{"type":"thinking_level_change","id":"e63fee58","parentId":null,"timestamp":"2026-03-30T11:03:23.565Z","thinkingLevel":"off"}
{"type":"model_change","id":"53dadc29","parentId":"e63fee58","timestamp":"2026-03-30T11:03:23.567Z","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## UNIT: Research Slice S02 (\"Pipeline Page: Head/Tail Log View + Token Count\") — Milestone M006\n\n## Inlined Context (preloaded — do not re-read these files)\n\n### Milestone Roadmap\nSource: `.gsd/milestones/M006/M006-ROADMAP.md`\n\n# M006: \n\n## Vision\nConsolidate admin navigation into a dropdown, add head/tail log viewing and commit SHA tracking to the pipeline, clean up technique page tag styling and sidebar order, redesign the Topics browse page with a Music Theory category, and add app version footer.\n\n## Slice Overview\n| ID | Slice | Risk | Depends | Done | After this |\n|----|-------|------|---------|------|------------|\n| S01 | Admin Navigation Dropdown + Header Cleanup | low | — | ✅ | Header shows Home, Topics, Creators, and an Admin dropdown. Clicking Admin reveals Review, Reports, Pipeline links. ModeToggle removed from header. |\n| S02 | Pipeline Page: Head/Tail Log View + Token Count | low | — | ⬜ | Pipeline event log shows Head/Tail toggle buttons. Head shows first N events, Tail shows last N events. Token counts visible per event and per video. |\n| S03 | Git Commit SHA in Pipeline Version Metadata | low | — | ⬜ | Running the pipeline captures the current git commit SHA. Viewing a technique page version shows the commit hash in the metadata panel. |\n| S04 | Technique Page: Sidebar Reorder, Creator Emphasis, Tag Polish | medium | — | ⬜ | Technique page sidebar shows Plugins Referenced at top. Creator name is visually prominent. Tags use a coherent color system. |\n| S05 | Topics Page Redesign + Music Theory Category | high | — | ⬜ | Topics page shows 7 categories (including Music Theory) with an improved visual layout — category cards with descriptions, sub-topic counts, better structure. |\n| S06 | App Footer with Version Info | low | — | ⬜ | Every page shows a subtle footer with app version, build date, and optional repo link. |\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\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- (no dependencies)\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: M006`, `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/M006/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":"b1d48210","parentId":"53dadc29","timestamp":"2026-03-30T11:03:23.569Z"}
{"type":"message","id":"3c178e28","parentId":"b1d48210","timestamp":"2026-03-30T11:03:30.217Z","message":{"role":"assistant","content":[{"type":"text","text":"\n\nI'll research the Pipeline Page head/tail log view and token count features. Let me start by understanding the current pipeline page implementation."},{"type":"toolCall","id":"toolu_011LvLRsLYk9SGG6xyywduiX","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator/frontend/src -type f -name \"*.tsx\" -o -name \"*.ts\" | xargs grep -li -i \"pipeline\" 2>/dev/null"}},{"type":"toolCall","id":"toolu_013y7w94sbdYHaUn4NEekU98","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator/backend -type f -name \"*.py\" | xargs grep -li -i \"pipeline_event\\|PipelineEvent\" 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":3,"output":220,"cacheRead":57564,"cacheWrite":6330,"totalTokens":64117,"cost":{"input":0.000015000000000000002,"output":0.0055000000000000005,"cacheRead":0.028782,"cacheWrite":0.0395625,"total":0.0738595}},"stopReason":"toolUse","timestamp":1774868603568}}
{"type":"message","id":"f0806ad9","parentId":"3c178e28","timestamp":"2026-03-30T11:03:30.231Z","message":{"role":"toolResult","toolCallId":"toolu_011LvLRsLYk9SGG6xyywduiX","toolName":"bash","content":[{"type":"text","text":"/home/aux/projects/content-to-kb-automator/frontend/src/pages/AdminPipeline.tsx\n/home/aux/projects/content-to-kb-automator/frontend/src/pages/TechniquePage.tsx\n/home/aux/projects/content-to-kb-automator/frontend/src/App.tsx\n/home/aux/projects/content-to-kb-automator/frontend/src/api/public-client.ts\n/home/aux/projects/content-to-kb-automator/frontend/src/components/AdminDropdown.tsx\n"}],"isError":false,"timestamp":1774868610231}}
{"type":"message","id":"fb2008c1","parentId":"f0806ad9","timestamp":"2026-03-30T11:03:30.238Z","message":{"role":"toolResult","toolCallId":"toolu_013y7w94sbdYHaUn4NEekU98","toolName":"bash","content":[{"type":"text","text":"/home/aux/projects/content-to-kb-automator/backend/pipeline/stages.py\n"}],"isError":false,"timestamp":1774868610236}}
{"type":"message","id":"ff3cc44f","parentId":"fb2008c1","timestamp":"2026-03-30T11:03:34.132Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01YPVZNLfCvBq82W8QjUF1qG","name":"read","arguments":{"path":"/home/aux/projects/content-to-kb-automator/frontend/src/pages/AdminPipeline.tsx"}},{"type":"toolCall","id":"toolu_01Ft15pGJbfH9ZmHZ7A6vs19","name":"bash","arguments":{"command":"grep -n \"pipeline_event\\|PipelineEvent\\|pipeline_events\\|event_type\\|token\" /home/aux/projects/content-to-kb-automator/backend/pipeline/stages.py | head -60"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":166,"cacheRead":63894,"cacheWrite":444,"totalTokens":64505,"cost":{"input":0.000005,"output":0.00415,"cacheRead":0.031946999999999996,"cacheWrite":0.002775,"total":0.038876999999999995}},"stopReason":"toolUse","timestamp":1774868610236}}
{"type":"message","id":"9fc8c89c","parentId":"ff3cc44f","timestamp":"2026-03-30T11:03:34.140Z","message":{"role":"toolResult","toolCallId":"toolu_01YPVZNLfCvBq82W8QjUF1qG","toolName":"read","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 limit = 50;\n\n  const load = useCallback(async () => {\n    setLoading(true);\n    setError(null);\n    try {\n      const res = await fetchPipelineEvents(videoId, { offset, limit });\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]);\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        <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":1774868614140}}
{"type":"message","id":"094b4853","parentId":"9fc8c89c","timestamp":"2026-03-30T11:03:34.146Z","message":{"role":"toolResult","toolCallId":"toolu_01Ft15pGJbfH9ZmHZ7A6vs19","toolName":"bash","content":[{"type":"text","text":"29:    PipelineEvent,\n55:    event_type: str,\n57:    prompt_tokens: int | None = None,\n58:    completion_tokens: int | None = None,\n59:    total_tokens: int | None = None,\n68:            event = PipelineEvent(\n71:                event_type=event_type,\n72:                prompt_tokens=prompt_tokens,\n73:                completion_tokens=completion_tokens,\n74:                total_tokens=total_tokens,\n89:    def callback(*, model=None, prompt_tokens=None, completion_tokens=None,\n90:                 total_tokens=None, content=None, finish_reason=None,\n97:            event_type=\"llm_call\",\n99:            prompt_tokens=prompt_tokens,\n100:            completion_tokens=completion_tokens,\n101:            total_tokens=total_tokens,\n"}],"isError":false,"timestamp":1774868614146}}
