GET /admin/pipeline/embed-status/{video_id} returns technique pages
linked to the video, Qdrant vector count, and last stage 6 event —
provides data for the currently non-functional Embed tab in admin UI.
- Added avatar_url, avatar_source, avatar_fetched_at columns to Creator
model with Alembic migration 014
- New backend/services/avatar.py — TheAudioDB lookup with token-based
name similarity scoring and genre overlap bonus
- New Celery task fetch_creator_avatar for background avatar fetching
- Admin endpoints: POST /creators/{id}/fetch-avatar (single) and
POST /creators/fetch-all-avatars (batch for missing avatars)
- Wired avatar_url into CreatorRead, CreatorInfo, and CreatorBrowseItem
schemas so all API responses include avatar data
- Rewrote stale-pages endpoint to use a single query with row_number
window function instead of per-page queries for latest version + creator
- Added optional offset/limit/status/creator_id params to videos endpoint
(backward compatible — defaults return all results)
- Added 1-hour Redis cache to _find_dynamic_related technique scoring
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>
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
Deleting transcript_segments left the pipeline with nothing to process —
all stages would skip immediately. Segments come from the ingest step,
not from pipeline stages 2-6. Only pipeline_events and key_moments
(pipeline output) are deleted during clean reprocess.
- 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
