{"type":"thinking_level_change","id":"2ff63cf5","parentId":null,"timestamp":"2026-03-29T22:04:37.060Z","thinkingLevel":"off"}
{"type":"model_change","id":"43902cf8","parentId":"2ff63cf5","timestamp":"2026-03-29T22:04:37.061Z","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## Executor Context Constraints\n\nThe agent that executes each task has a **200K token** context window.\n- Recommended task count for this slice: **2–6 tasks**\n- Each task gets ~320K chars of inline context (plans, code, decisions)\n- Keep individual tasks completable within a single context window — if a task needs more context than fits, split it\n\nThen:\n0. If `REQUIREMENTS.md` was preloaded above, identify which Active requirements the roadmap says this slice owns or supports. These are the requirements this plan must deliver — every owned requirement needs at least one task that directly advances it, and verification must prove the requirement is met.\n1. Read the templates:\n   - `~/.gsd/agent/extensions/gsd/templates/plan.md`\n   - `~/.gsd/agent/extensions/gsd/templates/task-plan.md`\n2.  Record the installed skills you expect executors to use in each task plan's `skills_used` frontmatter.\n3. Define slice-level verification — the objective stopping condition for this slice:\n   - For non-trivial slices: plan actual test files with real assertions. Name the files.\n   - For simple slices: executable commands or script assertions are fine.\n   - If the project is non-trivial and has no test framework, the first task should set one up.\n   - If this slice establishes a boundary contract, verification must exercise that contract.\n4. **For non-trivial slices only** — plan observability, proof level, and integration closure:\n   - Include `Observability / Diagnostics` for backend, integration, async, stateful, or UI slices where failure diagnosis matters.\n   - Fill `Proof Level` and `Integration Closure` when the slice crosses runtime boundaries or has meaningful integration concerns.\n   - **Omit these sections entirely for simple slices** where they would all be \"none\" or trivially obvious.\n5. **Quality gates** — for non-trivial slices, fill the Threat Surface (Q3) and Requirement Impact (Q4) sections in the slice plan:\n   - **Threat Surface:** Identify abuse scenarios, data exposure risks, and input trust boundaries. Required when the slice handles user input, authentication, authorization, or sensitive data. Omit entirely for internal refactoring or simple changes.\n   - **Requirement Impact:** List which existing requirements this slice touches, what must be re-verified after shipping, and which prior decisions should be reconsidered. Omit entirely if no existing requirements are affected.\n   - For each task in a non-trivial slice, fill Failure Modes (Q5), Load Profile (Q6), and Negative Tests (Q7) in the task plan when the task has external dependencies, shared resources, or non-trivial input handling. Omit for simple tasks.\n6. Decompose the slice into tasks, each fitting one context window. Each task needs:\n   - a concrete, action-oriented title\n   - the inline task entry fields defined in the plan.md template (Why / Files / Do / Verify / Done when)\n   - a matching task plan file with description, steps, must-haves, verification, inputs, and expected output\n   - **Inputs and Expected Output must list concrete backtick-wrapped file paths** (e.g. `` `src/types.ts` ``). These are machine-parsed to derive task dependencies — vague prose without paths breaks parallel execution. Every task must have at least one output file path.\n   - Observability Impact section **only if the task touches runtime boundaries, async flows, or error paths** — omit it otherwise\n7. **Persist planning state through `gsd_plan_slice`.** Call it with the full slice planning payload (goal, demo, must-haves, verification, tasks, and metadata). The tool inserts all tasks in the same transaction, writes to the DB, and renders `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M001/slices/S02/S02-PLAN.md` and `.gsd/milestones/M001/slices/S02/tasks/T##-PLAN.md` files automatically. Do **not** call `gsd_plan_task` separately — `gsd_plan_slice` handles task persistence. Do **not** rely on direct `PLAN.md` writes as the source of truth; the DB-backed tool is the canonical write path for slice and task planning state.\n8. **Self-audit the plan.** Walk through each check — if any fail, fix the plan files before moving on:\n    - **Completion semantics:** If every task were completed exactly as written, the slice goal/demo should actually be true.\n    - **Requirement coverage:** Every must-have in the slice maps to at least one task. No must-have is orphaned. If `REQUIREMENTS.md` exists, every Active requirement this slice owns maps to at least one task.\n    - **Task completeness:** Every task has steps, must-haves, verification, inputs, and expected output — none are blank or vague. Inputs and Expected Output list backtick-wrapped file paths, not prose descriptions.\n    - **Dependency correctness:** Task ordering is consistent. No task references work from a later task.\n    - **Key links planned:** For every pair of artifacts that must connect, there is an explicit step that wires them.\n    - **Scope sanity:** Target 2–5 steps and 3–8 files per task. 10+ steps or 12+ files — must split. Each task must be completable in a single fresh context window.\n    - **Feature completeness:** Every task produces real, user-facing progress — not just internal scaffolding.\n    - **Quality gate coverage:** For non-trivial slices, Threat Surface and Requirement Impact sections are present and specific (not placeholder text). For non-trivial tasks, Failure Modes, Load Profile, and Negative Tests are addressed in the task plan.\n10. If planning produced structural decisions, append them to `.gsd/DECISIONS.md`\n11. Do not commit — .gsd/ planning docs are managed externally and not tracked in git.\n\nThe slice directory and tasks/ subdirectory already exist. Do NOT mkdir. All work stays in your working directory: `/home/aux/projects/content-to-kb-automator`.\n\n**You MUST call `gsd_plan_slice` to persist the planning state before finishing.**\n\nWhen done, say: \"Slice S02 planned.\"\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: Plan 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### Slice Research\nSource: `.gsd/milestones/M001/slices/S02/S02-RESEARCH.md`\n\n# 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\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# {{sliceId}}: {{sliceTitle}}\n\n**Goal:** {{goal}}\n**Demo:** {{demo}}\n\n## Must-Haves\n\n- {{mustHave}}\n- {{mustHave}}\n\n## Threat Surface\n\n<!