{"type":"thinking_level_change","id":"adfee1e5","parentId":null,"timestamp":"2026-03-29T22:02:48.611Z","thinkingLevel":"off"}
{"type":"model_change","id":"e071c6bd","parentId":"adfee1e5","timestamp":"2026-03-29T22:02:48.612Z","provider":"anthropic","modelId":"claude-opus-4-6"}
{"type":"custom_message","customType":"gsd-auto","content":"You are executing GSD auto-mode.\n\n## Working Directory\n\nYour working directory is `/home/aux/projects/content-to-kb-automator`. All file reads, writes, and shell commands MUST operate relative to this directory. Do NOT `cd` to any other directory.\n\nAll relevant context has been preloaded below — start working immediately without re-reading these files.\n\n## Requirements Advanced\n\n- R001 — Desktop Whisper script built with all required features: ffmpeg extraction, Whisper large-v3, word-level timestamps, resumability, batch mode, spec-compliant JSON output\n- R010 — Docker Compose project created with all 5 services following XPLTD conventions; docker compose config validates successfully\n- R011 — Canonical tag system established via config/canonical_tags.yaml with 6 top-level categories and 13 genres; Tag model in database with aliases support\n\n## Requirements Validated\n\nNone.\n\n## Requirements Invalidated or Re-scoped\n\nNone.\n\n## UNIT: Research Slice S02 (\"Transcript Ingestion API\") — Milestone M001\n\n## Inlined Context (preloaded — do not re-read these files)\n\n### Milestone Roadmap\nSource: `.gsd/milestones/M001/M001-ROADMAP.md`\n\n# M001: Chrysopedia Foundation — Infrastructure, Pipeline Core, and Skeleton UI\n\n## Vision\nStand up the complete Chrysopedia stack: Docker Compose deployment on ub01, PostgreSQL data model, FastAPI backend with transcript ingestion, Whisper transcription script for the desktop, LLM extraction pipeline (stages 2-5), review queue, Qdrant integration, and the search-first web UI with technique pages, creators, and topics browsing. By the end, a video file can be transcribed → ingested → extracted → reviewed → searched and read in the web UI.\n\n## Slice Overview\n| ID | Slice | Risk | Depends | Done | After this |\n|----|-------|------|---------|------|------------|\n| S01 | Docker Compose + Database + Whisper Script | low | — | ✅ | docker compose up -d starts all services on ub01; Whisper script transcribes a sample video to JSON |\n| S02 | Transcript Ingestion API | low | S01 | ⬜ | POST a transcript JSON file to the API; Creator and Source Video records appear in PostgreSQL |\n| S03 | LLM Extraction Pipeline + Qdrant Integration | high | S02 | ⬜ | A transcript JSON triggers stages 2-5: segmentation → extraction → classification → synthesis. Technique pages with key moments appear in DB. Qdrant has searchable embeddings. |\n| S04 | Review Queue Admin UI | medium | S03 | ⬜ | Admin views pending key moments, approves/edits/rejects them, toggles between review and auto mode |\n| S05 | Search-First Web UI | medium | S03 | ⬜ | User searches for a technique, gets semantic results in <500ms, clicks through to a full technique page with study guide prose, key moments, and related links |\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 | Docker Compose project naming and path conventions | xpltd_chrysopedia with bind mounts at /vmPool/r/services/chrysopedia_*, compose at /vmPool/r/compose/chrysopedia/ | XPLTD lore: compose projects at /vmPool/r/compose/{name}/, service data at /vmPool/r/services/{service}_{role}/, project naming follows xpltd_{name} pattern. Network will be a dedicated bridge subnet avoiding existing 172.16-172.23 and 172.29-172.30 ranges. | Yes | agent |\n\n---\n\n### Requirements\nSource: `.gsd/REQUIREMENTS.md`\n\n# Requirements\n\n## R001 — Whisper Transcription Pipeline\n**Status:** active\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:** active\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:** active\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:** active\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:** active\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:** active\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:** active\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:** active\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:** active\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:** active\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:** active\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:** active\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:** active\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:** active\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### Project Knowledge\nSource: `.gsd/KNOWLEDGE.md`\n\n# KNOWLEDGE\n\n## SQLAlchemy column names that shadow ORM functions\n\n**Context:** If a model has a column named `relationship` (or any other ORM function name like `query`, `metadata`), Python resolves the name to the column's `MappedColumn` descriptor within the class body. This causes `relationship(...)` calls below it to fail with \"MappedColumn object is not callable\".\n\n**Fix:** Import with an alias: `from sqlalchemy.orm import relationship as sa_relationship` and use `sa_relationship(...)` throughout. Alternatively, rename the database column, but the spec defines `relationship` as the column name so we preserved it.\n\n## Docker Compose variable interpolation and `:?` syntax\n\n**Context:** `${VAR:?error message}` in docker-compose.yml makes `docker compose config` fail when the variable is unset, even if `env_file: required: false` is used. The `required: false` only controls whether the `.env` file must exist — it does NOT provide defaults for variables referenced with `:?`.\n\n**Fix:** Use `${VAR:-default}` for variables that need a fallback, or ensure the variable is always set in the environment.\n\n## Host port 8000 conflict with kerf-engine\n\n**Context:** The kerf-engine Docker container (`kerf-engine-kerf-engine-1`) binds to `0.0.0.0:8000`. When testing the Chrysopedia API locally (outside Docker), curl requests to `localhost:8000` hit the kerf-engine container instead of the local uvicorn process, even when uvicorn binds to `127.0.0.1:8000`.\n\n**Fix:** Use an alternate port (e.g., 8001) for local testing. In Docker Compose, chrysopedia-api maps `127.0.0.1:8000:8000` which is fine because it goes through Docker's port forwarding, but will conflict with kerf-engine if both stacks run simultaneously. Consider changing one project's external port mapping.\n\n---\n\n# {{scope}} — Research\n\n**Date:** {{date}}\n\n<!-- Required sections: Summary, Recommendation, Implementation Landscape.\n     All other sections: include only when they have real content.\n     For light research (straightforward work with known patterns),\n     the required sections alone are sufficient. -->\n\n## Summary\n\n{{summary — 2-3 paragraphs with primary recommendation}}\n\n## Recommendation\n\n{{whatApproachToTake_AND_why}}\n\n## Implementation Landscape\n\n<!-- This section is the primary input for the planner agent.\n     Be specific — file paths, function names, patterns to follow.\n     The planner uses this to scope tasks to files and decide build order. -->\n\n### Key Files\n\n- `{{filePath}}` — {{whatItDoesAndHowItRelates}}\n- `{{filePath}}` — {{whatNeedsToChange}}\n\n### Build Order\n\n{{whatToProveOrBuildFirst_AND_why — whatUnblocksDownstreamWork}}\n\n### Verification Approach\n\n{{howToConfirmTheSliceWorks — commands, tests, observable behaviors}}\n\n<!-- Sections below: include when applicable, omit entirely when not. -->\n\n## Don't Hand-Roll\n\n<!-- Include when existing libraries/tools solve problems the slice would otherwise reimplement. -->\n\n| Problem | Existing Solution | Why Use It |\n|---------|------------------|------------|\n| {{problem}} | {{solution}} | {{why}} |\n\n## Constraints\n\n<!-- Include when the codebase, runtime, or dependencies impose hard limits on approach. -->\n\n- {{hardConstraintFromCodebaseOrRuntime}}\n- {{constraintFromDependencies}}\n\n## Common Pitfalls\n\n<!-- Include when there are non-obvious failure modes worth flagging. -->\n\n- **{{pitfall}}** — {{howToAvoid}}\n- **{{pitfall}}** — {{howToAvoid}}\n\n## Open Risks\n\n<!-- Include when execution could hit unknowns that affect the plan. -->\n\n- {{riskThatCouldSurfaceDuringExecution}}\n\n## Skills Discovered\n\n<!-- Include when skill discovery found relevant skills. -->\n\n| Technology | Skill | Status |\n|------------|-------|--------|\n| {{technology}} | {{owner/repo@skill}} | {{installed / available / none found}} |\n\n## Sources\n\n<!-- Include when external docs, articles, or references informed the research. -->\n\n- {{whatWasLearned}} (source: [{{title}}]({{url}}))\n\n### Output Template: Research\nSource: `templates/research.md`\n\n### Dependency Slice Summaries\n\nPay particular attention to **Forward Intelligence** sections — they contain hard-won knowledge about what's fragile, what assumptions changed, and what to watch out for.\n\n#### S01 Summary\nSource: `.gsd/milestones/M001/slices/S01/S01-SUMMARY.md`\n\n---\nid: S01\nparent: M001\nmilestone: M001\nprovides:\n  - Docker Compose project definition (5 services) for deployment\n  - PostgreSQL schema with 7 tables via Alembic migration\n  - FastAPI app with health check and CRUD endpoints pattern\n  - Pydantic schemas for all 7 entities (reusable in S02+)\n  - SQLAlchemy async session infrastructure\n  - Sample transcript JSON fixture for S02 ingestion testing\n  - Canonical tags configuration (6 categories, 13 genres)\nrequires:\n  []\naffects:\n  - S02\n  - S03\nkey_files:\n  - docker-compose.yml\n  - .env.example\n  - docker/Dockerfile.api\n  - docker/Dockerfile.web\n  - backend/main.py\n  - backend/models.py\n  - backend/database.py\n  - backend/schemas.py\n  - backend/config.py\n  - backend/routers/health.py\n  - backend/routers/creators.py\n  - backend/routers/videos.py\n  - alembic.ini\n  - alembic/env.py\n  - alembic/versions/001_initial.py\n  - whisper/transcribe.py\n  - whisper/requirements.txt\n  - config/canonical_tags.yaml\n  - README.md\n  - tests/fixtures/sample_transcript.json\nkey_decisions:\n  - D001: XPLTD Docker conventions — xpltd_chrysopedia project, bind mounts at /vmPool/r/services/, network 172.24.0.0/24\n  - env_file uses required: false so docker compose config validates on fresh clones\n  - POSTGRES_PASSWORD uses :-changeme default instead of :? to avoid config failures\n  - PostgreSQL exposed on host port 5433 to avoid conflicts with other projects\n  - SQLAlchemy relationship import aliased to sa_relationship to avoid column name clash\n  - Separate PostgreSQL enum type names to avoid collisions (key_moment_content_type vs content_type)\n  - Health check at /health performs real DB SELECT 1; lightweight /api/v1/health also available\n  - Whisper import deferred so --help works without openai-whisper installed\n  - Sample transcript uses realistic music production content for downstream pipeline testing\npatterns_established:\n  - Docker Compose service naming: chrysopedia-{role} (chrysopedia-db, chrysopedia-api, etc.)