I was playing around with embedding models and I realized the moving between embedding models on a large corpus can cause a huge backfill, as all of the previous documents would have to be re embedded. embedflow tries to forgo that; it takes candidate documents from the previous index, and reran...
Source: [Hacker News](https://github.com/arnsri33/embedflow)