-- Q3: How can this be exploited? OMIT ENTIRELY for simple slices with no auth, user input, or data exposure. -->\n\n- **Abuse**: {{abuseScenarios — parameter tampering, replay, privilege escalation, or N/A}}\n- **Data exposure**: {{sensitiveDataAccessible — PII, tokens, secrets, or none}}\n- **Input trust**: {{untrustedInput — user input reaching DB/API/filesystem, or none}}\n\n## Requirement Impact\n\n<!-- Q4: What existing promises does this break? OMIT ENTIRELY if no existing requirements are affected. -->\n\n- **Requirements touched**: {{requirementIds — e.g. R001, R003, or none}}\n- **Re-verify**: {{whatMustBeRetested — e.g. login flow, API contract, or N/A}}\n- **Decisions revisited**: {{decisionIds — e.g. D002, or none}}\n\n## Proof Level\n\n<!-- Omit this section entirely for simple slices where the answer is trivially obvious. -->\n\n- This slice proves: {{contract | integration | operational | final-assembly}}\n- Real runtime required: {{yes/no}}\n- Human/UAT required: {{yes/no}}\n\n## Verification\n\n<!-- Define what \"done\" looks like BEFORE detailing tasks.\n     This section is the slice's objective stopping condition — execution isn't done\n     until everything here passes.\n\n     For non-trivial projects:\n     - Write actual test files into the codebase during the first task\n     - Tests should assert on the slice's demo outcome and boundary contracts\n     - Name the test files here so execution has an unambiguous target\n\n     For simple projects or scripts:\n     - Executable verification commands (bash assertions, curl checks, etc.) are sufficient\n\n     If the project has no test framework and the work is non-trivial,\n     the first task should set one up. A test runner costs 2 minutes\n     and pays for itself immediately.\n\n     For non-trivial backend, integration, async, stateful, or UI work:\n     - Include at least one verification check for an observability or failure-path signal\n     - Verify not just that the feature works, but that a future agent can inspect its state when it fails -->\n\n- {{testFileOrCommand — e.g. `npm test -- --grep \"auth flow\"` or `bash scripts/verify-s01.sh`}}\n- {{testFileOrCommand}}\n\n## Observability / Diagnostics\n\n<!-- Include this section for non-trivial backend, integration, async, stateful, or UI slices.\n     OMIT ENTIRELY for simple slices where all fields would be \"none\".\n\n     When included, describe how a future agent will inspect current state, detect failure,\n     and localize the problem with minimal ambiguity. Keep it concise and high-signal. -->\n\n- Runtime signals: {{structured log/event, state transition, metric, or none}}\n- Inspection surfaces: {{status endpoint, CLI command, script, UI state, DB table, or none}}\n- Failure visibility: {{last error, retry count, phase, timestamp, correlation id, or none}}\n- Redaction constraints: {{secret/PII boundary or none}}\n\n## Integration Closure\n\n<!-- Omit this section entirely for simple slices with no meaningful integration concerns. -->\n\n- Upstream surfaces consumed: {{specific files / modules / contracts}}\n- New wiring introduced in this slice: {{entrypoint / composition / runtime hookup, or none}}\n- What remains before the milestone is truly usable end-to-end: {{list or \"nothing\"}}\n\n## Tasks\n\n<!--\n  If every task below is completed exactly as written, the Goal and Demo above\n  should be true at the stated proof level. Tasks should close the loop on the\n  slice, not merely prepare for later work unless the Demo truthfully says the\n  slice only proves fixture/contract-level behavior.\n\n  Write each task as an executable increment, not a vague intention.\n\n  Prefer action-oriented titles:\n  - \"Wire real auth middleware into dashboard routes\"\n  - \"Persist job status and expose failure diagnostics\"\n  - \"Add browser test covering empty-state recovery\"\n\n  Avoid vague titles:\n  - \"Set up auth\"\n  - \"Handle errors\"\n  - \"Improve UI\"\n\n  Each task should usually include:\n  - Why: why this task exists / what part of the slice it closes\n  - Files: the main files likely touched\n  - Do: concrete implementation steps and important constraints\n  - Verify: the command, test, or runtime check that proves it worked\n  - Done when: a measurable acceptance condition\n\n  Keep the checkbox line format exactly:\n  - [ ] **T01: Title** `est:30m`\n-->\n\n- [ ] **T01: {{taskTitle}}** `est:{{estimate}}`\n  - Why: {{whyThisTaskExists}}\n  - Files: `{{filePath}}`, `{{filePath}}`\n  - Do: {{specificImplementationStepsAndConstraints}}\n  - Verify: {{testCommandOrRuntimeCheck}}\n  - Done when: {{measurableAcceptanceCondition}}\n- [ ] **T02: {{taskTitle}}** `est:{{estimate}}`\n  - Why: {{whyThisTaskExists}}\n  - Files: `{{filePath}}`, `{{filePath}}`\n  - Do: {{specificImplementationStepsAndConstraints}}\n  - Verify: {{testCommandOrRuntimeCheck}}\n  - Done when: {{measurableAcceptanceCondition}}\n<!--\n  Format rules (parsers depend on this exact structure):\n  - Checkbox line: - [ ] **T01: Title** `est:30m`\n  - Description:   indented text on the next line(s)\n  - Mark done:     change [ ] to [x]\n  - Tasks execute sequentially in order (T01, T02, T03, ...)\n  - est: is informational (e.g. 30m, 1h, 2h) and optional\n\n  Verify field rules:\n  - MUST be a mechanically executable command: `npm test`, `grep -q \"pattern\" file`, `test -f path`\n  - For content/document tasks: verify file existence, section count, YAML validity, or word count\n    NOT exact phrasing, specific formulas, or \"zero TBD\" aspirational criteria\n  - If no command can verify the output, write: \"Manual review — file exists and is non-empty\"\n  - BAD: \"Sections 3.1 and 3.2 exist with exact formulas. Zero TBD/TODO.\"\n  - GOOD: `grep -c \"^## \" doc.md` returns >= 4 (4+ sections), `! grep -q \"TBD\\|TODO\" doc.md`\n\n  Integration closure rule:\n  - At least one slice in any multi-boundary milestone should perform real composition/wiring, not just contract hardening\n  - For the final assembly slice, verification must exercise the real entrypoint or runtime path\n-->\n\n## Files Likely Touched\n\n- `{{filePath}}`\n- `{{filePath}}`\n\n### Output Template: Slice Plan\nSource: `templates/plan.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 this slice should 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 have full tool access. Before decomposing, explore the relevant code to ground your plan in reality.