LlamaIndex Vector_Stores Integration: BigQuery

Vector store index using Google BigQuery. Supports efficient storage and querying of vector embeddings using BigQuery's native vector search capabilities. For more information, see the official BigQuery Vector Search Documentation

🔐 Required IAM Permissions

To use this integration, ensure your account has the following permissions:

roles/bigquery.dataOwner (BigQuery Data Owner)
roles/bigquery.dataEditor (BigQuery Data Editor)

🔧 Installation

bash

pip install llama-index-vector-stores-bigquery

💻 Example Usage

python

from google.cloud.bigquery import Client
from llama_index.vector_stores.bigquery import BigQueryVectorStore

client = Client()

vector_store = BigQueryVectorStore(
    table_id="my_bigquery_table",
    dataset_id="my_bigquery_dataset",
    bigquery_client=client,
)