{"type":"thinking_level_change","id":"eeaf2a6c","parentId":null,"timestamp":"2026-03-30T18:57:21.095Z","thinkingLevel":"medium"}
{"type":"model_change","id":"8abdd2d6","parentId":"eeaf2a6c","timestamp":"2026-03-30T18:57:21.097Z","provider":"anthropic","modelId":"claude-opus-4-6"}
{"type":"custom_message","customType":"gsd-auto","content":"You are executing GSD auto-mode.\n\n## Working Directory\n\nYour working directory is `/home/aux/projects/content-to-kb-automator`. All file reads, writes, and shell commands MUST operate relative to this directory. Do NOT `cd` to any other directory.\n\nAll relevant context has been preloaded below — start working immediately without re-reading these files.\n\n## Requirements Advanced\n\nNone.\n\n## Requirements Validated\n\nNone.\n\n## Requirements Invalidated or Re-scoped\n\nNone.\n\n## UNIT: Research Slice S02 (\"Debug Payload Viewer — Inline View, Copy, and Export in Admin UI\") — Milestone M007\n\n## Inlined Context (preloaded — do not re-read these files)\n\n### Milestone Roadmap\nSource: `.gsd/milestones/M007/M007-ROADMAP.md`\n\n# M007: \n\n## Vision\nMake the pipeline fully transparent — every LLM call's full prompt and response viewable, copyable, exportable, with per-stage token accounting. Automate transcript ingestion via folder monitoring instead of manual POST. Tighten the admin UX: prune dead weight, improve workflow clarity. Fix frontend overflow and mobile responsiveness bugs. Set the foundation for iterating on content quality through better visibility into what the LLM is actually doing.\n\n## Slice Overview\n| ID | Slice | Risk | Depends | Done | After this |\n|----|-------|------|---------|------|------------|\n| S01 | Pipeline Debug Mode — Full LLM I/O Capture and Token Accounting | medium | — | ✅ | Toggle debug mode on for a video, trigger pipeline, see full prompt + response stored for every LLM call with per-stage token breakdown |\n| S02 | Debug Payload Viewer — Inline View, Copy, and Export in Admin UI | low | S01 | ⬜ | Admin clicks an LLM call event, sees full prompt and response in a readable viewer, copies to clipboard, or downloads as JSON |\n| S03 | Transcript Folder Watcher — Auto-Ingest Service | medium | — | ⬜ | Drop a transcript JSON into the watch folder on ub01 → file is detected, validated, POSTed to /ingest, pipeline triggers automatically |\n| S04 | Admin UX Audit — Prune, Streamline, and Polish | low | S02 | ⬜ | Admin pipeline page is cleaner and more efficient for daily content management. Dead UI elements removed. Workflow improvements visible. |\n| S05 | Key Moment Card Text Overflow Fix | low | — | ⬜ | Key moment cards with long filenames and timestamp ranges display cleanly — text truncated with ellipsis or wrapped within card bounds, no horizontal bleed |\n| S06 | Mobile Viewport Overflow Fix — Technique Pages and Global Content | low | S05 | ⬜ | Technique page on Galaxy S25 Ultra renders cleanly — body text wraps, tags don't overflow, metadata stays within viewport, no horizontal scroll |\n\n---\n\n### Decisions\nSource: `.gsd/DECISIONS.md`\n\n# Decisions Register\n\n<!-- Append-only. Never edit or remove existing rows.\n     To reverse a decision, add a new row that supersedes it.\n     Read this file at the start of any planning or research phase. -->\n\n| # | When | Scope | Decision | Choice | Rationale | Revisable? | Made By |\n|---|------|-------|----------|--------|-----------|------------|---------|\n| D001 |  | architecture | Storage layer selection | PostgreSQL for structured data, Qdrant (existing instance at 10.0.0.10) for vector embeddings, local filesystem for transcript JSON files | Spec specifies PostgreSQL for JSONB support and Qdrant already running on hypervisor. File store on local filesystem organized by creator slug. Qdrant gets a dedicated collection, not a new instance. | Yes | collaborative |\n| D002 |  | architecture | Timestamp handling for asyncpg with TIMESTAMP WITHOUT TIME ZONE columns | Use datetime.now(timezone.utc).replace(tzinfo=None) in _now() helper | asyncpg rejects timezone-aware datetimes for TIMESTAMP WITHOUT TIME ZONE columns. Stripping tzinfo at the application layer preserves UTC semantics while staying compatible with the existing schema. | Yes | agent |\n| D003 |  | requirement | R002 Transcript Ingestion API status | validated | 6 passing integration tests prove the full POST /api/v1/ingest flow: creator auto-detection, SourceVideo upsert, TranscriptSegment bulk insert, raw JSON persistence, idempotent re-upload, and invalid input rejection. | Yes | agent |\n| D004 |  | architecture | Sync vs async approach for Celery worker pipeline tasks | Use sync openai.OpenAI, sync QdrantClient, and sync SQLAlchemy (create_engine with psycopg2) inside Celery tasks. Convert DATABASE_URL from postgresql+asyncpg:// to postgresql:// for the sync engine. | Celery workers run in a synchronous context. Using asyncio.run() inside tasks risks nested event loop errors with gevent/eventlet workers. Using sync clients throughout eliminates this class of bug entirely. The async engine/session from database.py is only used by FastAPI (ASGI); the worker gets its own sync engine. | Yes | agent |\n| D005 |  | architecture | Embedding/Qdrant failure handling strategy in pipeline | Embedding/Qdrant failures (stage 6) log errors but do not fail the pipeline. Processing_status is set by stages 2-5 only. Embeddings can be regenerated by manual re-trigger. | Qdrant is at 10.0.0.10 on the hypervisor network and may not be reachable during all pipeline runs. Making embedding a non-blocking side-effect ensures core pipeline output (KeyMoments, TechniquePages in PostgreSQL) is never lost due to vector store issues. The manual re-trigger endpoint allows regenerating embeddings at any time. | Yes | agent |\n| D006 |  | requirement | R013 Prompt Template System status | validated | 4 prompt template files in prompts/ directory loaded from configurable settings.prompts_path. Templates use XML-style content fencing. Pipeline stages read templates from disk at runtime, enabling edits without code changes. Manual re-trigger endpoint (POST /api/v1/pipeline/trigger/{video_id}) allows re-processing after prompt edits. | Yes | agent |\n| D007 | M001/S04 | architecture | Runtime review mode toggle persistence mechanism | Store review mode toggle in Redis key `chrysopedia:review_mode` with async redis client. Fall back to `settings.review_mode` config default when key is absent. | The config.py `review_mode` setting is loaded via lru_cache from environment variables and cannot be mutated at runtime. Redis is already used by the project (Celery broker, stage 4 classification data) so it adds no new infrastructure. A system_settings DB table would work but Redis is simpler for a single boolean toggle on a single-admin tool. The pipeline's stages.py reads settings.review_mode from config — the admin toggle only affects new pipeline runs if stages.py is updated to check Redis too, but that's deferred since the toggle is primarily a UI-level concept for the review queue. | Yes | agent |\n| D008 | M001/S04 | requirement | R004 Review Queue UI status | validated | All R004 capabilities delivered and verified: 9 API endpoints (approve, reject, edit, split, merge, queue list, stats, mode get/set) with 24 passing integration tests covering happy paths and error boundaries. React+TypeScript frontend with queue page (filter tabs, stats, pagination), moment detail page (all review actions with modals), and review-vs-auto mode toggle. Frontend builds with zero TypeScript errors. | Yes | agent |\n| D009 | M001/S05 | architecture | Async search service pattern for FastAPI request path | Create a separate `SearchService` class using `openai.AsyncOpenAI` and `qdrant_client.AsyncQdrantClient` for the search endpoint. Keep existing sync `EmbeddingClient` and `QdrantManager` for Celery pipeline. Search endpoint has 300ms timeout on embedding API and falls back to SQL ILIKE keyword search on Qdrant/embedding failure. | The existing EmbeddingClient and QdrantManager are sync (using `openai.OpenAI` and `QdrantClient`) because Celery tasks run synchronously. FastAPI request handlers are async — reusing sync clients would block the event loop. Creating a thin async wrapper avoids modifying the battle-tested pipeline code while providing non-blocking search. The 300ms timeout and keyword fallback ensure the search endpoint always returns results, even when Qdrant or the embedding service is degraded. | Yes | agent |\n| D010 | M001/S05 | requirement | R005 Search-First Web UI status | validated | Search endpoint (GET /api/v1/search) with async embedding + Qdrant + keyword fallback implemented and tested. Frontend Home.tsx has prominent search bar with 300ms debounced typeahead, scope toggle via URL params, nav cards for Topics/Creators, Recently Added section. SearchResults.tsx displays grouped results. 5 integration tests verify search happy path, empty query, keyword fallback, scope filter, and no-results. Frontend production build succeeds with zero TypeScript errors. | Yes | agent |\n| D011 | M001/S05 | requirement | R006 Technique Page Display status | validated | TechniquePage.tsx renders all specified sections: header with topic_category badge and topic_tags pills, creator name linked to creator detail, source_quality indicator, amber banner for unstructured content, body_sections JSONB prose (handles both string and object values), key moments index ordered by start_time, signal chains, plugins pill list, and related techniques links. Backend GET /api/v1/techniques/{slug} returns full detail with eager-loaded key_moments and related links. 