\n\n### Verify Roadmap Assumptions\n\nCheck prior slice summaries (inlined above as dependency summaries, if present). If prior slices discovered constraints, changed approaches, or flagged fragility, adjust your plan accordingly. The roadmap description may be stale — verify it against the current codebase state.\n\n### Explore Slice Scope\n\nRead the code files relevant to this slice. Confirm the roadmap's description of what exists, what needs to change, and what boundaries apply. Use `rg`, `find`, and targeted reads.\n\n### Source Files\n\n- **Requirements**: `.gsd/REQUIREMENTS.md`\n- **Decisions**: `.gsd/DECISIONS.md`\n- **Roadmap**: `.gsd/milestones/M001/M001-ROADMAP.md`\n- **Slice Research**: `.gsd/milestones/M001/slices/S02/S02-RESEARCH.md`\n\nIf slice research exists (inlined above), trust those findings and skip redundant exploration.\n\nAfter you finish, **executor agents** implement each task in isolated fresh context windows. They see only their task plan, the slice plan excerpt (goal/demo/verification), and compressed summaries of prior tasks. They do not see the research doc, the roadmap, or REQUIREMENTS.md. Everything an executor needs must be in the task plan itself — file paths, specific steps, expected inputs and outputs.\n\nNarrate your decomposition reasoning — why you're grouping work this way, what risks are driving the order, what verification strategy you're choosing and why. Keep the narration proportional to the work — a simple slice doesn't need a long justification — but write in complete sentences, not planner shorthand.\n\n**Right-size the plan.** If the slice is simple enough to be 1 task, plan 1 task. Don't split into multiple tasks just because you can identify sub-steps. Don't fill in sections with \"None\" when the section doesn't apply — omit them entirely. The plan's job is to guide execution, not to fill a template.\n","display":false,"id":"ff202a87","parentId":"43902cf8","timestamp":"2026-03-29T22:04:37.062Z"}
{"type":"message","id":"b32f09fc","parentId":"ff202a87","timestamp":"2026-03-29T22:04:43.231Z","message":{"role":"assistant","content":[{"type":"text","text":"\n\nI'll start by exploring the current codebase to ground the plan in reality, then read the templates."},{"type":"toolCall","id":"toolu_01QP2UQ2dGbUmxMwUmQjwZKV","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && find backend -type f -name \"*.py\" | head -30 && echo \"---\" && cat backend/requirements.txt"}},{"type":"toolCall","id":"toolu_018sXnxfBV6yCJfvK2ipmcMU","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && cat backend/schemas.py"}},{"type":"toolCall","id":"toolu_01VhUG8M6Lw2ZJjh6gjT32Js","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && cat backend/main.py"}},{"type":"toolCall","id":"toolu_012sDfpW9XwVPL6kniFip1eG","name":"read","arguments":{"path":"~/.gsd/agent/extensions/gsd/templates/plan.md"}},{"type":"toolCall","id":"toolu_01JZeapvMfhvZDnCzk3xwshx","name":"read","arguments":{"path":"~/.gsd/agent/extensions/gsd/templates/task-plan.md"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":2,"output":336,"cacheRead":49033,"cacheWrite":12155,"totalTokens":61526,"cost":{"input":0.00001,"output":0.008400000000000001,"cacheRead":0.0245165,"cacheWrite":0.07596875,"total":0.10889525}},"stopReason":"toolUse","timestamp":1774821877061}}
{"type":"message","id":"26a5f6a0","parentId":"b32f09fc","timestamp":"2026-03-29T22:04:43.249Z","message":{"role":"toolResult","toolCallId":"toolu_01QP2UQ2dGbUmxMwUmQjwZKV","toolName":"bash","content":[{"type":"text","text":"backend/models.py\nbackend/main.py\nbackend/routers/health.py\nbackend/routers/videos.py\nbackend/routers/__init__.py\nbackend/routers/creators.py\nbackend/database.py\nbackend/config.py\nbackend/schemas.py\n---\nfastapi>=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":1774821883249}}
{"type":"message","id":"0d6d5af6","parentId":"26a5f6a0","timestamp":"2026-03-29T22:04:43.250Z","message":{"role":"toolResult","toolCallId":"toolu_018sXnxfBV6yCJfvK2ipmcMU","toolName":"bash","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":1774821883249}}
{"type":"message","id":"349d09eb","parentId":"0d6d5af6","timestamp":"2026-03-29T22:04:43.253Z","message":{"role":"toolResult","toolCallId":"toolu_01VhUG8M6Lw2ZJjh6gjT32Js","toolName":"bash","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":1774821883253}}
{"type":"message","id":"8f099d0e","parentId":"349d09eb","timestamp":"2026-03-29T22:04:43.255Z","message":{"role":"toolResult","toolCallId":"toolu_012sDfpW9XwVPL6kniFip1eG","toolName":"read","content":[{"type":"text","text":"# {{sliceId}}: {{sliceTitle}}\n\n**Goal:** {{goal}}\n**Demo:** {{demo}}\n\n## Must-Haves\n\n- {{mustHave}}\n- {{mustHave}}\n\n## Threat Surface\n\n<!-- Q3: How can this be exploited? OMIT ENTIRELY for simple slices with no auth, user input, or data exposure. -->\n\n- **Abuse**: {{abuseScenarios — parameter tampering, replay, privilege escalation, or N/A}}\n- **Data exposure**: {{sensitiveDataAccessible — PII, tokens, secrets, or none}}\n- **Input trust**: {{untrustedInput — user input reaching DB/API/filesystem, or none}}\n\n## Requirement Impact\n\n<!-- Q4: What existing promises does this break? OMIT ENTIRELY if no existing requirements are affected. -->\n\n- **Requirements touched**: {{requirementIds — e.g. R001, R003, or none}}\n- **Re-verify**: {{whatMustBeRetested — e.g. login flow, API contract, or N/A}}\n- **Decisions revisited**: {{decisionIds — e.g. D002, or none}}\n\n## Proof Level\n\n<!-- Omit this section entirely for simple slices where the answer is trivially obvious. -->\n\n- This slice proves: {{contract | integration | operational | final-assembly}}\n- Real runtime required: {{yes/no}}\n- Human/UAT required: {{yes/no}}\n\n## Verification\n\n<!-- Define what \"done\" looks like BEFORE detailing tasks.\n     This section is the slice's objective stopping condition — execution isn't done\n     until everything here passes.\n\n     For non-trivial projects:\n     - Write actual test files into the codebase during the first task\n     - Tests should assert on the slice's demo outcome and boundary contracts\n     - Name the test files here so execution has an unambiguous target\n\n     For simple projects or scripts:\n     - Executable verification commands (bash assertions, curl checks, etc.) are sufficient\n\n     If the project has no test framework and the work is non-trivial,\n     the first task should set one up. A test runner costs 2 minutes\n     and pays for itself immediately.