# refactor: Check for embedding model consistency #58
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−130
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refactor: Check for embedding model consistency
This pull request introduces a check to ensure that the embedding model used during inference is consistent with the model used when creating the index.
Changes:
enhanced_kt_retriever.py, the_load_node_embedding_cachemethod now checks for anembedding_model_info.jsonfile and compares the model name.faiss_filter.py, the dimension transformation logic has been removed, and thebuild_indicesmethod now checks forembedding_model_info.jsonand its consistency._save_embedding_model_infohas been added to save the embedding model name.These changes prevent the use of inconsistent embeddings, which could lead to unexpected behavior.