fix: INSIGHTFACE_HOME path, entrypoint, caching default, CRON_SCHEDULE opt-in

- Dockerfile: ENV INSIGHTFACE_HOME=/models → /models/.insightface to
  match compose.yml and .env.example; the old value caused InsightFace
  to store models at /models/models/buffalo_l (double-appended subdir)
- entrypoint.sh: use /app/.venv/bin/winnow (installed entry point)
  instead of python -m winnow.cli
- config.py: ENABLE_CACHE default false → true; embedding cache is
  always beneficial in practice; users can opt out with ENABLE_CACHE=false
- compose.yml: comment out CRON_SCHEDULE so scheduling is opt-in;
  flip ENABLE_CACHE to commented opt-out to reflect new default
- README.md: update ENABLE_CACHE default documentation to true
- tests/test_config.py: update default assertion to match

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

README.md

@@ -192,7 +192,7 @@ The first run after a fresh install downloads the embedding models (~1-2 GB). Su
 | Variable | Default | Description |
 | :--- | :--- | :--- |
 | `FORCE_CPU` | `false` | Disable GPU — fall back to CPU for embedding computation |
-| `ENABLE_CACHE` | `false` | Cache computed embeddings to disk (speeds up re-runs on the same library) |
+| `ENABLE_CACHE` | `true` | Cache computed embeddings to disk (speeds up re-runs on the same library) |
 | `CACHE_DIR` | `.if_cache` | Path for embedding cache and upload tracker files |
 | `HF_HOME` | *(system)* | HuggingFace model cache location (SigLIP) |
 | `INSIGHTFACE_HOME` | *(system)* | InsightFace model cache location (Buffalo_L) |