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

# Weaviate

## Credentials

Open the file named `io_config.yaml` at the root of your Mage project and enter weaviate required fields:

```yaml theme={"system"}
version: 0.1.1
default:
  WEAVIATE_ENDPOINT: https://some-endpoint.weaviate.network
  WEAVIATE_INSTANCE_API_KEY: YOUR-WEAVIATE-API-KEY
  WEAVIATE_INFERENCE_API_KEY: YOUR-OPENAI-API-KEY
  WEAVIATE_COLLECTION: collectionn_name
```

## Required Weaviate Libraries

Add `weaviate-client==3.25.3` into `requirements.txt` to install the required weaviate library.

## Using Python block

1. Create a new pipeline or open an existing pipeline.
2. Add a data loader or data exporter with Template. Under "Databases" category you can
   find the "Weaviate" template. Then use corresponding load and export functions.

* data loader arguments:
  * properties (List): list of columns to load.
  * collection (str): name of the collection. Defaults to the name defined in io\_config.yaml.
  * with\_limit (int): limit number of results returned.
  * with\_text (str): text to query.

* data exporter arguments:
  * df (DataFrame): data frame to write.
  * collection (str): name of the collection.

3. Add your customized code into the loader, exporter or add extra transformer blocks.
4. Run the block.