\n\n     For non-trivial backend, integration, async, stateful, or UI work:\n     - Include at least one verification check for an observability or failure-path signal\n     - Verify not just that the feature works, but that a future agent can inspect its state when it fails -->\n\n- {{testFileOrCommand — e.g. `npm test -- --grep \"auth flow\"` or `bash scripts/verify-s01.sh`}}\n- {{testFileOrCommand}}\n\n## Observability / Diagnostics\n\n<!-- Include this section for non-trivial backend, integration, async, stateful, or UI slices.\n     OMIT ENTIRELY for simple slices where all fields would be \"none\".\n\n     When included, describe how a future agent will inspect current state, detect failure,\n     and localize the problem with minimal ambiguity. Keep it concise and high-signal. -->\n\n- Runtime signals: {{structured log/event, state transition, metric, or none}}\n- Inspection surfaces: {{status endpoint, CLI command, script, UI state, DB table, or none}}\n- Failure visibility: {{last error, retry count, phase, timestamp, correlation id, or none}}\n- Redaction constraints: {{secret/PII boundary or none}}\n\n## Integration Closure\n\n<!-- Omit this section entirely for simple slices with no meaningful integration concerns. -->\n\n- Upstream surfaces consumed: {{specific files / modules / contracts}}\n- New wiring introduced in this slice: {{entrypoint / composition / runtime hookup, or none}}\n- What remains before the milestone is truly usable end-to-end: {{list or \"nothing\"}}\n\n## Tasks\n\n<!--\n  If every task below is completed exactly as written, the Goal and Demo above\n  should be true at the stated proof level. Tasks should close the loop on the\n  slice, not merely prepare for later work unless the Demo truthfully says the\n  slice only proves fixture/contract-level behavior.\n\n  Write each task as an executable increment, not a vague intention.\n\n  Prefer action-oriented titles:\n  - \"Wire real auth middleware into dashboard routes\"\n  - \"Persist job status and expose failure diagnostics\"\n  - \"Add browser test covering empty-state recovery\"\n\n  Avoid vague titles:\n  - \"Set up auth\"\n  - \"Handle errors\"\n  - \"Improve UI\"\n\n  Each task should usually include:\n  - Why: why this task exists / what part of the slice it closes\n  - Files: the main files likely touched\n  - Do: concrete implementation steps and important constraints\n  - Verify: the command, test, or runtime check that proves it worked\n  - Done when: a measurable acceptance condition\n\n  Keep the checkbox line format exactly:\n  - [ ] **T01: Title** `est:30m`\n-->\n\n- [ ] **T01: {{taskTitle}}** `est:{{estimate}}`\n  - Why: {{whyThisTaskExists}}\n  - Files: `{{filePath}}`, `{{filePath}}`\n  - Do: {{specificImplementationStepsAndConstraints}}\n  - Verify: {{testCommandOrRuntimeCheck}}\n  - Done when: {{measurableAcceptanceCondition}}\n- [ ] **T02: {{taskTitle}}** `est:{{estimate}}`\n  - Why: {{whyThisTaskExists}}\n  - Files: `{{filePath}}`, `{{filePath}}`\n  - Do: {{specificImplementationStepsAndConstraints}}\n  - Verify: {{testCommandOrRuntimeCheck}}\n  - Done when: {{measurableAcceptanceCondition}}\n<!--\n  Format rules (parsers depend on this exact structure):\n  - Checkbox line: - [ ] **T01: Title** `est:30m`\n  - Description:   indented text on the next line(s)\n  - Mark done:     change [ ] to [x]\n  - Tasks execute sequentially in order (T01, T02, T03, ...)\n  - est: is informational (e.g. 30m, 1h, 2h) and optional\n\n  Verify field rules:\n  - MUST be a mechanically executable command: `npm test`, `grep -q \"pattern\" file`, `test -f path`\n  - For content/document tasks: verify file existence, section count, YAML validity, or word count\n    NOT exact phrasing, specific formulas, or \"zero TBD\" aspirational criteria\n  - If no command can verify the output, write: \"Manual review — file exists and is non-empty\"\n  - BAD: \"Sections 3.1 and 3.2 exist with exact formulas. Zero TBD/TODO.\"\n  - GOOD: `grep -c \"^## \" doc.md` returns >= 4 (4+ sections), `! grep -q \"TBD\\|TODO\" doc.md`\n\n  Integration closure rule:\n  - At least one slice in any multi-boundary milestone should perform real composition/wiring, not just contract hardening\n  - For the final assembly slice, verification must exercise the real entrypoint or runtime path\n-->\n\n## Files Likely Touched\n\n- `{{filePath}}`\n- `{{filePath}}`\n"}],"isError":false,"timestamp":1774821883254}}
{"type":"message","id":"14099b90","parentId":"8f099d0e","timestamp":"2026-03-29T22:04:43.257Z","message":{"role":"toolResult","toolCallId":"toolu_01JZeapvMfhvZDnCzk3xwshx","toolName":"read","content":[{"type":"text","text":"---\n# Optional scope estimate — helps the plan quality validator detect over-scoped tasks.\n# Tasks with 10+ estimated steps or 12+ estimated files trigger a warning to consider splitting.\nestimated_steps: {{estimatedSteps}}\nestimated_files: {{estimatedFiles}}\n# Installed skills the planner expects the executor to load before coding.\nskills_used:\n  - {{skillName}}\n---\n\n# {{taskId}}: {{taskTitle}}\n\n**Slice:** {{sliceId}} — {{sliceTitle}}\n**Milestone:** {{milestoneId}}\n\n## Description\n\n{{description}}\n\n## Failure Modes\n\n<!-- Q5: What breaks when dependencies fail? OMIT ENTIRELY for tasks with no external dependencies. -->\n\n| Dependency | On error | On timeout | On malformed response |\n|------------|----------|-----------|----------------------|\n| {{dependency}} | {{errorStrategy}} | {{timeoutStrategy}} | {{malformedStrategy}} |\n\n## Load Profile\n\n<!-- Q6: What breaks at 10x load? OMIT ENTIRELY for tasks with no shared resources or scaling concerns. -->\n\n- **Shared resources**: {{sharedResources — DB connections, caches, rate limiters, or none}}\n- **Per-operation cost**: {{perOpCost — N API calls, M DB queries, K bytes, or trivial}}\n- **10x breakpoint**: {{whatBreaksFirst — pool exhaustion, rate limit, memory, or N/A}}\n\n## Negative Tests\n\n<!-- Q7: What negative tests prove robustness? OMIT ENTIRELY for trivial tasks. -->\n\n- **Malformed inputs**: {{malformedInputTests — empty string, null, oversized, wrong type}}\n- **Error paths**: {{errorPathTests — network timeout, auth failure, 5xx, invalid JSON}}\n- **Boundary conditions**: {{boundaryTests — empty list, max length, zero, off-by-one}}\n\n## Steps\n\n1. {{step}}\n2. {{step}}\n3. {{step}}\n\n## Must-Haves\n\n- [ ] {{mustHave}}\n- [ ] {{mustHave}}\n\n## Verification\n\n- {{howToVerifyThisTaskIsActuallyDone}}\n- {{commandToRun_OR_behaviorToCheck}}\n\n## Observability Impact\n\n<!-- OMIT THIS SECTION ENTIRELY for simple tasks that don't touch runtime boundaries,\n     async flows, APIs, background processes, or error paths.