WeaviateSink
class is designed to integrate with the Weaviate vector database, storing vectors produced from the Neum AI pipeline and retrieving them for semantic search operations.
Properties
Required properties:url
: The URL of the Weaviate instance.api_key
: The API key for authentication with the Weaviate service.class_name
: The name of the class in Weaviate to store the data. Can be defined to any string you want.
num_workers
: The number of workers used for batch processing.shard_count
: The number of shards for the Weaviate class.batch_size
: The number of vectors to store in a single batch.is_dynamic_batch
: A flag indicating if batching should adapt based on the response time of the Weaviate instance.batch_connection_error_retries
: The number of retries for batch connection errors.