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EmbedFlow

github.com/arnsri33/embedflow
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Category
Developer Tools
Rank
No. 1061Tools index
Pricing
Open Source
Platform
cli · web
Type
TOOL
GitHub
43 stars
Date

About

EmbedFlow enables progressive migration between embedding models over an existing vector index by serving candidates from the old model's index while target vectors are materialized in the background, avoiding a full corpus re-embedding before cutover. It provides migration-safety diagnostics, a measurement framework for candidate-depth quality loss, and integrations with FAISS, Qdrant, and pgvector.

What it can do

  • Migrate a vector index from one embedding model to another with zero downtime

    Existing vector index and new embedding model → Migrated vector index

  • Serve search candidates from the old model's index while target vectors are materialized in the background

    Old embedding index → Search candidates

  • Measure retrieval quality loss at candidate depth during migration

    Old and new embedding indexes → Quality loss measurements

  • Integrate with FAISS, Qdrant, and pgvector vector stores

    Vector store configuration → Connected vector backend

  • Control migration via CLI or Python API

    CLI commands or Python code → Migration execution

Tags

embeddingsvector-searchragfaissqdrantpgvectorsemantic-searchinformation-retrieval

Tech Stack

Python

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