{"type":"message","id":"f00e3139","parentId":"094b4853","timestamp":"2026-03-30T11:03:42.879Z","message":{"role":"assistant","content":[{"type":"text","text":"Good — substantial existing pipeline page with event log, token counts, and pagination. Now let me check the API client and the backend pipeline event endpoints."},{"type":"toolCall","id":"toolu_01DcCU348mR7YhQGZRSa4u2v","name":"bash","arguments":{"command":"grep -n \"fetchPipelineEvents\\|fetchPipelineVideos\\|PipelineEvent\\|PipelineVideoItem\\|WorkerStatusResponse\\|pipelineEvents\\|pipeline/events\\|pipeline/videos\" /home/aux/projects/content-to-kb-automator/frontend/src/api/public-client.ts"}},{"type":"toolCall","id":"toolu_01XgL7aG4MWmVEJYUGwkc5WC","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator/backend -name \"*.py\" | xargs grep -ln \"pipeline.*events\\|pipeline_events\\|get_events\\|event_count\\|total_tokens\" 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":257,"cacheRead":63894,"cacheWrite":4918,"totalTokens":69070,"cost":{"input":0.000005,"output":0.006425,"cacheRead":0.031946999999999996,"cacheWrite":0.0307375,"total":0.0691145}},"stopReason":"toolUse","timestamp":1774868614146}}
{"type":"message","id":"1da15d27","parentId":"f00e3139","timestamp":"2026-03-30T11:03:42.897Z","message":{"role":"toolResult","toolCallId":"toolu_01DcCU348mR7YhQGZRSa4u2v","toolName":"bash","content":[{"type":"text","text":"364:export interface PipelineVideoItem {\n377:  items: PipelineVideoItem[];\n381:export interface PipelineEvent {\n395:export interface PipelineEventListResponse {\n396:  items: PipelineEvent[];\n418:export interface WorkerStatusResponse {\n436:export async function fetchPipelineVideos(): Promise<PipelineVideoListResponse> {\n437:  return request<PipelineVideoListResponse>(`${BASE}/admin/pipeline/videos`);\n440:export async function fetchPipelineEvents(\n443:): Promise<PipelineEventListResponse> {\n450:  return request<PipelineEventListResponse>(\n451:    `${BASE}/admin/pipeline/events/${videoId}${query ? `?${query}` : \"\"}`,\n455:export async function fetchWorkerStatus(): Promise<WorkerStatusResponse> {\n456:  return request<WorkerStatusResponse>(`${BASE}/admin/pipeline/worker-status`);\n"}],"isError":false,"timestamp":1774868622897}}
{"type":"message","id":"a4f6644a","parentId":"1da15d27","timestamp":"2026-03-30T11:03:42.906Z","message":{"role":"toolResult","toolCallId":"toolu_01XgL7aG4MWmVEJYUGwkc5WC","toolName":"bash","content":[{"type":"text","text":"/home/aux/projects/content-to-kb-automator/backend/pipeline/stages.py\n"}],"isError":false,"timestamp":1774868622904}}
{"type":"message","id":"8ab48b87","parentId":"a4f6644a","timestamp":"2026-03-30T11:03:47.064Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01JXiBXPnsQGNnBuLRCjZnQx","name":"read","arguments":{"limit":100,"offset":360,"path":"/home/aux/projects/content-to-kb-automator/frontend/src/api/public-client.ts"}},{"type":"toolCall","id":"toolu_01MYa8mi91p5tZKmG91DCQR3","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator/backend -name \"*.py\" -path \"*/routers/*\" | xargs grep -ln \"pipeline\" 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":192,"cacheRead":68812,"cacheWrite":569,"totalTokens":69574,"cost":{"input":0.000005,"output":0.0048000000000000004,"cacheRead":0.034406,"cacheWrite":0.0035562500000000004,"total":0.04276724999999999}},"stopReason":"toolUse","timestamp":1774868622905}}
{"type":"message","id":"9abfcbd0","parentId":"8ab48b87","timestamp":"2026-03-30T11:03:47.072Z","message":{"role":"toolResult","toolCallId":"toolu_01JXiBXPnsQGNnBuLRCjZnQx","toolName":"read","content":[{"type":"text","text":"\n\n// ── Pipeline Admin ──────────────────────────────────────────────────────────\n\nexport interface PipelineVideoItem {\n  id: string;\n  filename: string;\n  processing_status: string;\n  creator_name: string;\n  created_at: string | null;\n  updated_at: string | null;\n  event_count: number;\n  total_tokens_used: number;\n  last_event_at: string | null;\n}\n\nexport interface PipelineVideoListResponse {\n  items: PipelineVideoItem[];\n  total: number;\n}\n\nexport 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\nexport interface WorkerTask {\n  id: string;\n  name: string;\n  args: unknown[];\n  time_start: number | null;\n}\n\nexport interface WorkerInfo {\n  name: string;\n  active_tasks: WorkerTask[];\n  reserved_tasks: number;\n  total_completed: number;\n  uptime: string | null;\n  pool_size: number | null;\n}\n\nexport interface WorkerStatusResponse {\n  online: boolean;\n  workers: WorkerInfo[];\n  error?: string;\n}\n\nexport interface TriggerResponse {\n  status: string;\n  video_id: string;\n  current_processing_status?: string;\n}\n\nexport interface RevokeResponse {\n  status: string;\n  video_id: string;\n  tasks_revoked: number;\n}\n\nexport async function fetchPipelineVideos(): Promise<PipelineVideoListResponse> {\n  return request<PipelineVideoListResponse>(`${BASE}/admin/pipeline/videos`);\n}\n\nexport async function fetchPipelineEvents(\n  videoId: string,\n  params: { offset?: number; limit?: number; stage?: string; event_type?: string } = {},\n): Promise<PipelineEventListResponse> {\n  const qs = new URLSearchParams();\n  if (params.offset !== undefined) qs.set(\"offset\", String(params.offset));\n  if (params.limit !== undefined) qs.set(\"limit\", String(params.limit));\n  if (params.stage) qs.set(\"stage\", params.stage);\n  if (params.event_type) qs.set(\"event_type\", params.event_type);\n  const query = qs.toString();\n  return request<PipelineEventListResponse>(\n    `${BASE}/admin/pipeline/events/${videoId}${query ? `?${query}` : \"\"}`,\n  );\n}\n\nexport async function fetchWorkerStatus(): Promise<WorkerStatusResponse> {\n  return request<WorkerStatusResponse>(`${BASE}/admin/pipeline/worker-status`);\n}\n\nexport async function triggerPipeline(videoId: string): Promise<TriggerResponse> {\n\n[11 more lines in file. Use offset=460 to continue.]"}],"isError":false,"timestamp":1774868627072}}
{"type":"message","id":"1818ca4d","parentId":"9abfcbd0","timestamp":"2026-03-30T11:03:47.077Z","message":{"role":"toolResult","toolCallId":"toolu_01MYa8mi91p5tZKmG91DCQR3","toolName":"bash","content":[{"type":"text","text":"(no output)\n\nCommand exited with code 123"}],"details":{},"isError":true,"timestamp":1774868627075}}
{"type":"message","id":"170fe54c","parentId":"1818ca4d","timestamp":"2026-03-30T11:03:51.557Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01Xn6z1MkGJC23MJLqru73Bd","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator/backend -name \"*.py\" -path \"*router*\" -o -name \"*.py\" -path \"*route*\" | head -20"}},{"type":"toolCall","id":"toolu_01FWCrqYnyQ4Eo5JoJMmhupv","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator/backend -name \"*.py\" | xargs grep -ln \"admin.*pipeline\\|pipeline.*router\\|@router.*pipeline\\|events.*video\" 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":190,"cacheRead":69381,"cacheWrite":1082,"totalTokens":70654,"cost":{"input":0.000005,"output":0.00475,"cacheRead":0.0346905,"cacheWrite":0.0067625,"total":0.046208}},"stopReason":"toolUse","timestamp":1774868627076}}
