embedflow enables embedding model migration without re-embedding
The author released embedflow, a method and tool to migrate embedding models by reranking K documents from the old index instead of re-embedding the entire corpus. Tested on up to 1M documents across 63 migrations; best result was qwen4b→qwen8b matching native retrieval with K=50. embedflow supports qdrant, pgvector, and faiss and is available on PyPI and GitHub.