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Embedding extension to omop-graph

Project description

omop-emb

Embedding layer for OMOP CDM.

omop-emb now separates model metadata from embedding storage:

  • model metadata is stored locally in SQLite (metadata.db)
  • embedding vectors are stored by the selected backend (pgvector or faiss)
  • OMOP concept metadata remains in the OMOP CDM database

Installation

omop-emb now exposes backend-specific optional dependencies so installation can match the embedding backend you actually intend to use.

pip install "omop-emb[pgvector]"
pip install "omop-emb[faiss]"
pip install "omop-emb[all]"

Notes:

  • pgvector installs the PostgreSQL/pgvector dependencies.
  • faiss installs the FAISS-based backend dependencies. This currently only includes CPU support
  • all installs both backend stacks for development or mixed environments.
  • A plain pip install omop-emb installs the shared core package only.
  • PostgreSQL-specific embedding dependencies are optional, but omop-emb still requires OMOP CDM database access.
  • Non-PostgreSQL database backends have not yet been tested.

Runtime Configuration

Common environment variables:

  • OMOP_EMB_BACKEND: backend name (pgvector or faiss) used by the backend factory.
  • OMOP_EMB_BASE_STORAGE_DIR: local base directory for omop-emb artifacts, including local metadata (metadata.db) and FAISS files. If unset, omop-emb defaults to ./.omop_emb in the current working directory.
  • OMOP_DATABASE_URL: SQLAlchemy URL for the OMOP CDM database.

Extended documentation can be found here.

Project Roadmap

  • Interface for PostgreSQL storage of vectors
  • Interface for FAISS storage of embeddings
  • Extensive unit testing
    • Backend testing
    • Corruption and restoration of DB testing
  • Support non-Flat indices for each backend
  • faiss GPU support
  • pgvectorscale support
  • Vector-quantisation for more efficient storage

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