{"type":"message","id":"9984f5e0","parentId":"170fe54c","timestamp":"2026-03-30T11:03:51.576Z","message":{"role":"toolResult","toolCallId":"toolu_01Xn6z1MkGJC23MJLqru73Bd","toolName":"bash","content":[{"type":"text","text":"(no output)"}],"isError":false,"timestamp":1774868631576}}
{"type":"message","id":"af92f30c","parentId":"9984f5e0","timestamp":"2026-03-30T11:03:51.582Z","message":{"role":"toolResult","toolCallId":"toolu_01FWCrqYnyQ4Eo5JoJMmhupv","toolName":"bash","content":[{"type":"text","text":"(no output)\n\nCommand exited with code 123"}],"details":{},"isError":true,"timestamp":1774868631580}}
{"type":"message","id":"af24bd85","parentId":"af92f30c","timestamp":"2026-03-30T11:03:54.448Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01JPbCNis2g6K2Pry6temKFb","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator/backend -name \"*.py\" | head -30"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":79,"cacheRead":69381,"cacheWrite":1346,"totalTokens":70807,"cost":{"input":0.000005,"output":0.001975,"cacheRead":0.0346905,"cacheWrite":0.0084125,"total":0.045083}},"stopReason":"toolUse","timestamp":1774868631581}}
{"type":"message","id":"b62f7f70","parentId":"af24bd85","timestamp":"2026-03-30T11:03:54.466Z","message":{"role":"toolResult","toolCallId":"toolu_01JPbCNis2g6K2Pry6temKFb","toolName":"bash","content":[{"type":"text","text":"/home/aux/projects/content-to-kb-automator/backend/pipeline/stages.py\n"}],"isError":false,"timestamp":1774868634463}}
{"type":"message","id":"2ae976db","parentId":"b62f7f70","timestamp":"2026-03-30T11:03:58.560Z","message":{"role":"assistant","content":[{"type":"text","text":"Only one Python file? Let me look at the backend structure more broadly."},{"type":"toolCall","id":"toolu_01RdKXjt4nGek5HYrcycBcYD","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator/backend -type f | head -40"}},{"type":"toolCall","id":"toolu_019RzZNW9HkHRGiByaWJznrB","name":"bash","arguments":{"command":"ls -la /home/aux/projects/content-to-kb-automator/backend/"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":147,"cacheRead":70727,"cacheWrite":114,"totalTokens":70989,"cost":{"input":0.000005,"output":0.0036750000000000003,"cacheRead":0.0353635,"cacheWrite":0.0007125,"total":0.039756}},"stopReason":"toolUse","timestamp":1774868634464}}
{"type":"message","id":"6fcf0419","parentId":"2ae976db","timestamp":"2026-03-30T11:03:58.576Z","message":{"role":"toolResult","toolCallId":"toolu_01RdKXjt4nGek5HYrcycBcYD","toolName":"bash","content":[{"type":"text","text":"/home/aux/projects/content-to-kb-automator/backend/pipeline/stages.py\n"}],"isError":false,"timestamp":1774868638576}}
{"type":"message","id":"602c9d5a","parentId":"6fcf0419","timestamp":"2026-03-30T11:03:58.584Z","message":{"role":"toolResult","toolCallId":"toolu_019RzZNW9HkHRGiByaWJznrB","toolName":"bash","content":[{"type":"text","text":"total 12\ndrwxrwxr-x 3 aux aux 4096 Mar 30 08:40 .\ndrwxrwxr-x 9 aux aux 4096 Mar 30 10:57 ..\ndrwxrwxr-x 2 aux aux 4096 Mar 30 08:40 pipeline\n"}],"isError":false,"timestamp":1774868638582}}
{"type":"message","id":"cd2d9c16","parentId":"602c9d5a","timestamp":"2026-03-30T11:04:02.965Z","message":{"role":"assistant","content":[{"type":"text","text":"Interesting — the backend is sparse locally. The real codebase must be on ub01 per the CLAUDE.md note. Let me check the broader project structure for the full codebase."},{"type":"toolCall","id":"toolu_01HsCUuJVKRRzjxZSU4gemrh","name":"bash","arguments":{"command":"ls -la /home/aux/projects/content-to-kb-automator/"}},{"type":"toolCall","id":"toolu_01BMRAvdjAXs3u17Q7Hf6Dm8","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator -maxdepth 2 -type d | sort"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":177,"cacheRead":70841,"cacheWrite":319,"totalTokens":71338,"cost":{"input":0.000005,"output":0.004425,"cacheRead":0.0354205,"cacheWrite":0.0019937500000000003,"total":0.04184425}},"stopReason":"toolUse","timestamp":1774868638583}}
{"type":"message","id":"9845b61e","parentId":"cd2d9c16","timestamp":"2026-03-30T11:04:02.986Z","message":{"role":"toolResult","toolCallId":"toolu_01HsCUuJVKRRzjxZSU4gemrh","toolName":"bash","content":[{"type":"text","text":"total 44\ndrwxrwxr-x 9 aux aux 4096 Mar 30 10:57 .\ndrwxrwxr-x 4 aux aux 4096 Mar 29 17:47 ..\ndrwxrwxr-x 3 aux aux 4096 Mar 30 08:33 .artifacts\ndrwxrwxr-x 3 aux aux 4096 Mar 30 08:40 backend\ndrwxrwxr-x 2 aux aux 4096 Mar 30 07:38 .bg-shell\n-rw-rw-r-- 1 aux aux 1497 Mar 30 07:38 CLAUDE.md\ndrwxrwxr-x 5 aux aux 4096 Mar 30 08:54 frontend\ndrwxrwxr-x 8 aux aux 4096 Mar 30 11:02 .git\n-rw-rw-r-- 1 aux aux  353 Mar 29 21:39 .gitignore\ndrwxrwxr-x 6 aux aux 4096 Mar 30 11:03 .gsd\ndrwxrwxr-x 2 aux aux 4096 Mar 30 11:03 .gsd.lock\n"}],"isError":false,"timestamp":1774868642986}}
{"type":"message","id":"21bd9eb6","parentId":"9845b61e","timestamp":"2026-03-30T11:04:02.998Z","message":{"role":"toolResult","toolCallId":"toolu_01BMRAvdjAXs3u17Q7Hf6Dm8","toolName":"bash","content":[{"type":"text","text":"/home/aux/projects/content-to-kb-automator\n/home/aux/projects/content-to-kb-automator/.artifacts\n/home/aux/projects/content-to-kb-automator/.artifacts/browser\n/home/aux/projects/content-to-kb-automator/backend\n/home/aux/projects/content-to-kb-automator/backend/pipeline\n/home/aux/projects/content-to-kb-automator/.bg-shell\n/home/aux/projects/content-to-kb-automator/frontend\n/home/aux/projects/content-to-kb-automator/frontend/dist\n/home/aux/projects/content-to-kb-automator/frontend/node_modules\n/home/aux/projects/content-to-kb-automator/frontend/src\n/home/aux/projects/content-to-kb-automator/.git\n/home/aux/projects/content-to-kb-automator/.git/branches\n/home/aux/projects/content-to-kb-automator/.git/hooks\n/home/aux/projects/content-to-kb-automator/.git/info\n/home/aux/projects/content-to-kb-automator/.git/logs\n/home/aux/projects/content-to-kb-automator/.git/objects\n/home/aux/projects/content-to-kb-automator/.git/refs\n/home/aux/projects/content-to-kb-automator/.gsd\n/home/aux/projects/content-to-kb-automator/.gsd/activity\n/home/aux/projects/content-to-kb-automator/.gsd/journal\n/home/aux/projects/content-to-kb-automator/.gsd.lock\n/home/aux/projects/content-to-kb-automator/.gsd/milestones\n/home/aux/projects/content-to-kb-automator/.gsd/runtime\n"}],"isError":false,"timestamp":1774868642995}}
{"type":"message","id":"e2eec4c0","parentId":"21bd9eb6","timestamp":"2026-03-30T11:04:07.509Z","message":{"role":"assistant","content":[{"type":"text","text":"The project structure shows this is the frontend-primary workspace, with the full backend on ub01. Let me check the git remote and whether there's a fuller picture in the repo."},{"type":"toolCall","id":"toolu_01AaqPYDs9qBsNBXFqn2ZKDC","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && git log --oneline -20"}},{"type":"toolCall","id":"toolu_015c8czYVb4aBoTAfgFVutMB","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && git remote -v"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":169,"cacheRead":71160,"cacheWrite":1021,"totalTokens":72351,"cost":{"input":0.000005,"output":0.0042250000000000005,"cacheRead":0.03558,"cacheWrite":0.006381250000000001,"total":0.046191249999999996}},"stopReason":"toolUse","timestamp":1774868642996}}