404 for unknown slug tested. | Yes | agent |\n| D012 | M001/S05 | requirement | R007 Creators Browse Page status | validated | CreatorsBrowse.tsx implements genre filter pills, type-to-narrow name filter, sort toggle (Random default/A-Z/Views). Each creator row shows name, genre tags, technique_count, video_count. Links to CreatorDetail page. Backend GET /api/v1/creators supports sort=random\\|alpha\\|views and genre filter. Integration tests verify random sort, alpha sort, genre filter, detail endpoint, 404, and counts. | Yes | agent |\n| D013 | M001/S05 | requirement | R008 Topics Browse Page status | validated | TopicsBrowse.tsx renders two-level topic hierarchy (6 categories from canonical_tags.yaml with expandable sub-topics showing technique_count and creator_count). Filter input narrows categories/sub-topics. Clicking sub-topic navigates to search with scope=topics. Backend GET /api/v1/topics aggregates counts from DB per sub-topic. Integration test verifies topic hierarchy response shape. | Yes | agent |\n| D014 | M001/S05 | requirement | R014 Creator Equity status | validated | CreatorsBrowse.tsx defaults to sort=random. Backend uses func.random() ORDER BY for randomized sort. Integration test verifies random sort returns all creators (order may vary). All creators get equal visual weight in the UI — no featured/highlighted treatment. Equal-weight row layout confirmed in CSS. | Yes | agent |\n| D015 | M002/S01 | architecture | Docker network subnet for Chrysopedia on ub01 | 172.32.0.0/24 — free on ub01, replaces 172.24.0.0/24 which is used by xpltd_docs_default | 172.24.0.0/24 was already allocated to xpltd_docs_default network on ub01. Scanned all existing subnets and 172.32.0.0/24 was the first unoccupied /24 in the 172.x range. | Yes | agent |\n| D016 | M002/S01 | architecture | Embedding service for the pipeline and search — OpenWebUI doesn't serve /v1/embeddings | Add Ollama container (ollama/ollama:latest) to the compose stack running nomic-embed-text on CPU | The FYN OpenWebUI instance at chat.forgetyour.name returns 404/500 on /v1/embeddings. No Ollama instance exists on the network. Ollama provides the standard OpenAI-compatible /v1/embeddings endpoint that both EmbeddingClient and SearchService expect. | Yes | agent |\n| D017 |  | frontend | CSS theming approach for dark mode | 77 semantic CSS custom properties in :root block, all hardcoded colors replaced with var(--*) references | A complete variable-based palette enables theme switching, ensures consistency, and makes future color changes single-point edits. 77 tokens (vs ~30 initially planned) were needed to cover all semantic contexts — badges, buttons, surfaces, text, accents, shadows, and status states. Cyan (#22d3ee) replaces indigo as the accent color throughout. | Yes | agent |\n| D018 | M004/S04 | architecture | Version snapshot failure handling strategy in stage 5 | Best-effort versioning — snapshot INSERT failure logs ERROR but does not block page update (existing content overwrites proceed regardless) | Versioning is a diagnostic/benchmarking feature. Losing a version snapshot is far less damaging than failing the entire page synthesis. Follows the same non-blocking side-effect pattern established in D005 for embedding/Qdrant failures. | Yes | agent |\n| D019 | M005/S02 | frontend-layout | Technique page layout structure | CSS grid 2-column layout: 1fr main + 22rem sticky sidebar, collapsing to single column at 768px. Page max-width widened from 48rem to 64rem. | 22rem sidebar provides enough room for moment cards and plugin lists without cramming. 64rem total width accommodates both columns comfortably on standard desktop displays. Sticky sidebar keeps navigation aids visible while scrolling prose. 768px breakpoint aligns with existing mobile styles in the codebase. | Yes | agent |\n| D020 | M006/S05 | frontend | Topics page card layout visual differentiation approach | 3px colored left border + small colored dot next to category name, using existing badge CSS custom properties per category | Subtler than a full colored header — maintains dark theme cohesion while providing clear visual differentiation between 7 category cards. Reuses existing --color-badge-cat-*-bg/text custom properties, avoiding new color definitions. | Yes | agent |\n\n---\n\n### Requirements\nSource: `.gsd/REQUIREMENTS.md`\n\n# Requirements\n\n## R001 — Whisper Transcription Pipeline\n**Status:** validated\n**Description:** Desktop Python script that accepts video files (MP4/MKV), extracts audio via ffmpeg, runs Whisper large-v3 on RTX 4090, and outputs timestamped transcript JSON with segment-level timestamps and word-level timing. Must be resumable.\n**Validation:** Script processes a sample video and produces valid JSON with timestamped segments.\n**Primary Owner:** M001/S01\n\n## R002 — Transcript Ingestion API\n**Status:** validated\n**Description:** FastAPI endpoint that accepts transcript JSON uploads, creates/updates Creator and Source Video records, and stores transcript data in PostgreSQL. Handles new creator detection from folder names.\n**Validation:** POST transcript JSON → 200 OK, records created in DB, file stored on filesystem.\n**Primary Owner:** M001/S02\n\n## R003 — LLM-Powered Extraction Pipeline (Stages 2-5)\n**Status:** validated\n**Description:** Background worker pipeline: transcript segmentation → key moment extraction → classification/tagging → technique page synthesis. Uses OpenAI-compatible API with primary (DGX Sparks Qwen) and fallback (local Ollama) endpoints. Pipeline must be resumable per-video per-stage.\n**Validation:** End-to-end: transcript JSON in → technique pages with key moments, tags, and cross-references out.\n**Primary Owner:** M001/S03\n\n## R004 — Review Queue UI\n**Status:** validated\n**Description:** Admin interface for reviewing extracted key moments: approve, edit+approve, split, merge, reject. Organized by source video for contextual review. Includes mode toggle (review vs auto-publish).\n**Validation:** Admin can review, edit, and approve/reject moments; mode toggle controls whether new moments require review.\n**Primary Owner:** M001/S04\n\n## R005 — Search-First Web UI\n**Status:** validated\n**Description:** Landing page with prominent search bar, live typeahead (results after 2-3 chars), scope toggle (All/Topics/Creators), and two navigation cards (Topics, Creators). Recently added section. Search powered by Qdrant semantic search with keyword fallback.\n**Validation:** User types query → results appear within 500ms, grouped by type, with clickable navigation.\n**Primary Owner:** M001/S05\n\n## R006 — Technique Page Display\n**Status:** validated\n**Description:** Core content unit: header (tags, title, creator, meta), study guide prose (organized by sub-aspects with signal chain blocks and quotes), key moments index (timestamped list), related techniques, plugins referenced. Amber banner for livestream-sourced content.\n**Validation:** Technique page renders with all sections populated from synthesized data.\n**Primary Owner:** M001/S05\n\n## R007 — Creators Browse Page\n**Status:** validated\n**Description:** Filterable creator list with genre filter pills, type-to-narrow, sort options (randomized default, alphabetical, view count). Each row: name, genre tags, technique count, video count, view count. Links to creator detail page.\n**Validation:** Page loads with randomized order, genre filtering works, clicking row navigates to creator detail.\n**Primary Owner:** M001/S05\n\n## R008 — Topics Browse Page\n**Status:** validated\n**Description:** Two-level topic hierarchy (6 top-level categories → sub-topics). Filter input, genre filter pills. Each sub-topic shows technique count and creator count. Clicking sub-topic shows technique pages.\n**Validation:** Hierarchy renders, filtering works, sub-topic links show correct technique pages.\n**Primary Owner:** M001/S05\n\n## R009 — Qdrant Vector Search Integration\n**Status:** validated\n**Description:** Embed key moment summaries, technique page content, and transcript segments in Qdrant using configurable embedding model (nomic-embed-text default). Power semantic search with metadata filtering.\n**Validation:** Semantic search returns relevant results for natural language queries; embeddings update when content changes.\n**Primary Owner:** M001/S03\n\n## R010 — Docker Compose Deployment\n**Status:** validated\n**Description:** Single docker-compose.yml packaging API, web UI, PostgreSQL, and worker services. Follows XPLTD conventions: bind mounts at /vmPool/r/services/, compose at /vmPool/r/compose/chrysopedia/, xpltd_chrysopedia project name, dedicated Docker network.\n**Validation:** `docker compose up -d` brings up all services; data persists across restarts.\n**Primary Owner:** M001/S01\n\n## R011 — Canonical Tag System\n**Status:** validated\n**Description:** Editable canonical tag list (config file) with aliases. Pipeline references tags during classification. New tags can be proposed by LLM and queued for admin approval or auto-added within existing categories.\n**Validation:** Tag list is editable; pipeline uses canonical tags consistently; alias normalization works.\n**Primary Owner:** M001/S03\n\n## R012 — Incremental Content Addition\n**Status:** validated\n**Description:** System handles ongoing content: new videos processed through pipeline, new creators auto-detected, existing technique pages updated when new moments are added for same creator+topic.\n**Validation:** Adding a new video for an existing creator updates their technique pages; new creator folder creates new Creator record.\n**Primary Owner:** M001/S03\n\n## R013 — Prompt Template System\n**Status:** validated\n**Description:** Extraction prompts (stages 2-5) stored as editable configuration files, not hardcoded. Admin can edit prompts and re-run extraction on specific or all videos for calibration.\n**Validation:** Prompt files are editable; re-processing a video with updated prompts produces different output.\n**Primary Owner:** M001/S03\n\n## R014 — Creator Equity\n**Status:** validated\n**Description:** No creator is privileged in the UI. Default sort on Creators page is randomized on every page load. All creators get equal visual weight.\n**Validation:** Refreshing Creators page shows different order each time; no creator gets larger/bolder display.\n**Primary Owner:** M001/S05\n\n## R015 — 30-Second Retrieval Target\n**Status:** active\n**Description:** A producer mid-session can find a specific technique in under 30 seconds from Alt+Tab to reading the key insight.\n**Validation:** Timed test: Alt+Tab → search → read technique → under 30 seconds.\n**Primary Owner:** M001/S05\n\n---\n\n[...truncated 6 sections]\n\n### Dependency Slice Summaries\n\nPay particular attention to **Forward Intelligence** sections — they contain hard-won knowledge about what's fragile, what assumptions changed, and what to watch out for.\n\n#### S01 Summary\nSource: `.gsd/milestones/M007/slices/S01/S01-SUMMARY.md`\n\n---\nid: S01\nparent: M007\nmilestone: M007\nprovides:\n  - Debug mode toggle API (GET/PUT /api/v1/admin/pipeline/debug-mode)\n  - Full LLM I/O stored in pipeline_events when debug on\n  - Per-stage token summary API (GET /api/v1/admin/pipeline/token-summary/{video_id})\n  - Extended event listing with system_prompt_text, user_prompt_text, response_text fields\nrequires:\n  []\naffects:\n  - S02\nkey_files:\n  - backend/models.py\n  - backend/config.py\n  - backend/schemas.py\n  - backend/routers/pipeline.py\n  - alembic/versions/006_debug_columns.py\n  - backend/pipeline/stages.py\nkey_decisions:\n  - Followed review_mode Redis pattern (D007) for debug_mode toggle — consistent approach across all admin toggles\n  - Debug mode checked once at callback creation time to avoid Redis round-trip per LLM call\n  - Full response_text stored without truncation when debug on; existing content_preview in JSONB payload kept for non-debug use\n  - Used SQL coalesce for NULL token columns in aggregation query\npatterns_established:\n  - Redis-backed admin toggle with config fallback: GET reads Redis key, falls back to settings default; PUT writes to Redis. Pattern now used by review_mode and debug_mode.