\n     Include it only when the task meaningfully changes how failures are detected or diagnosed. -->\n\n- Signals added/changed: {{structured logs, statuses, errors, metrics}}\n- How a future agent inspects this: {{command, endpoint, file, UI state}}\n- Failure state exposed: {{what becomes visible on failure}}\n\n## Inputs\n\n<!-- Every input MUST be a backtick-wrapped file path. These paths are machine-parsed to\n     derive task dependencies — vague descriptions without paths break dependency detection.\n     For the first task in a slice with no prior task outputs, list the existing source files\n     this task reads or modifies. -->\n\n- `{{filePath}}` — {{whatThisTaskNeedsFromPriorWork}}\n\n## Expected Output\n\n<!-- Every output MUST be a backtick-wrapped file path — the specific files this task creates\n     or modifies. These paths are machine-parsed to derive task dependencies.\n     This task should produce a real increment toward making the slice goal/demo true. A full\n     slice plan should not be able to mark every task complete while the claimed slice behavior\n     still does not work at the stated proof level. -->\n\n- `{{filePath}}` — {{whatThisTaskCreatesOrModifies}}\n"}],"isError":false,"timestamp":1774821883254}}
{"type":"message","id":"39066a53","parentId":"14099b90","timestamp":"2026-03-29T22:04:49.037Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me check the existing models and config to confirm the exact column definitions and the test fixture:"},{"type":"toolCall","id":"toolu_01Df63ViEVBmVX8f8tf6eHUn","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && cat backend/models.py"}},{"type":"toolCall","id":"toolu_011KGAc39nfgRrMChzxxHc2R","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && cat backend/config.py"}},{"type":"toolCall","id":"toolu_01CLrx6nARotj2qutjSddfA9","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && cat tests/fixtures/sample_transcript.json"}},{"type":"toolCall","id":"toolu_01MTyCPENMFZrRwAWaiLkhS1","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && cat backend/database.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":270,"cacheRead":61188,"cacheWrite":5372,"totalTokens":66831,"cost":{"input":0.000005,"output":0.00675,"cacheRead":0.030594,"cacheWrite":0.033575,"total":0.070924}},"stopReason":"toolUse","timestamp":1774821883255}}
{"type":"message","id":"7c70efbb","parentId":"39066a53","timestamp":"2026-03-29T22:04:49.059Z","message":{"role":"toolResult","toolCallId":"toolu_01Df63ViEVBmVX8f8tf6eHUn","toolName":"bash","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":1774821889059}}
{"type":"message","id":"a2d2fb35","parentId":"7c70efbb","timestamp":"2026-03-29T22:04:49.060Z","message":{"role":"toolResult","toolCallId":"toolu_011KGAc39nfgRrMChzxxHc2R","toolName":"bash","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":1774821889059}}
{"type":"message","id":"8f4b02d8","parentId":"a2d2fb35","timestamp":"2026-03-29T22:04:49.061Z","message":{"role":"toolResult","toolCallId":"toolu_01CLrx6nARotj2qutjSddfA9","toolName":"bash","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":1774821889060}}
{"type":"message","id":"d8cf6de3","parentId":"8f4b02d8","timestamp":"2026-03-29T22:04:49.065Z","message":{"role":"toolResult","toolCallId":"toolu_01MTyCPENMFZrRwAWaiLkhS1","toolName":"bash","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":1774821889064}}
{"type":"message","id":"c8046498","parentId":"d8cf6de3","timestamp":"2026-03-29T22:04:53.123Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me check the existing routers for patterns and the `__init__.py`:"},{"type":"toolCall","id":"toolu_01LDs2DRLGBPPdRjoMj68AWY","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && cat backend/routers/__init__.py && echo \"=== creators ===\" && cat backend/routers/creators.py"}},{"type":"toolCall","id":"toolu_01UPmS3jJ8yEEP1Gc9A22wH4","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && ls -la tests/ && echo \"---\" && ls -la tests/fixtures/"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":183,"cacheRead":66560,"cacheWrite":7418,"totalTokens":74162,"cost":{"input":0.000005,"output":0.004575,"cacheRead":0.03328,"cacheWrite":0.0463625,"total":0.0842225}},"stopReason":"toolUse","timestamp":1774821889064}}
{"type":"message","id":"a0cd8b1e","parentId":"c8046498","timestamp":"2026-03-29T22:04:53.134Z","message":{"role":"toolResult","toolCallId":"toolu_01LDs2DRLGBPPdRjoMj68AWY","toolName":"bash","content":[{"type":"text","text":"\"\"\"Chrysopedia API routers package.\"\"\"\n=== creators ===\n\"\"\"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":1774821893133}}
{"type":"message","id":"00b412a4","parentId":"a0cd8b1e","timestamp":"2026-03-29T22:04:53.138Z","message":{"role":"toolResult","toolCallId":"toolu_01UPmS3jJ8yEEP1Gc9A22wH4","toolName":"bash","content":[{"type":"text","text":"total 12\ndrwxrwxr-x  3 aux aux 4096 Mar 29 21:40 .\ndrwxrwxr-x 15 aux aux 4096 Mar 29 21:59 ..\ndrwxrwxr-x  2 aux aux 4096 Mar 29 21:59 fixtures\n---\ntotal 16\ndrwxrwxr-x 2 aux aux 4096 Mar 29 21:59 .\ndrwxrwxr-x 3 aux aux 4096 Mar 29 21:40 ..\n-rw-rw-r-- 1 aux aux 7282 Mar 29 21:59 sample_transcript.json\n"}],"isError":false,"timestamp":1774821893136}}
{"type":"message","id":"cbf50277","parentId":"00b412a4","timestamp":"2026-03-29T22:04:56.590Z","message":{"role":"assistant","content":[{"type":"text","text":"Good. I now have a complete picture of the codebase. Let me check if there's any existing test infrastructure (conftest, pytest config):"},{"type":"toolCall","id":"toolu_01VaJfYGUZc9CbaoToyhGE5p","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && find . -name \"conftest.py\" -o -name \"pytest.ini\" -o -name \"pyproject.toml\" -o -name \"setup.cfg\" | head -10 && echo \"---\" && find . -name \"test_*.py\" -o -name \"*_test.py\" | head -10"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":174,"cacheRead":73978,"cacheWrite":1007,"totalTokens":75160,"cost":{"input":0.000005,"output":0.004350000000000001,"cacheRead":0.036989,"cacheWrite":0.006293750000000001,"total":0.04763775}},"stopReason":"toolUse","timestamp":1774821893136}}