\n  - Backend router pattern: backend/routers/{domain}.py with prefix-per-router mounted under /api/v1\n  - SQLAlchemy async pattern: asyncpg engine + async_sessionmaker + get_session dependency\n  - Pydantic v2 schema pattern: Base/Create/Read variants per entity with model_config from_attributes=True\n  - Config via pydantic-settings BaseSettings loading from .env with sensible defaults\n  - Alembic async migration pattern with run_async_migrations() wrapper\n  - UUID primary keys with gen_random_uuid() server default for all entities\nobservability_surfaces:\n  - GET /health — returns database connectivity status (connected/error)\n  - Structured logging via Python logging module in FastAPI lifespan\ndrill_down_paths:\n  - .gsd/milestones/M001/slices/S01/tasks/T01-SUMMARY.md\n  - .gsd/milestones/M001/slices/S01/tasks/T02-SUMMARY.md\n  - .gsd/milestones/M001/slices/S01/tasks/T03-SUMMARY.md\n  - .gsd/milestones/M001/slices/S01/tasks/T04-SUMMARY.md\n  - .gsd/milestones/M001/slices/S01/tasks/T05-SUMMARY.md\nduration: \"\"\nverification_result: passed\ncompleted_at: 2026-03-29T22:02:45.503Z\nblocker_discovered: false\n---\n\n# S01: Docker Compose + Database + Whisper Script\n\n**Delivered deployable Docker Compose infrastructure with PostgreSQL schema (7 tables), FastAPI skeleton API with CRUD endpoints, desktop Whisper transcription script, and sample transcript fixture.**\n\n## What Happened\n\nThis slice established the complete foundation for the Chrysopedia stack across five tasks.\n\n**T01 — Docker Compose scaffolding:** Created the xpltd_chrysopedia Docker Compose project following XPLTD conventions (D001): bind mounts at /vmPool/r/services/chrysopedia_*, dedicated bridge network on 172.24.0.0/24, five services (PostgreSQL 16, Redis 7, FastAPI API, Celery worker, React/nginx web). Dockerfiles for API and web, nginx.conf, .env.example with all required vars, and config/canonical_tags.yaml with 6 topic categories and 13 genres.\n\n**T02 — Database schema:** Built SQLAlchemy async models for all 7 entities from the spec: Creator, SourceVideo, TranscriptSegment, KeyMoment, TechniquePage, RelatedTechniqueLink, Tag. UUID primary keys, CASCADE/SET NULL FK constraints, JSONB columns for body_sections/signal_chains, 7 custom PostgreSQL enum types. Alembic async migration infrastructure with initial migration 001_initial.py. Also fixed docker-compose.yml POSTGRES_PASSWORD from `:?` (hard fail) to `:-changeme` default.\n\n**T03 — FastAPI API skeleton:** Rewrote backend/main.py with lifespan manager, CORS, structured logging. Created pydantic-settings config, Pydantic v2 schemas (Base/Create/Read) for all entities, three router modules: health (GET /health with real DB SELECT 1), creators (list with pagination + get by slug), videos (list with optional creator filter). All endpoints async with SQLAlchemy session dependency.\n\n**T04 — Whisper transcription script:** Built whisper/transcribe.py with argparse CLI (--input, --output-dir, --model, --device, --creator), ffmpeg audio extraction to 16kHz mono WAV, Whisper transcription with word-level timestamps, spec-compliant JSON output, resumability (skip if output exists), batch mode for directories, progress logging. Deferred whisper import so --help works without the dependency installed.\n\n**T05 — README and fixtures:** Comprehensive README.md with architecture diagram, setup instructions, env var docs, dev workflow, API endpoint reference. Sample transcript JSON (5 segments, 106 words) with realistic music production content for downstream pipeline testing.\n\n## Verification\n\nAll slice-level verification checks passed:\n\n1. `docker compose config` — exits 0, all 5 services validated with correct env interpolation, volumes, networks, healthchecks, and dependency ordering.\n2. `python3 whisper/transcribe.py --help` — exits 0, shows full usage with all CLI args and examples.\n3. `python3 -c \"import json; ...\"` on sample_transcript.json — valid JSON with 5 segments, all required keys (source_file, creator_folder, duration_seconds, segments with words).\n4. All 7 SQLAlchemy models import successfully with correct entity definitions.\n5. All Pydantic schemas and config import successfully.\n6. All 3 router modules (health, creators, videos) import with correct route counts.\n7. Alembic files (alembic.ini, env.py, 001_initial.py) all present.\n8. config/canonical_tags.yaml loads with 6 topic categories.\n9. README.md exists with all required sections.\n\n## New Requirements Surfaced\n\nNone.\n\n## Deviations\n\n- env_file set to `required: false` to support fresh clones without .env present (T01).\n- POSTGRES_PASSWORD changed from `:?` (hard fail when unset) to `:-changeme` default to fix docker compose config validation (T02, captured in KNOWLEDGE.md).\n- Added docker/nginx.conf and frontend/package.json placeholders not in original plan but required for Dockerfile.web build context (T01).\n- Added backend/routers/videos.py not in T03 expected output list but required by plan's endpoint list (T03).\n- Whisper script uses subprocess directly for ffmpeg instead of ffmpeg-python library for reliability (T04).\n- Added --creator CLI flag for overriding inferred creator folder name (T04).\n\n## Known Limitations\n\n- Docker Compose stack not tested end-to-end with `docker compose up -d` (requires deployment to ub01 with bind mount paths).\n- API endpoints verified locally with test PostgreSQL container, not inside the Docker Compose network.\n- Whisper script validated structurally (--help, ffmpeg check, AST parse) but not with actual video transcription (requires CUDA GPU + Whisper model).\n- Host port 8000 conflicts with kerf-engine container — local testing uses port 8001 (documented in KNOWLEDGE.md).\n\n## Follow-ups\n\nNone.\n\n## Files Created/Modified\n\n- `docker-compose.yml` — Docker Compose project with 5 services (PostgreSQL 16, Redis 7, FastAPI API, Celery worker, React/nginx web)\n- `.env.example` — Template with all required environment variables and descriptions\n- `docker/Dockerfile.api` — Multi-stage Dockerfile for FastAPI + Celery worker service\n- `docker/Dockerfile.web` — Dockerfile for React app served via nginx\n- `docker/nginx.conf` — Nginx config for serving React SPA with API proxy\n- `backend/main.py` — FastAPI app with lifespan, CORS, structured logging, router mounting\n- `backend/models.py` — SQLAlchemy async models for all 7 entities with enums, FKs, JSONB\n- `backend/database.py` — Async engine, session factory, declarative base\n- `backend/schemas.py` — Pydantic v2 schemas (Base/Create/Read) for all entities\n- `backend/config.py` — pydantic-settings config loading from .env\n- `backend/routers/health.py` — GET /health with DB connectivity check\n- `backend/routers/creators.py` — GET /api/v1/creators (paginated), GET /api/v1/creators/{slug}\n- `backend/routers/videos.py` — GET /api/v1/videos (paginated, optional creator filter)\n- `backend/requirements.txt` — Python dependencies for FastAPI, SQLAlchemy, asyncpg, etc.\n- `alembic.ini` — Alembic configuration pointing to async database URL\n- `alembic/env.py` — Async Alembic migration runner\n- `alembic/versions/001_initial.py` — Initial migration creating all 7 tables with constraints\n- `alembic/script.py.mako` — Alembic migration template\n- `whisper/transcribe.py` — Desktop Whisper transcription script with CLI, batch mode, resumability\n- `whisper/requirements.txt` — Whisper script Python dependencies\n- `whisper/README.md` — Whisper script usage documentation\n- `config/canonical_tags.yaml` — 6 topic categories and 13 genres for tag classification\n- `README.md` — Project README with architecture, setup, env vars, dev workflow\n- `tests/fixtures/sample_transcript.json` — 5-segment sample transcript matching Whisper output format\n- `frontend/package.json` — Placeholder React app package.json\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: M001`, `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/M001/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":"7775831a","parentId":"e071c6bd","timestamp":"2026-03-29T22:02:48.613Z"}
{"type":"message","id":"cfba0d25","parentId":"7775831a","timestamp":"2026-03-29T22:02:55.918Z","message":{"role":"assistant","content":[{"type":"text","text":"\n\nI'll research Slice S02 (\"Transcript Ingestion API\") by exploring the existing codebase established in S01 to understand what's already built and what the ingestion endpoint needs.\n\n**Target Requirements:** R002 (Transcript Ingestion API - primary owner), with supporting awareness of R012 (Incremental Content Addition).\n\nLet me explore the existing code in parallel:"},{"type":"toolCall","id":"toolu_01YNA9UcwUNfMnJuyLkNkYAs","name":"read","arguments":{"path":"backend/models.py"}},{"type":"toolCall","id":"toolu_01VNvrWZQPwqTyBoZ1cfwpbX","name":"read","arguments":{"path":"backend/schemas.py"}},{"type":"toolCall","id":"toolu_01TYKEy2R5DpYVZ9AWGP8wW2","name":"read","arguments":{"path":"backend/main.py"}},{"type":"toolCall","id":"toolu_011Xq2bHJXcUcqHvVvMqHyxD","name":"read","arguments":{"path":"backend/database.py"}},{"type":"toolCall","id":"toolu_01RxA6GjDHqsYCYnsETj2Ax8","name":"read","arguments":{"path":"backend/config.py"}},{"type":"toolCall","id":"toolu_01KZdp8T7cgsfGgL6XZHxmKw","name":"read","arguments":{"path":"tests/fixtures/sample_transcript.json"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":3,"output":336,"cacheRead":49033,"cacheWrite":7910,"totalTokens":57282,"cost":{"input":0.000015000000000000002,"output":0.008400000000000001,"cacheRead":0.0245165,"cacheWrite":0.0494375,"total":0.082369}},"stopReason":"toolUse","timestamp":1774821768612}}
{"type":"message","id":"e853e0f3","parentId":"cfba0d25","timestamp":"2026-03-29T22:02:55.922Z","message":{"role":"toolResult","toolCallId":"toolu_01YNA9UcwUNfMnJuyLkNkYAs","toolName":"read","content":[{"type":"text","text":"\"\"\"SQLAlchemy ORM models for the Chrysopedia knowledge base.\n\nSeven entities matching chrysopedia-spec.md §6.1:\n  Creator, SourceVideo, TranscriptSegment, KeyMoment,\n  TechniquePage, RelatedTechniqueLink, Tag\n\"\"\"\n\nfrom __future__ import annotations\n\nimport enum\nimport uuid\nfrom datetime import datetime, timezone\n\nfrom sqlalchemy import (\n    Enum,\n    Float,\n    ForeignKey,\n    Integer,\n    String,\n    Text,\n    UniqueConstraint,\n    func,\n)\nfrom sqlalchemy.dialects.postgresql import ARRAY, JSONB, UUID\nfrom sqlalchemy.orm import Mapped, mapped_column\nfrom sqlalchemy.orm import relationship as sa_relationship\n\nfrom database import Base\n\n\n# ── Enums ────────────────────────────────────────────────────────────────────\n\nclass ContentType(str, enum.Enum):\n    \"\"\"Source video content type.\"\"\"\n    tutorial = \"tutorial\"\n    livestream = \"livestream\"\n    breakdown = \"breakdown\"\n    short_form = \"short_form\"\n\n\nclass ProcessingStatus(str, enum.Enum):\n    \"\"\"Pipeline processing status for a source video.\"\"\"\n    pending = \"pending\"\n    transcribed = \"transcribed\"\n    extracted = \"extracted\"\n    reviewed = \"reviewed\"\n    published = \"published\"\n\n\nclass KeyMomentContentType(str, enum.Enum):\n    \"\"\"Content classification for a key moment.\"\"\"\n    technique = \"technique\"\n    settings = \"settings\"\n    reasoning = \"reasoning\"\n    workflow = \"workflow\"\n\n\nclass ReviewStatus(str, enum.Enum):\n    \"\"\"Human review status for key moments.\"\"\"\n    pending = \"pending\"\n    approved = \"approved\"\n    edited = \"edited\"\n    rejected = \"rejected\"\n\n\nclass SourceQuality(str, enum.Enum):\n    \"\"\"Derived source quality for technique pages.\"\"\"\n    structured = \"structured\"\n    mixed = \"mixed\"\n    unstructured = \"unstructured\"\n\n\nclass PageReviewStatus(str, enum.Enum):\n    \"\"\"Review lifecycle for technique pages.