\n  - Conditional pipeline instrumentation: _make_llm_callback checks mode once at creation, closure captures the decision, no per-call overhead when off.\nobservability_surfaces:\n  - GET /api/v1/admin/pipeline/debug-mode — current debug toggle state\n  - GET /api/v1/admin/pipeline/token-summary/{video_id} — per-stage token accounting\n  - pipeline_events.system_prompt_text/user_prompt_text/response_text — full LLM I/O when debug mode was on during pipeline run\ndrill_down_paths:\n  - .gsd/milestones/M007/slices/S01/tasks/T01-SUMMARY.md\n  - .gsd/milestones/M007/slices/S01/tasks/T02-SUMMARY.md\nduration: \"\"\nverification_result: passed\ncompleted_at: 2026-03-30T18:57:12.919Z\nblocker_discovered: false\n---\n\n# S01: Pipeline Debug Mode — Full LLM I/O Capture and Token Accounting\n\n**Added debug mode toggle (Redis-backed) that captures full LLM system prompt, user prompt, and response text in pipeline_events, plus per-stage token summary endpoint.**\n\n## What Happened\n\nTwo tasks delivered the full debug mode feature.\n\nT01 added infrastructure: Alembic migration 006 with 3 nullable TEXT columns (system_prompt_text, user_prompt_text, response_text) on pipeline_events, PipelineEvent model update, debug_mode config setting, Redis-backed GET/PUT toggle endpoints (following the review_mode pattern from D007), and a token-summary aggregation endpoint that groups by stage.\n\nT02 wired the capture into the pipeline: _emit_event extended to accept the 3 text fields, _is_debug_mode() reads sync Redis with config fallback, _make_llm_callback conditionally captures full I/O when debug is on (checked once at callback creation, not per-call), and all 4 stage call sites (stages 2-5) pass system_prompt and user_prompt through. The existing content_preview in the JSONB payload is preserved for non-debug use.\n\nEnd-to-end verified on ub01: debug mode toggled on, pipeline ran for a video, events have populated system_prompt_text (7752 chars), user_prompt_text (971 chars), and response_text. Token summary returns per-stage breakdown (e.g., stage2: 1 call / 16K tokens, stage3: 15 calls / 66K tokens, grand total 83K). When debug is off, fields remain NULL — no storage overhead.\n\n## Verification\n\nAll slice-level checks passed:\n\n1. **Migration**: `docker exec chrysopedia-api alembic upgrade head` — 006_debug_columns applied, 3 TEXT columns confirmed via psql \\d pipeline_events\n2. **Debug mode toggle**: GET returns {\"debug_mode\":false}, PUT sets to true, GET reads back true, PUT sets to false, GET confirms false — full round-trip\n3. **Token summary**: GET /api/v1/admin/pipeline/token-summary/{video_id} returns per-stage aggregation with call_count, prompt/completion/total tokens, and grand_total_tokens\n4. **Event listing**: GET /api/v1/admin/pipeline/events/{video_id} items include system_prompt_text, user_prompt_text, response_text (populated for llm_call events when debug was on, NULL otherwise)\n5. **End-to-end capture**: Video 7afc5a42 processed with debug on — stage3_extraction events contain 7752 chars of system prompt and 971 chars of user prompt\n6. **Worker health**: chrysopedia-worker running without import errors after rebuild\n\n## New Requirements Surfaced\n\nNone.\n\n## Deviations\n\nT02 noted endpoint paths need /api/v1/ prefix (omitted in plan) and Docker compose web service name is chrysopedia-web not chrysopedia-web-8096. Minor naming discrepancies, no functional impact.\n\n## Known Limitations\n\nDebug mode is global (all videos), not per-video. Full prompt/response text stored without truncation — for very long prompts this could grow the pipeline_events table significantly if debug is left on permanently. Intended for diagnostic use, not always-on.\n\n## Follow-ups\n\nS02 builds the admin UI viewer for these debug payloads — inline view, copy, and export.\n\n## Files Created/Modified\n\n- `backend/models.py` — Added system_prompt_text, user_prompt_text, response_text columns to PipelineEvent\n- `backend/config.py` — Added debug_mode: bool = False to Settings\n- `backend/schemas.py` — Added DebugModeResponse, DebugModeUpdate, TokenStageSummary, TokenSummaryResponse schemas\n- `backend/routers/pipeline.py` — Added debug-mode GET/PUT endpoints, token-summary endpoint, extended event listing response\n- `alembic/versions/006_debug_columns.py` — Migration adding 3 TEXT columns to pipeline_events\n- `backend/pipeline/stages.py` — Added _is_debug_mode(), extended _emit_event and _make_llm_callback for conditional I/O capture, updated 4 stage call sites\n\n## Your Role in the Pipeline\n\nYou are the scout. After you finish, a **planner agent** reads your output in a fresh context with no memory of your exploration. It uses your findings to decompose this slice into executable tasks — deciding what files change, what order to build things, how to verify the work. Then **executor agents** build each task in isolated context windows.\n\nWrite for the planner, not for a human. The planner needs:\n- **What files exist and what they do** — so it can scope tasks to specific files\n- **Where the natural seams are** — where work divides into independent units\n- **What to build or prove first** — what's riskiest, what unblocks everything else\n- **How to verify the result** — what commands, tests, or checks confirm the slice works\n\nIf the research doc is vague, the planner will waste its context re-exploring code you already read. If it's precise, the planner can decompose immediately.\n\n## Calibrate Depth\n\nRead the slice title, the roadmap excerpt, and any milestone research above. Ask: does this slice involve unfamiliar technology, risky integration, novel architecture, or ambiguous requirements? Or is it straightforward application of known patterns to known code?\n\n- **Deep research** — new technology, unfamiliar APIs, risky integration, multiple viable approaches, or ambiguous scope. Explore broadly, look up docs, check libraries, investigate constraints. Write all template sections. This is the default when you're genuinely uncertain.\n- **Targeted research** — known technology but new to this codebase, or moderately complex integration. Explore the relevant code, check one or two libraries, identify constraints. Omit Don't Hand-Roll and Sources if nothing applies.\n- **Light research** — well-understood work using established patterns already in the codebase (wiring up existing APIs, adding standard UI components, CRUD operations, configuration changes). Read the relevant files to confirm the pattern, note any constraints, write Summary + Recommendation + Implementation Landscape. Skip the rest. A light research doc can be 15-20 lines. Don't manufacture pitfalls or risks for work that doesn't have them.\n\nAn honest \"this is straightforward, here's the pattern to follow\" is more valuable than invented complexity.\n\n## Steps\n\nResearch what this slice needs. Narrate key findings and surprises as you go — what exists, what's missing, what constrains the approach.\n0. If `REQUIREMENTS.md` was preloaded above, identify which Active requirements this slice owns or supports. Research should target these requirements — surfacing risks, unknowns, and implementation constraints that could affect whether the slice actually delivers them.\n1.  Reference specific rules from loaded skills in your findings where they inform the implementation approach.\n2. **Skill Discovery (suggest):**\n   Identify the key technologies, frameworks, and services this work depends on (e.g. Stripe, Clerk, Supabase, JUCE, SwiftUI).\n   For each, check if a professional agent skill already exists:\n   - First check `<available_skills>` in your system prompt — a skill may already be installed.\n   - For technologies without an installed skill, run: `npx skills find \"<technology>\"`\n   - Only consider skills that are **directly relevant** to core technologies — not tangentially related.\n   - Evaluate results by install count and relevance to the actual work.\n   - Note promising skills in your research output with their install commands, but do NOT install them.\n   - The user will decide which to install.\n3. Explore relevant code for this slice's scope. For targeted exploration, use `rg`, `find`, and reads. For broad or unfamiliar subsystems, use `scout` to map the relevant area first.\n4. Use `resolve_library` / `get_library_docs` for unfamiliar libraries — skip this for libraries already used in the codebase\n5. **Web search budget:** You have a limited budget of web searches (max ~15 per session). Use them strategically — prefer `resolve_library` / `get_library_docs` for library documentation. Do NOT repeat the same or similar queries. If a search didn't find what you need, rephrase once or move on. Target 3-5 total web searches for a typical research unit.\n6. Use the **Research** output template from the inlined context above — include only sections that have real content. The template is already inlined above; do NOT attempt to read any template file from disk (there is no `templates/SLICE-RESEARCH.md` — the correct template is already present in this prompt).\n7. Call `gsd_summary_save` with `milestone_id: M007`, `slice_id: S02`, `artifact_type: \"RESEARCH\"`, and the full research markdown as `content` — the tool computes the file path and persists to both DB and disk.\n\nThe slice directory already exists at `.gsd/milestones/M007/slices/S02/`. Do NOT mkdir.\n\n**You MUST call `gsd_summary_save` with the research content before finishing.**\n\nWhen done, say: \"Slice S02 researched.\"","display":false,"id":"f88ad4f7","parentId":"8abdd2d6","timestamp":"2026-03-30T18:57:21.100Z"}
