result = func(*args, kwargs) File "/Users/ilpinto/dev/lightspeed-rag-content/.conda/lib/python3.10/site-packages/llama_index/core/indices/vector_store/retrievers/retriever.py", line 101, in _retrieve return self._get_nodes_with_embeddings(query_bundle) File "/Users/ilpinto/dev/lightspeed-rag-content/.conda/lib/python3.10/site-packages/llama_index/core/indices/vector_store/retrievers/retriever.py", line 177, in _get_nodes_with_embeddings query_result = self._vector_store.query(query, self._kwargs) File "/Users/ilpinto/dev/lightspeed-rag-content/.conda/lib/python3.10/site-packages/llama_index/vector_stores/faiss/base.py", line 182, in query dists, indices = self._faiss_index.search( File "/Users/ilpinto/dev/lightspeed-rag-content/.conda/lib/python3.10/site-packages/faiss/class_wrappers.py", line 329, in replacement_search assert d == self.d AssertionError
The dimensions come from the embedding model -- the error meant that you aren't using the same embedding model to query that you used to build the index