{"type":"message","id":"e4eaba3d","parentId":"cbf50277","timestamp":"2026-03-29T22:04:56.625Z","message":{"role":"toolResult","toolCallId":"toolu_01VaJfYGUZc9CbaoToyhGE5p","toolName":"bash","content":[{"type":"text","text":"---\n./.venv/lib/python3.12/site-packages/pip/_vendor/colorama/tests/isatty_test.py\n./.venv/lib/python3.12/site-packages/pip/_vendor/colorama/tests/ansitowin32_test.py\n./.venv/lib/python3.12/site-packages/pip/_vendor/colorama/tests/ansi_test.py\n./.venv/lib/python3.12/site-packages/pip/_vendor/colorama/tests/winterm_test.py\n./.venv/lib/python3.12/site-packages/pip/_vendor/colorama/tests/initialise_test.py\n./.venv/lib/python3.12/site-packages/greenlet/tests/test_version.py\n./.venv/lib/python3.12/site-packages/greenlet/tests/test_greenlet_trash.py\n./.venv/lib/python3.12/site-packages/greenlet/tests/test_leaks.py\n./.venv/lib/python3.12/site-packages/greenlet/tests/test_contextvars.py\n./.venv/lib/python3.12/site-packages/greenlet/tests/test_stack_saved.py\n"}],"isError":false,"timestamp":1774821896624}}
{"type":"message","id":"ad22d953","parentId":"e4eaba3d","timestamp":"2026-03-29T22:04:59.920Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01D9rJsip7Xi5Aak8HWMGpxT","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && pip list 2>/dev/null | grep -iE \"pytest|httpx|multipart\" && echo \"---\" && cat .venv/pyvenv.cfg 2>/dev/null | head 5"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":116,"cacheRead":74985,"cacheWrite":495,"totalTokens":75597,"cost":{"input":0.000005,"output":0.0029000000000000002,"cacheRead":0.0374925,"cacheWrite":0.00309375,"total":0.043491249999999995}},"stopReason":"toolUse","timestamp":1774821896624}}
{"type":"message","id":"abc1cc04","parentId":"ad22d953","timestamp":"2026-03-29T22:05:00.472Z","message":{"role":"toolResult","toolCallId":"toolu_01D9rJsip7Xi5Aak8HWMGpxT","toolName":"bash","content":[{"type":"text","text":"httpx                 0.28.1\n---\nhead: cannot open '5' for reading: No such file or directory\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1774821900470}}
{"type":"message","id":"7aef998d","parentId":"abc1cc04","timestamp":"2026-03-29T22:05:03.132Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01H7T67EW9Ze5NErWs412ykP","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && pip list 2>/dev/null | grep -iE \"pytest|aiofile|python-multipart\""}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":93,"cacheRead":75480,"cacheWrite":171,"totalTokens":75745,"cost":{"input":0.000005,"output":0.0023250000000000002,"cacheRead":0.037739999999999996,"cacheWrite":0.00106875,"total":0.041138749999999995}},"stopReason":"toolUse","timestamp":1774821900471}}
{"type":"message","id":"4edc4ebd","parentId":"7aef998d","timestamp":"2026-03-29T22:05:03.534Z","message":{"role":"toolResult","toolCallId":"toolu_01H7T67EW9Ze5NErWs412ykP","toolName":"bash","content":[{"type":"text","text":"(no output)\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1774821903532}}
{"type":"message","id":"b75e13dd","parentId":"4edc4ebd","timestamp":"2026-03-29T22:06:30.130Z","message":{"role":"assistant","content":[{"type":"text","text":"Now I have the full picture. Let me reason through the decomposition:\n\n**What this slice needs to deliver (R002):** A `POST /api/v1/ingest` endpoint that accepts a transcript JSON upload, auto-creates/finds Creator records, creates SourceVideo, bulk-inserts TranscriptSegments, saves the raw JSON to disk, and supports idempotent re-uploads.\n\n**Codebase state:**\n- Models, schemas, database infrastructure, config, and router patterns all exist from S01\n- No test framework set up yet (no pytest, no conftest.py, no test files)\n- `python-multipart` not installed (needed for `UploadFile`)\n- `httpx` is installed (for async test client)\n- Sample transcript fixture exists at `tests/fixtures/sample_transcript.json`\n\n**Decomposition reasoning:**\n\nThis is a moderate-complexity slice — one API endpoint with DB interactions, file I/O, idempotency logic, and it needs integration tests. The work naturally splits into two tasks:\n\n1. **T01: Build the ingestion endpoint + schema + router wiring** — This is the core implementation: add `python-multipart` dep, create the `TranscriptIngestResponse` schema, build the `ingest.py` router with all the business logic (JSON parsing, creator find-or-create, SourceVideo create, segment bulk insert, file save, idempotency), and wire it into `main.py`. Verify via import checks and a structural Python test.\n\n2. **T02: Write integration tests proving the endpoint works end-to-end** — Set up pytest + pytest-asyncio, create conftest.py with test DB fixtures, write `tests/test_ingest.py` with tests for: successful ingest, creator auto-creation, idempotent re-upload, and error cases (invalid JSON, missing fields). This is the verification that proves R002.\n\nI considered collapsing this into a single task, but the test infrastructure setup (conftest with async DB session management) plus the integration tests themselves make it large enough that splitting improves executor reliability. The first task is already ~6 files; adding test infra would push it to 10+ files.\n\nNow let me persist the plan:"},{"type":"toolCall","id":"toolu_01GzUXL5A7BxG1LmcYNo1QQa","name":"gsd_plan_slice","arguments":{"goal":"POST a transcript JSON file to the API; Creator and Source Video records appear in PostgreSQL","integrationClosure":"- Upstream surfaces consumed: `backend/models.py` (Creator, SourceVideo, TranscriptSegment), `backend/database.py` (get_session), `backend/config.py` (transcript_storage_path), `backend/schemas.py` (existing schema patterns), `tests/fixtures/sample_transcript.json`\n- New wiring introduced in this slice: `backend/routers/ingest.py` router mounted in `backend/main.py` under `/api/v1`\n- What remains before the milestone is truly usable end-to-end: S03 (LLM extraction pipeline), S04 (review UI), S05 (search UI)","milestoneId":"M001","observabilityImpact":"- Runtime signals: structured log messages for ingest start/completion with creator name, video filename, and segment count\n- Inspection surfaces: `source_videos` table `processing_status` column, `transcript_segments` table row count\n- Failure visibility: HTTP error responses with descriptive messages for invalid JSON, missing required fields, and DB constraint violations\n- Redaction constraints: none (no PII or secrets in transcript data)","proofLevel":"- This slice proves: integration\n- Real runtime required: yes (PostgreSQL for integration tests)\n- Human/UAT required: no","sliceId":"S02","successCriteria":"- `POST /api/v1/ingest` accepts a multipart transcript JSON upload and returns 200 with video_id, creator_id, and segment count\n- Creator record is auto-created from `creator_folder` with correct slug, or existing Creator is reused\n- SourceVideo record is created with `processing_status = \"transcribed\"` and `content_type = \"tutorial\"` (default)\n- TranscriptSegment rows are bulk-inserted with correct `segment_index` ordering\n- Raw JSON file is saved to the configured `transcript_storage_path`\n- Re-uploading the same transcript is idempotent — no duplicate records, segments are replaced\n- `docker compose config` still validates\n- Integration tests pass with real PostgreSQL","tasks":[{"description":"Create the POST /api/v1/ingest endpoint that accepts a Whisper transcript JSON as multipart UploadFile, parses it, finds-or-creates a Creator record from creator_folder, creates/updates a SourceVideo, bulk-inserts TranscriptSegments, saves the raw JSON to disk, and returns a structured response. Wire the router into main.py.