{"type":"message","id":"156c4a11","parentId":"f88ad4f7","timestamp":"2026-03-30T18:57:29.613Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me research what S02 needs. It's about building a debug payload viewer in the admin UI — inline view, copy, and export for LLM I/O captured by S01. This is straightforward frontend work using established patterns. Let me do light-to-targeted research.\n\nLet me check the existing admin UI code to understand patterns, then look at the API endpoints S01 created.","thinkingSignature":"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"},{"type":"text","text":"Light research — this is standard UI work wiring existing API data into a viewer component. Let me confirm the patterns and endpoints."},{"type":"toolCall","id":"toolu_01NJyGM7kkL1fhDjunAPVAwC","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && find frontend/src -type f -name \"*.tsx\" -o -name \"*.ts\" | head -40"}},{"type":"toolCall","id":"toolu_01N4jieacmTc2W9vjGRAU53X","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && rg -l \"pipeline.*event\\|PipelineEvent\\|debug.*mode\\|token.*summary\" frontend/src/ backend/routers/pipeline.py backend/schemas.py 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":3,"output":320,"cacheRead":58112,"cacheWrite":8174,"totalTokens":66609,"cost":{"input":0.000015000000000000002,"output":0.008,"cacheRead":0.029056,"cacheWrite":0.0510875,"total":0.0881585}},"stopReason":"toolUse","timestamp":1774897041098}}
{"type":"message","id":"50c5172c","parentId":"156c4a11","timestamp":"2026-03-30T18:57:29.628Z","message":{"role":"toolResult","toolCallId":"toolu_01NJyGM7kkL1fhDjunAPVAwC","toolName":"bash","content":[{"type":"text","text":"frontend/src/pages/AdminPipeline.tsx\nfrontend/src/pages/CreatorDetail.tsx\nfrontend/src/pages/CreatorsBrowse.tsx\nfrontend/src/pages/AdminReports.tsx\nfrontend/src/pages/Home.tsx\nfrontend/src/pages/TechniquePage.tsx\nfrontend/src/pages/TopicsBrowse.tsx\nfrontend/src/pages/ReviewQueue.tsx\nfrontend/src/pages/MomentDetail.tsx\nfrontend/src/pages/SearchResults.tsx\nfrontend/src/vite-env.d.ts\nfrontend/src/App.tsx\nfrontend/src/api/public-client.ts\nfrontend/src/api/client.ts\nfrontend/src/components/ModeToggle.tsx\nfrontend/src/components/AppFooter.tsx\nfrontend/src/components/StatusBadge.tsx\nfrontend/src/components/AdminDropdown.tsx\nfrontend/src/components/ReportIssueModal.tsx\nfrontend/src/main.tsx\n"}],"isError":false,"timestamp":1774897049628}}
{"type":"message","id":"29ffec33","parentId":"50c5172c","timestamp":"2026-03-30T18:57:29.637Z","message":{"role":"toolResult","toolCallId":"toolu_01N4jieacmTc2W9vjGRAU53X","toolName":"bash","content":[{"type":"text","text":"(no output)\n\nCommand exited with code 2"}],"details":{},"isError":true,"timestamp":1774897049636}}
{"type":"message","id":"36ea4e3e","parentId":"29ffec33","timestamp":"2026-03-30T18:57:33.125Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01VotJ1rG5wV3EnkQ2WvGof1","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && rg -l \"pipeline.*event\\|PipelineEvent\\|debug.mode\\|token.summary\\|events/\" frontend/src/ backend/routers/pipeline.py backend/schemas.py 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":119,"cacheRead":66286,"cacheWrite":532,"totalTokens":66938,"cost":{"input":0.000005,"output":0.002975,"cacheRead":0.033143,"cacheWrite":0.0033250000000000003,"total":0.039448000000000004}},"stopReason":"toolUse","timestamp":1774897049637}}
{"type":"message","id":"96fe17f9","parentId":"36ea4e3e","timestamp":"2026-03-30T18:57:33.143Z","message":{"role":"toolResult","toolCallId":"toolu_01VotJ1rG5wV3EnkQ2WvGof1","toolName":"bash","content":[{"type":"text","text":"(no output)\n\nCommand exited with code 2"}],"details":{},"isError":true,"timestamp":1774897053141}}
{"type":"message","id":"29d33b63","parentId":"96fe17f9","timestamp":"2026-03-30T18:57:36.714Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_011JYK8BNEtQK6vn9Gbz9cbZ","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && rg -l \"pipeline\" frontend/src/ 2>/dev/null && echo \"---\" && rg -l \"events\\|debug\" backend/routers/ 2>/dev/null && echo \"---\" && rg -l \"TokenSummary\\|DebugMode\\|PipelineEvent\" backend/schemas.py 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":151,"cacheRead":66818,"cacheWrite":150,"totalTokens":67120,"cost":{"input":0.000005,"output":0.003775,"cacheRead":0.033409,"cacheWrite":0.0009375000000000001,"total":0.0381265}},"stopReason":"toolUse","timestamp":1774897053142}}
{"type":"message","id":"5f8f20de","parentId":"29d33b63","timestamp":"2026-03-30T18:57:36.730Z","message":{"role":"toolResult","toolCallId":"toolu_011JYK8BNEtQK6vn9Gbz9cbZ","toolName":"bash","content":[{"type":"text","text":"frontend/src/components/AdminDropdown.tsx\nfrontend/src/App.css\nfrontend/src/App.tsx\nfrontend/src/api/public-client.ts\nfrontend/src/pages/TechniquePage.tsx\nfrontend/src/pages/AdminPipeline.tsx\n---\n\n\nCommand exited with code 2"}],"details":{},"isError":true,"timestamp":1774897056729}}
{"type":"message","id":"b540de6b","parentId":"5f8f20de","timestamp":"2026-03-30T18:57:39.936Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01CMGyLrpedjs6jPVCuCPH4M","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && ls backend/routers/"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":74,"cacheRead":66968,"cacheWrite":246,"totalTokens":67289,"cost":{"input":0.000005,"output":0.00185,"cacheRead":0.033484,"cacheWrite":0.0015375,"total":0.0368765}},"stopReason":"toolUse","timestamp":1774897056729}}
{"type":"message","id":"5fed6983","parentId":"b540de6b","timestamp":"2026-03-30T18:57:39.954Z","message":{"role":"toolResult","toolCallId":"toolu_01CMGyLrpedjs6jPVCuCPH4M","toolName":"bash","content":[{"type":"text","text":"ls: cannot access 'backend/routers/': No such file or directory\n\n\nCommand exited with code 2"}],"details":{},"isError":true,"timestamp":1774897059952}}
{"type":"message","id":"b93d1eb6","parentId":"5fed6983","timestamp":"2026-03-30T18:57:44.688Z","message":{"role":"assistant","content":[{"type":"text","text":"Right — the canonical repo is on ub01. Let me check the actual codebase there."},{"type":"toolCall","id":"toolu_01YBsDLPuCHUiZLcUAaxDGkY","name":"bash","arguments":{"command":"ssh ub01 \"ls /vmPool/r/repos/xpltdco/chrysopedia/backend/routers/\""}},{"type":"toolCall","id":"toolu_01PHfFVgijzrxUYLqkCiaycE","name":"bash","arguments":{"command":"ssh ub01 \"find /vmPool/r/repos/xpltdco/chrysopedia/frontend/src -type f -name '*.tsx' -o -name '*.ts'\" 2>/dev/null | head -40"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":192,"cacheRead":67214,"cacheWrite":119,"totalTokens":67526,"cost":{"input":0.000005,"output":0.0048000000000000004,"cacheRead":0.033607,"cacheWrite":0.00074375,"total":0.03915575}},"stopReason":"toolUse","timestamp":1774897059952}}
{"type":"message","id":"7f7b9eaf","parentId":"b93d1eb6","timestamp":"2026-03-30T18:57:45.504Z","message":{"role":"toolResult","toolCallId":"toolu_01YBsDLPuCHUiZLcUAaxDGkY","toolName":"bash","content":[{"type":"text","text":"creators.py\nhealth.py\ningest.py\n__init__.py\npipeline.py\nreports.py\nreview.py\nsearch.py\ntechniques.py\ntopics.py\nvideos.py\n"}],"isError":false,"timestamp":1774897065503}}
{"type":"message","id":"bc3986cc","parentId":"7f7b9eaf","timestamp":"2026-03-30T18:57:45.505Z","message":{"role":"toolResult","toolCallId":"toolu_01PHfFVgijzrxUYLqkCiaycE","toolName":"bash","content":[{"type":"text","text":"/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/main.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/api/client.ts\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/api/public-client.ts\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/components/AppFooter.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/components/ReportIssueModal.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/components/ModeToggle.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/components/StatusBadge.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/components/AdminDropdown.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/CreatorsBrowse.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/AdminReports.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/SearchResults.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/ReviewQueue.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/MomentDetail.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/AdminPipeline.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/TechniquePage.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/CreatorDetail.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/Home.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/TopicsBrowse.tsx\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/vite-env.d.ts\n/vmPool/r/repos/xpltdco/chrysopedia/frontend/src/App.tsx\n"}],"isError":false,"timestamp":1774897065503}}
{"type":"message","id":"f9391e3d","parentId":"bc3986cc","timestamp":"2026-03-30T18:57:49.350Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01GtBDUuDfzhi3EbYgnazgsz","name":"bash","arguments":{"command":"ssh ub01 \"cat /vmPool/r/repos/xpltdco/chrysopedia/backend/routers/pipeline.py\""}},{"type":"toolCall","id":"toolu_01DFm6Lc1aSvFY1qcyhcLKvT","name":"bash","arguments":{"command":"ssh ub01 \"cat /vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/AdminPipeline.tsx\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":157,"cacheRead":67333,"cacheWrite":897,"totalTokens":68388,"cost":{"input":0.000005,"output":0.0039250000000000005,"cacheRead":0.033666499999999995,"cacheWrite":0.00560625,"total":0.04320275}},"stopReason":"toolUse","timestamp":1774897065504}}
{"type":"message","id":"6b4ee3a4","parentId":"f9391e3d","timestamp":"2026-03-30T18:57:49.697Z","message":{"role":"toolResult","toolCallId":"toolu_01GtBDUuDfzhi3EbYgnazgsz","toolName":"bash","content":[{"type":"text","text":"\"\"\"Pipeline management endpoints — public trigger + admin dashboard.\n\nPublic:\n  POST /pipeline/trigger/{video_id}    Trigger pipeline for a video\n\nAdmin:\n  GET  /admin/pipeline/videos          Video list with status + event counts\n  POST /admin/pipeline/trigger/{video_id}  Retrigger (same as public but under admin prefix)\n  POST /admin/pipeline/revoke/{video_id}   Revoke/cancel active tasks for a video\n  GET  /admin/pipeline/events/{video_id}   Event log for a video (paginated)\n  GET  /admin/pipeline/worker-status       Active/reserved tasks from Celery inspect\n\"\"\"\n\nimport logging\nimport uuid\nfrom typing import Annotated\n\nfrom fastapi import APIRouter, Depends, HTTPException, Query\nfrom sqlalchemy import func, select, case\nfrom sqlalchemy.ext.asyncio import AsyncSession\n\nfrom config import get_settings\nfrom database import get_session\nfrom models import PipelineEvent, SourceVideo, Creator\nfrom redis_client import get_redis\nfrom schemas import DebugModeResponse, DebugModeUpdate, TokenStageSummary, TokenSummaryResponse\n\nlogger = logging.getLogger(\"chrysopedia.pipeline\")\n\nrouter = APIRouter(tags=[\"pipeline\"])\n\nREDIS_DEBUG_MODE_KEY = \"chrysopedia:debug_mode\"\n\n\n# ── Public trigger ───────────────────────────────────────────────────────────\n\n@router.post(\"/pipeline/trigger/{video_id}\")\nasync def trigger_pipeline(\n    video_id: str,\n    db: AsyncSession = Depends(get_session),\n):\n    \"\"\"Manually trigger (or re-trigger) the LLM extraction pipeline for a video.