[Question]: way to emit similarity score from the retriever? about llama_index HOT 1 OPEN

To emit similarity scores along with the retrieved results using the VectorIndexRetriever, you need to ensure that the _retrieve method returns a list of NodeWithScore objects, which include both the nodes and their corresponding similarity scores.

Here's how you can modify the _retrieve method:

def _retrieve(
    self,
    query_bundle: QueryBundle,
) -> List[NodeWithScore]:
    query_result = self._index.query(
        query_str=query_bundle.query_str,
        top_k=self._similarity_top_k,
        **self._kwargs,
    )
    
    # Assuming query_result is a VectorStoreQueryResult object
    nodes_with_scores = self._build_node_list_from_query_result(query_result)
    
    return nodes_with_scores

In this modification, it is assumed that the self._index.query method returns a VectorStoreQueryResult object, which contains the nodes and their similarity scores. The nodes_with_scores list is then created using the _build_node_list_from_query_result method, which processes the VectorStoreQueryResult to include the similarity scores.

The VectorStoreQueryResult object typically contains the following attributes:

• nodes: A list of nodes.
• ids: A list of node IDs.
• similarities: A list of similarity scores corresponding to the nodes or node IDs.

The _build_node_list_from_query_result method processes these attributes to build a list of NodeWithScore objects, which include both the nodes and their similarity scores ^[1][2].

This approach ensures that the retrieved results include the similarity scores.

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from llama_index.