> ## Documentation Index
> Fetch the complete documentation index at: https://docs.neum.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# WeaviateSink

> WeaviateSink facilitates the storage and retrieval of vectorized data in the Weaviate vector database, allowing for efficient semantic search capabilities.

The `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.

Optional properties:

* `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.

<CodeGroup>
  ```python Local Development
  from neumai.SinkConnectors import WeaviateSink

  # Initialize the WeaviateSink connector with necessary information
  weaviate_sink = WeaviateSink(
      url = "your-weaviate-url",
      api_key = "your-api-key",
      class_name = "your-class-name",
      num_workers = 2,
      shard_count = 4,
      batch_size = 100,
      is_dynamic_batch = True,
      batch_connection_error_retries = 3
  )

  ```

  ```json Cloud
  {
      "sink": {
          "sink_name":"WeaviateSink",
          "sink_information":{
              "url": "your-weaviate-url",
              "api_key": "your-api-key",
              "class_name": "your-class-name",
              "num_workers": 2,
              "shard_count": 4,
              "batch_size": 100,
              "is_dynamic_batch": True,
              "batch_connection_error_retries": 3
          }
      }
  }
  ```
</CodeGroup>