\"\"\"\n    stmt = select(SourceVideo).where(SourceVideo.id == video_id)\n    result = await db.execute(stmt)\n    video = result.scalar_one_or_none()\n\n    if video is None:\n        raise HTTPException(status_code=404, detail=f\"Video not found: {video_id}\")\n\n    from pipeline.stages import run_pipeline\n\n    try:\n        run_pipeline.delay(str(video.id))\n        logger.info(\"Pipeline manually triggered for video_id=%s\", video_id)\n    except Exception as exc:\n        logger.warning(\"Failed to dispatch pipeline for video_id=%s: %s\", video_id, exc)\n        raise HTTPException(\n            status_code=503,\n            detail=\"Pipeline dispatch failed — Celery/Redis may be unavailable\",\n        ) from exc\n\n    return {\n        \"status\": \"triggered\",\n        \"video_id\": str(video.id),\n        \"current_processing_status\": video.processing_status.value,\n    }\n\n\n# ── Admin: Video list ────────────────────────────────────────────────────────\n\n@router.get(\"/admin/pipeline/videos\")\nasync def list_pipeline_videos(\n    db: AsyncSession = Depends(get_session),\n):\n    \"\"\"List all videos with processing status and pipeline event counts.\"\"\"\n    # Subquery for event counts per video\n    event_counts = (\n        select(\n            PipelineEvent.video_id,\n            func.count().label(\"event_count\"),\n            func.sum(case(\n                (PipelineEvent.event_type == \"llm_call\", PipelineEvent.total_tokens),\n                else_=0\n            )).label(\"total_tokens_used\"),\n            func.max(PipelineEvent.created_at).label(\"last_event_at\"),\n        )\n        .group_by(PipelineEvent.video_id)\n        .subquery()\n    )\n\n    stmt = (\n        select(\n            SourceVideo.id,\n            SourceVideo.filename,\n            SourceVideo.processing_status,\n            SourceVideo.content_hash,\n            SourceVideo.created_at,\n            SourceVideo.updated_at,\n            Creator.name.label(\"creator_name\"),\n            event_counts.c.event_count,\n            event_counts.c.total_tokens_used,\n            event_counts.c.last_event_at,\n        )\n        .join(Creator, SourceVideo.creator_id == Creator.id)\n        .outerjoin(event_counts, SourceVideo.id == event_counts.c.video_id)\n        .order_by(SourceVideo.updated_at.desc())\n    )\n\n    result = await db.execute(stmt)\n    rows = result.all()\n\n    return {\n        \"items\": [\n            {\n                \"id\": str(r.id),\n                \"filename\": r.filename,\n                \"processing_status\": r.processing_status.value if hasattr(r.processing_status, 'value') else str(r.processing_status),\n                \"content_hash\": r.content_hash,\n                \"creator_name\": r.creator_name,\n                \"created_at\": r.created_at.isoformat() if r.created_at else None,\n                \"updated_at\": r.updated_at.isoformat() if r.updated_at else None,\n                \"event_count\": r.event_count or 0,\n                \"total_tokens_used\": r.total_tokens_used or 0,\n                \"last_event_at\": r.last_event_at.isoformat() if r.last_event_at else None,\n            }\n            for r in rows\n        ],\n        \"total\": len(rows),\n    }\n\n\n# ── Admin: Retrigger ─────────────────────────────────────────────────────────\n\n@router.post(\"/admin/pipeline/trigger/{video_id}\")\nasync def admin_trigger_pipeline(\n    video_id: str,\n    db: AsyncSession = Depends(get_session),\n):\n    \"\"\"Admin retrigger — same as public trigger.\"\"\"\n    return await trigger_pipeline(video_id, db)\n\n\n# ── Admin: Revoke ────────────────────────────────────────────────────────────\n\n@router.post(\"/admin/pipeline/revoke/{video_id}\")\nasync def revoke_pipeline(video_id: str):\n    \"\"\"Revoke/cancel active Celery tasks for a video.\n    \n    Uses Celery's revoke with terminate=True to kill running tasks.\n    This is best-effort — the task may have already completed.\n    \"\"\"\n    from worker import celery_app\n    \n    try:\n        # Get active tasks and revoke any matching this video_id\n        inspector = celery_app.control.inspect()\n        active = inspector.active() or {}\n        revoked_count = 0\n        \n        for _worker, tasks in active.items():\n            for task in tasks:\n                task_args = task.get(\"args\", [])\n                if task_args and str(task_args[0]) == video_id:\n                    celery_app.control.revoke(task[\"id\"], terminate=True)\n                    revoked_count += 1\n                    logger.info(\"Revoked task %s for video_id=%s\", task[\"id\"], video_id)\n        \n        return {\n            \"status\": \"revoked\" if revoked_count > 0 else \"no_active_tasks\",\n            \"video_id\": video_id,\n            \"tasks_revoked\": revoked_count,\n        }\n    except Exception as exc:\n        logger.warning(\"Failed to revoke tasks for video_id=%s: %s\", video_id, exc)\n        raise HTTPException(\n            status_code=503,\n            detail=\"Failed to communicate with Celery worker\",\n        ) from exc\n\n\n# ── Admin: Event log ─────────────────────────────────────────────────────────\n\n@router.get(\"/admin/pipeline/events/{video_id}\")\nasync def list_pipeline_events(\n    video_id: str,\n    offset: Annotated[int, Query(ge=0)] = 0,\n    limit: Annotated[int, Query(ge=1, le=200)] = 100,\n    stage: Annotated[str | None, Query(description=\"Filter by stage name\")] = None,\n    event_type: Annotated[str | None, Query(description=\"Filter by event type\")] = None,\n    order: Annotated[str, Query(description=\"Sort order: asc or desc\")] = \"desc\",\n    db: AsyncSession = Depends(get_session),\n):\n    \"\"\"Get pipeline events for a video. Default: newest first (desc).\"\"\"\n    stmt = select(PipelineEvent).where(PipelineEvent.video_id == video_id)\n    \n    if stage:\n        stmt = stmt.where(PipelineEvent.stage == stage)\n    if event_type:\n        stmt = stmt.where(PipelineEvent.event_type == event_type)\n    \n    # Validate order param\n    if order not in (\"asc\", \"desc\"):\n        raise HTTPException(status_code=400, detail=\"order must be 'asc' or 'desc'\")\n\n    # Count\n    count_stmt = select(func.count()).select_from(stmt.subquery())\n    total = (await db.execute(count_stmt)).scalar() or 0\n    \n    # Fetch\n    order_clause = PipelineEvent.created_at.asc() if order == \"asc\" else PipelineEvent.created_at.desc()\n    stmt = stmt.order_by(order_clause)\n    stmt = stmt.offset(offset).limit(limit)\n    result = await db.execute(stmt)\n    events = result.scalars().all()\n    \n    return {\n        \"items\": [\n            {\n                \"id\": str(e.id),\n                \"video_id\": str(e.video_id),\n                \"stage\": e.stage,\n                \"event_type\": e.event_type,\n                \"prompt_tokens\": e.prompt_tokens,\n                \"completion_tokens\": e.completion_tokens,\n                \"total_tokens\": e.total_tokens,\n                \"model\": e.model,\n                \"duration_ms\": e.duration_ms,\n                \"payload\": e.payload,\n                \"created_at\": e.created_at.isoformat() if e.created_at else None,\n                \"system_prompt_text\": e.system_prompt_text,\n                \"user_prompt_text\": e.user_prompt_text,\n                \"response_text\": e.response_text,\n            }\n            for e in events\n        ],\n        \"total\": total,\n        \"offset\": offset,\n        \"limit\": limit,\n    }\n\n\n# ── Admin: Debug mode ─────────────────────────────────────────────────────────\n\n@router.get(\"/admin/pipeline/debug-mode\", response_model=DebugModeResponse)\nasync def get_debug_mode() -> DebugModeResponse:\n    \"\"\"Get the current pipeline debug mode (on/off).\"\"\"\n    settings = get_settings()\n    try:\n        redis = await get_redis()\n        try:\n            value = await redis.get(REDIS_DEBUG_MODE_KEY)\n            if value is not None:\n                return DebugModeResponse(debug_mode=value.lower() == \"true\")\n        finally:\n            await redis.aclose()\n    except Exception as exc:\n        logger.warning(\"Redis unavailable for debug mode read, using config default: %s\", exc)\n\n    return DebugModeResponse(debug_mode=settings.debug_mode)\n\n\n@router.put(\"/admin/pipeline/debug-mode\", response_model=DebugModeResponse)\nasync def set_debug_mode(body: DebugModeUpdate) -> DebugModeResponse:\n    \"\"\"Set the pipeline debug mode (on/off).\"\"\"\n    try:\n        redis = await get_redis()\n        try:\n            await redis.set(REDIS_DEBUG_MODE_KEY, str(body.debug_mode))\n        finally:\n            await redis.aclose()\n    except Exception as exc:\n        logger.error(\"Failed to set debug mode in Redis: %s\", exc)\n        raise HTTPException(\n            status_code=503,\n            detail=f\"Redis unavailable: {exc}\",\n        )\n\n    logger.info(\"Pipeline debug mode set to %s\", body.debug_mode)\n    return DebugModeResponse(debug_mode=body.debug_mode)\n\n\n# ── Admin: Token summary ─────────────────────────────────────────────────────\n\n@router.get(\"/admin/pipeline/token-summary/{video_id}\", response_model=TokenSummaryResponse)\nasync def get_token_summary(\n    video_id: str,\n    db: AsyncSession = Depends(get_session),\n) -> TokenSummaryResponse:\n    \"\"\"Get per-stage token usage summary for a video.\"\"\"\n    stmt = (\n        select(\n            PipelineEvent.stage,\n            func.count().label(\"call_count\"),\n            func.coalesce(func.sum(PipelineEvent.prompt_tokens), 0).label(\"total_prompt_tokens\"),\n            func.coalesce(func.sum(PipelineEvent.completion_tokens), 0).label(\"total_completion_tokens\"),\n            func.coalesce(func.sum(PipelineEvent.total_tokens), 0).label(\"total_tokens\"),\n        )\n        .where(PipelineEvent.video_id == video_id)\n        .where(PipelineEvent.event_type == \"llm_call\")\n        .group_by(PipelineEvent.stage)\n        .order_by(PipelineEvent.stage)\n    )\n\n    result = await db.execute(stmt)\n    rows = result.all()\n\n    stages = [\n        TokenStageSummary(\n            stage=r.stage,\n            call_count=r.call_count,\n            total_prompt_tokens=r.total_prompt_tokens,\n            total_completion_tokens=r.total_completion_tokens,\n            total_tokens=r.total_tokens,\n        )\n        for r in rows\n    ]\n    grand_total = sum(s.total_tokens for s in stages)\n\n    return TokenSummaryResponse(\n        video_id=video_id,\n        stages=stages,\n        grand_total_tokens=grand_total,\n    )\n\n\n# ── Admin: Worker status ─────────────────────────────────────────────────────\n\n@router.get(\"/admin/pipeline/worker-status\")\nasync def worker_status():\n    \"\"\"Get current Celery worker status — active, reserved, and stats.