---
id: S01
parent: M001
milestone: M001
provides:
  - Docker Compose project definition (5 services) for deployment
  - PostgreSQL schema with 7 tables via Alembic migration
  - FastAPI app with health check and CRUD endpoints pattern
  - Pydantic schemas for all 7 entities (reusable in S02+)
  - SQLAlchemy async session infrastructure
  - Sample transcript JSON fixture for S02 ingestion testing
  - Canonical tags configuration (6 categories, 13 genres)
requires:
  []
affects:
  - S02
  - S03
key_files:
  - docker-compose.yml
  - .env.example
  - docker/Dockerfile.api
  - docker/Dockerfile.web
  - backend/main.py
  - backend/models.py
  - backend/database.py
  - backend/schemas.py
  - backend/config.py
  - backend/routers/health.py
  - backend/routers/creators.py
  - backend/routers/videos.py
  - alembic.ini
  - alembic/env.py
  - alembic/versions/001_initial.py
  - whisper/transcribe.py
  - whisper/requirements.txt
  - config/canonical_tags.yaml
  - README.md
  - tests/fixtures/sample_transcript.json
key_decisions:
  - D001: XPLTD Docker conventions — xpltd_chrysopedia project, bind mounts at /vmPool/r/services/, network 172.24.0.0/24
  - env_file uses required: false so docker compose config validates on fresh clones
  - POSTGRES_PASSWORD uses :-changeme default instead of :? to avoid config failures
  - PostgreSQL exposed on host port 5433 to avoid conflicts with other projects
  - SQLAlchemy relationship import aliased to sa_relationship to avoid column name clash
  - Separate PostgreSQL enum type names to avoid collisions (key_moment_content_type vs content_type)
  - Health check at /health performs real DB SELECT 1; lightweight /api/v1/health also available
  - Whisper import deferred so --help works without openai-whisper installed
  - Sample transcript uses realistic music production content for downstream pipeline testing
patterns_established:
  - Docker Compose service naming: chrysopedia-{role} (chrysopedia-db, chrysopedia-api, etc.)
  - Backend router pattern: backend/routers/{domain}.py with prefix-per-router mounted under /api/v1
  - SQLAlchemy async pattern: asyncpg engine + async_sessionmaker + get_session dependency
  - Pydantic v2 schema pattern: Base/Create/Read variants per entity with model_config from_attributes=True
  - Config via pydantic-settings BaseSettings loading from .env with sensible defaults
  - Alembic async migration pattern with run_async_migrations() wrapper
  - UUID primary keys with gen_random_uuid() server default for all entities
observability_surfaces:
  - GET /health — returns database connectivity status (connected/error)
  - Structured logging via Python logging module in FastAPI lifespan
drill_down_paths:
  - .gsd/milestones/M001/slices/S01/tasks/T01-SUMMARY.md
  - .gsd/milestones/M001/slices/S01/tasks/T02-SUMMARY.md
  - .gsd/milestones/M001/slices/S01/tasks/T03-SUMMARY.md
  - .gsd/milestones/M001/slices/S01/tasks/T04-SUMMARY.md
  - .gsd/milestones/M001/slices/S01/tasks/T05-SUMMARY.md
duration: ""
verification_result: passed
completed_at: 2026-03-29T22:02:45.503Z
blocker_discovered: false
---

# S01: Docker Compose + Database + Whisper Script

**Delivered deployable Docker Compose infrastructure with PostgreSQL schema (7 tables), FastAPI skeleton API with CRUD endpoints, desktop Whisper transcription script, and sample transcript fixture.**

## What Happened

This slice established the complete foundation for the Chrysopedia stack across five tasks.

**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.

**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.

**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.

**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.

**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.

## Verification

All slice-level verification checks passed:

1. `docker compose config` — exits 0, all 5 services validated with correct env interpolation, volumes, networks, healthchecks, and dependency ordering.
2. `python3 whisper/transcribe.py --help` — exits 0, shows full usage with all CLI args and examples.
3. `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).
4. All 7 SQLAlchemy models import successfully with correct entity definitions.
5. All Pydantic schemas and config import successfully.
6. All 3 router modules (health, creators, videos) import with correct route counts.
7. Alembic files (alembic.ini, env.py, 001_initial.py) all present.
8. config/canonical_tags.yaml loads with 6 topic categories.
9. README.md exists with all required sections.

