| @@ -1,5 +1,6 @@ | |||
| from typing import Optional, cast | |||
| import requests | |||
| import weaviate | |||
| from langchain.embeddings.base import Embeddings | |||
| from langchain.schema import Document, BaseRetriever | |||
| @@ -34,12 +35,15 @@ class WeaviateVectorIndex(BaseVectorIndex): | |||
| weaviate.connect.connection.has_grpc = False | |||
| client = weaviate.Client( | |||
| url=config.endpoint, | |||
| auth_client_secret=auth_config, | |||
| timeout_config=(5, 60), | |||
| startup_period=None | |||
| ) | |||
| try: | |||
| client = weaviate.Client( | |||
| url=config.endpoint, | |||
| auth_client_secret=auth_config, | |||
| timeout_config=(5, 60), | |||
| startup_period=None | |||
| ) | |||
| except requests.exceptions.ConnectionError: | |||
| raise ConnectionError("Vector database connection error") | |||
| client.batch.configure( | |||
| # `batch_size` takes an `int` value to enable auto-batching | |||