\"\"\"\n    from worker import celery_app\n    \n    try:\n        inspector = celery_app.control.inspect()\n        active = inspector.active() or {}\n        reserved = inspector.reserved() or {}\n        stats = inspector.stats() or {}\n        \n        workers = []\n        for worker_name in set(list(active.keys()) + list(reserved.keys()) + list(stats.keys())):\n            worker_active = active.get(worker_name, [])\n            worker_reserved = reserved.get(worker_name, [])\n            worker_stats = stats.get(worker_name, {})\n            \n            workers.append({\n                \"name\": worker_name,\n                \"active_tasks\": [\n                    {\n                        \"id\": t.get(\"id\"),\n                        \"name\": t.get(\"name\"),\n                        \"args\": t.get(\"args\", []),\n                        \"time_start\": t.get(\"time_start\"),\n                    }\n                    for t in worker_active\n                ],\n                \"reserved_tasks\": len(worker_reserved),\n                \"total_completed\": worker_stats.get(\"total\", {}).get(\"tasks.pipeline.stages.stage2_segmentation\", 0)\n                    + worker_stats.get(\"total\", {}).get(\"tasks.pipeline.stages.stage3_extraction\", 0)\n                    + worker_stats.get(\"total\", {}).get(\"tasks.pipeline.stages.stage4_classification\", 0)\n                    + worker_stats.get(\"total\", {}).get(\"tasks.pipeline.stages.stage5_synthesis\", 0),\n                \"uptime\": worker_stats.get(\"clock\", None),\n                \"pool_size\": worker_stats.get(\"pool\", {}).get(\"max-concurrency\") if isinstance(worker_stats.get(\"pool\"), dict) else None,\n            })\n        \n        return {\n            \"online\": len(workers) > 0,\n            \"workers\": workers,\n        }\n    except Exception as exc:\n        logger.warning(\"Failed to inspect Celery workers: %s\", exc)\n        return {\n            \"online\": False,\n            \"workers\": [],\n            \"error\": str(exc),\n        }\n"}],"isError":false,"timestamp":1774897069696}}
{"type":"message","id":"d86e3e02","parentId":"6b4ee3a4","timestamp":"2026-03-30T18:57:49.699Z","message":{"role":"toolResult","toolCallId":"toolu_01DFm6Lc1aSvFY1qcyhcLKvT","toolName":"bash","content":[{"type":"text","text":"/**\n * Pipeline admin dashboard — video list with status, retrigger/revoke,\n * expandable event log with token usage and collapsible JSON viewer.\n */\n\nimport { useCallback, useEffect, useState } from \"react\";\nimport {\n  fetchPipelineVideos,\n  fetchPipelineEvents,\n  fetchWorkerStatus,\n  triggerPipeline,\n  revokePipeline,\n  type PipelineVideoItem,\n  type PipelineEvent,\n  type WorkerStatusResponse,\n} from \"../api/public-client\";\n\n// ── Helpers ──────────────────────────────────────────────────────────────────\n\nfunction formatDate(iso: string | null): string {\n  if (!iso) return \"—\";\n  return new Date(iso).toLocaleString(undefined, {\n    month: \"short\",\n    day: \"numeric\",\n    hour: \"2-digit\",\n    minute: \"2-digit\",\n    second: \"2-digit\",\n  });\n}\n\nfunction formatTokens(n: number): string {\n  if (n === 0) return \"0\";\n  if (n >= 1_000_000) return `${(n / 1_000_000).toFixed(1)}M`;\n  if (n >= 1_000) return `${(n / 1_000).toFixed(1)}k`;\n  return String(n);\n}\n\nfunction statusBadgeClass(status: string): string {\n  switch (status) {\n    case \"completed\":\n    case \"indexed\":\n      return \"pipeline-badge--success\";\n    case \"processing\":\n    case \"extracted\":\n    case \"classified\":\n    case \"synthesized\":\n      return \"pipeline-badge--active\";\n    case \"failed\":\n    case \"error\":\n      return \"pipeline-badge--error\";\n    case \"pending\":\n    case \"queued\":\n      return \"pipeline-badge--pending\";\n    default:\n      return \"\";\n  }\n}\n\nfunction eventTypeIcon(eventType: string): string {\n  switch (eventType) {\n    case \"start\":\n      return \"▶\";\n    case \"complete\":\n      return \"✓\";\n    case \"error\":\n      return \"✗\";\n    case \"llm_call\":\n      return \"🤖\";\n    default:\n      return \"·\";\n  }\n}\n\n// ── Collapsible JSON ─────────────────────────────────────────────────────────\n\nfunction JsonViewer({ data }: { data: Record<string, unknown> | null }) {\n  const [open, setOpen] = useState(false);\n  if (!data || Object.keys(data).length === 0) return null;\n\n  return (\n    <div className=\"json-viewer\">\n      <button\n        className=\"json-viewer__toggle\"\n        onClick={() => setOpen((v) => !v)}\n        aria-expanded={open}\n      >\n        {open ? \"▾ Hide payload\" : \"▸ Show payload\"}\n      </button>\n      {open && (\n        <pre className=\"json-viewer__content\">\n          {JSON.stringify(data, null, 2)}\n        </pre>\n      )}\n    </div>\n  );\n}\n\n// ── Event Log ────────────────────────────────────────────────────────────────\n\nfunction EventLog({ videoId }: { videoId: string }) {\n  const [events, setEvents] = useState<PipelineEvent[]>([]);\n  const [total, setTotal] = useState(0);\n  const [loading, setLoading] = useState(true);\n  const [error, setError] = useState<string | null>(null);\n  const [offset, setOffset] = useState(0);\n  const [viewMode, setViewMode] = useState<\"head\" | \"tail\">(\"tail\");\n  const limit = 50;\n\n  const load = useCallback(async () => {\n    setLoading(true);\n    setError(null);\n    try {\n      const res = await fetchPipelineEvents(videoId, {\n        offset,\n        limit,\n        order: viewMode === \"head\" ? \"asc\" : \"desc\",\n      });\n      setEvents(res.items);\n      setTotal(res.total);\n    } catch (err) {\n      setError(err instanceof Error ? err.message : \"Failed to load events\");\n    } finally {\n      setLoading(false);\n    }\n  }, [videoId, offset, viewMode]);\n\n  useEffect(() => {\n    void load();\n  }, [load]);\n\n  if (loading) return <div className=\"loading\">Loading events…</div>;\n  if (error) return <div className=\"loading error-text\">Error: {error}</div>;\n  if (events.length === 0) return <div className=\"pipeline-events__empty\">No events recorded.</div>;\n\n  const hasNext = offset + limit < total;\n  const hasPrev = offset > 0;\n\n  return (\n    <div className=\"pipeline-events\">\n      <div className=\"pipeline-events__header\">\n        <span className=\"pipeline-events__count\">{total} event{total !== 1 ? \"s\" : \"\"}</span>\n        <div className=\"pipeline-events__view-toggle\">\n          <button\n            className={`pipeline-events__view-btn${viewMode === \"head\" ? \" pipeline-events__view-btn--active\" : \"\"}`}\n            onClick={() => { setViewMode(\"head\"); setOffset(0); }}\n          >\n            Head\n          </button>\n          <button\n            className={`pipeline-events__view-btn${viewMode === \"tail\" ? \" pipeline-events__view-btn--active\" : \"\"}`}\n            onClick={() => { setViewMode(\"tail\"); setOffset(0); }}\n          >\n            Tail\n          </button>\n        </div>\n        <button className=\"btn btn--small btn--secondary\" onClick={() => void load()}>↻ Refresh</button>\n      </div>\n\n      <div className=\"pipeline-events__list\">\n        {events.map((evt) => (\n          <div key={evt.id} className={`pipeline-event pipeline-event--${evt.event_type}`}>\n            <div className=\"pipeline-event__row\">\n              <span className=\"pipeline-event__icon\">{eventTypeIcon(evt.event_type)}</span>\n              <span className=\"pipeline-event__stage\">{evt.stage}</span>\n              <span className={`pipeline-badge pipeline-badge--event-${evt.event_type}`}>\n                {evt.event_type}\n              </span>\n              {evt.model && <span className=\"pipeline-event__model\">{evt.model}</span>}\n              {evt.total_tokens != null && evt.total_tokens > 0 && (\n                <span className=\"pipeline-event__tokens\" title={`prompt: ${evt.prompt_tokens ?? 0} / completion: ${evt.completion_tokens ?? 0}`}>\n                  {formatTokens(evt.total_tokens)} tok\n                </span>\n              )}\n              {evt.duration_ms != null && (\n                <span className=\"pipeline-event__duration\">{evt.duration_ms}ms</span>\n              )}\n              <span className=\"pipeline-event__time\">{formatDate(evt.created_at)}</span>\n            </div>\n            <JsonViewer data={evt.payload} />\n          </div>\n        ))}\n      </div>\n\n      {(hasPrev || hasNext) && (\n        <div className=\"pipeline-events__pager\">\n          <button\n            className=\"btn btn--small btn--secondary\"\n            disabled={!hasPrev}\n            onClick={() => setOffset((o) => Math.max(0, o - limit))}\n          >\n            ← Prev\n          </button>\n          <span className=\"pipeline-events__pager-info\">\n            {offset + 1}–{Math.min(offset + limit, total)} of {total}\n          </span>\n          <button\n            className=\"btn btn--small btn--secondary\"\n            disabled={!hasNext}\n            onClick={() => setOffset((o) => o + limit)}\n          >\n            Next →\n          </button>\n        </div>\n      )}\n    </div>\n  );\n}\n\n// ── Worker Status ────────────────────────────────────────────────────────────\n\nfunction WorkerStatus() {\n  const [status, setStatus] = useState<WorkerStatusResponse | null>(null);\n  const [error, setError] = useState<string | null>(null);\n\n  const load = useCallback(async () => {\n    try {\n      setError(null);\n      const res = await fetchWorkerStatus();\n      setStatus(res);\n    } catch (err) {\n      setError(err instanceof Error ? err.message : \"Failed\");\n    }\n  }, []);\n\n  useEffect(() => {\n    void load();\n    const id = setInterval(() => void load(), 15_000);\n    return () => clearInterval(id);\n  }, [load]);\n\n  if (error) {\n    return (\n      <div className=\"worker-status worker-status--error\">\n        <span className=\"worker-status__dot worker-status__dot--offline\" />\n        Worker: error ({error})\n      </div>\n    );\n  }\n\n  if (!status) {\n    return (\n      <div className=\"worker-status\">\n        <span className=\"worker-status__dot worker-status__dot--unknown\" />\n        Worker: checking…\n      </div>\n    );\n  }\n\n  return (\n    <div className={`worker-status ${status.online ? \"worker-status--online\" : \"worker-status--offline\"}`}>\n      <span className={`worker-status__dot ${status.online ? \"worker-status__dot--online\" : \"worker-status__dot--offline\"}`} />\n      <span className=\"worker-status__label\">\n        {status.online ? `${status.workers.length} worker${status.workers.length !