\"\"\"\n    draft = \"draft\"\n    reviewed = \"reviewed\"\n    published = \"published\"\n\n\nclass RelationshipType(str, enum.Enum):\n    \"\"\"Types of links between technique pages.\"\"\"\n    same_technique_other_creator = \"same_technique_other_creator\"\n    same_creator_adjacent = \"same_creator_adjacent\"\n    general_cross_reference = \"general_cross_reference\"\n\n\n# ── Helpers ──────────────────────────────────────────────────────────────────\n\ndef _uuid_pk() -> Mapped[uuid.UUID]:\n    return mapped_column(\n        UUID(as_uuid=True),\n        primary_key=True,\n        default=uuid.uuid4,\n        server_default=func.gen_random_uuid(),\n    )\n\n\ndef _now() -> datetime:\n    return datetime.now(timezone.utc)\n\n\n# ── Models ───────────────────────────────────────────────────────────────────\n\nclass Creator(Base):\n    __tablename__ = \"creators\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    name: Mapped[str] = mapped_column(String(255), nullable=False)\n    slug: Mapped[str] = mapped_column(String(255), unique=True, nullable=False)\n    genres: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n    folder_name: Mapped[str] = mapped_column(String(255), nullable=False)\n    view_count: Mapped[int] = mapped_column(Integer, default=0, server_default=\"0\")\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    updated_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now(), onupdate=_now\n    )\n\n    # relationships\n    videos: Mapped[list[SourceVideo]] = sa_relationship(back_populates=\"creator\")\n    technique_pages: Mapped[list[TechniquePage]] = sa_relationship(back_populates=\"creator\")\n\n\nclass SourceVideo(Base):\n    __tablename__ = \"source_videos\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    creator_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"creators.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    filename: Mapped[str] = mapped_column(String(500), nullable=False)\n    file_path: Mapped[str] = mapped_column(String(1000), nullable=False)\n    duration_seconds: Mapped[int] = mapped_column(Integer, nullable=True)\n    content_type: Mapped[ContentType] = mapped_column(\n        Enum(ContentType, name=\"content_type\", create_constraint=True),\n        nullable=False,\n    )\n    transcript_path: Mapped[str | None] = mapped_column(String(1000), nullable=True)\n    processing_status: Mapped[ProcessingStatus] = mapped_column(\n        Enum(ProcessingStatus, name=\"processing_status\", create_constraint=True),\n        default=ProcessingStatus.pending,\n        server_default=\"pending\",\n    )\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    updated_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now(), onupdate=_now\n    )\n\n    # relationships\n    creator: Mapped[Creator] = sa_relationship(back_populates=\"videos\")\n    segments: Mapped[list[TranscriptSegment]] = sa_relationship(back_populates=\"source_video\")\n    key_moments: Mapped[list[KeyMoment]] = sa_relationship(back_populates=\"source_video\")\n\n\nclass TranscriptSegment(Base):\n    __tablename__ = \"transcript_segments\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    source_video_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    start_time: Mapped[float] = mapped_column(Float, nullable=False)\n    end_time: Mapped[float] = mapped_column(Float, nullable=False)\n    text: Mapped[str] = mapped_column(Text, nullable=False)\n    segment_index: Mapped[int] = mapped_column(Integer, nullable=False)\n    topic_label: Mapped[str | None] = mapped_column(String(255), nullable=True)\n\n    # relationships\n    source_video: Mapped[SourceVideo] = sa_relationship(back_populates=\"segments\")\n\n\nclass KeyMoment(Base):\n    __tablename__ = \"key_moments\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    source_video_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    technique_page_id: Mapped[uuid.UUID | None] = mapped_column(\n        ForeignKey(\"technique_pages.id\", ondelete=\"SET NULL\"), nullable=True\n    )\n    title: Mapped[str] = mapped_column(String(500), nullable=False)\n    summary: Mapped[str] = mapped_column(Text, nullable=False)\n    start_time: Mapped[float] = mapped_column(Float, nullable=False)\n    end_time: Mapped[float] = mapped_column(Float, nullable=False)\n    content_type: Mapped[KeyMomentContentType] = mapped_column(\n        Enum(KeyMomentContentType, name=\"key_moment_content_type\", create_constraint=True),\n        nullable=False,\n    )\n    plugins: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n    review_status: Mapped[ReviewStatus] = mapped_column(\n        Enum(ReviewStatus, name=\"review_status\", create_constraint=True),\n        default=ReviewStatus.pending,\n        server_default=\"pending\",\n    )\n    raw_transcript: Mapped[str | None] = mapped_column(Text, nullable=True)\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    updated_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now(), onupdate=_now\n    )\n\n    # relationships\n    source_video: Mapped[SourceVideo] = sa_relationship(back_populates=\"key_moments\")\n    technique_page: Mapped[TechniquePage | None] = sa_relationship(\n        back_populates=\"key_moments\", foreign_keys=[technique_page_id]\n    )\n\n\nclass TechniquePage(Base):\n    __tablename__ = \"technique_pages\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    creator_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"creators.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    title: Mapped[str] = mapped_column(String(500), nullable=False)\n    slug: Mapped[str] = mapped_column(String(500), unique=True, nullable=False)\n    topic_category: Mapped[str] = mapped_column(String(255), nullable=False)\n    topic_tags: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n    summary: Mapped[str | None] = mapped_column(Text, nullable=True)\n    body_sections: Mapped[dict | None] = mapped_column(JSONB, nullable=True)\n    signal_chains: Mapped[list | None] = mapped_column(JSONB, nullable=True)\n    plugins: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n    source_quality: Mapped[SourceQuality | None] = mapped_column(\n        Enum(SourceQuality, name=\"source_quality\", create_constraint=True),\n        nullable=True,\n    )\n    view_count: Mapped[int] = mapped_column(Integer, default=0, server_default=\"0\")\n    review_status: Mapped[PageReviewStatus] = mapped_column(\n        Enum(PageReviewStatus, name=\"page_review_status\", create_constraint=True),\n        default=PageReviewStatus.draft,\n        server_default=\"draft\",\n    )\n    created_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now()\n    )\n    updated_at: Mapped[datetime] = mapped_column(\n        default=_now, server_default=func.now(), onupdate=_now\n    )\n\n    # relationships\n    creator: Mapped[Creator] = sa_relationship(back_populates=\"technique_pages\")\n    key_moments: Mapped[list[KeyMoment]] = sa_relationship(\n        back_populates=\"technique_page\", foreign_keys=[KeyMoment.technique_page_id]\n    )\n    outgoing_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(\n        foreign_keys=\"RelatedTechniqueLink.source_page_id\", back_populates=\"source_page\"\n    )\n    incoming_links: Mapped[list[RelatedTechniqueLink]] = sa_relationship(\n        foreign_keys=\"RelatedTechniqueLink.target_page_id\", back_populates=\"target_page\"\n    )\n\n\nclass RelatedTechniqueLink(Base):\n    __tablename__ = \"related_technique_links\"\n    __table_args__ = (\n        UniqueConstraint(\"source_page_id\", \"target_page_id\", \"relationship\", name=\"uq_technique_link\"),\n    )\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    source_page_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    target_page_id: Mapped[uuid.UUID] = mapped_column(\n        ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False\n    )\n    relationship: Mapped[RelationshipType] = mapped_column(\n        Enum(RelationshipType, name=\"relationship_type\", create_constraint=True),\n        nullable=False,\n    )\n\n    # relationships\n    source_page: Mapped[TechniquePage] = sa_relationship(\n        foreign_keys=[source_page_id], back_populates=\"outgoing_links\"\n    )\n    target_page: Mapped[TechniquePage] = sa_relationship(\n        foreign_keys=[target_page_id], back_populates=\"incoming_links\"\n    )\n\n\nclass Tag(Base):\n    __tablename__ = \"tags\"\n\n    id: Mapped[uuid.UUID] = _uuid_pk()\n    name: Mapped[str] = mapped_column(String(255), unique=True, nullable=False)\n    category: Mapped[str] = mapped_column(String(255), nullable=False)\n    aliases: Mapped[list[str] | None] = mapped_column(ARRAY(String), nullable=True)\n"}],"isError":false,"timestamp":1774821775921}}
{"type":"message","id":"22b0f477","parentId":"e853e0f3","timestamp":"2026-03-29T22:02:55.923Z","message":{"role":"toolResult","toolCallId":"toolu_01VNvrWZQPwqTyBoZ1cfwpbX","toolName":"read","content":[{"type":"text","text":"\"\"\"Pydantic schemas for the Chrysopedia API.\n\nRead-only schemas for list/detail endpoints and input schemas for creation.\nEach schema mirrors the corresponding SQLAlchemy model in models.py.\n\"\"\"\n\nfrom __future__ import annotations\n\nimport uuid\nfrom datetime import datetime\n\nfrom pydantic import BaseModel, ConfigDict, Field\n\n\n# ── Health ───────────────────────────────────────────────────────────────────\n\nclass HealthResponse(BaseModel):\n    status: str = \"ok\"\n    service: str = \"chrysopedia-api\"\n    version: str = \"0.1.0\"\n    database: str = \"unknown\"\n\n\n# ── Creator ──────────────────────────────────────────────────────────────────\n\nclass CreatorBase(BaseModel):\n    name: str\n    slug: str\n    genres: list[str] | None = None\n    folder_name: str\n\nclass CreatorCreate(CreatorBase):\n    pass\n\nclass CreatorRead(CreatorBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    view_count: int = 0\n    created_at: datetime\n    updated_at: datetime\n\n\nclass CreatorDetail(CreatorRead):\n    \"\"\"Creator with nested video count.