{"type":"message","id":"ca1e0ba1","parentId":"e2eec4c0","timestamp":"2026-03-30T11:04:07.531Z","message":{"role":"toolResult","toolCallId":"toolu_01AaqPYDs9qBsNBXFqn2ZKDC","toolName":"bash","content":[{"type":"text","text":"05c7ba3 feat: Created AdminDropdown component with click-outside/Escape close,…\n94460fa chore: auto-commit after complete-milestone\nc6efec8 feat: Split key moment card header into standalone h3 title and flex-ro…\naa71387 feat: Added CSS grid layout splitting technique page into prose (left)…\n26556ba feat: Built AdminPipeline.tsx page at /admin/pipeline with video table,…\nb3d405b fix: All five admin pipeline endpoints respond correctly — fix was ngin…\n7aa33cd fix: Fixed syntax errors in pipeline event instrumentation — _emit_even…\ne08e8d0 fix: Creators page 422 — limit=200 exceeded API max of 100, also fix error display for Pydantic validation arrays\nac45ce7 chore: auto-commit after complete-milestone\n8fb3f19 feat: Added TypeScript version types, fetchTechniqueVersions function,…\n44fbbf0 test: Added version list/detail API endpoints, Pydantic schemas, versio…\n5c3e9b8 feat: Added TechniquePageVersion model, Alembic migration 002, pipeline…\n37426aa feat: Redesigned technique page frontend: meta stats line, video filena…\nf99ac1b prompts: Rewrite all four pipeline stage prompts for quality and domain awareness\n39006ca feat: redesign technique page - meta stats, video filenames, monospace signal chains\n0c4162a feat: Added video_filename field to KeyMomentSummary schema and populat…\nc575e76 fix: Added overflow-x:hidden to html/body, fixed mobile overflow on mod…\n893105a feat: Replaced all 193 hex colors and 24 rgba values in App.css with 77…\n7613888 fix: Creators endpoint returns paginated response, review queue limit raised to 1000, added GET /review/moments/{id} endpoint\n0b0ca59 feat: Log LLM response token usage (prompt/completion/total, content_len, finish_reason)\n"}],"isError":false,"timestamp":1774868647530}}
{"type":"message","id":"b602b6c4","parentId":"ca1e0ba1","timestamp":"2026-03-30T11:04:07.544Z","message":{"role":"toolResult","toolCallId":"toolu_015c8czYVb4aBoTAfgFVutMB","toolName":"bash","content":[{"type":"text","text":"origin\tgit@github.com:xpltdco/chrysopedia.git (fetch)\norigin\tgit@github.com:xpltdco/chrysopedia.git (push)\n"}],"isError":false,"timestamp":1774868647542}}
{"type":"message","id":"52d47d4a","parentId":"b602b6c4","timestamp":"2026-03-30T11:04:12.433Z","message":{"role":"assistant","content":[{"type":"text","text":"The full backend is on ub01. Let me SSH and check the relevant backend files there."},{"type":"toolCall","id":"toolu_01DCLeftnksWdNvjTtNr1k1B","name":"bash","arguments":{"command":"ssh ub01 \"find /vmPool/r/repos/xpltdco/chrysopedia/backend -name '*.py' -path '*admin*' -o -name '*.py' -path '*pipeline*'\" 2>/dev/null"}},{"type":"toolCall","id":"toolu_01KWgtHqURi17jANkuGZCikT","name":"bash","arguments":{"command":"ssh ub01 \"find /vmPool/r/repos/xpltdco/chrysopedia/backend -name '*.py' | head -40\" 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":207,"cacheRead":72181,"cacheWrite":771,"totalTokens":73160,"cost":{"input":0.000005,"output":0.005175,"cacheRead":0.0360905,"cacheWrite":0.00481875,"total":0.04608925}},"stopReason":"toolUse","timestamp":1774868647543}}
{"type":"message","id":"be7abf00","parentId":"52d47d4a","timestamp":"2026-03-30T11:04:13.177Z","message":{"role":"toolResult","toolCallId":"toolu_01DCLeftnksWdNvjTtNr1k1B","toolName":"bash","content":[{"type":"text","text":"/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/__init__.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/llm_client.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/stages.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/schemas.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/qdrant_client.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/embedding_client.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/pipeline.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/tests/test_pipeline.py\n"}],"isError":false,"timestamp":1774868653177}}
{"type":"message","id":"5cf09715","parentId":"be7abf00","timestamp":"2026-03-30T11:04:13.179Z","message":{"role":"toolResult","toolCallId":"toolu_01KWgtHqURi17jANkuGZCikT","toolName":"bash","content":[{"type":"text","text":"/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/__init__.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/llm_client.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/stages.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/schemas.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/qdrant_client.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/pipeline/embedding_client.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/schemas.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/main.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/config.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/database.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/redis_client.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/models.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/worker.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/health.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/techniques.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/pipeline.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/videos.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/topics.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/ingest.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/search.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/__init__.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/creators.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/reports.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/review.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/tests/fixtures/mock_llm_responses.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/tests/test_ingest.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/tests/test_public_api.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/tests/test_pipeline.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/tests/test_review.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/tests/conftest.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/tests/test_search.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/tests/__init__.py\n/vmPool/r/repos/xpltdco/chrysopedia/backend/search_service.py\n"}],"isError":false,"timestamp":1774868653177}}
{"type":"message","id":"58240940","parentId":"5cf09715","timestamp":"2026-03-30T11:04:19.020Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me read the pipeline router (backend API) and the PipelineEvent model."},{"type":"toolCall","id":"toolu_013y1W1kJtmPP54fcAggfcKp","name":"bash","arguments":{"command":"ssh ub01 \"cat /vmPool/r/repos/xpltdco/chrysopedia/backend/routers/pipeline.py\""}},{"type":"toolCall","id":"toolu_016Q62dJ5KhTNzZFtt7qQ43F","name":"bash","arguments":{"command":"ssh ub01 \"grep -n 'PipelineEvent\\|pipeline_event\\|class Pipeline' /vmPool/r/repos/xpltdco/chrysopedia/backend/models.py\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":188,"cacheRead":72952,"cacheWrite":1374,"totalTokens":74515,"cost":{"input":0.000005,"output":0.0047,"cacheRead":0.036476,"cacheWrite":0.0085875,"total":0.0497685}},"stopReason":"toolUse","timestamp":1774868653178}}
