Vector embeddings created by different embedding models can't be compared even if they have the same dimensions. If you switch between embedding models, rerun the mapping, including all Source, Chunking, Vector Embedding, and Target transformations, to create embeddings for all documents using the new model.

Because the Vector Embedding transformation is a passive transformation that produces one output row for each input row, input columns that contain null or empty strings return an empty output vector. If the vector is empty, vector databases like Pinecone might drop the row.

The Vector Embedding transformation can process only English text.