\"\"\"\n    video_count: int = 0\n\n\n# ── SourceVideo ──────────────────────────────────────────────────────────────\n\nclass SourceVideoBase(BaseModel):\n    filename: str\n    file_path: str\n    duration_seconds: int | None = None\n    content_type: str\n    transcript_path: str | None = None\n\nclass SourceVideoCreate(SourceVideoBase):\n    creator_id: uuid.UUID\n\nclass SourceVideoRead(SourceVideoBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    creator_id: uuid.UUID\n    processing_status: str = \"pending\"\n    created_at: datetime\n    updated_at: datetime\n\n\n# ── TranscriptSegment ────────────────────────────────────────────────────────\n\nclass TranscriptSegmentBase(BaseModel):\n    start_time: float\n    end_time: float\n    text: str\n    segment_index: int\n    topic_label: str | None = None\n\nclass TranscriptSegmentCreate(TranscriptSegmentBase):\n    source_video_id: uuid.UUID\n\nclass TranscriptSegmentRead(TranscriptSegmentBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    source_video_id: uuid.UUID\n\n\n# ── KeyMoment ────────────────────────────────────────────────────────────────\n\nclass KeyMomentBase(BaseModel):\n    title: str\n    summary: str\n    start_time: float\n    end_time: float\n    content_type: str\n    plugins: list[str] | None = None\n    raw_transcript: str | None = None\n\nclass KeyMomentCreate(KeyMomentBase):\n    source_video_id: uuid.UUID\n    technique_page_id: uuid.UUID | None = None\n\nclass KeyMomentRead(KeyMomentBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    source_video_id: uuid.UUID\n    technique_page_id: uuid.UUID | None = None\n    review_status: str = \"pending\"\n    created_at: datetime\n    updated_at: datetime\n\n\n# ── TechniquePage ────────────────────────────────────────────────────────────\n\nclass TechniquePageBase(BaseModel):\n    title: str\n    slug: str\n    topic_category: str\n    topic_tags: list[str] | None = None\n    summary: str | None = None\n    body_sections: dict | None = None\n    signal_chains: list | None = None\n    plugins: list[str] | None = None\n\nclass TechniquePageCreate(TechniquePageBase):\n    creator_id: uuid.UUID\n    source_quality: str | None = None\n\nclass TechniquePageRead(TechniquePageBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n    creator_id: uuid.UUID\n    source_quality: str | None = None\n    view_count: int = 0\n    review_status: str = \"draft\"\n    created_at: datetime\n    updated_at: datetime\n\n\n# ── RelatedTechniqueLink ─────────────────────────────────────────────────────\n\nclass RelatedTechniqueLinkBase(BaseModel):\n    source_page_id: uuid.UUID\n    target_page_id: uuid.UUID\n    relationship: str\n\nclass RelatedTechniqueLinkCreate(RelatedTechniqueLinkBase):\n    pass\n\nclass RelatedTechniqueLinkRead(RelatedTechniqueLinkBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n\n\n# ── Tag ──────────────────────────────────────────────────────────────────────\n\nclass TagBase(BaseModel):\n    name: str\n    category: str\n    aliases: list[str] | None = None\n\nclass TagCreate(TagBase):\n    pass\n\nclass TagRead(TagBase):\n    model_config = ConfigDict(from_attributes=True)\n\n    id: uuid.UUID\n\n\n# ── Pagination wrapper ───────────────────────────────────────────────────────\n\nclass PaginatedResponse(BaseModel):\n    \"\"\"Generic paginated list response.\"\"\"\n    items: list = Field(default_factory=list)\n    total: int = 0\n    offset: int = 0\n    limit: int = 50\n"}],"isError":false,"timestamp":1774821775923}}
{"type":"message","id":"fdd2815d","parentId":"22b0f477","timestamp":"2026-03-29T22:02:55.924Z","message":{"role":"toolResult","toolCallId":"toolu_01TYKEy2R5DpYVZ9AWGP8wW2","toolName":"read","content":[{"type":"text","text":"\"\"\"Chrysopedia API — Knowledge extraction and retrieval system.\n\nEntry point for the FastAPI application. Configures middleware,\nstructured logging, and mounts versioned API routers.\n\"\"\"\n\nimport logging\nimport sys\nfrom contextlib import asynccontextmanager\n\nfrom fastapi import FastAPI\nfrom fastapi.middleware.cors import CORSMiddleware\n\nfrom config import get_settings\nfrom routers import creators, health, videos\n\n\ndef _setup_logging() -> None:\n    \"\"\"Configure structured logging to stdout.\"\"\"\n    settings = get_settings()\n    level = getattr(logging, settings.app_log_level.upper(), logging.INFO)\n\n    handler = logging.StreamHandler(sys.stdout)\n    handler.setFormatter(\n        logging.Formatter(\n            fmt=\"%(asctime)s | %(levelname)-8s | %(name)s | %(message)s\",\n            datefmt=\"%Y-%m-%dT%H:%M:%S\",\n        )\n    )\n\n    root = logging.getLogger()\n    root.setLevel(level)\n    # Avoid duplicate handlers on reload\n    root.handlers.clear()\n    root.addHandler(handler)\n\n    # Quiet noisy libraries\n    logging.getLogger(\"uvicorn.access\").setLevel(logging.WARNING)\n    logging.getLogger(\"sqlalchemy.engine\").setLevel(logging.WARNING)\n\n\n@asynccontextmanager\nasync def lifespan(app: FastAPI):  # noqa: ARG001\n    \"\"\"Application lifespan: setup on startup, teardown on shutdown.\"\"\"\n    _setup_logging()\n    logger = logging.getLogger(\"chrysopedia\")\n    settings = get_settings()\n    logger.info(\n        \"Chrysopedia API starting (env=%s, log_level=%s)\",\n        settings.app_env,\n        settings.app_log_level,\n    )\n    yield\n    logger.info(\"Chrysopedia API shutting down\")\n\n\napp = FastAPI(\n    title=\"Chrysopedia API\",\n    description=\"Knowledge extraction and retrieval for music production content\",\n    version=\"0.1.0\",\n    lifespan=lifespan,\n)\n\n# ── Middleware ────────────────────────────────────────────────────────────────\n\nsettings = get_settings()\napp.add_middleware(\n    CORSMiddleware,\n    allow_origins=settings.cors_origins,\n    allow_credentials=True,\n    allow_methods=[\"*\"],\n    allow_headers=[\"*\"],\n)\n\n# ── Routers ──────────────────────────────────────────────────────────────────\n\n# Root-level health (no prefix)\napp.include_router(health.router)\n\n# Versioned API\napp.include_router(creators.router, prefix=\"/api/v1\")\napp.include_router(videos.router, prefix=\"/api/v1\")\n\n\n@app.get(\"/api/v1/health\")\nasync def api_health():\n    \"\"\"Lightweight version-prefixed health endpoint (no DB check).\"\"\"\n    return {\"status\": \"ok\", \"version\": \"0.1.0\"}\n"}],"isError":false,"timestamp":1774821775924}}
{"type":"message","id":"a77c7fe0","parentId":"fdd2815d","timestamp":"2026-03-29T22:02:55.925Z","message":{"role":"toolResult","toolCallId":"toolu_011Xq2bHJXcUcqHvVvMqHyxD","toolName":"read","content":[{"type":"text","text":"\"\"\"Database engine, session factory, and declarative base for Chrysopedia.\"\"\"\n\nimport os\n\nfrom sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine\nfrom sqlalchemy.orm import DeclarativeBase\n\nDATABASE_URL = os.getenv(\n    \"DATABASE_URL\",\n    \"postgresql+asyncpg://chrysopedia:changeme@localhost:5433/chrysopedia\",\n)\n\nengine = create_async_engine(DATABASE_URL, echo=False, pool_pre_ping=True)\n\nasync_session = async_sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)\n\n\nclass Base(DeclarativeBase):\n    \"\"\"Declarative base for all ORM models.\"\"\"\n    pass\n\n\nasync def get_session() -> AsyncSession:  # type: ignore[misc]\n    \"\"\"FastAPI dependency that yields an async DB session.\"\"\"\n    async with async_session() as session:\n        yield session\n"}],"isError":false,"timestamp":1774821775925}}
{"type":"message","id":"347ca9d2","parentId":"a77c7fe0","timestamp":"2026-03-29T22:02:55.926Z","message":{"role":"toolResult","toolCallId":"toolu_01RxA6GjDHqsYCYnsETj2Ax8","toolName":"read","content":[{"type":"text","text":"\"\"\"Application configuration loaded from environment variables.\"\"\"\n\nfrom functools import lru_cache\n\nfrom pydantic_settings import BaseSettings\n\n\nclass Settings(BaseSettings):\n    \"\"\"Chrysopedia API settings.\n\n    Values are loaded from environment variables (or .env file via\n    pydantic-settings' dotenv support).\n    \"\"\"\n\n    # Database\n    database_url: str = \"postgresql+asyncpg://chrysopedia:changeme@localhost:5433/chrysopedia\"\n\n    # Redis\n    redis_url: str = \"redis://localhost:6379/0\"\n\n    # Application\n    app_env: str = \"development\"\n    app_log_level: str = \"info\"\n    app_secret_key: str = \"changeme-generate-a-real-secret\"\n\n    # CORS\n    cors_origins: list[str] = [\"*\"]\n\n    # File storage\n    transcript_storage_path: str = \"/data/transcripts\"\n    video_metadata_path: str = \"/data/video_meta\"\n\n    model_config = {\n        \"env_file\": \".env\",\n        \"env_file_encoding\": \"utf-8\",\n        \"case_sensitive\": False,\n    }\n\n\n@lru_cache\ndef get_settings() -> Settings:\n    \"\"\"Return cached application settings (singleton).\"\"\"\n    return Settings()\n"}],"isError":false,"timestamp":1774821775925}}
{"type":"message","id":"1f835981","parentId":"347ca9d2","timestamp":"2026-03-29T22:02:55.928Z","message":{"role":"toolResult","toolCallId":"toolu_01KZdp8T7cgsfGgL6XZHxmKw","toolName":"read","content":[{"type":"text","text":"{\n  \"source_file\": \"Skope — Sound Design Masterclass pt1.mp4\",\n  \"creator_folder\": \"Skope\",\n  \"duration_seconds\": 3847,\n  \"segments\": [\n    {\n      \"start\": 0.0,\n      \"end\": 4.52,\n      \"text\": \"Hey everyone welcome back to part one of this sound design masterclass.\",\n      \"words\": [\n        { \"word\": \"Hey\", \"start\": 0.0, \"end\": 0.28 },\n        { \"word\": \"everyone\", \"start\": 0.32, \"end\": 0.74 },\n        { \"word\": \"welcome\", \"start\": 0.78, \"end\": 1.12 },\n        { \"word\": \"back\", \"start\": 1.14, \"end\": 1.38 },\n        { \"word\": \"to\", \"start\": 1.40, \"end\": 1.52 },\n        { \"word\": \"part\", \"start\": 1.54, \"end\": 1.76 },\n        { \"word\": \"one\", \"start\": 1.78, \"end\": 1.98 },\n        { \"word\": \"of\", \"start\": 2.00, \"end\": 2.12 },\n        { \"word\": \"this\", \"start\": 2.14, \"end\": 2.34 },\n        { \"word\": \"sound\", \"start\": 2.38, \"end\": 2.68 },\n        { \"word\": \"design\", \"start\": 2.72, \"end\": 3.08 },\n        { \"word\": \"masterclass\", \"start\": 3.14, \"end\": 4.52 }\n      ]\n    },\n    {\n      \"start\": 5.10,\n      \"end\": 12.84,\n      \"text\": \"Today we're going to be looking at how to create really aggressive bass sounds using Serum.\",\n      \"words\": [\n        { \"word\": \"Today\", \"start\": 5.10, \"end\": 5.48 },\n        { \"word\": \"we're\", \"start\": 5.52, \"end\": 5.74 },\n        { \"word\": \"going\", \"start\": 5.78, \"end\": 5.98 },\n        { \"word\": \"to\", \"start\": 6.00, \"end\": 6.12 },\n        { \"word\": \"be\", \"start\": 6.14, \"end\": 6.28 },\n        { \"word\": \"looking\", \"start\": 6.32, \"end\": 6.64 },\n        { \"word\": \"at\", \"start\": 6.68, \"end\": 6.82 },\n        { \"word\": \"how\", \"start\": 6.86, \"end\": 7.08 },\n        { \"word\": \"to\", \"start\": 7.12, \"end\": 7.24 },\n        { \"word\": \"create\", \"start\": 7.28, \"end\": 7.62 },\n        { \"word\": \"really\", \"start\": 7.68, \"end\": 8.02 },\n        { \"word\": \"aggressive\", \"start\": 8.08, \"end\": 8.72 },\n        { \"word\": \"bass\", \"start\": 8.78, \"end\": 9.14 },\n        { \"word\": \"sounds\", \"start\": 9.18, \"end\": 9.56 },\n        { \"word\": \"using\", \"start\": 9.62, \"end\": 9.98 },\n        { \"word\": \"Serum\", \"start\": 10.04, \"end\": 12.84 }\n      ]\n    },\n    {\n      \"start\": 13.40,\n      \"end\": 22.18,\n      \"text\": \"So the first thing I always do is start with the init preset and then I'll load up a basic wavetable.\",\n      \"words\": [\n        { \"word\": \"So\", \"start\": 13.40, \"end\": 13.58 },\n        { \"word\": \"the\", \"start\": 13.62, \"end\": 13.78 },\n        { \"word\": \"first\", \"start\": 13.82, \"end\": 14.12 },\n        { \"word\": \"thing\", \"start\": 14.16, \"end\": 14.42 },\n        { \"word\": \"I\", \"start\": 14.48, \"end\": 14.58 },\n        { \"word\": \"always\", \"start\": 14.62, \"end\": 14.98 },\n        { \"word\": \"do\", \"start\": 15.02, \"end\": 15.18 },\n        { \"word\": \"is\", \"start\": 15.22, \"end\": 15.38 },\n        { \"word\": \"start\", \"start\": 15.44, \"end\": 15.78 },\n        { \"word\": \"with\", \"start\": 15.82, \"end\": 16.02 },\n        { \"word\": \"the\", \"start\": 16.06, \"end\": 16.18 },\n        { \"word\": \"init\", \"start\": 16.24, \"end\": 16.52 },\n        { \"word\": \"preset\", \"start\": 16.58, \"end\": 17.02 },\n        { \"word\": \"and\", \"start\": 17.32, \"end\": 17.48 },\n        { \"word\": \"then\", \"start\": 17.52, \"end\": 17.74 },\n        { \"word\": \"I'll\", \"start\": 17.78, \"end\": 17.98 },\n        { \"word\": \"load\", \"start\": 18.04, \"end\": 18.32 },\n        { \"word\": \"up\", \"start\": 18.36, \"end\": 18.52 },\n        { \"word\": \"a\", \"start\": 18.56, \"end\": 18.64 },\n        { \"word\": \"basic\", \"start\": 18.68, \"end\": 19.08 },\n        { \"word\": \"wavetable\", \"start\": 19.14, \"end\": 22.18 }\n      ]\n    },\n    {\n      \"start\": 23.00,\n      \"end\": 35.42,\n      \"text\": \"What makes this technique work is the FM modulation from oscillator B. You want to set the ratio to something like 3.5 and then automate the depth.