I’m updating a semantic search feature and may switch to a newer OpenAI embedding model. The existing vectors are already in a production index, so I’m unsure whether to replace them all at once or maintain separate versions while the new one is tested.

How have you handled an embedding model upgrade alongside incremental document updates? I’m especially interested in avoiding mismatched vectors during the transition and keeping search available while the index changes.