docs/versioned_docs/version-1.8.0/Components/bundles-weaviate.mdx
import Icon from "@site/src/components/icon"; import PartialParams from '@site/docs/_partial-hidden-params.mdx'; import PartialConditionalParams from '@site/docs/_partial-conditional-params.mdx'; import PartialVectorSearchResults from '@site/docs/_partial-vector-search-results.mdx'; import PartialVectorStoreInstance from '@site/docs/_partial-vector-store-instance.mdx';
<Icon name="Blocks" aria-hidden="true" /> Bundles contain custom components that support specific third-party integrations with Langflow.
This page describes the components that are available in the Weaviate bundle.
The Weaviate component reads and writes to Weaviate vector stores using an instance of Weaviate vector store.
:::tip For a tutorial using a vector database in a flow, see Create a vector RAG chatbot. :::
You can inspect a vector store component's parameters to learn more about the inputs it accepts, the features it supports, and how to configure it.
<PartialParams /> <PartialConditionalParams />For information about accepted values and functionality, see the Weaviate documentation or inspect component code.
| Name | Type | Description |
|---|---|---|
| weaviate_url | String | Input parameter. The default instance URL. |
| api_key | SecretString | Input parameter. The optional API key for authentication. |
| index_name | String | Input parameter. The optional index name. |
| text_key | String | Input parameter. The default text extraction key. |
| input | Data or DataFrame | Input parameter. The document or record. |
| cache_vector_store | Cache Vector Store | Input parameter. If true, the component caches the vector store in memory for faster reads. Default: Enabled (true). |
| embedding | Embeddings | Input parameter. Connect an embedding model component. |
| number_of_results | Integer | Input parameter. The number of search results to return. Default: 4. |
| search_by_text | Boolean | Input parameter. Indicates whether to search by text. Default: Disabled (false). |