint that
deletes pipeline_events, key_moments, transcript_segments, and Qdrant
vectors before retriggering the pipeline
- Backend: QdrantManager.delete_by_video_id() for vector cleanup
- Frontend: Creator filter dropdown on pipeline admin page
- Frontend: Checkbox selection column with select-all
- Frontend: Bulk toolbar with Retrigger Selected and Clean Reprocess
actions, sequential dispatch with progress bar, cancel support
- Bulk dispatch uses 500ms delay between requests to avoid slamming API
773 key moments sat at 'pending' with 0 approved/edited/rejected.
review_status was never checked by any public-facing query — all content
was always visible regardless of review state.
Removed:
- backend/routers/review.py (10 endpoints)
- backend/tests/test_review.py
- frontend ReviewQueue, MomentDetail pages
- frontend client.ts (review-only API client)
- frontend ModeToggle, StatusBadge components
- Review link from AdminDropdown, Moments link from pipeline rows
- ReviewStatus, PageReviewStatus enums from models
- review_mode config flag
- review_status columns (migration 007)
- ~80 lines of mode-toggle CSS
Pipeline now always sets processing_status to 'published'.
Migration 007 drops columns, enums, and migrates 'reviewed' → 'published'.
TechniquePage's 'Inspect pipeline' button passes ?video=<id> to AdminPipeline.
Previously the query param was ignored. Now AdminPipeline reads it on mount,
auto-expands the matching video row, and smooth-scrolls it into view.