\",\n      \"words\": [\n        { \"word\": \"What\", \"start\": 23.00, \"end\": 23.22 },\n        { \"word\": \"makes\", \"start\": 23.26, \"end\": 23.54 },\n        { \"word\": \"this\", \"start\": 23.58, \"end\": 23.78 },\n        { \"word\": \"technique\", \"start\": 23.82, \"end\": 24.34 },\n        { \"word\": \"work\", \"start\": 24.38, \"end\": 24.68 },\n        { \"word\": \"is\", \"start\": 24.72, \"end\": 24.88 },\n        { \"word\": \"the\", \"start\": 24.92, \"end\": 25.04 },\n        { \"word\": \"FM\", \"start\": 25.10, \"end\": 25.42 },\n        { \"word\": \"modulation\", \"start\": 25.48, \"end\": 26.12 },\n        { \"word\": \"from\", \"start\": 26.16, \"end\": 26.38 },\n        { \"word\": \"oscillator\", \"start\": 26.44, \"end\": 27.08 },\n        { \"word\": \"B\", \"start\": 27.14, \"end\": 27.42 },\n        { \"word\": \"You\", \"start\": 28.02, \"end\": 28.22 },\n        { \"word\": \"want\", \"start\": 28.26, \"end\": 28.52 },\n        { \"word\": \"to\", \"start\": 28.56, \"end\": 28.68 },\n        { \"word\": \"set\", \"start\": 28.72, \"end\": 28.98 },\n        { \"word\": \"the\", \"start\": 29.02, \"end\": 29.14 },\n        { \"word\": \"ratio\", \"start\": 29.18, \"end\": 29.58 },\n        { \"word\": \"to\", \"start\": 29.62, \"end\": 29.76 },\n        { \"word\": \"something\", \"start\": 29.80, \"end\": 30.22 },\n        { \"word\": \"like\", \"start\": 30.26, \"end\": 30.48 },\n        { \"word\": \"3.5\", \"start\": 30.54, \"end\": 31.02 },\n        { \"word\": \"and\", \"start\": 31.32, \"end\": 31.48 },\n        { \"word\": \"then\", \"start\": 31.52, \"end\": 31.74 },\n        { \"word\": \"automate\", \"start\": 31.80, \"end\": 32.38 },\n        { \"word\": \"the\", \"start\": 32.42, \"end\": 32.58 },\n        { \"word\": \"depth\", \"start\": 32.64, \"end\": 35.42 }\n      ]\n    },\n    {\n      \"start\": 36.00,\n      \"end\": 48.76,\n      \"text\": \"Now I'm going to add some distortion. OTT is great for this. Crank it to like 60 percent and then back off the highs a bit with a shelf EQ.\",\n      \"words\": [\n        { \"word\": \"Now\", \"start\": 36.00, \"end\": 36.28 },\n        { \"word\": \"I'm\", \"start\": 36.32, \"end\": 36.52 },\n        { \"word\": \"going\", \"start\": 36.56, \"end\": 36.82 },\n        { \"word\": \"to\", \"start\": 36.86, \"end\": 36.98 },\n        { \"word\": \"add\", \"start\": 37.02, \"end\": 37.28 },\n        { \"word\": \"some\", \"start\": 37.32, \"end\": 37.58 },\n        { \"word\": \"distortion\", \"start\": 37.64, \"end\": 38.34 },\n        { \"word\": \"OTT\", \"start\": 39.02, \"end\": 39.42 },\n        { \"word\": \"is\", \"start\": 39.46, \"end\": 39.58 },\n        { \"word\": \"great\", \"start\": 39.62, \"end\": 39.92 },\n        { \"word\": \"for\", \"start\": 39.96, \"end\": 40.12 },\n        { \"word\": \"this\", \"start\": 40.16, \"end\": 40.42 },\n        { \"word\": \"Crank\", \"start\": 41.02, \"end\": 41.38 },\n        { \"word\": \"it\", \"start\": 41.42, \"end\": 41.56 },\n        { \"word\": \"to\", \"start\": 41.60, \"end\": 41.72 },\n        { \"word\": \"like\", \"start\": 41.76, \"end\": 41.98 },\n        { \"word\": \"60\", \"start\": 42.04, \"end\": 42.38 },\n        { \"word\": \"percent\", \"start\": 42.42, \"end\": 42.86 },\n        { \"word\": \"and\", \"start\": 43.12, \"end\": 43.28 },\n        { \"word\": \"then\", \"start\": 43.32, \"end\": 43.54 },\n        { \"word\": \"back\", \"start\": 43.58, \"end\": 43.84 },\n        { \"word\": \"off\", \"start\": 43.88, \"end\": 44.08 },\n        { \"word\": \"the\", \"start\": 44.12, \"end\": 44.24 },\n        { \"word\": \"highs\", \"start\": 44.28, \"end\": 44.68 },\n        { \"word\": \"a\", \"start\": 44.72, \"end\": 44.82 },\n        { \"word\": \"bit\", \"start\": 44.86, \"end\": 45.08 },\n        { \"word\": \"with\", \"start\": 45.14, \"end\": 45.38 },\n        { \"word\": \"a\", \"start\": 45.42, \"end\": 45.52 },\n        { \"word\": \"shelf\", \"start\": 45.58, \"end\": 45.96 },\n        { \"word\": \"EQ\", \"start\": 46.02, \"end\": 48.76 }\n      ]\n    }\n  ]\n}\n"}],"isError":false,"timestamp":1774821775926}}
{"type":"message","id":"dff5e137","parentId":"1f835981","timestamp":"2026-03-29T22:03:01.460Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me check existing routers and the Whisper output format more closely:"},{"type":"toolCall","id":"toolu_015J7etWRAWQznGQ5fcQMLoj","name":"read","arguments":{"path":"backend/routers/creators.py"}},{"type":"toolCall","id":"toolu_01Qrhn2vNL9VNTA4XHUk3NtE","name":"read","arguments":{"path":"backend/routers/videos.py"}},{"type":"toolCall","id":"toolu_019b5rdktnA5Pg1MKHVRAwPh","name":"read","arguments":{"path":"backend/routers/health.py"}},{"type":"toolCall","id":"toolu_014nDekEDxEbfmnx1QwZNuvS","name":"bash","arguments":{"command":"ls backend/routers/"}},{"type":"toolCall","id":"toolu_01GxQ1WXLzKG9T5gDKk1Z2Kg","name":"bash","arguments":{"command":"ls backend/"}},{"type":"toolCall","id":"toolu_01AHHYZNUWJSx6ZAbv9Jkhqw","name":"read","arguments":{"path":"backend/requirements.txt"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":273,"cacheRead":56943,"cacheWrite":9653,"totalTokens":66870,"cost":{"input":0.000005,"output":0.006825,"cacheRead":0.0284715,"cacheWrite":0.06033125,"total":0.09563275}},"stopReason":"toolUse","timestamp":1774821775926}}
{"type":"message","id":"8da7d999","parentId":"dff5e137","timestamp":"2026-03-29T22:03:01.473Z","message":{"role":"toolResult","toolCallId":"toolu_015J7etWRAWQznGQ5fcQMLoj","toolName":"read","content":[{"type":"text","text":"\"\"\"Creator endpoints for Chrysopedia API.\"\"\"\n\nimport logging\nfrom typing import Annotated\n\nfrom fastapi import APIRouter, Depends, HTTPException, Query\nfrom sqlalchemy import func, select\nfrom sqlalchemy.ext.asyncio import AsyncSession\n\nfrom database import get_session\nfrom models import Creator, SourceVideo\nfrom schemas import CreatorDetail, CreatorRead\n\nlogger = logging.getLogger(\"chrysopedia.creators\")\n\nrouter = APIRouter(prefix=\"/creators\", tags=[\"creators\"])\n\n\n@router.get(\"\", response_model=list[CreatorRead])\nasync def list_creators(\n    offset: Annotated[int, Query(ge=0)] = 0,\n    limit: Annotated[int, Query(ge=1, le=100)] = 50,\n    db: AsyncSession = Depends(get_session),\n) -> list[CreatorRead]:\n    \"\"\"List all creators with pagination.\"\"\"\n    stmt = select(Creator).order_by(Creator.name).offset(offset).limit(limit)\n    result = await db.execute(stmt)\n    creators = result.scalars().all()\n    logger.debug(\"Listed %d creators (offset=%d, limit=%d)\", len(creators), offset, limit)\n    return [CreatorRead.model_validate(c) for c in creators]\n\n\n@router.get(\"/{slug}\", response_model=CreatorDetail)\nasync def get_creator(\n    slug: str,\n    db: AsyncSession = Depends(get_session),\n) -> CreatorDetail:\n    \"\"\"Get a single creator by slug, including video count.\"\"\"\n    stmt = select(Creator).where(Creator.slug == slug)\n    result = await db.execute(stmt)\n    creator = result.scalar_one_or_none()\n\n    if creator is None:\n        raise HTTPException(status_code=404, detail=f\"Creator '{slug}' not found\")\n\n    # Count videos for this creator\n    count_stmt = (\n        select(func.count())\n        .select_from(SourceVideo)\n        .where(SourceVideo.creator_id == creator.id)\n    )\n    count_result = await db.execute(count_stmt)\n    video_count = count_result.scalar() or 0\n\n    creator_data = CreatorRead.model_validate(creator)\n    return CreatorDetail(**creator_data.model_dump(), video_count=video_count)\n"}],"isError":false,"timestamp":1774821781473}}
{"type":"message","id":"1a923547","parentId":"8da7d999","timestamp":"2026-03-29T22:03:01.475Z","message":{"role":"toolResult","toolCallId":"toolu_01Qrhn2vNL9VNTA4XHUk3NtE","toolName":"read","content":[{"type":"text","text":"\"\"\"Source video endpoints for Chrysopedia API.\"\"\"\n\nimport logging\nfrom typing import Annotated\n\nfrom fastapi import APIRouter, Depends, Query\nfrom sqlalchemy import select\nfrom sqlalchemy.ext.asyncio import AsyncSession\n\nfrom database import get_session\nfrom models import SourceVideo\nfrom schemas import SourceVideoRead\n\nlogger = logging.getLogger(\"chrysopedia.videos\")\n\nrouter = APIRouter(prefix=\"/videos\", tags=[\"videos\"])\n\n\n@router.get(\"\", response_model=list[SourceVideoRead])\nasync def list_videos(\n    offset: Annotated[int, Query(ge=0)] = 0,\n    limit: Annotated[int, Query(ge=1, le=100)] = 50,\n    creator_id: str | None = None,\n    db: AsyncSession = Depends(get_session),\n) -> list[SourceVideoRead]:\n    \"\"\"List source videos with optional filtering by creator.\"\"\"\n    stmt = select(SourceVideo).order_by(SourceVideo.created_at.desc())\n\n    if creator_id:\n        stmt = stmt.where(SourceVideo.creator_id == creator_id)\n\n    stmt = stmt.offset(offset).limit(limit)\n    result = await db.execute(stmt)\n    videos = result.scalars().all()\n    logger.debug(\"Listed %d videos (offset=%d, limit=%d)\", len(videos), offset, limit)\n    return [SourceVideoRead.model_validate(v) for v in videos]\n"}],"isError":false,"timestamp":1774821781475}}
{"type":"message","id":"54796925","parentId":"1a923547","timestamp":"2026-03-29T22:03:01.476Z","message":{"role":"toolResult","toolCallId":"toolu_019b5rdktnA5Pg1MKHVRAwPh","toolName":"read","content":[{"type":"text","text":"\"\"\"Health check endpoints for Chrysopedia API.\"\"\"\n\nimport logging\n\nfrom fastapi import APIRouter, Depends\nfrom sqlalchemy import text\nfrom sqlalchemy.ext.asyncio import AsyncSession\n\nfrom database import get_session\nfrom schemas import HealthResponse\n\nlogger = logging.getLogger(\"chrysopedia.health\")\n\nrouter = APIRouter(tags=[\"health\"])\n\n\n@router.get(\"/health\", response_model=HealthResponse)\nasync def health_check(db: AsyncSession = Depends(get_session)) -> HealthResponse:\n    \"\"\"Root health check — verifies API is running and DB is reachable.\"\"\"\n    db_status = \"unknown\"\n    try:\n        result = await db.execute(text(\"SELECT 1\"))\n        result.scalar()\n        db_status = \"connected\"\n    except Exception:\n        logger.warning(\"Database health check failed\", exc_info=True)\n        db_status = \"unreachable\"\n\n    return HealthResponse(\n        status=\"ok\",\n        service=\"chrysopedia-api\",\n        version=\"0.1.0\",\n        database=db_status,\n    )\n"}],"isError":false,"timestamp":1774821781476}}
{"type":"message","id":"4b258e2e","parentId":"54796925","timestamp":"2026-03-29T22:03:01.476Z","message":{"role":"toolResult","toolCallId":"toolu_014nDekEDxEbfmnx1QwZNuvS","toolName":"bash","content":[{"type":"text","text":"creators.py\nhealth.py\n__init__.py\n__pycache__\nvideos.py\n"}],"isError":false,"timestamp":1774821781476}}
