evadb.EvaDBCursor.create_vector_index#

EvaDBCursor.create_vector_index(index_name: str, table_name: str, expr: str, using: str) → EvaDBCursor[source]#

Creates a vector index using the provided expr on the table.

Parameters:

  • index_name (str) – Name of the index.

  • table_name (str) – Name of the table.

  • expr (str) – Expression used to build the vector index.

  • using (str) – Method used for indexing, can be FAISS or QDRANT.

Returns:

The EvaDBCursor object.

Return type:

EvaDBCursor

Examples

Create a Vector Index using QDRANT

>>> cursor.create_vector_index(
        "faiss_index",
        table_name="meme_images",
        expr="SiftFeatureExtractor(data)",
        using="QDRANT"
    ).df()
            0
    0       Index faiss_index successfully added to the database
>>> relation = cursor.table("PDFs")
>>> relation.order("Similarity(ImageFeatureExtractor(Open('/images/my_meme')), ImageFeatureExtractor(data) ) DESC")
>>> relation.df()