streamlit_hf/README.md

Hugging Face Space (Docker + Streamlit)

The root README.md starts with the YAML card Hugging Face reads for the Space (title, tags, colours, sdk: docker, app_port: 7860). Copy that block if you maintain a separate Space README.

---
title: FateFormer Explorer
short_description: Multimodal fate from RNA, ATAC, and metabolic flux models.
emoji: 🧬
colorFrom: purple
colorTo: indigo
tags:
  - single-cell
  - multi-omics
  - genomics
  - atac-seq
  - rna-seq
  - fluxomic
  - metabolic-modeling
  - deep-learning
  - biology
license: mit
sdk: docker
app_port: 7860
---

app_port 7860 matches the root Dockerfile (streamlit ... --server.port 7860). Local runs use Streamlit’s default 8501 unless you pass --server.port.

Before first deploy

1. Run locally: python scripts/precompute_streamlit_cache.py (requires GPU/CPU time for attention).
2. Commit streamlit_hf/cache/ contents (latent_umap.pkl, attention_summary.pkl, attention_feature_ranks.pkl, df_features.parquet, and optionally samples.parquet if you use it elsewhere). Hugging Face rejects raw Parquet in git: *.parquet is tracked with Git LFS via root .gitattributes (same idea as *.pkl). If an old commit still has Parquet as a normal blob, run git lfs migrate import --include="*.parquet" --everything then force-push. These paths may be in .gitignore; use git add -f streamlit_hf/cache/* when you want them in the remote.
3. Keep ckp/ model weights available only if you run precompute in CI; the slim Docker image does not include PyTorch and expects precomputed caches.

The repository Dockerfile at the root builds the Space.