llama-index vector_stores bigquery vector search integration
Project description
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
pip install llama-index-vector-stores-bigquery
💻 Example Usage
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,
)
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