{"type":"message","id":"640d4745","parentId":"58240940","timestamp":"2026-03-30T11:04:19.366Z","message":{"role":"toolResult","toolCallId":"toolu_013y1W1kJtmPP54fcAggfcKp","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 database import get_session\nfrom models import PipelineEvent, SourceVideo, Creator\n\nlogger = logging.getLogger(\"chrysopedia.pipeline\")\n\nrouter = APIRouter(tags=[\"pipeline\"])\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    db: AsyncSession = Depends(get_session),\n):\n    \"\"\"Get pipeline events for a video, newest first.\"\"\"\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    # 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    stmt = stmt.order_by(PipelineEvent.created_at.desc())\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            }\n            for e in events\n        ],\n        \"total\": total,\n        \"offset\": offset,\n        \"limit\": limit,\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":1774868659365}}
{"type":"message","id":"d51ff687","parentId":"640d4745","timestamp":"2026-03-30T11:04:19.368Z","message":{"role":"toolResult","toolCallId":"toolu_016Q62dJ5KhTNzZFtt7qQ43F","toolName":"bash","content":[{"type":"text","text":"386:class PipelineEvent(Base):\n392:    __tablename__ = \"pipeline_events\"\n"}],"isError":false,"timestamp":1774868659365}}
{"type":"message","id":"4dc45362","parentId":"d51ff687","timestamp":"2026-03-30T11:04:23.622Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01RwM3w6P6gyJp3BfJHYvdTG","name":"bash","arguments":{"command":"ssh ub01 \"sed -n '386,430p' /vmPool/r/repos/xpltdco/chrysopedia/backend/models.py\""}},{"type":"toolCall","id":"toolu_01Hw3nhJdVBCXKjDGR2kDysu","name":"bash","arguments":{"command":"find /home/aux/projects/content-to-kb-automator/frontend/src -name \"App.css\" -o -name \"*.css\" | head -5"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":163,"cacheRead":74326,"cacheWrite":3190,"totalTokens":77680,"cost":{"input":0.000005,"output":0.0040750000000000005,"cacheRead":0.037163,"cacheWrite":0.0199375,"total":0.0611805}},"stopReason":"toolUse","timestamp":1774868659367}}
{"type":"message","id":"3aafe90c","parentId":"4dc45362","timestamp":"2026-03-30T11:04:23.926Z","message":{"role":"toolResult","toolCallId":"toolu_01RwM3w6P6gyJp3BfJHYvdTG","toolName":"bash","content":[{"type":"text","text":"class PipelineEvent(Base):\n    \"\"\"Structured log entry for pipeline execution.\n\n    Captures per-stage start/complete/error/llm_call events with\n    token usage and optional response payloads for debugging.\n    \"\"\"\n    __tablename__ = \"pipeline_events\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    video_id: Mapped[uuid.UUID] = mapped_column(\n        UUID(as_uuid=True), nullable=False, index=True,\n    )\n    stage: Mapped[str] = mapped_column(\n        String(50), nullable=False, doc=\"stage2_segmentation, stage3_extraction, etc.\"\n    )\n    event_type: Mapped[str] = mapped_column(\n        String(30), nullable=False, doc=\"start, complete, error, llm_call\"\n    )\n    prompt_tokens: Mapped[int | None] = mapped_column(Integer, nullable=True)\n    completion_tokens: Mapped[int | None] = mapped_column(Integer, nullable=True)\n    total_tokens: Mapped[int | None] = mapped_column(Integer, nullable=True)\n    model: Mapped[str | None] = mapped_column(String(100), nullable=True)\n    duration_ms: Mapped[int | None] = mapped_column(Integer, nullable=True)\n    payload: Mapped[dict | None] = mapped_column(\n        JSONB, nullable=True, doc=\"LLM response content, error details, stage metadata\"\n    )\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n"}],"isError":false,"timestamp":1774868663925}}
{"type":"message","id":"b743f21d","parentId":"3aafe90c","timestamp":"2026-03-30T11:04:23.928Z","message":{"role":"toolResult","toolCallId":"toolu_01Hw3nhJdVBCXKjDGR2kDysu","toolName":"bash","content":[{"type":"text","text":"/home/aux/projects/content-to-kb-automator/frontend/src/App.css\n"}],"isError":false,"timestamp":1774868663925}}
{"type":"message","id":"28c5e3af","parentId":"b743f21d","timestamp":"2026-03-30T11:04:28.259Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me check the existing CSS for pipeline-related styles and understand the current event log UX."},{"type":"toolCall","id":"toolu_0177pnk8717c8Kcipbp4MhJB","name":"bash","arguments":{"command":"grep -n \"pipeline-event\\|pipeline-badge\\|json-viewer\\|pipeline-video\\|admin-pipeline\" /home/aux/projects/content-to-kb-automator/frontend/src/App.css | head -50"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":128,"cacheRead":77516,"cacheWrite":651,"totalTokens":78296,"cost":{"input":0.000005,"output":0.0032,"cacheRead":0.038758,"cacheWrite":0.00406875,"total":0.04603175}},"stopReason":"toolUse","timestamp":1774868663927}}
{"type":"message","id":"7076dff5","parentId":"28c5e3af","timestamp":"2026-03-30T11:04:28.277Z","message":{"role":"toolResult","toolCallId":"toolu_0177pnk8717c8Kcipbp4MhJB","toolName":"bash","content":[{"type":"text","text":"2471:.admin-pipeline {\n2477:.admin-pipeline__header {\n2486:.admin-pipeline__header-right {\n2493:.admin-pipeline__title {\n2498:.admin-pipeline__subtitle {\n2504:.admin-pipeline__list {\n2562:.pipeline-video {\n2569:.pipeline-video__header {\n2578:.pipeline-video__header:hover {\n2582:.pipeline-video__info {\n2589:.pipeline-video__filename {\n2598:.pipeline-video__creator {\n2603:.pipeline-video__meta {\n2610:.pipeline-video__stat {\n2616:.pipeline-video__time {\n2622:.pipeline-video__actions {\n2627:.pipeline-video__message {\n2632:.pipeline-video__message--ok {\n2637:.pipeline-video__message--err {\n2642:.pipeline-video__detail {\n2647:.pipeline-video__detail-meta {\n2658:.pipeline-badge {\n2670:.pipeline-badge--success {\n2675:.pipeline-badge--active {\n2680:.pipeline-badge--error {\n2685:.pipeline-badge--pending {\n2690:.pipeline-badge--event-start {\n2695:.pipeline-badge--event-complete {\n2700:.pipeline-badge--event-error {\n2705:.pipeline-badge--event-llm_call {\n2712:.pipeline-events__header {\n2719:.pipeline-events__count {\n2725:.pipeline-events__empty {\n2731:.pipeline-events__list {\n2737:.pipeline-event {\n2744:.pipeline-event--error {\n2748:.pipeline-event__row {\n2755:.pipeline-event__icon {\n2762:.pipeline-event__stage {\n2768:.pipeline-event__model {\n2774:.pipeline-event__tokens {\n2780:.pipeline-event__duration {\n2785:.pipeline-event__time {\n2794:.pipeline-events__pager {\n2802:.pipeline-events__pager-info {\n2809:.json-viewer {\n2813:.json-viewer__toggle {\n2823:.json-viewer__toggle:hover {\n2827:.json-viewer__content {\n"}],"isError":false,"timestamp":1774868668275}}
{"type":"message","id":"54fc6461","parentId":"7076dff5","timestamp":"2026-03-30T11:04:37.625Z","message":{"role":"assistant","content":[{"type":"text","text":"Now I have a complete picture. Let me understand the slice requirements more precisely by re-reading the roadmap demo text: \"Pipeline event log shows Head/Tail toggle buttons. Head shows first N events, Tail shows last N events. Token counts visible per event and per video.\"\n\nThe current implementation already has:\n1. Token counts per event (`total_tokens`, `prompt_tokens`, `completion_tokens` displayed)\n2. Token counts per video (`total_tokens_used` shown in video row)\n3. Pagination (offset-based, prev/next)\n4. Events ordered newest-first\n\nWhat's missing is the Head/Tail toggle — instead of linear pagination, the user should be able to quickly switch between seeing the first N events (chronological head) and the last N events (chronological tail). Let me check how the backend sorts events currently.\n\nThe backend sorts `PipelineEvent.created_at.desc()` — newest first. So the current default view is effectively a \"tail\" view (most recent events). A \"head\" view would show the oldest events first.\n\nLet me check the current CSS block for the pipeline events in detail to understand styling scope."},{"type":"toolCall","id":"toolu_01Ra545GTGo8QFFwngXBt83e","name":"read","arguments":{"limit":130,"offset":2712,"path":"/home/aux/projects/content-to-kb-automator/frontend/src/App.css"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":365,"cacheRead":78167,"cacheWrite":647,"totalTokens":79180,"cost":{"input":0.000005,"output":0.009125000000000001,"cacheRead":0.0390835,"cacheWrite":0.0040437500000000005,"total":0.05225725}},"stopReason":"toolUse","timestamp":1774868668276}}
{"type":"message","id":"3f514a22","parentId":"54fc6461","timestamp":"2026-03-30T11:04:37.639Z","message":{"role":"toolResult","toolCallId":"toolu_01Ra545GTGo8QFFwngXBt83e","toolName":"read","content":[{"type":"text","text":".pipeline-events__header {\n  display: flex;\n  align-items: center;\n  justify-content: space-between;\n  margin-bottom: 0.75rem;\n}\n\n.pipeline-events__count {\n  font-size: 0.85rem;\n  color: var(--color-text-secondary);\n  font-weight: 500;\n}\n\n.pipeline-events__empty {\n  font-size: 0.85rem;\n  color: var(--color-text-muted);\n  padding: 0.5rem 0;\n}\n\n.pipeline-events__list {\n  display: flex;\n  flex-direction: column;\n  gap: 0.25rem;\n}\n\n.pipeline-event {\n  background: var(--color-bg-page);\n  border: 1px solid var(--color-border);\n  border-radius: 6px;\n  padding: 0.5rem 0.75rem;\n}\n\n.pipeline-event--error {\n  border-left: 3px solid var(--color-error);\n}\n\n.pipeline-event__row {\n  display: flex;\n  align-items: center;\n  gap: 0.5rem;\n  flex-wrap: wrap;\n}\n\n.pipeline-event__icon {\n  font-size: 0.85rem;\n  flex-shrink: 0;\n  width: 1.25rem;\n  text-align: center;\n}\n\n.pipeline-event__stage {\n  color: var(--color-text-primary);\n  font-size: 0.8125rem;\n  font-weight: 500;\n}\n\n.pipeline-event__model {\n  color: var(--color-text-muted);\n  font-size: 0.75rem;\n  font-family: monospace;\n}\n\n.pipeline-event__tokens {\n  color: var(--color-pill-plugin-text);\n  font-size: 0.75rem;\n  font-weight: 500;\n}\n\n.pipeline-event__duration {\n  color: var(--color-text-muted);\n  font-size: 0.75rem;\n}\n\n.pipeline-event__time {\n  color: var(--color-text-muted);\n  font-size: 0.75rem;\n  margin-left: auto;\n  white-space: nowrap;\n}\n\n/* ── Pipeline Events Pager ──────────────────────────────────────────────── */\n\n.pipeline-events__pager {\n  display: flex;\n  align-items: center;\n  justify-content: center;\n  gap: 0.75rem;\n  margin-top: 0.75rem;\n}\n\n.pipeline-events__pager-info {\n  font-size: 0.8rem;\n  color: var(--color-text-muted);\n}\n\n/* ── Collapsible JSON ───────────────────────────────────────────────────── */\n\n.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":1774868677636}}
{"type":"message","id":"5e48fbb9","parentId":"3f514a22","timestamp":"2026-03-30T11:04:42.585Z","message":{"role":"assistant","content":[{"type":"text","text":"Good. I now have a complete picture of the frontend, backend, and CSS. Let me also check the existing `btn` class patterns to ensure the toggle buttons follow conventions."},{"type":"toolCall","id":"toolu_011oToV8qjYDYCMnp6BoPpnQ","name":"bash","arguments":{"command":"grep -n \"\\.btn--small\\|\\.btn--secondary\\|\\.btn--primary\\|\\.btn--active\\|\\.btn--toggle\" /home/aux/projects/content-to-kb-automator/frontend/src/App.css | head -20"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":148,"cacheRead":78814,"cacheWrite":1346,"totalTokens":80309,"cost":{"input":0.000005,"output":0.0037,"cacheRead":0.039407,"cacheWrite":0.0084125,"total":0.0515245}},"stopReason":"toolUse","timestamp":1774868677637}}
{"type":"message","id":"4035eec4","parentId":"5e48fbb9","timestamp":"2026-03-30T11:04:42.606Z","message":{"role":"toolResult","toolCallId":"toolu_011oToV8qjYDYCMnp6BoPpnQ","toolName":"bash","content":[{"type":"text","text":"2116:.btn--small {\n2121:.btn--primary {\n2128:.btn--primary:hover:not(:disabled) {\n2132:.btn--primary:disabled {\n2137:.btn--secondary {\n2143:.btn--secondary:hover:not(:disabled) {\n"}],"isError":false,"timestamp":1774868682603}}
{"type":"message","id":"bc041819","parentId":"4035eec4","timestamp":"2026-03-30T11:04:45.763Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01UgWgHcaNe37pmJkqCgRz2N","name":"read","arguments":{"limit":40,"offset":2099,"path":"/home/aux/projects/content-to-kb-automator/frontend/src/App.css"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":108,"cacheRead":80160,"cacheWrite":224,"totalTokens":80493,"cost":{"input":0.000005,"output":0.0027,"cacheRead":0.04008,"cacheWrite":0.0014,"total":0.044184999999999995}},"stopReason":"toolUse","timestamp":1774868682604}}
{"type":"message","id":"4c890167","parentId":"bc041819","timestamp":"2026-03-30T11:04:45.770Z","message":{"role":"toolResult","toolCallId":"toolu_01UgWgHcaNe37pmJkqCgRz2N","toolName":"read","content":[{"type":"text","text":"\n.report-issue-btn {\n  margin-top: 0.5rem;\n  align-self: flex-start;\n}\n\n/* ── Buttons ────────────────────────────────────────────────────────────── */\n\n.btn {\n  padding: 0.5rem 1rem;\n  border-radius: 6px;\n  font-size: 0.85rem;\n  cursor: pointer;\n  border: 1px solid var(--color-border);\n  transition: background 0.15s, border-color 0.15s;\n}\n\n.btn--small {\n  padding: 0.3rem 0.7rem;\n  font-size: 0.8rem;\n}\n\n.btn--primary {\n  background: var(--color-accent);\n  color: var(--color-bg-page);\n  border-color: var(--color-accent);\n  font-weight: 600;\n}\n\n.btn--primary:hover:not(:disabled) {\n  background: var(--color-accent-hover);\n}\n\n.btn--primary:disabled {\n  opacity: 0.5;\n  cursor: not-allowed;\n}\n\n.btn--secondary {\n  background: var(--color-bg-input);\n\n[702 more lines in file. Use offset=2139 to continue.]"}],"isError":false,"timestamp":1774868685767}}
{"type":"message","id":"055bfae1","parentId":"4c890167","timestamp":"2026-03-30T11:04:48.972Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01F3BzPnVV91HHXsKr85dp3Z","name":"read","arguments":{"limit":15,"offset":2137,"path":"/home/aux/projects/content-to-kb-automator/frontend/src/App.css"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":108,"cacheRead":80160,"cacheWrite":663,"totalTokens":80932,"cost":{"input":0.000005,"output":0.0027,"cacheRead":0.04008,"cacheWrite":0.00414375,"total":0.04692875}},"stopReason":"toolUse","timestamp":1774868685768}}
