ENCODE / COMMIT_CONTENTS.md
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Deploy ENCODE with private artifact bucket
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Initial Commit Contents

This file defines the deployed contents of the lightweight ENCODE Space and its separate private runtime-artifact bucket.

Application and deployment

  • README.md β€” project overview and Hugging Face Space metadata.
  • COMMIT_CONTENTS.md β€” this auditable release inventory.
  • Dockerfile β€” CPU-only backend container listening on port 7860.
  • netlify.toml and deploy/ β€” Netlify build/Drop package that proxies the static frontend's API requests to the Hugging Face Space backend.
  • .dockerignore β€” excludes development-only files from container builds.
  • .gitignore β€” excludes raw data, archives, experiments, profiles, and caches.
  • src/requirements.txt β€” pinned Python runtime dependencies.

Backend

  • src/backend/app.py β€” FastAPI application and HTTP endpoints.
  • src/backend/codesearch.py β€” medical-code retrieval.
  • src/backend/retriever.py β€” phenotype retrieval using Vidul's fine-tuned embeddings.
  • src/backend/encode.py β€” annotation and response handling.
  • src/backend/graph.py β€” phenotype detail graph construction.
  • src/backend/rxnav.py β€” conservative, cached RxNAV/RxNorm completion for medication mappings that are absent from packaged artifacts.
  • src/backend/__init__.py β€” backend package marker.

Frontend

  • src/frontend/index.html β€” browser application shell.
  • src/frontend/app.js β€” search, review, and annotation behavior.
  • src/frontend/styles.css β€” application styling.

Private bucket: runtime model and indexes

  • artifacts/vidul/BGE_FT_VA/ β€” Vidul's fine-tuned model weights, tokenizer, and configuration.
  • artifacts/vidul/icd_index/ β€” diagnosis FAISS index and metadata.
  • artifacts/vidul/med_index/ β€” medication FAISS index and metadata.
  • artifacts/vidul/ndc_index/ β€” NDC FAISS index and metadata.
  • artifacts/vidul/labchem_index/ β€” LOINC/lab FAISS index and metadata.
  • artifacts/vidul/cpt_index/ β€” procedure FAISS index and metadata.
  • artifacts/part_a_embeddings/code.npy
  • artifacts/part_a_embeddings/code_meta.json
  • artifacts/part_a_embeddings/config.json
  • artifacts/part_a_embeddings/metadata.npy
  • artifacts/part_a_embeddings/metadata_ids.json

Private bucket: runtime phenotype records

  • artifacts/part_a_canonical/algorithm_components.jsonl
  • artifacts/part_a_canonical/canonical_phenotypes.jsonl
  • artifacts/part_a_canonical/cipher_links.jsonl
  • artifacts/part_a_canonical/code_descriptions.jsonl
  • artifacts/part_a_canonical/loinc_terms.jsonl
  • artifacts/part_a_canonical/med_ingredient_map.jsonl
  • artifacts/part_a_canonical/rxcui_ingredient_map.jsonl

Verification

  • tests/test_retrieval.py β€” focused tests for the retained dense-retrieval path.
  • tests/test_rxnav_and_deployment.py β€” RxNAV provenance and Netlify Drop deployment checks.

Explicitly excluded

  • Raw VA source data and local data exports.
  • Source ZIPs, including the original application bundle, plus LOINC and RxNorm distribution archives.
  • Training, evaluation, reranker, extracted-facet, and profiling outputs.
  • Historical documentation, retired scripts, generated demos, and caches.
  • Local environments, credentials, editor settings, and annotations.

The release contains one retrieval path: Vidul's fine-tuned model, prebuilt embeddings, and exact dense search. Large runtime assets are stored in hf://buckets/hiasgnpsadgd/encode-artifacts and mounted read-only at /home/user/app/artifacts; they are not committed to the Space repository or copied into the Docker image.