\n\n## Steps\n\n1. Add `python-multipart>=0.0.9` to `backend/requirements.txt` and install it (`pip install python-multipart`).\n2. Add `TranscriptIngestResponse` Pydantic schema to `backend/schemas.py` with fields: `video_id: uuid.UUID`, `creator_id: uuid.UUID`, `creator_name: str`, `filename: str`, `segments_stored: int`, `processing_status: str`, `is_reupload: bool`.\n3. Create `backend/routers/ingest.py` with an `APIRouter(prefix=\"/ingest\", tags=[\"ingest\"])`. Implement `POST \"\"` endpoint accepting `file: UploadFile`. Core logic:\n   - Read and parse JSON from the uploaded file. Validate required top-level keys: `source_file`, `creator_folder`, `duration_seconds`, `segments`.\n   - Implement a `slugify()` helper: lowercase, replace non-alphanumeric chars with hyphens, strip leading/trailing hyphens, collapse consecutive hyphens.\n   - Find Creator by `folder_name`. If not found, create one with `name=creator_folder`, `slug=slugify(creator_folder)`, `folder_name=creator_folder`.\n   - Check for existing SourceVideo by `(creator_id, filename)`. If found, delete old TranscriptSegments for that video and update the SourceVideo record (upsert). If not found, create new SourceVideo with `content_type=\"tutorial\"`, `processing_status=\"transcribed\"`.\n   - Bulk-insert TranscriptSegment rows from `segments` array. Map: `start` → `start_time`, `end` → `end_time`, `text` → `text`, array index → `segment_index`.\n   - Save raw JSON to `{transcript_storage_path}/{creator_folder}/{source_file}.json`. Create parent directories with `os.makedirs(..., exist_ok=True)`.\n   - Set SourceVideo `transcript_path` to the saved file path.\n   - Commit the transaction. Return `TranscriptIngestResponse`.\n4. Add structured logging: log at INFO level on successful ingest with creator name, filename, segment count.\n5. Import and mount the ingest router in `backend/main.py`: `from routers import ingest` and `app.include_router(ingest.router, prefix=\"/api/v1\")`.\n6. Verify: `cd backend && python3 -c \"from routers.ingest import router; print([r.path for r in router.routes])\"` prints the ingest route.\n\n## Must-Haves\n\n- [ ] `python-multipart` in requirements.txt\n- [ ] `TranscriptIngestResponse` schema in schemas.py\n- [ ] `POST /api/v1/ingest` endpoint in ingest.py\n- [ ] Creator find-or-create by folder_name with slugify\n- [ ] SourceVideo upsert by (creator_id, filename)\n- [ ] TranscriptSegment bulk insert with segment_index\n- [ ] Raw JSON saved to transcript_storage_path\n- [ ] Router mounted in main.py\n- [ ] Structured logging on successful ingest\n\n## Failure Modes\n\n| Dependency | On error | On timeout | On malformed response |\n|------------|----------|-----------|----------------------|\n| UploadFile read | Return 400 with 'Invalid file' message | N/A (local read) | Return 422 with JSON parse error details |\n| PostgreSQL | Transaction rollback, return 500 | Return 500 with timeout message | N/A |\n| Filesystem write | Return 500 with 'Failed to save transcript' | N/A | N/A |\n\n## Negative Tests\n\n- **Malformed inputs**: Non-JSON file upload, JSON missing `segments` key, JSON missing `creator_folder`, empty segments array\n- **Error paths**: Invalid JSON syntax, file system permission error\n- **Boundary conditions**: Re-upload same file (idempotency), very long creator_folder name, special characters in source_file name\n\n## Verification\n\n- `cd backend && python3 -c \"from routers.ingest import router; print([r.path for r in router.routes])\"` outputs `['/ingest']`\n- `cd backend && python3 -c \"from schemas import TranscriptIngestResponse; print(TranscriptIngestResponse.model_fields.keys())\"` outputs the expected fields\n- `grep -q 'python-multipart' backend/requirements.txt` exits 0\n- `grep -q 'ingest' backend/main.py` exits 0","estimate":"45m","expectedOutput":["`backend/routers/ingest.py` — new ingestion endpoint router with POST handler","`backend/schemas.py` — modified with TranscriptIngestResponse schema","`backend/requirements.txt` — modified with python-multipart dependency","`backend/main.py` — modified to mount ingest router"],"files":["backend/requirements.txt","backend/schemas.py","backend/routers/ingest.py","backend/main.py"],"inputs":["`backend/models.py` — Creator, SourceVideo, TranscriptSegment ORM models with column definitions","`backend/database.py` — get_session async dependency for DB access","`backend/config.py` — Settings with transcript_storage_path","`backend/schemas.py` — existing Pydantic schema patterns (Base/Create/Read convention)","`backend/routers/creators.py` — existing router pattern to follow (APIRouter, Depends, logging)","`backend/main.py` — existing router mounting pattern","`tests/fixtures/sample_transcript.json` — reference for expected JSON shape"],"taskId":"T01","title":"Build transcript ingestion endpoint with creator auto-detection and idempotent upsert","verify":"cd backend && python3 -c \"from routers.ingest import router; print([r.path for r in router.routes])\" && python3 -c \"from schemas import TranscriptIngestResponse; print(TranscriptIngestResponse.model_fields.keys())\" && grep -q 'python-multipart' requirements.txt && grep -q 'ingest' main.py"},{"description":"Set up pytest + pytest-asyncio test infrastructure and write integration tests for the ingest endpoint. Tests run against a real PostgreSQL database using httpx.AsyncClient on the FastAPI app.\n\n## Steps\n\n1. Add test dependencies to `backend/requirements.txt`: `pytest>=8.0`, `pytest-asyncio>=0.24`, `python-multipart>=0.0.9` (if not already present).\n2. Install: `cd backend && pip install pytest pytest-asyncio`.\n3. Create `tests/conftest.py` with:\n   - Import `create_async_engine`, `async_sessionmaker` from SQLAlchemy.\n   - Create a test database URL fixture using env var `TEST_DATABASE_URL` with default `postgresql+asyncpg://chrysopedia:changeme@localhost:5433/chrysopedia_test`.\n   - `@pytest_asyncio.fixture` for `db_engine` that creates all tables via `Base.metadata.create_all` at setup and drops them at teardown (use `run_sync`).