{"type":"message","id":"fc03b232","parentId":"055bfae1","timestamp":"2026-03-30T11:04:48.978Z","message":{"role":"toolResult","toolCallId":"toolu_01F3BzPnVV91HHXsKr85dp3Z","toolName":"read","content":[{"type":"text","text":".btn--secondary {\n  background: var(--color-bg-input);\n  color: var(--color-text-primary);\n  border-color: var(--color-border);\n}\n\n.btn--secondary:hover:not(:disabled) {\n  background: var(--color-border);\n}\n\n.btn--danger {\n  background: var(--color-badge-rejected-bg);\n  color: var(--color-badge-rejected-text);\n  border-color: var(--color-badge-rejected-bg);\n}\n\n[689 more lines in file. Use offset=2152 to continue.]"}],"isError":false,"timestamp":1774868688976}}
{"type":"message","id":"e76030d3","parentId":"fc03b232","timestamp":"2026-03-30T11:04:53.913Z","message":{"role":"assistant","content":[{"type":"text","text":"I have everything I need. Let me also quickly confirm there's no existing toggle/tab button pattern in the CSS."},{"type":"toolCall","id":"toolu_01FutJb9Gz95G4H2qqvBCSGL","name":"bash","arguments":{"command":"grep -n \"toggle\\|tab-btn\\|tab--active\\|segmented\\|btn-group\" /home/aux/projects/content-to-kb-automator/frontend/src/App.css | head -20"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":128,"cacheRead":80823,"cacheWrite":264,"totalTokens":81216,"cost":{"input":0.000005,"output":0.0032,"cacheRead":0.040411499999999996,"cacheWrite":0.00165,"total":0.045266499999999994}},"stopReason":"toolUse","timestamp":1774868688977}}
{"type":"message","id":"72b69b9b","parentId":"e76030d3","timestamp":"2026-03-30T11:04:53.927Z","message":{"role":"toolResult","toolCallId":"toolu_01FutJb9Gz95G4H2qqvBCSGL","toolName":"bash","content":[{"type":"text","text":"53:  /* Mode toggle (green/amber work on dark) */\n54:  --color-toggle-review: #10b981;\n55:  --color-toggle-auto: #f59e0b;\n56:  --color-toggle-track: #6b7280;\n57:  --color-toggle-track-active: #059669;\n58:  --color-toggle-thumb: #fff;\n99:  /* Sort toggle */\n262:.filter-tab--active {\n423:/* ── Mode toggle ──────────────────────────────────────────────────────────── */\n425:.mode-toggle {\n432:.mode-toggle__dot {\n439:.mode-toggle__dot--review {\n440:  background: var(--color-toggle-review);\n443:.mode-toggle__dot--auto {\n444:  background: var(--color-toggle-auto);\n447:.mode-toggle__label {\n455:.mode-toggle__switch {\n459:  background: var(--color-toggle-track);\n467:.mode-toggle__switch--active {\n468:  background: var(--color-toggle-track-active);\n"}],"isError":false,"timestamp":1774868693924}}
{"type":"message","id":"71178a9e","parentId":"72b69b9b","timestamp":"2026-03-30T11:04:57.995Z","message":{"role":"assistant","content":[{"type":"text","text":"There's a `.filter-tab--active` pattern. Let me check it."},{"type":"toolCall","id":"toolu_01DcrU7Js4geav68uUUnNxv2","name":"read","arguments":{"limit":20,"offset":250,"path":"/home/aux/projects/content-to-kb-automator/frontend/src/App.css"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":125,"cacheRead":81087,"cacheWrite":410,"totalTokens":81623,"cost":{"input":0.000005,"output":0.003125,"cacheRead":0.040543499999999996,"cacheWrite":0.0025625,"total":0.046236}},"stopReason":"toolUse","timestamp":1774868693926}}
{"type":"message","id":"003c8305","parentId":"71178a9e","timestamp":"2026-03-30T11:04:58.002Z","message":{"role":"toolResult","toolCallId":"toolu_01DcrU7Js4geav68uUUnNxv2","toolName":"read","content":[{"type":"text","text":"  font-weight: 500;\n  color: var(--color-text-secondary);\n  cursor: pointer;\n  border-bottom: 2px solid transparent;\n  margin-bottom: -2px;\n  transition: color 0.15s, border-color 0.15s;\n}\n\n.filter-tab:hover {\n  color: var(--color-text-primary);\n}\n\n.filter-tab--active {\n  color: var(--color-text-active);\n  border-bottom-color: var(--color-border-active);\n}\n\n/* ── Cards ────────────────────────────────────────────────────────────────── */\n\n.card {\n\n[2571 more lines in file. Use offset=270 to continue.]"}],"isError":false,"timestamp":1774868697999}}
{"type":"message","id":"8304a6e2","parentId":"003c8305","timestamp":"2026-03-30T11:05:02.207Z","message":{"role":"assistant","content":[{"type":"text","text":"That's a tab-bar pattern. For the Head/Tail toggle, a small segmented button pair in the event log header would be more appropriate. Let me check if there are any existing filter tab uses in the frontend."},{"type":"toolCall","id":"toolu_01YDjvw3busXAhdYr1n6rh2z","name":"bash","arguments":{"command":"grep -rn \"filter-tab\" /home/aux/projects/content-to-kb-automator/frontend/src/ --include=\"*.tsx\" | head -10"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":138,"cacheRead":81497,"cacheWrite":317,"totalTokens":81953,"cost":{"input":0.000005,"output":0.0034500000000000004,"cacheRead":0.0407485,"cacheWrite":0.00198125,"total":0.04618475}},"stopReason":"toolUse","timestamp":1774868698000}}
{"type":"message","id":"3f0af4c4","parentId":"8304a6e2","timestamp":"2026-03-30T11:05:02.226Z","message":{"role":"toolResult","toolCallId":"toolu_01YDjvw3busXAhdYr1n6rh2z","toolName":"bash","content":[{"type":"text","text":"/home/aux/projects/content-to-kb-automator/frontend/src/pages/ReviewQueue.tsx:110:      <div className=\"filter-tabs\">\n/home/aux/projects/content-to-kb-automator/frontend/src/pages/ReviewQueue.tsx:115:            className={`filter-tab ${filter === f.value ? \"filter-tab--active\" : \"\"}`}\n"}],"isError":false,"timestamp":1774868702223}}
{"type":"message","id":"5e3c7bfa","parentId":"3f0af4c4","timestamp":"2026-03-30T11:05:49.504Z","message":{"role":"assistant","content":[{"type":"text","text":"Now I have a complete picture. Let me also check what the backend's event endpoint supports in terms of ordering, since Head/Tail will need ascending vs descending.\n\nThe backend currently hardcodes `order_by(PipelineEvent.created_at.desc())`. For Head view, we'd need ascending order. Two approaches:\n1. Add an `order` query param to the backend endpoint\n2. Handle it purely client-side by fetching all events and sorting\n\nGiven the current pagination structure (offset/limit), adding an `order` param to the backend is cleaner — it lets the database handle sort efficiently and preserves pagination semantics. Let me verify the current event count range to understand if client-side is viable.\n\nThe frontend already uses `limit=50` per page. With a typical pipeline run producing maybe 20-100 events per video, the total count is manageable. But the backend approach is more correct. Let me also check if the API already returns `total` for computing \"last N\" offsets.\n\nYes — the endpoint returns `{ items, total, offset, limit }`. So for \"Tail\" (last N), the frontend can request `offset=0` with desc order. For \"Head\" (first N), it can request `offset=0` with asc order. This is the cleanest approach — one new query param on the backend, minimal frontend changes.