{"type":"message","id":"a6f25115","parentId":"4b258e2e","timestamp":"2026-03-29T22:03:01.477Z","message":{"role":"toolResult","toolCallId":"toolu_01GxQ1WXLzKG9T5gDKk1Z2Kg","toolName":"bash","content":[{"type":"text","text":"config.py\ndatabase.py\nmain.py\nmodels.py\n__pycache__\nrequirements.txt\nrouters\nschemas.py\n"}],"isError":false,"timestamp":1774821781476}}
{"type":"message","id":"df333a87","parentId":"a6f25115","timestamp":"2026-03-29T22:03:01.479Z","message":{"role":"toolResult","toolCallId":"toolu_01AHHYZNUWJSx6ZAbv9Jkhqw","toolName":"read","content":[{"type":"text","text":"fastapi>=0.115.0,<1.0\nuvicorn[standard]>=0.32.0,<1.0\nsqlalchemy[asyncio]>=2.0,<3.0\nasyncpg>=0.30.0,<1.0\nalembic>=1.14.0,<2.0\npydantic>=2.0,<3.0\npydantic-settings>=2.0,<3.0\ncelery[redis]>=5.4.0,<6.0\nredis>=5.0,<6.0\npython-dotenv>=1.0,<2.0\nhttpx>=0.27.0,<1.0\n"}],"isError":false,"timestamp":1774821781477}}
{"type":"message","id":"6c71777f","parentId":"df333a87","timestamp":"2026-03-29T22:03:05.001Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me check the Alembic migration and the docker-compose for file storage paths:"},{"type":"toolCall","id":"toolu_01TUqkNvpE1CLfzNbYvmepuz","name":"read","arguments":{"path":"alembic/versions/001_initial.py"}},{"type":"toolCall","id":"toolu_011x3vc7fcCVxMdFormWcUrS","name":"read","arguments":{"path":"docker-compose.yml"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":120,"cacheRead":66596,"cacheWrite":1823,"totalTokens":68540,"cost":{"input":0.000005,"output":0.003,"cacheRead":0.033298,"cacheWrite":0.011393750000000001,"total":0.04769675}},"stopReason":"toolUse","timestamp":1774821781478}}
{"type":"message","id":"40644f00","parentId":"6c71777f","timestamp":"2026-03-29T22:03:05.004Z","message":{"role":"toolResult","toolCallId":"toolu_01TUqkNvpE1CLfzNbYvmepuz","toolName":"read","content":[{"type":"text","text":"\"\"\"initial schema — 7 core entities\n\nRevision ID: 001_initial\nRevises:\nCreate Date: 2026-03-29\n\"\"\"\nfrom typing import Sequence, Union\n\nfrom alembic import op\nimport sqlalchemy as sa\nfrom sqlalchemy.dialects.postgresql import ARRAY, JSONB, UUID\n\n# revision identifiers, used by Alembic.\nrevision: str = \"001_initial\"\ndown_revision: Union[str, None] = None\nbranch_labels: Union[str, Sequence[str], None] = None\ndepends_on: Union[str, Sequence[str], None] = None\n\n\ndef upgrade() -> None:\n    # ── Enum types ───────────────────────────────────────────────────────\n    content_type = sa.Enum(\n        \"tutorial\", \"livestream\", \"breakdown\", \"short_form\",\n        name=\"content_type\",\n    )\n    processing_status = sa.Enum(\n        \"pending\", \"transcribed\", \"extracted\", \"reviewed\", \"published\",\n        name=\"processing_status\",\n    )\n    key_moment_content_type = sa.Enum(\n        \"technique\", \"settings\", \"reasoning\", \"workflow\",\n        name=\"key_moment_content_type\",\n    )\n    review_status = sa.Enum(\n        \"pending\", \"approved\", \"edited\", \"rejected\",\n        name=\"review_status\",\n    )\n    source_quality = sa.Enum(\n        \"structured\", \"mixed\", \"unstructured\",\n        name=\"source_quality\",\n    )\n    page_review_status = sa.Enum(\n        \"draft\", \"reviewed\", \"published\",\n        name=\"page_review_status\",\n    )\n    relationship_type = sa.Enum(\n        \"same_technique_other_creator\", \"same_creator_adjacent\", \"general_cross_reference\",\n        name=\"relationship_type\",\n    )\n\n    # ── creators ─────────────────────────────────────────────────────────\n    op.create_table(\n        \"creators\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"name\", sa.String(255), nullable=False),\n        sa.Column(\"slug\", sa.String(255), nullable=False, unique=True),\n        sa.Column(\"genres\", ARRAY(sa.String), nullable=True),\n        sa.Column(\"folder_name\", sa.String(255), nullable=False),\n        sa.Column(\"view_count\", sa.Integer, nullable=False, server_default=\"0\"),\n        sa.Column(\"created_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n        sa.Column(\"updated_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n    )\n\n    # ── source_videos ────────────────────────────────────────────────────\n    op.create_table(\n        \"source_videos\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"creator_id\", UUID(as_uuid=True), sa.ForeignKey(\"creators.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"filename\", sa.String(500), nullable=False),\n        sa.Column(\"file_path\", sa.String(1000), nullable=False),\n        sa.Column(\"duration_seconds\", sa.Integer, nullable=True),\n        sa.Column(\"content_type\", content_type, nullable=False),\n        sa.Column(\"transcript_path\", sa.String(1000), nullable=True),\n        sa.Column(\"processing_status\", processing_status, nullable=False, server_default=\"pending\"),\n        sa.Column(\"created_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n        sa.Column(\"updated_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n    )\n    op.create_index(\"ix_source_videos_creator_id\", \"source_videos\", [\"creator_id\"])\n\n    # ── transcript_segments ──────────────────────────────────────────────\n    op.create_table(\n        \"transcript_segments\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"source_video_id\", UUID(as_uuid=True), sa.ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"start_time\", sa.Float, nullable=False),\n        sa.Column(\"end_time\", sa.Float, nullable=False),\n        sa.Column(\"text\", sa.Text, nullable=False),\n        sa.Column(\"segment_index\", sa.Integer, nullable=False),\n        sa.Column(\"topic_label\", sa.String(255), nullable=True),\n    )\n    op.create_index(\"ix_transcript_segments_video_id\", \"transcript_segments\", [\"source_video_id\"])\n\n    # ── technique_pages (must come before key_moments due to FK) ─────────\n    op.create_table(\n        \"technique_pages\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"creator_id\", UUID(as_uuid=True), sa.ForeignKey(\"creators.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"title\", sa.String(500), nullable=False),\n        sa.Column(\"slug\", sa.String(500), nullable=False, unique=True),\n        sa.Column(\"topic_category\", sa.String(255), nullable=False),\n        sa.Column(\"topic_tags\", ARRAY(sa.String), nullable=True),\n        sa.Column(\"summary\", sa.Text, nullable=True),\n        sa.Column(\"body_sections\", JSONB, nullable=True),\n        sa.Column(\"signal_chains\", JSONB, nullable=True),\n        sa.Column(\"plugins\", ARRAY(sa.String), nullable=True),\n        sa.Column(\"source_quality\", source_quality, nullable=True),\n        sa.Column(\"view_count\", sa.Integer, nullable=False, server_default=\"0\"),\n        sa.Column(\"review_status\", page_review_status, nullable=False, server_default=\"draft\"),\n        sa.Column(\"created_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n        sa.Column(\"updated_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n    )\n    op.create_index(\"ix_technique_pages_creator_id\", \"technique_pages\", [\"creator_id\"])\n    op.create_index(\"ix_technique_pages_topic_category\", \"technique_pages\", [\"topic_category\"])\n\n    # ── key_moments ──────────────────────────────────────────────────────\n    op.create_table(\n        \"key_moments\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"source_video_id\", UUID(as_uuid=True), sa.ForeignKey(\"source_videos.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"technique_page_id\", UUID(as_uuid=True), sa.ForeignKey(\"technique_pages.id\", ondelete=\"SET NULL\"), nullable=True),\n        sa.Column(\"title\", sa.String(500), nullable=False),\n        sa.Column(\"summary\", sa.Text, nullable=False),\n        sa.Column(\"start_time\", sa.Float, nullable=False),\n        sa.Column(\"end_time\", sa.Float, nullable=False),\n        sa.Column(\"content_type\", key_moment_content_type, nullable=False),\n        sa.Column(\"plugins\", ARRAY(sa.String), nullable=True),\n        sa.Column(\"review_status\", review_status, nullable=False, server_default=\"pending\"),\n        sa.Column(\"raw_transcript\", sa.Text, nullable=True),\n        sa.Column(\"created_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n        sa.Column(\"updated_at\", sa.DateTime(), nullable=False, server_default=sa.func.now()),\n    )\n    op.create_index(\"ix_key_moments_source_video_id\", \"key_moments\", [\"source_video_id\"])\n    op.create_index(\"ix_key_moments_technique_page_id\", \"key_moments\", [\"technique_page_id\"])\n\n    # ── related_technique_links ──────────────────────────────────────────\n    op.create_table(\n        \"related_technique_links\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"source_page_id\", UUID(as_uuid=True), sa.ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"target_page_id\", UUID(as_uuid=True), sa.ForeignKey(\"technique_pages.id\", ondelete=\"CASCADE\"), nullable=False),\n        sa.Column(\"relationship\", relationship_type, nullable=False),\n        sa.UniqueConstraint(\"source_page_id\", \"target_page_id\", \"relationship\", name=\"uq_technique_link\"),\n    )\n\n    # ── tags ─────────────────────────────────────────────────────────────\n    op.create_table(\n        \"tags\",\n        sa.Column(\"id\", UUID(as_uuid=True), primary_key=True, server_default=sa.text(\"gen_random_uuid()\")),\n        sa.Column(\"name\", sa.String(255), nullable=False, unique=True),\n        sa.Column(\"category\", sa.String(255), nullable=False),\n        sa.Column(\"aliases\", ARRAY(sa.String), nullable=True),\n    )\n    op.create_index(\"ix_tags_category\", \"tags\", [\"category\"])\n\n\ndef downgrade() -> None:\n    op.drop_table(\"tags\")\n    op.drop_table(\"related_technique_links\")\n    op.drop_table(\"key_moments\")\n    op.drop_table(\"technique_pages\")\n    op.drop_table(\"transcript_segments\")\n    op.drop_table(\"source_videos\")\n    op.drop_table(\"creators\")\n\n    # Drop enum types\n    for name in [\n        \"relationship_type\", \"page_review_status\", \"source_quality\",\n        \"review_status\", \"key_moment_content_type\", \"processing_status\",\n        \"content_type\",\n    ]:\n        sa.Enum(name=name).drop(op.get_bind(), checkfirst=True)\n"}],"isError":false,"timestamp":1774821785003}}
