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I'm looking into using multiple storage contexts for initializing VectorStoreIndex.
My dataset includes 20 documents, each relevant to particular users.
For instance, I'd like to set up a storage context with Documents A, B, and D for one user query, and Documents A, B, and F for another.
Is this feasible?
Should I generate all document vectors first and then apply metadata filters?
Additionally, how would I go about filtering these in ChatEngine?
The text was updated successfully, but these errors were encountered:
@leoz2007 I think you can add metadata to the documents that can be used to relate the user to the document and then query using that metadata. In the simplest case, that would be adding the userId to the metadata.
I'm looking into using multiple storage contexts for initializing VectorStoreIndex.
My dataset includes 20 documents, each relevant to particular users.
For instance, I'd like to set up a storage context with Documents A, B, and D for one user query, and Documents A, B, and F for another.
Is this feasible?
Should I generate all document vectors first and then apply metadata filters?
Additionally, how would I go about filtering these in ChatEngine?
The text was updated successfully, but these errors were encountered: