embedflow
A tool for gradually replacing an embedding model using an existing vector index
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WHAT IT DOES
What does it do?
EmbedFlow uses candidates found in an existing vector index to serve a new embedding model while gradually creating target document vectors. It provides model migration analysis, a persistent cache, and background jobs. It can be used with vector stores including FAISS, Qdrant, and pgvector, as well as through a CLI and FastAPI.
KEY FEATURES
Key features
- Migrate models gradually using candidates from an existing vector index
- Analyze embedding model migration feasibility
- Generate target document vectors in the background and cache them persistently
- Integrate with multiple vector stores, a CLI, and FastAPI