\n   - `@pytest_asyncio.fixture` for `db_session` that yields an AsyncSession.\n   - `@pytest_asyncio.fixture` for `client` that patches `get_session` dependency override on the FastAPI app and yields an `httpx.AsyncClient` with `ASGITransport`.\n   - `@pytest.fixture` for `sample_transcript_path` returning `tests/fixtures/sample_transcript.json`.\n   - `@pytest.fixture` for `tmp_transcript_dir` using `tmp_path` to override `transcript_storage_path`.\n4. Create `tests/test_ingest.py` with `@pytest.mark.asyncio` tests:\n   - `test_ingest_creates_creator_and_video`: POST sample_transcript.json → 200, response has video_id, creator_id, segments_stored=5, creator_name='Skope'. Query DB to confirm Creator with folder_name='Skope' and slug='skope' exists. Confirm SourceVideo with processing_status='transcribed' exists. Confirm 5 TranscriptSegment rows with segment_index 0-4.\n   - `test_ingest_reuses_existing_creator`: Pre-create a Creator with folder_name='Skope'. POST transcript → response creator_id matches pre-created ID. Only 1 Creator row in DB.\n   - `test_ingest_idempotent_reupload`: POST same transcript twice → second returns is_reupload=True, same video_id. Still only 5 segments (not 10). Only 1 SourceVideo row.\n   - `test_ingest_saves_json_to_disk`: POST transcript → raw JSON file exists at the expected path in tmp_transcript_dir.\n   - `test_ingest_rejects_invalid_json`: POST a file with invalid JSON → 400/422 error.\n   - `test_ingest_rejects_missing_fields`: POST JSON without `creator_folder` → 400/422 error.\n5. Add a `pytest.ini` or `pyproject.toml` section with `asyncio_mode = \"auto\"` to avoid per-test markers.\n\n## Must-Haves\n\n- [ ] pytest and pytest-asyncio installed and configured\n- [ ] conftest.py with async DB fixtures and ASGI test client\n- [ ] test_ingest_creates_creator_and_video passes\n- [ ] test_ingest_reuses_existing_creator passes\n- [ ] test_ingest_idempotent_reupload passes\n- [ ] test_ingest_saves_json_to_disk passes\n- [ ] test_ingest_rejects_invalid_json passes\n- [ ] test_ingest_rejects_missing_fields passes\n- [ ] All tests pass: `cd backend && python -m pytest tests/test_ingest.py -v`\n\n## Failure Modes\n\n| Dependency | On error | On timeout | On malformed response |\n|------------|----------|-----------|----------------------|\n| PostgreSQL (test DB) | Tests skip or fail with clear connection error | pytest-asyncio timeout | N/A |\n| FastAPI test client | Test fails with assertion error | httpx timeout | Response schema mismatch caught by assertions |\n\n## Verification\n\n- `cd backend && python -m pytest tests/test_ingest.py -v` — all 6 tests pass\n- `docker compose config` exits 0 (no regressions)\n\n## Observability Impact\n\n- Signals added/changed: test output showing pass/fail per test case with timing\n- How a future agent inspects this: `cd backend && python -m pytest tests/test_ingest.py -v --tb=short`\n- Failure state exposed: pytest output shows which assertion failed, with full diff","estimate":"45m","expectedOutput":["`tests/conftest.py` — pytest fixtures for async DB, test client, and transcript paths","`tests/test_ingest.py` — 6 integration tests covering happy path, idempotency, and error cases","`pytest.ini` — pytest configuration with asyncio_mode=auto","`backend/requirements.txt` — modified with pytest and pytest-asyncio dependencies"],"files":["backend/requirements.txt","tests/conftest.py","tests/test_ingest.py","pytest.ini"],"inputs":["`backend/routers/ingest.py` — the ingestion endpoint to test (created in T01)","`backend/main.py` — FastAPI app with ingest router mounted (modified in T01)","`backend/schemas.py` — TranscriptIngestResponse schema (modified in T01)","`backend/models.py` — Creator, SourceVideo, TranscriptSegment models for DB assertions","`backend/database.py` — get_session dependency to override in tests","`backend/config.py` — Settings to override transcript_storage_path in tests","`tests/fixtures/sample_transcript.json` — test input file with 5 segments"],"taskId":"T02","title":"Write integration tests proving ingestion, creator auto-detection, and idempotent re-upload","verify":"cd backend && python -m pytest tests/test_ingest.py -v && docker compose config > /dev/null 2>&1"}]}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":4461,"cacheRead":75651,"cacheWrite":124,"totalTokens":80237,"cost":{"input":0.000005,"output":0.111525,"cacheRead":0.0378255,"cacheWrite":0.0007750000000000001,"total":0.1501305}},"stopReason":"toolUse","timestamp":1774821903533}}
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{"type":"message","id":"428daa81","parentId":"8569c2a0","timestamp":"2026-03-29T22:06:43.934Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me self-audit the plan:\n\n**Completion semantics:** If T01 is done, the ingestion endpoint exists and is wired. If T02 is done, integration tests prove it actually works with real PostgreSQL. Together they deliver the slice goal: \"POST a transcript JSON → Creator and SourceVideo appear in PostgreSQL.\" ✅\n\n**Requirement coverage:** R002 (Transcript Ingestion API) is the primary requirement. T01 builds the endpoint (creates/updates Creator and SourceVideo, stores transcript data). T02 proves it works. R012 (incremental content addition) is partially addressed via creator auto-detection and idempotent re-upload. ✅\n\n**Task completeness:** Both tasks have steps, must-haves, verification commands, concrete file path inputs, and concrete file path outputs. ✅\n\n**Dependency correctness:** T02 depends on T01 outputs (`backend/routers/ingest.py`, modified `backend/main.py`, modified `backend/schemas.py`). Order is correct. ✅\n\n**Key links planned:** T01 wires the router into main.py. T02 overrides `get_session` in conftest.py to use test DB. ✅\n\n**Scope sanity:** T01 = 6 steps, 4 files. T02 = 5 steps, 4 files. Both well within limits. ✅\n\n**Feature completeness:** Both tasks produce user-facing progress — T01 delivers a working endpoint, T02 proves it. ✅\n\n**Quality gate coverage:** Threat Surface not needed (internal API, no auth yet, no PII). Requirement Impact addressed via R002 ownership. Failure Modes and Negative Tests are present in both task plans. ✅\n\nSlice S02 planned."}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":416,"cacheRead":75775,"cacheWrite":4482,"totalTokens":80674,"cost":{"input":0.000005,"output":0.010400000000000001,"cacheRead":0.0378875,"cacheWrite":0.028012500000000003,"total":0.07630500000000001}},"stopReason":"stop","timestamp":1774821990142}}