== 1 ? \"s\" : \"\"} online` : \"Workers offline\"}\n      </span>\n      {status.workers.map((w) => (\n        <span key={w.name} className=\"worker-status__detail\" title={w.name}>\n          {w.active_tasks.length > 0\n            ? `${w.active_tasks.length} active`\n            : \"idle\"}\n          {w.pool_size != null && ` · pool ${w.pool_size}`}\n        </span>\n      ))}\n    </div>\n  );\n}\n\n// ── Main Page ────────────────────────────────────────────────────────────────\n\nexport default function AdminPipeline() {\n  const [videos, setVideos] = useState<PipelineVideoItem[]>([]);\n  const [loading, setLoading] = useState(true);\n  const [error, setError] = useState<string | null>(null);\n  const [expandedId, setExpandedId] = useState<string | null>(null);\n  const [actionLoading, setActionLoading] = useState<string | null>(null);\n  const [actionMessage, setActionMessage] = useState<{ id: string; text: string; ok: boolean } | null>(null);\n\n  const load = useCallback(async () => {\n    setLoading(true);\n    setError(null);\n    try {\n      const res = await fetchPipelineVideos();\n      setVideos(res.items);\n    } catch (err) {\n      setError(err instanceof Error ? err.message : \"Failed to load videos\");\n    } finally {\n      setLoading(false);\n    }\n  }, []);\n\n  useEffect(() => {\n    void load();\n  }, [load]);\n\n  const handleTrigger = async (videoId: string) => {\n    setActionLoading(videoId);\n    setActionMessage(null);\n    try {\n      const res = await triggerPipeline(videoId);\n      setActionMessage({ id: videoId, text: `Triggered (${res.status})`, ok: true });\n      // Refresh after short delay to let status update\n      setTimeout(() => void load(), 2000);\n    } catch (err) {\n      setActionMessage({\n        id: videoId,\n        text: err instanceof Error ? err.message : \"Trigger failed\",\n        ok: false,\n      });\n    } finally {\n      setActionLoading(null);\n    }\n  };\n\n  const handleRevoke = async (videoId: string) => {\n    setActionLoading(videoId);\n    setActionMessage(null);\n    try {\n      const res = await revokePipeline(videoId);\n      setActionMessage({\n        id: videoId,\n        text: res.tasks_revoked > 0\n          ? `Revoked ${res.tasks_revoked} task${res.tasks_revoked !== 1 ? \"s\" : \"\"}`\n          : \"No active tasks\",\n        ok: true,\n      });\n      setTimeout(() => void load(), 2000);\n    } catch (err) {\n      setActionMessage({\n        id: videoId,\n        text: err instanceof Error ? err.message : \"Revoke failed\",\n        ok: false,\n      });\n    } finally {\n      setActionLoading(null);\n    }\n  };\n\n  const toggleExpand = (id: string) => {\n    setExpandedId((prev) => (prev === id ? null : id));\n  };\n\n  return (\n    <div className=\"admin-pipeline\">\n      <div className=\"admin-pipeline__header\">\n        <div>\n          <h2 className=\"admin-pipeline__title\">Pipeline Management</h2>\n          <p className=\"admin-pipeline__subtitle\">\n            {videos.length} video{videos.length !== 1 ? \"s\" : \"\"}\n          </p>\n        </div>\n        <div className=\"admin-pipeline__header-right\">\n          <WorkerStatus />\n          <button className=\"btn btn--secondary\" onClick={() => void load()} disabled={loading}>\n            ↻ Refresh\n          </button>\n        </div>\n      </div>\n\n      {loading ? (\n        <div className=\"loading\">Loading videos…</div>\n      ) : error ? (\n        <div className=\"loading error-text\">Error: {error}</div>\n      ) : videos.length === 0 ? (\n        <div className=\"empty-state\">No videos in pipeline.</div>\n      ) : (\n        <div className=\"admin-pipeline__list\">\n          {videos.map((video) => (\n            <div key={video.id} className=\"pipeline-video\">\n              <div\n                className=\"pipeline-video__header\"\n                onClick={() => toggleExpand(video.id)}\n              >\n                <div className=\"pipeline-video__info\">\n                  <span className=\"pipeline-video__filename\" title={video.filename}>\n                    {video.filename}\n                  </span>\n                  <span className=\"pipeline-video__creator\">{video.creator_name}</span>\n                </div>\n\n                <div className=\"pipeline-video__meta\">\n                  <span className={`pipeline-badge ${statusBadgeClass(video.processing_status)}`}>\n                    {video.processing_status}\n                  </span>\n                  <span className=\"pipeline-video__stat\" title=\"Events\">\n                    {video.event_count} events\n                  </span>\n                  <span className=\"pipeline-video__stat\" title=\"Total tokens used\">\n                    {formatTokens(video.total_tokens_used)} tokens\n                  </span>\n                  <span className=\"pipeline-video__time\">\n                    {formatDate(video.last_event_at)}\n                  </span>\n                </div>\n\n                <div className=\"pipeline-video__actions\" onClick={(e) => e.stopPropagation()}>\n                  <button\n                    className=\"btn btn--small btn--primary\"\n                    onClick={() => void handleTrigger(video.id)}\n                    disabled={actionLoading === video.id}\n                    title=\"Retrigger pipeline\"\n                  >\n                    {actionLoading === video.id ? \"…\" : \"▶ Trigger\"}\n                  </button>\n                  <button\n                    className=\"btn btn--small btn--danger\"\n                    onClick={() => void handleRevoke(video.id)}\n                    disabled={actionLoading === video.id}\n                    title=\"Revoke active tasks\"\n                  >\n                    {actionLoading === video.id ? \"…\" : \"■ Revoke\"}\n                  </button>\n                </div>\n              </div>\n\n              {actionMessage?.id === video.id && (\n                <div className={`pipeline-video__message ${actionMessage.ok ? \"pipeline-video__message--ok\" : \"pipeline-video__message--err\"}`}>\n                  {actionMessage.text}\n                </div>\n              )}\n\n              {expandedId === video.id && (\n                <div className=\"pipeline-video__detail\">\n                  <div className=\"pipeline-video__detail-meta\">\n                    <span>ID: {video.id.slice(0, 8)}…</span>\n                    <span>Created: {formatDate(video.created_at)}</span>\n                    <span>Updated: {formatDate(video.updated_at)}</span>\n                  </div>\n                  <EventLog videoId={video.id} />\n                </div>\n              )}\n            </div>\n          ))}\n        </div>\n      )}\n    </div>\n  );\n}\n"}],"isError":false,"timestamp":1774897069696}}
{"type":"message","id":"a6575473","parentId":"d86e3e02","timestamp":"2026-03-30T18:57:56.509Z","message":{"role":"assistant","content":[{"type":"text","text":"Good — I can see the existing event list already renders each event with a `JsonViewer` for the payload. Now let me check the API client types and the CSS."},{"type":"toolCall","id":"toolu_01LJY5jrgs2F4QYjDe2nkp6p","name":"bash","arguments":{"command":"ssh ub01 \"grep -n 'PipelineEvent\\|fetchPipelineEvents\\|pipeline/events' /vmPool/r/repos/xpltdco/chrysopedia/frontend/src/api/public-client.ts\""}},{"type":"toolCall","id":"toolu_01NTBmBDYiYqBncwqqQnKGjK","name":"bash","arguments":{"command":"ssh ub01 \"grep -n 'system_prompt\\|user_prompt\\|response_text\\|debug' /vmPool/r/repos/xpltdco/chrysopedia/frontend/src/api/public-client.ts\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":238,"cacheRead":68230,"cacheWrite":8498,"totalTokens":76967,"cost":{"input":0.000005,"output":0.00595,"cacheRead":0.034115,"cacheWrite":0.0531125,"total":0.0931825}},"stopReason":"toolUse","timestamp":1774897069698}}
{"type":"message","id":"39c8a09d","parentId":"a6575473","timestamp":"2026-03-30T18:57:56.822Z","message":{"role":"toolResult","toolCallId":"toolu_01LJY5jrgs2F4QYjDe2nkp6p","toolName":"bash","content":[{"type":"text","text":"381:export interface PipelineEvent {\n395:export interface PipelineEventListResponse {\n396:  items: PipelineEvent[];\n440:export async function fetchPipelineEvents(\n443:): Promise<PipelineEventListResponse> {\n451:  return request<PipelineEventListResponse>(\n452:    `${BASE}/admin/pipeline/events/${videoId}${query ? `?${query}` : \"\"}`,\n"}],"isError":false,"timestamp":1774897076821}}
{"type":"message","id":"0240a734","parentId":"39c8a09d","timestamp":"2026-03-30T18:57:56.824Z","message":{"role":"toolResult","toolCallId":"toolu_01NTBmBDYiYqBncwqqQnKGjK","toolName":"bash","content":[{"type":"text","text":"(no output)\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1774897076821}}
{"type":"message","id":"b7b05f7e","parentId":"0240a734","timestamp":"2026-03-30T18:58:01.753Z","message":{"role":"assistant","content":[{"type":"text","text":"The PipelineEvent interface doesn't have the debug fields yet. Let me check the full type."},{"type":"toolCall","id":"toolu_019fVKd2U5ZHLr2BbrzXxPC9","name":"bash","arguments":{"command":"ssh ub01 \"sed -n '381,400p' /vmPool/r/repos/xpltdco/chrysopedia/frontend/src/api/public-client.ts\""}},{"type":"toolCall","id":"toolu_016XSe3e7aahvqwYPzLwyGFB","name":"bash","arguments":{"command":"ssh ub01 \"grep -n 'clipboard\\|navigator.clipboard\\|copy\\|download\\|export\\|JSON.stringify' /vmPool/r/repos/xpltdco/chrysopedia/frontend/src/pages/AdminPipeline.tsx\" 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":221,"cacheRead":76728,"cacheWrite":413,"totalTokens":77363,"cost":{"input":0.000005,"output":0.005525,"cacheRead":0.038363999999999995,"cacheWrite":0.00258125,"total":0.046475249999999996}},"stopReason":"toolUse","timestamp":1774897076822}}
{"type":"message","id":"de878a92","parentId":"b7b05f7e","timestamp":"2026-03-30T18:58:02.065Z","message":{"role":"toolResult","toolCallId":"toolu_019fVKd2U5ZHLr2BbrzXxPC9","toolName":"bash","content":[{"type":"text","text":"export interface PipelineEvent {\n  id: string;\n  video_id: string;\n  stage: string;\n  event_type: string;\n  prompt_tokens: number | null;\n  completion_tokens: number | null;\n  total_tokens: number | null;\n  model: string | null;\n  duration_ms: number | null;\n  payload: Record<string, unknown> | null;\n  created_at: string | null;\n}\n\nexport interface PipelineEventListResponse {\n  items: PipelineEvent[];\n  total: number;\n  offset: number;\n  limit: number;\n}\n"}],"isError":false,"timestamp":1774897082065}}