{"type":"message","id":"a4b3c8f6","parentId":"40644f00","timestamp":"2026-03-29T22:03:05.006Z","message":{"role":"toolResult","toolCallId":"toolu_011x3vc7fcCVxMdFormWcUrS","toolName":"read","content":[{"type":"text","text":"# Chrysopedia — Docker Compose\n# XPLTD convention: xpltd_chrysopedia project, bind mounts, dedicated bridge\nname: xpltd_chrysopedia\n\nservices:\n  # ── PostgreSQL 16 ──\n  chrysopedia-db:\n    image: postgres:16-alpine\n    container_name: chrysopedia-db\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: ${POSTGRES_USER:-chrysopedia}\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-changeme}\n      POSTGRES_DB: ${POSTGRES_DB:-chrysopedia}\n    volumes:\n      - /vmPool/r/services/chrysopedia_db:/var/lib/postgresql/data\n    ports:\n      - \"127.0.0.1:5433:5432\"\n    networks:\n      - chrysopedia\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U ${POSTGRES_USER:-chrysopedia}\"]\n      interval: 10s\n      timeout: 5s\n      retries: 5\n\n  # ── Redis (Celery broker) ──\n  chrysopedia-redis:\n    image: redis:7-alpine\n    container_name: chrysopedia-redis\n    restart: unless-stopped\n    volumes:\n      - /vmPool/r/services/chrysopedia_redis:/data\n    networks:\n      - chrysopedia\n    healthcheck:\n      test: [\"CMD\", \"redis-cli\", \"ping\"]\n      interval: 10s\n      timeout: 5s\n      retries: 5\n\n  # ── FastAPI application ──\n  chrysopedia-api:\n    build:\n      context: .\n      dockerfile: docker/Dockerfile.api\n    container_name: chrysopedia-api\n    restart: unless-stopped\n    env_file:\n      - path: .env\n        required: false\n    environment:\n      DATABASE_URL: postgresql+asyncpg://${POSTGRES_USER:-chrysopedia}:${POSTGRES_PASSWORD}@chrysopedia-db:5432/${POSTGRES_DB:-chrysopedia}\n      REDIS_URL: redis://chrysopedia-redis:6379/0\n    volumes:\n      - ./backend:/app\n      - /vmPool/r/services/chrysopedia_data:/data\n    ports:\n      - \"127.0.0.1:8000:8000\"\n    depends_on:\n      chrysopedia-db:\n        condition: service_healthy\n      chrysopedia-redis:\n        condition: service_healthy\n    networks:\n      - chrysopedia\n\n  # ── Celery worker (pipeline stages 2-5) ──\n  chrysopedia-worker:\n    build:\n      context: .\n      dockerfile: docker/Dockerfile.api\n    container_name: chrysopedia-worker\n    restart: unless-stopped\n    env_file:\n      - path: .env\n        required: false\n    environment:\n      DATABASE_URL: postgresql+asyncpg://${POSTGRES_USER:-chrysopedia}:${POSTGRES_PASSWORD}@chrysopedia-db:5432/${POSTGRES_DB:-chrysopedia}\n      REDIS_URL: redis://chrysopedia-redis:6379/0\n    command: [\"celery\", \"-A\", \"worker\", \"worker\", \"--loglevel=info\"]\n    volumes:\n      - ./backend:/app\n      - /vmPool/r/services/chrysopedia_data:/data\n      - ./prompts:/prompts:ro\n    depends_on:\n      chrysopedia-db:\n        condition: service_healthy\n      chrysopedia-redis:\n        condition: service_healthy\n    networks:\n      - chrysopedia\n\n  # ── React web UI (nginx) ──\n  chrysopedia-web:\n    build:\n      context: .\n      dockerfile: docker/Dockerfile.web\n    container_name: chrysopedia-web\n    restart: unless-stopped\n    ports:\n      - \"127.0.0.1:3000:80\"\n    depends_on:\n      - chrysopedia-api\n    networks:\n      - chrysopedia\n\nnetworks:\n  chrysopedia:\n    driver: bridge\n    ipam:\n      config:\n        - subnet: 172.24.0.0/24\n"}],"isError":false,"timestamp":1774821785005}}
{"type":"message","id":"a824fd76","parentId":"a4b3c8f6","timestamp":"2026-03-29T22:03:11.171Z","message":{"role":"assistant","content":[{"type":"text","text":"Good. Now I have a complete picture. Let me also check if there's a `__init__.py` in routers and the Whisper script output format for completeness:"},{"type":"toolCall","id":"toolu_01UeTTRjHLKjeo8hKRF2FP7f","name":"read","arguments":{"path":"backend/routers/__init__.py"}},{"type":"toolCall","id":"toolu_01XafzewnKuMxgsGDRBmAChw","name":"bash","arguments":{"command":"grep -n \"content_type\" backend/models.py | head -20"}},{"type":"toolCall","id":"toolu_017x527ND7raym6734A3iup7","name":"bash","arguments":{"command":"grep -rn \"python-multipart\\|UploadFile\\|File(\" backend/ 2>/dev/null"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":209,"cacheRead":68419,"cacheWrite":3893,"totalTokens":72522,"cost":{"input":0.000005,"output":0.0052250000000000005,"cacheRead":0.0342095,"cacheWrite":0.024331250000000002,"total":0.06377075}},"stopReason":"toolUse","timestamp":1774821785005}}
{"type":"message","id":"33a8ca26","parentId":"a824fd76","timestamp":"2026-03-29T22:03:11.182Z","message":{"role":"toolResult","toolCallId":"toolu_01UeTTRjHLKjeo8hKRF2FP7f","toolName":"read","content":[{"type":"text","text":"\"\"\"Chrysopedia API routers package.\"\"\"\n"}],"isError":false,"timestamp":1774821791181}}
{"type":"message","id":"c3514820","parentId":"33a8ca26","timestamp":"2026-03-29T22:03:11.182Z","message":{"role":"toolResult","toolCallId":"toolu_01XafzewnKuMxgsGDRBmAChw","toolName":"bash","content":[{"type":"text","text":"135:    content_type: Mapped[ContentType] = mapped_column(\n136:        Enum(ContentType, name=\"content_type\", create_constraint=True),\n189:    content_type: Mapped[KeyMomentContentType] = mapped_column(\n190:        Enum(KeyMomentContentType, name=\"key_moment_content_type\", create_constraint=True),\n"}],"isError":false,"timestamp":1774821791182}}
{"type":"message","id":"ff130b8b","parentId":"c3514820","timestamp":"2026-03-29T22:03:11.185Z","message":{"role":"toolResult","toolCallId":"toolu_017x527ND7raym6734A3iup7","toolName":"bash","content":[{"type":"text","text":"(no output)\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1774821791184}}
{"type":"message","id":"862be2aa","parentId":"ff130b8b","timestamp":"2026-03-29T22:03:16.935Z","message":{"role":"assistant","content":[{"type":"text","text":"Key finding: `python-multipart` is NOT in requirements.txt. FastAPI needs it for `UploadFile`. Let me check what the sample transcript structure looks like — specifically the fields needed for ingestion:"},{"type":"toolCall","id":"toolu_01CjkGFhBv9jMcpHehN3AqLG","name":"bash","arguments":{"command":"python3 -c \"\nimport json\nwith open('tests/fixtures/sample_transcript.json') as f:\n    d = json.load(f)\nprint('Top-level keys:', list(d.keys()))\nprint('Segment keys:', list(d['segments'][0].keys()))\nprint('Word keys:', list(d['segments'][0]['words'][0].keys()))\nprint('Number of segments:', len(d['segments']))\nprint('source_file:', d['source_file'])\nprint('creator_folder:', d['creator_folder'])\nprint('duration_seconds:', d['duration_seconds'])\n\"\n"}},{"type":"toolCall","id":"toolu_01BSNwDHBdcgLqwVfY5v3fGC","name":"bash","arguments":{"command":"grep -n \"slug\" backend/models.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":285,"cacheRead":72312,"cacheWrite":409,"totalTokens":73007,"cost":{"input":0.000005,"output":0.007125,"cacheRead":0.036156,"cacheWrite":0.00255625,"total":0.04584225}},"stopReason":"toolUse","timestamp":1774821791184}}
{"type":"message","id":"2b1053f6","parentId":"862be2aa","timestamp":"2026-03-29T22:03:16.963Z","message":{"role":"toolResult","toolCallId":"toolu_01CjkGFhBv9jMcpHehN3AqLG","toolName":"bash","content":[{"type":"text","text":"Top-level keys: ['source_file', 'creator_folder', 'duration_seconds', 'segments']\nSegment keys: ['start', 'end', 'text', 'words']\nWord keys: ['word', 'start', 'end']\nNumber of segments: 5\nsource_file: Skope — Sound Design Masterclass pt1.mp4\ncreator_folder: Skope\nduration_seconds: 3847\n"}],"isError":false,"timestamp":1774821796962}}
{"type":"message","id":"55f08fa2","parentId":"2b1053f6","timestamp":"2026-03-29T22:03:16.965Z","message":{"role":"toolResult","toolCallId":"toolu_01BSNwDHBdcgLqwVfY5v3fGC","toolName":"bash","content":[{"type":"text","text":"109:    slug: Mapped[str] = mapped_column(String(255), unique=True, nullable=False)\n222:    slug: Mapped[str] = mapped_column(String(500), unique=True, nullable=False)\n"}],"isError":false,"timestamp":1774821796962}}
{"type":"message","id":"c5bf0f73","parentId":"55f08fa2","timestamp":"2026-03-29T22:03:21.808Z","message":{"role":"assistant","content":[{"type":"text","text":"Now I have everything I need. Let me verify the existing `SourceVideo.content_type` is an enum — important for ingestion since the transcript JSON doesn't include a content_type field, so the API will need to accept it or default it:"},{"type":"toolCall","id":"toolu_01HfrjsVG5CcdNhRkxQkV1HM","name":"bash","arguments":{"command":"grep -A2 \"class ContentType\" backend/models.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":121,"cacheRead":72721,"cacheWrite":506,"totalTokens":73349,"cost":{"input":0.000005,"output":0.0030250000000000003,"cacheRead":0.0363605,"cacheWrite":0.0031625,"total":0.042552999999999994}},"stopReason":"toolUse","timestamp":1774821796963}}
{"type":"message","id":"dd84b4a1","parentId":"c5bf0f73","timestamp":"2026-03-29T22:03:21.819Z","message":{"role":"toolResult","toolCallId":"toolu_01HfrjsVG5CcdNhRkxQkV1HM","toolName":"bash","content":[{"type":"text","text":"class ContentType(str, enum.Enum):\n    \"\"\"Source video content type.\"\"\"\n    tutorial = \"tutorial\"\n"}],"isError":false,"timestamp":1774821801818}}
{"type":"message","id":"2b81e9c6","parentId":"dd84b4a1","timestamp":"2026-03-29T22:03:25.031Z","message":{"role":"assistant","content":[{"type":"text","text":"Let me also quickly check for any existing test infrastructure:"},{"type":"toolCall","id":"toolu_01DoJ74ag1HtpWegNQp6pxAL","name":"bash","arguments":{"command":"find tests/ -type f 2>/dev/null; ls -la conftest.py pytest.ini pyproject.toml setup.cfg 2>/dev/null | head -20"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":104,"cacheRead":73227,"cacheWrite":160,"totalTokens":73492,"cost":{"input":0.000005,"output":0.0026000000000000003,"cacheRead":0.0366135,"cacheWrite":0.001,"total":0.040218500000000004}},"stopReason":"toolUse","timestamp":1774821801818}}
{"type":"message","id":"cc9e332e","parentId":"2b81e9c6","timestamp":"2026-03-29T22:03:25.042Z","message":{"role":"toolResult","toolCallId":"toolu_01DoJ74ag1HtpWegNQp6pxAL","toolName":"bash","content":[{"type":"text","text":"tests/fixtures/sample_transcript.json\n"}],"isError":false,"timestamp":1774821805041}}
{"type":"message","id":"368c2997","parentId":"cc9e332e","timestamp":"2026-03-29T22:03:28.756Z","message":{"role":"assistant","content":[{"type":"text","text":"No test infrastructure exists yet. Now let me check for skill discovery for FastAPI file upload patterns:"},{"type":"toolCall","id":"toolu_01PB6HcgKHVZzx2YaD8uxaxq","name":"bash","arguments":{"command":"npx skills find \"FastAPI\" 2>/dev/null | head -30"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":90,"cacheRead":73387,"cacheWrite":126,"totalTokens":73604,"cost":{"input":0.000005,"output":0.0022500000000000003,"cacheRead":0.0366935,"cacheWrite":0.0007875,"total":0.039735999999999994}},"stopReason":"toolUse","timestamp":1774821805041}}
{"type":"message","id":"8a45c8dc","parentId":"368c2997","timestamp":"2026-03-29T22:03:30.347Z","message":{"role":"toolResult","toolCallId":"toolu_01PB6HcgKHVZzx2YaD8uxaxq","toolName":"bash","content":[{"type":"text","text":"\n\u001b[38;5;250m███████╗██╗  ██╗██╗██╗     ██╗     ███████╗\u001b[0m\n\u001b[38;5;248m██╔════╝██║ ██╔╝██║██║     ██║     ██╔════╝\u001b[0m\n\u001b[38;5;245m███████╗█████╔╝ ██║██║     ██║     ███████╗\u001b[0m\n\u001b[38;5;243m╚════██║██╔═██╗ ██║██║     ██║     ╚════██║\u001b[0m\n\u001b[38;5;240m███████║██║  ██╗██║███████╗███████╗███████║\u001b[0m\n\u001b[38;5;238m╚══════╝╚═╝  ╚═╝╚═╝╚══════╝╚══════╝╚══════╝\u001b[0m\n\n\u001b[38;5;102mInstall with\u001b[0m npx skills add <owner/repo@skill>\n\n\u001b[38;5;145mwshobson/agents@fastapi-templates\u001b[0m \u001b[36m9.6K installs\u001b[0m\n\u001b[38;5;102m└ https://skills.sh/wshobson/agents/fastapi-templates\u001b[0m\n\n\u001b[38;5;145mmindrally/skills@fastapi-python\u001b[0m \u001b[36m4.3K installs\u001b[0m\n\u001b[38;5;102m└ https://skills.sh/mindrally/skills/fastapi-python\u001b[0m\n\n\u001b[38;5;145mjezweb/claude-skills@fastapi\u001b[0m \u001b[36m2K installs\u001b[0m\n\u001b[38;5;102m└ https://skills.sh/jezweb/claude-skills/fastapi\u001b[0m\n\n\u001b[38;5;145mjeffallan/claude-skills@fastapi-expert\u001b[0m \u001b[36m1.7K installs\u001b[0m\n\u001b[38;5;102m└ https://skills.sh/jeffallan/claude-skills/fastapi-expert\u001b[0m\n\n\u001b[38;5;145mfastapi/fastapi@fastapi\u001b[0m \u001b[36m870 installs\u001b[0m\n\u001b[38;5;102m└ https://skills.sh/fastapi/fastapi/fastapi\u001b[0m\n\n\u001b[38;5;145mthebushidocollective/han@fastapi-async-patterns\u001b[0m \u001b[36m538 installs\u001b[0m\n\u001b[38;5;102m└ https://skills.sh/thebushidocollective/han/fastapi-async-patterns\u001b[0m\n\n"}],"isError":false,"timestamp":1774821810345}}