## Requirements Advanced

- R001 — Desktop Whisper script built with all required features: ffmpeg extraction, Whisper large-v3, word-level timestamps, resumability, batch mode, spec-compliant JSON output
- R010 — Docker Compose project created with all 5 services following XPLTD conventions; docker compose config validates successfully
- 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

## Requirements Validated

None.

## New Requirements Surfaced

None.

## Requirements Invalidated or Re-scoped

None.

## Deviations

- env_file set to `required: false` to support fresh clones without .env present (T01).
- POSTGRES_PASSWORD changed from `:?` (hard fail when unset) to `:-changeme` default to fix docker compose config validation (T02, captured in KNOWLEDGE.md).
- Added docker/nginx.conf and frontend/package.json placeholders not in original plan but required for Dockerfile.web build context (T01).
- Added backend/routers/videos.py not in T03 expected output list but required by plan's endpoint list (T03).
- Whisper script uses subprocess directly for ffmpeg instead of ffmpeg-python library for reliability (T04).
- Added --creator CLI flag for overriding inferred creator folder name (T04).

## Known Limitations

- Docker Compose stack not tested end-to-end with `docker compose up -d` (requires deployment to ub01 with bind mount paths).
- API endpoints verified locally with test PostgreSQL container, not inside the Docker Compose network.
- Whisper script validated structurally (--help, ffmpeg check, AST parse) but not with actual video transcription (requires CUDA GPU + Whisper model).
- Host port 8000 conflicts with kerf-engine container — local testing uses port 8001 (documented in KNOWLEDGE.md).

## Follow-ups

None.

## Files Created/Modified

- `docker-compose.yml` — Docker Compose project with 5 services (PostgreSQL 16, Redis 7, FastAPI API, Celery worker, React/nginx web)
- `.env.example` — Template with all required environment variables and descriptions
- `docker/Dockerfile.api` — Multi-stage Dockerfile for FastAPI + Celery worker service
- `docker/Dockerfile.web` — Dockerfile for React app served via nginx
- `docker/nginx.conf` — Nginx config for serving React SPA with API proxy
- `backend/main.py` — FastAPI app with lifespan, CORS, structured logging, router mounting
- `backend/models.py` — SQLAlchemy async models for all 7 entities with enums, FKs, JSONB
- `backend/database.py` — Async engine, session factory, declarative base
- `backend/schemas.py` — Pydantic v2 schemas (Base/Create/Read) for all entities
- `backend/config.py` — pydantic-settings config loading from .env
- `backend/routers/health.py` — GET /health with DB connectivity check
- `backend/routers/creators.py` — GET /api/v1/creators (paginated), GET /api/v1/creators/{slug}
- `backend/routers/videos.py` — GET /api/v1/videos (paginated, optional creator filter)
- `backend/requirements.txt` — Python dependencies for FastAPI, SQLAlchemy, asyncpg, etc.
- `alembic.ini` — Alembic configuration pointing to async database URL
- `alembic/env.py` — Async Alembic migration runner
- `alembic/versions/001_initial.py` — Initial migration creating all 7 tables with constraints
- `alembic/script.py.mako` — Alembic migration template
- `whisper/transcribe.py` — Desktop Whisper transcription script with CLI, batch mode, resumability
- `whisper/requirements.txt` — Whisper script Python dependencies
- `whisper/README.md` — Whisper script usage documentation
- `config/canonical_tags.yaml` — 6 topic categories and 13 genres for tag classification
- `README.md` — Project README with architecture, setup, env vars, dev workflow
- `tests/fixtures/sample_transcript.json` — 5-segment sample transcript matching Whisper output format
- `frontend/package.json` — Placeholder React app package.json
