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The issue lies in the metadata_dict_to_node function which doesn't correctly parse the response from the pinecone index query. If this issue is acknowledged as a bug I would to happy to provide a fix for this.
Relevant Logs/Tracbacks
The text was updated successfully, but these errors were encountered:
Hey @LHFO94! I'm here to help you with any bugs, questions, or contributions. Let me know how I can assist you!
I found a similar closed issue titled "[Bug]: Metadata is missing from vector store results" which was resolved by a pull request that fixed a variable name clash for legacy vector indexes [1].
In your case, the issue seems to be related to the metadata_dict_to_node function not correctly parsing the response from the Pinecone index query. The get_nodes method should assign the embedding values from the Pinecone query response to the node.embedding attribute. The embedding values are included in the match.values field of the response [2].
You might want to check if the metadata_dict_to_node function is correctly handling the embedding values and ensure that the get_nodes method is properly assigning these values to the nodes.
Bug Description
When trying to call .get_nodes() on a PineconeVectorStore the embedding values are not returned despite them being in the index.
Versions
llama-index-core == 0.12.11
llama-index-vector-stores-pinecone == 0.4.2
Version
0.12.11
Steps to Reproduce
The code above results in the following output
The issue lies in the
metadata_dict_to_node
function which doesn't correctly parse the response from the pinecone index query. If this issue is acknowledged as a bug I would to happy to provide a fix for this.Relevant Logs/Tracbacks
The text was updated successfully, but these errors were encountered: