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Hey @johnhu33! 👋 I'm here to help you with any bugs, questions, or contributions while you wait for a human maintainer. Let's squash those bugs together! I found a similar closed issue that might be relevant: [Question]: Retriever documents, embeddings = None. The suggested solution is to modify the To store embeddings after inserting nodes into a
Here is a code snippet demonstrating these steps: # Assuming you have a VectorStoreIndex instance `index` and a list of nodes `nodes`
# Step 1: Generate embeddings for the nodes
nodes_with_embeddings = index._get_node_with_embedding(nodes)
# Step 2: Insert nodes with embeddings into the index
index._add_nodes_to_index(index._index_struct, nodes_with_embeddings) The |
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How to get node's corresponding embedding with node_id? |
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vector_store = VectorStoreIndex(redis_client=redis_client, overwrite=True, schema=schema) load storage contextstorage_context = StorageContext.from_defaults(vector_store=vector_store) build and load index from documents and storage contextindex = VectorStoreIndex.from_vector_store(vector_store=vector_store, embed_model=BGEEmbeddings()) index.insert_nodes(nodes) result_nodes[0].embedding is None How could I store index in the VectorStoreIndex? |
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Embedding is None after inserting nodes to a VectorStoreIndex that is initialised using from_vector_store, how can I store embeddings?
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