VectorStoreQuery#

class llama_index.vector_stores.VectorStoreQuery(query_embedding: Optional[List[float]] = None, similarity_top_k: int = 1, doc_ids: Optional[List[str]] = None, node_ids: Optional[List[str]] = None, query_str: Optional[str] = None, output_fields: Optional[List[str]] = None, embedding_field: Optional[str] = None, mode: VectorStoreQueryMode = VectorStoreQueryMode.DEFAULT, alpha: Optional[float] = None, filters: Optional[MetadataFilters] = None, mmr_threshold: Optional[float] = None, sparse_top_k: Optional[int] = None, hybrid_top_k: Optional[int] = None)#

Bases: object

Vector store query.

Attributes Summary

Attributes Documentation

alpha: Optional[float] = None#
doc_ids: Optional[List[str]] = None#
embedding_field: Optional[str] = None#
filters: Optional[MetadataFilters] = None#
hybrid_top_k: Optional[int] = None#
mmr_threshold: Optional[float] = None#
mode: VectorStoreQueryMode = 'default'#
node_ids: Optional[List[str]] = None#
output_fields: Optional[List[str]] = None#
query_embedding: Optional[List[float]] = None#
query_str: Optional[str] = None#
similarity_top_k: int = 1#
sparse_top_k: Optional[int] = None#