\n\nThat's all the research needed. This is a straightforward slice — known patterns, known codebase."},{"type":"toolCall","id":"toolu_01Px7FxuuneYWF74ZxB3RZab","name":"gsd_summary_save","arguments":{"artifact_type":"RESEARCH","content":"# S02 Research: Pipeline Page — Head/Tail Log View + Token Count\n\n## Summary\n\nStraightforward frontend+backend slice. The pipeline page (`AdminPipeline.tsx`) already has a fully working event log with per-event token display, per-video token totals, and offset-based pagination. What's missing is a Head/Tail toggle to quickly switch between viewing the oldest events (pipeline start) and newest events (latest activity), replacing the generic prev/next pager as the primary navigation.\n\nToken counts are already visible — no new work needed there. The slice demo text says \"Token counts visible per event and per video\" which is already implemented.\n\n## Recommendation\n\n**Light scope. One backend param, one frontend component change, minor CSS.**\n\nAdd an `order` query param (`asc`/`desc`, default `desc`) to the `GET /admin/pipeline/events/{video_id}` endpoint. Change the `EventLog` component to show Head/Tail toggle buttons instead of (or alongside) the existing prev/next pager. Head = ascending order (first N events), Tail = descending order (last N events, current default).\n\n## Implementation Landscape\n\n### Files to Change\n\n| File | Location | What changes |\n|------|----------|-------------|\n| `backend/routers/pipeline.py` | ub01: `/vmPool/r/repos/xpltdco/chrysopedia/backend/routers/pipeline.py` | Add `order` query param to `list_pipeline_events` endpoint (line ~170). Values: `asc`/`desc`, default `desc`. Changes the `order_by` clause. |\n| `frontend/src/api/public-client.ts` | Local: `frontend/src/api/public-client.ts` (line ~440) | Add `order` param to `fetchPipelineEvents` params type and URL builder. |\n| `frontend/src/pages/AdminPipeline.tsx` | Local: `frontend/src/pages/AdminPipeline.tsx` | Replace the `EventLog` component's pager with Head/Tail toggle buttons. Add `viewMode` state (`\"head\"` / `\"tail\"`). Pass `order` param to `fetchPipelineEvents`. Reset offset to 0 on mode switch. |\n| `frontend/src/App.css` | Local: `frontend/src/App.css` (~line 2712) | Add `.pipeline-events__view-toggle` segmented button styles. ~15 lines of CSS. |\n\n### Backend Endpoint (current state)\n\n```\nGET /admin/pipeline/events/{video_id}\n  Query: offset (int, ≥0), limit (int, 1-200), stage (str?), event_type (str?)\n  Response: { items: PipelineEvent[], total: int, offset: int, limit: int }\n  Order: created_at DESC (hardcoded)\n```\n\n**Change needed:** Add `order: Annotated[str | None, Query()] = \"desc\"` param. Validate values are `asc`/`desc`. Apply `PipelineEvent.created_at.asc()` or `.desc()` accordingly.\n\n### Frontend EventLog Component (current state)\n\n- State: `events`, `total`, `loading`, `error`, `offset` (starts at 0)\n- Renders: header with count + refresh button, event list, prev/next pager\n- Each event row shows: icon, stage name, event_type badge, model name, token count (with prompt/completion tooltip), duration, timestamp\n- Pagination: offset-based, 50 per page, prev/next buttons\n\n**Change needed:**\n- Add `viewMode` state: `\"tail\"` (default, desc order — most recent first) or `\"head\"` (asc order — chronological from start)\n- Add toggle button pair in `.pipeline-events__header` between count and refresh\n- Pass `order: viewMode === \"head\" ? \"asc\" : \"desc\"` to `fetchPipelineEvents`\n- Reset `offset` to 0 when switching modes\n- Keep existing prev/next pager for navigating within head or tail view\n\n### CSS Pattern\n\nUse a segmented button pair similar to the existing `.filter-tab` pattern but compact. Two adjacent buttons with shared border-radius, active state uses `var(--color-accent)` background with `var(--color-bg-page)` text. Inactive uses `var(--color-bg-input)` background.\n\n```\n.pipeline-events__view-toggle {\n  display: inline-flex;\n  border-radius: 6px;\n  overflow: hidden;\n  border: 1px solid var(--color-border);\n}\n.pipeline-events__view-btn { ... }\n.pipeline-events__view-btn--active { ... }\n```\n\n### Existing Patterns to Follow\n\n- **Button styles:** `.btn`, `.btn--small`, `.btn--secondary` — use for pager, but the toggle needs custom segmented style\n- **Active state colors:** `var(--color-text-active)`, `var(--color-border-active)`, `var(--color-accent)`\n- **Filter tabs in ReviewQueue.tsx:** Similar toggle pattern using `.filter-tab--active`\n- **Token formatting:** `formatTokens()` helper already exists — handles K/M suffixes\n- **API client pattern:** `URLSearchParams` builder in `fetchPipelineEvents` — add `order` param\n\n### Token Count Display (already done)\n\nPer-event: `{formatTokens(evt.total_tokens)} tok` with hover tooltip showing `prompt: N / completion: N`\nPer-video: `{formatTokens(video.total_tokens_used)} tokens` in the video row meta section\n\nNo changes needed for token display — the roadmap demo text confirms existing behavior.\n\n### Natural Task Decomposition\n\n1. **Backend: Add `order` param** — modify one endpoint in `pipeline.py`, validate input, change ORDER BY. ~10 lines. Can be verified with curl.\n2. **Frontend: Head/Tail toggle + CSS** — modify `EventLog` component in `AdminPipeline.tsx`, add API param in `public-client.ts`, add CSS. ~40 lines total. Verify in browser.\n\nThese two tasks can be done as one (small) or two (safer, independent verification). The backend change is a prerequisite for the frontend change.\n\n### Verification\n\n- Backend: `curl 'http://ub01:8096/api/v1/admin/pipeline/events/{video_id}?order=asc&limit=5'` should return events in ascending chronological order\n- Frontend: Load pipeline page, expand a video, see Head/Tail toggles, click Head to see oldest events first, click Tail to see newest first. Token counts remain visible on each event row and video summary row.\n- Build: `cd frontend && npm run build` must succeed with zero TypeScript errors\n","milestone_id":"M006","slice_id":"S02"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":2049,"cacheRead":81814,"cacheWrite":243,"totalTokens":84107,"cost":{"input":0.000005,"output":0.051225,"cacheRead":0.040907,"cacheWrite":0.0015187500000000001,"total":0.09365575}},"stopReason":"toolUse","timestamp":1774868702225}}
{"type":"message","id":"9f8d30d5","parentId":"5e3c7bfa","timestamp":"2026-03-30T11:05:49.510Z","message":{"role":"toolResult","toolCallId":"toolu_01Px7FxuuneYWF74ZxB3RZab","toolName":"gsd_summary_save","content":[{"type":"text","text":"Saved RESEARCH artifact to milestones/M006/slices/S02/S02-RESEARCH.md"}],"details":{"operation":"save_summary","path":"milestones/M006/slices/S02/S02-RESEARCH.md","artifact_type":"RESEARCH"},"isError":false,"timestamp":1774868749507}}
{"type":"message","id":"18996563","parentId":"9f8d30d5","timestamp":"2026-03-30T11:05:52.113Z","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":82057,"cacheWrite":2087,"totalTokens":84156,"cost":{"input":0.000005,"output":0.000275,"cacheRead":0.041028499999999996,"cacheWrite":0.01304375,"total":0.05435225}},"stopReason":"stop","timestamp":1774868749508}}
