feat: dockerize app, add structured logging, fix rate limiter ...

Changes:
- Add Dockerfile with python:3.12-slim, alembic migrations, uvicorn
- Add .dockerignore
- Update docker-compose.yml with app service, port 8020, external Ollama
- Configure alembic/env.py to read DATABASE_URL from env
- Update .env.example with port 8020, Ollama host 192.168.1.75, gemma4 model
- Fix slowapi rate limiter: sync key_func instead of async
- Add structured JSON logging (structlog) to ingest endpoint, pipeline stages
- Fix logging output via logging.basicConfig for Docker stdout

Co-Authored-By: Claude <noreply@anthropic.com>

feat: core pipeline + FastAPI API (Phases 0-6) ...

Implemented the full VMK Data Collector foundation and processing pipeline:

- Config, logging, exception hierarchy
- DB models (listings, raw data, images, snapshots, enrichments, custom fields)
- Alembic async migrations
- Repositories with upsert/snapshot support
- Domain entities and Pydantic schemas
- Ollama AI client with mock mode
- AI normalizer, image analyzer, enricher
- Image downloader with SHA-256 dedup
- PropertyPipeline: raw -> AI validate -> upsert/snapshot -> images -> enrich
- FastAPI app with /api/v1/ingest endpoint

Co-Authored-By: Claude <noreply@anthropic.com>