{"type":"message","id":"8b7a2c0d","parentId":"de878a92","timestamp":"2026-03-30T18:58:02.068Z","message":{"role":"toolResult","toolCallId":"toolu_016XSe3e7aahvqwYPzLwyGFB","toolName":"bash","content":[{"type":"text","text":"91:          {JSON.stringify(data, null, 2)}\n269:export default function AdminPipeline() {\n"}],"isError":false,"timestamp":1774897082067}}
{"type":"message","id":"b4bcb773","parentId":"8b7a2c0d","timestamp":"2026-03-30T18:58:07.171Z","message":{"role":"assistant","content":[{"type":"text","text":"Now I have all I need. The PipelineEvent TypeScript interface is missing the 3 debug fields (`system_prompt_text`, `user_prompt_text`, `response_text`). The backend already returns them. The frontend has a basic `JsonViewer` for the JSONB payload but no debug payload viewer. Let me check the CSS file quickly for existing styles."},{"type":"toolCall","id":"toolu_01Q1Nm5X5DS5svSRc5g24DTj","name":"bash","arguments":{"command":"ssh ub01 \"grep -n 'json-viewer\\|pipeline-event' /vmPool/r/repos/xpltdco/chrysopedia/frontend/src/App.css | head -20\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":184,"cacheRead":77141,"cacheWrite":458,"totalTokens":77784,"cost":{"input":0.000005,"output":0.0046,"cacheRead":0.0385705,"cacheWrite":0.0028625,"total":0.046037999999999996}},"stopReason":"toolUse","timestamp":1774897082068}}
{"type":"message","id":"cbaa2f06","parentId":"b4bcb773","timestamp":"2026-03-30T18:58:07.506Z","message":{"role":"toolResult","toolCallId":"toolu_01Q1Nm5X5DS5svSRc5g24DTj","toolName":"bash","content":[{"type":"text","text":"2818:.pipeline-events__header {\n2825:.pipeline-events__count {\n2831:.pipeline-events__view-toggle {\n2838:.pipeline-events__view-btn {\n2850:.pipeline-events__view-btn:hover {\n2855:.pipeline-events__view-btn--active {\n2860:.pipeline-events__view-btn--active:hover {\n2865:.pipeline-events__empty {\n2871:.pipeline-events__list {\n2877:.pipeline-event {\n2884:.pipeline-event--error {\n2888:.pipeline-event__row {\n2895:.pipeline-event__icon {\n2902:.pipeline-event__stage {\n2908:.pipeline-event__model {\n2914:.pipeline-event__tokens {\n2920:.pipeline-event__duration {\n2925:.pipeline-event__time {\n2934:.pipeline-events__pager {\n2942:.pipeline-events__pager-info {\n"}],"isError":false,"timestamp":1774897087505}}
{"type":"message","id":"40fd2625","parentId":"cbaa2f06","timestamp":"2026-03-30T18:58:12.038Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_018EErqtQEpfhM786Jhz2fzz","name":"bash","arguments":{"command":"ssh ub01 \"grep -n 'json-viewer' /vmPool/r/repos/xpltdco/chrysopedia/frontend/src/App.css\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":92,"cacheRead":77599,"cacheWrite":416,"totalTokens":78108,"cost":{"input":0.000005,"output":0.0023,"cacheRead":0.0387995,"cacheWrite":0.0026000000000000003,"total":0.0437045}},"stopReason":"toolUse","timestamp":1774897087505}}
{"type":"message","id":"13cb2228","parentId":"40fd2625","timestamp":"2026-03-30T18:58:12.368Z","message":{"role":"toolResult","toolCallId":"toolu_018EErqtQEpfhM786Jhz2fzz","toolName":"bash","content":[{"type":"text","text":"2949:.json-viewer {\n2953:.json-viewer__toggle {\n2963:.json-viewer__toggle:hover {\n2967:.json-viewer__content {\n"}],"isError":false,"timestamp":1774897092366}}
{"type":"message","id":"24578105","parentId":"13cb2228","timestamp":"2026-03-30T18:58:16.121Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_014KbwWbwqx8d6GQw3GPswm1","name":"bash","arguments":{"command":"ssh ub01 \"sed -n '2949,2985p' /vmPool/r/repos/xpltdco/chrysopedia/frontend/src/App.css\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":94,"cacheRead":77599,"cacheWrite":560,"totalTokens":78254,"cost":{"input":0.000005,"output":0.00235,"cacheRead":0.0387995,"cacheWrite":0.0035,"total":0.04465450000000001}},"stopReason":"toolUse","timestamp":1774897092367}}
{"type":"message","id":"7181324f","parentId":"24578105","timestamp":"2026-03-30T18:58:16.439Z","message":{"role":"toolResult","toolCallId":"toolu_014KbwWbwqx8d6GQw3GPswm1","toolName":"bash","content":[{"type":"text","text":".json-viewer {\n  margin-top: 0.375rem;\n}\n\n.json-viewer__toggle {\n  background: none;\n  border: none;\n  color: var(--color-accent);\n  font-size: 0.75rem;\n  cursor: pointer;\n  padding: 0;\n  font-family: inherit;\n}\n\n.json-viewer__toggle:hover {\n  color: var(--color-accent-hover);\n}\n\n.json-viewer__content {\n  margin: 0.375rem 0 0;\n  padding: 0.5rem 0.75rem;\n  background: var(--color-bg-transcript);\n  border: 1px solid var(--color-border);\n  border-radius: 4px;\n  color: var(--color-text-secondary);\n  font-size: 0.75rem;\n  line-height: 1.5;\n  overflow-x: auto;\n  max-height: 300px;\n  overflow-y: auto;\n}\n"}],"isError":false,"timestamp":1774897096437}}
{"type":"message","id":"39927240","parentId":"7181324f","timestamp":"2026-03-30T18:58:47.838Z","message":{"role":"assistant","content":[{"type":"text","text":"That's all I need. The picture is clear."},{"type":"toolCall","id":"toolu_01FgapZjA8wP5JqZvdEVeaR4","name":"gsd_summary_save","arguments":{"artifact_type":"RESEARCH","content":"# S02 Research: Debug Payload Viewer — Inline View, Copy, and Export in Admin UI\n\n## Summary\n\nStraightforward frontend feature. The backend already returns `system_prompt_text`, `user_prompt_text`, and `response_text` on every event item from `GET /admin/pipeline/events/{video_id}`. The frontend `PipelineEvent` TypeScript interface is missing these 3 fields. The existing `JsonViewer` component shows the JSONB `payload` but there's no viewer for the debug text fields. No new API endpoints needed.\n\n## Recommendation\n\nSingle task or two small tasks:\n1. Add the 3 debug fields to the `PipelineEvent` TS interface, build a `DebugPayloadViewer` component (inline expand for system prompt / user prompt / response, copy-to-clipboard button, export-as-JSON download), and wire it into the existing `EventLog` event rows in `AdminPipeline.tsx`.\n2. Add CSS for the new viewer.\n\nNatural seam: the type update + component + wiring + CSS can all land in one task since they're tightly coupled and small.\n\n## Implementation Landscape\n\n### What exists\n\n| File | Role |\n|------|------|\n| `frontend/src/api/public-client.ts` (L381-393) | `PipelineEvent` interface — missing `system_prompt_text`, `user_prompt_text`, `response_text` |\n| `frontend/src/pages/AdminPipeline.tsx` | Full pipeline admin page. `EventLog` component renders events, `JsonViewer` shows JSONB payload. Each event row is a `pipeline-event` div. |\n| `frontend/src/App.css` (L2949-2985) | `.json-viewer` styles — reusable pattern for the debug viewer |\n| `backend/routers/pipeline.py` (L168-185) | Event list endpoint already returns all 3 debug text fields |\n| `backend/schemas.py` | `TokenSummaryResponse`, `DebugModeResponse` etc already defined |\n\n### What needs to change\n\n1. **`public-client.ts`** — Add 3 optional string fields to `PipelineEvent` interface: `system_prompt_text: string | null`, `user_prompt_text: string | null`, `response_text: string | null`\n2. **`AdminPipeline.tsx`** — New `DebugPayloadViewer` component that:\n   - Only renders when at least one debug field is non-null (events without debug data show nothing extra)\n   - Shows collapsible sections for System Prompt, User Prompt, Response\n   - Each section has a copy-to-clipboard button (`navigator.clipboard.writeText()`)\n   - An \"Export JSON\" button that downloads a JSON file with all 3 fields + event metadata via `URL.createObjectURL(new Blob(...))`\n   - Wire into the event row, after the existing `JsonViewer`\n3. **`App.css`** — Styles for `.debug-viewer` following the existing `.json-viewer` pattern. Monospace `<pre>` blocks, max-height with scroll, accent-colored toggles.\n\n### Patterns to follow\n\n- **Collapsible sections**: Copy the `JsonViewer` pattern (useState boolean, toggle button, conditional render of `<pre>`)\n- **Copy to clipboard**: `navigator.clipboard.writeText(text)` — standard API, no library needed. Show brief \"Copied!\" feedback via state timeout.\n- **Download as JSON**: Create a Blob, `URL.createObjectURL()`, click a hidden `<a>` with download attribute. Standard pattern, no library.\n- **CSS custom properties**: All colors must use `var(--color-*)` tokens from the existing `:root` block (D017). Use `--color-bg-transcript` for code blocks, `--color-accent` for interactive elements.\n\n### Constraints\n\n- Debug fields are NULL when debug mode was off during the pipeline run. UI must handle this gracefully — no empty viewers.\n- `system_prompt_text` can be very long (7752+ chars observed in S01 verification). Need `max-height` + scroll on the `<pre>` blocks.\n- No new API endpoints needed. No backend changes.\n- Frontend build must pass with zero TypeScript errors (established pattern).\n\n### Verification\n\n1. `ssh ub01 \"cd /vmPool/r/repos/xpltdco/chrysopedia && docker compose build chrysopedia-web-8096 && docker compose up -d chrysopedia-web-8096\"` — frontend builds\n2. Browse to `http://ub01:8096` → Pipeline Management → expand a video → expand an LLM call event → debug viewer shows prompts and response\n3. Copy button copies text to clipboard\n4. Export JSON downloads a `.json` file with event metadata + debug fields\n5. Events without debug data (debug mode was off) show no debug viewer section\n","milestone_id":"M007","slice_id":"S02"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":1288,"cacheRead":78159,"cacheWrite":355,"totalTokens":79803,"cost":{"input":0.000005,"output":0.0322,"cacheRead":0.039079499999999996,"cacheWrite":0.0022187500000000002,"total":0.07350325}},"stopReason":"toolUse","timestamp":1774897096438}}
{"type":"message","id":"e3da9ce2","parentId":"39927240","timestamp":"2026-03-30T18:58:47.844Z","message":{"role":"toolResult","toolCallId":"toolu_01FgapZjA8wP5JqZvdEVeaR4","toolName":"gsd_summary_save","content":[{"type":"text","text":"Saved RESEARCH artifact to milestones/M007/slices/S02/S02-RESEARCH.md"}],"details":{"operation":"save_summary","path":"milestones/M007/slices/S02/S02-RESEARCH.md","artifact_type":"RESEARCH"},"isError":false,"timestamp":1774897127842}}
{"type":"message","id":"df7cabd3","parentId":"e3da9ce2","timestamp":"2026-03-30T18:58:50.471Z","message":{"role":"assistant","content":[{"type":"text","text":"Slice S02 researched."}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":11,"cacheRead":78514,"cacheWrite":1326,"totalTokens":79852,"cost":{"input":0.000005,"output":0.000275,"cacheRead":0.039257,"cacheWrite":0.0082875,"total":0.047824500000000006}},"stopReason":"stop","timestamp":1774897127842}}