{"type":"message","id":"43ac9831","parentId":"8a45c8dc","timestamp":"2026-03-29T22:04:28.907Z","message":{"role":"assistant","content":[{"type":"text","text":"I now have all the information needed. This is a **light research** slice — it's straightforward CRUD/ingestion using established patterns already in the codebase (S01's router pattern, models, schemas, async sessions). The only new element is file upload handling.\n\nLet me compile the research:"},{"type":"toolCall","id":"toolu_01FFjLAZUS2PzuuqYx8udb1n","name":"gsd_summary_save","arguments":{"artifact_type":"RESEARCH","content":"# S02 — Transcript Ingestion API — Research\n\n**Date:** 2026-03-29\n\n## Summary\n\nS02 adds a single FastAPI endpoint: `POST /api/v1/ingest` that accepts a Whisper transcript JSON file, creates/finds the Creator record (auto-detected from `creator_folder`), creates a SourceVideo record, stores TranscriptSegment rows, saves the JSON file to the filesystem, and sets `processing_status = \"transcribed\"`. This is straightforward CRUD using established patterns from S01 — async SQLAlchemy sessions, Pydantic v2 schemas, and the router-per-domain convention.\n\nThe main design decisions are: (1) accept the file as `UploadFile` (multipart) or as a JSON body — `UploadFile` is better since the transcript files will be multi-MB and the API should also save the raw JSON to disk; (2) auto-create Creator records from `creator_folder` with slugified names; (3) handle idempotency for re-uploads of the same video (upsert by filename+creator).\n\nR002 is the primary requirement. R012 (incremental content addition) is partially addressed — new creators are auto-detected and existing creator records are reused.\n\n## Recommendation\n\nBuild one new router (`backend/routers/ingest.py`) with a single `POST /api/v1/ingest` endpoint that accepts `UploadFile`. It parses the JSON, finds-or-creates a Creator (by `folder_name`), creates a SourceVideo, bulk-inserts TranscriptSegments, saves the raw file to `transcript_storage_path`, and returns the created SourceVideo with segment count. Use a single DB transaction for atomicity. Add `python-multipart` to requirements.txt for file upload support.\n\n## Implementation Landscape\n\n### Key Files\n\n- `backend/routers/ingest.py` — **New file.** The ingestion endpoint. Follows the pattern from `backend/routers/creators.py`: `APIRouter` with prefix, `Depends(get_session)`, structured logging. Core logic: parse JSON → find/create Creator → create SourceVideo → bulk insert TranscriptSegments → save file to disk → return response.\n- `backend/schemas.py` — **Modify.** Add `TranscriptIngestResponse` schema (returning created video ID, creator ID, segment count, processing status). Add `TranscriptSegmentWord` schema if we want to validate the word-level data (optional — the words array is in the JSON but not stored in the DB per current schema).\n- `backend/main.py` — **Modify.** Import and mount the `ingest` router under `/api/v1`.\n- `backend/requirements.txt` — **Modify.** Add `python-multipart>=0.0.9` (required by FastAPI for `UploadFile`).\n- `tests/test_ingest.py` — **New file.** Integration test using `httpx.AsyncClient` against the FastAPI app with a test PostgreSQL database. Uses `tests/fixtures/sample_transcript.json` as test input.\n\n### Existing Infrastructure (no changes needed)\n\n- `backend/models.py` — Creator, SourceVideo, TranscriptSegment models are already defined with correct columns and relationships. `Creator.folder_name` exists for matching. `SourceVideo.transcript_path` exists for storing the filesystem path. `TranscriptSegment.segment_index` exists for ordering.\n- `backend/database.py` — `get_session` async dependency already exists and works.\n- `backend/config.py` — `transcript_storage_path` setting already exists (defaults to `/data/transcripts`).\n- `tests/fixtures/sample_transcript.json` — Sample transcript with 5 segments in the exact Whisper output format: `{source_file, creator_folder, duration_seconds, segments: [{start, end, text, words: [{word, start, end}]}]}`.\n\n### Transcript JSON Shape (from Whisper script output)\n\n```\n{\n  \"source_file\": \"Skope — Sound Design Masterclass pt1.mp4\",\n  \"creator_folder\": \"Skope\",\n  \"duration_seconds\": 3847,\n  \"segments\": [\n    {\n      \"start\": 0.0,\n      \"end\": 4.52,\n      \"text\": \"Hey everyone welcome back...\",\n      \"words\": [{\"word\": \"Hey\", \"start\": 0.0, \"end\": 0.28}, ...]\n    }\n  ]\n}\n```\n\n### Creator Auto-Detection Logic\n\n1. Extract `creator_folder` from transcript JSON (e.g., `\"Skope\"`)\n2. `SELECT * FROM creators WHERE folder_name = :folder_name`\n3. If not found: create with `name = creator_folder`, `slug = slugify(creator_folder)`, `folder_name = creator_folder`\n4. If found: reuse existing creator ID\n\nSlug generation: lowercase, replace spaces/special chars with hyphens. Use a simple function — no need for `python-slugify` dependency; a 3-line regex approach suffices for folder names.\n\n### SourceVideo Content Type\n\nThe transcript JSON does NOT include a `content_type` field. The `SourceVideo.content_type` column is NOT NULL with enum values `tutorial|livestream|breakdown|short_form`. Options:\n- **Recommended:** Default to `\"tutorial\"` at ingestion; allow optional override via query param or form field. The LLM pipeline (S03) can reclassify later.\n- Alternative: Make the column nullable (requires migration). Not worth it — defaulting is simpler.\n\n### Idempotency\n\nTo support re-uploading the same transcript (R012 incremental):\n- Check for existing `SourceVideo` by `(creator_id, filename)` before creating\n- If exists: delete old TranscriptSegments, update the SourceVideo record, re-insert segments\n- This makes the endpoint idempotent — uploading the same file twice produces the same result\n\n### Build Order\n\n1. **Add `python-multipart` to requirements.txt** — unblocks UploadFile usage\n2. **Add response schema to `schemas.py`** — small change, defines the API contract\n3. **Create `backend/routers/ingest.py`** — the main work: endpoint, creator auto-detection, segment insertion, file storage\n4. **Mount router in `main.py`** — one import + one `include_router` line\n5. **Write integration test** — verify with sample_transcript.json against real DB\n\nSteps 1-2 are independent. Step 3 is the bulk of work. Steps 4-5 depend on 3.\n\n### Verification Approach\n\n1. **Unit verification:** `python3 -c \"from routers import ingest; print(ingest.router.routes)\"` — confirms router imports and routes are registered.\n2. **Integration test:** Start a test PostgreSQL container, run the FastAPI app with `httpx.AsyncClient`, POST the sample transcript, assert:\n   - Response 200 with `video_id`, `creator_id`, `segments_stored` count\n   - Creator record exists in DB with `folder_name = \"Skope\"` and `slug = \"skope\"`\n   - SourceVideo record exists with `filename = \"Skope — Sound Design Masterclass pt1.mp4\"`, `processing_status = \"transcribed\"`\n   - 5 TranscriptSegment rows exist with correct `segment_index` ordering\n   - JSON file saved to configured `transcript_storage_path`\n3. **Idempotency test:** POST the same file twice → no duplicate records, same video ID returned\n4. **Docker compose config still validates:** `docker compose config` exits 0\n\n## Constraints\n\n- `python-multipart` must be added to `backend/requirements.txt` — FastAPI raises `RuntimeError` without it when using `UploadFile`.\n- `SourceVideo.content_type` is NOT NULL with an enum constraint — ingestion must provide a valid value. Default to `\"tutorial\"`.\n- Filesystem write to `transcript_storage_path` — in Docker this maps to `/vmPool/r/services/chrysopedia_data/transcripts`. For local testing, use a temp directory or `./data/transcripts`.\n- Creator `slug` must be unique — the slugify function must produce deterministic, URL-safe slugs from folder names.\n\n## Common Pitfalls\n\n- **Missing `python-multipart`** — FastAPI silently accepts `UploadFile` in type hints but raises at runtime. Must be in requirements.txt.\n- **Async file I/O** — `UploadFile.read()` is async but filesystem writes with `open()` are blocking. For transcript JSONs (typically <10MB), blocking writes in async handlers are acceptable. If concerned, use `aiofiles` but it's not necessary at this scale.\n- **Transaction scope** — Creator creation + SourceVideo creation + segment bulk insert should be in ONE transaction. If segment insertion fails, don't leave orphaned Creator/Video records. Use `session.begin()` or rely on the session's default transaction + `await session.commit()` at the end.\n\n## Skills Discovered\n\n| Technology | Skill | Status |\n|------------|-------|--------|\n| FastAPI | wshobson/agents@fastapi-templates | available (9.6K installs) — general FastAPI patterns |\n| FastAPI | mindrally/skills@fastapi-python | available (4.3K installs) — Python FastAPI patterns |\n","milestone_id":"M001","slice_id":"S02"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":2430,"cacheRead":73513,"cacheWrite":754,"totalTokens":76698,"cost":{"input":0.000005,"output":0.060750000000000005,"cacheRead":0.0367565,"cacheWrite":0.0047125000000000005,"total":0.102224}},"stopReason":"toolUse","timestamp":1774821810346}}
{"type":"message","id":"b056613f","parentId":"43ac9831","timestamp":"2026-03-29T22:04:28.910Z","message":{"role":"toolResult","toolCallId":"toolu_01FFjLAZUS2PzuuqYx8udb1n","toolName":"gsd_summary_save","content":[{"type":"text","text":"Saved RESEARCH artifact to milestones/M001/slices/S02/S02-RESEARCH.md"}],"details":{"operation":"save_summary","path":"milestones/M001/slices/S02/S02-RESEARCH.md","artifact_type":"RESEARCH"},"isError":false,"timestamp":1774821868909}}
{"type":"message","id":"1ce41f54","parentId":"b056613f","timestamp":"2026-03-29T22:04:36.737Z","message":{"role":"assistant","content":[{"type":"text","text":"Slice S02 researched.\n\n**Key findings summary:**\n- This is **straightforward CRUD** using patterns already established in S01 (router, schemas, async sessions)\n- One new router file (`ingest.py`), minor additions to `schemas.py` and `main.py`\n- **`python-multipart`** must be added to requirements — FastAPI needs it for `UploadFile`\n- Creator auto-detection from `creator_folder` field with simple slug generation\n- `SourceVideo.content_type` defaults to `\"tutorial\"` since transcript JSON doesn't include it\n- Idempotency via `(creator_id, filename)` uniqueness check\n- Transcript JSON shape is well-defined: `{source_file, creator_folder, duration_seconds, segments[{start, end, text, words}]}`\n- Words array is in the JSON but NOT stored in the DB (TranscriptSegment only has `text`, `start_time`, `end_time`)\n- No new technology or risky integration — all known patterns"}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":245,"cacheRead":74267,"cacheWrite":2468,"totalTokens":76981,"cost":{"input":0.000005,"output":0.006125,"cacheRead":0.0371335,"cacheWrite":0.015425000000000001,"total":0.0586885}},"stopReason":"stop","timestamp":1774821868909}}
