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langflow/docs/versioned_docs/version-1.10.0/Components/bundles-pinecone.mdx
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---
title: Pinecone
slug: /bundles-pinecone
---
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**](/components-bundle-components) contain custom components that support specific third-party integrations with Langflow.
This page describes the components that are available in the **Pinecone** bundle.
## Pinecone vector store
The **Pinecone** component reads and writes to Pinecone vector stores using an instance of `PineconeVectorStore`.
<details>
<summary>About vector store instances</summary>
<PartialVectorStoreInstance />
</details>
<PartialVectorSearchResults />
:::tip
For a tutorial using a vector database in a flow, see [Create a vector RAG chatbot](/chat-with-rag).
:::
### Pinecone vector store parameters
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 [Pinecone documentation](https://docs.pinecone.io/home) or inspect [component code](/concepts-components#component-code).
| Name | Type | Description |
| ----------------- | ------------ | ----------------------------------------- |
| index_name | String | Input parameter. The name of the Pinecone index. |
| namespace | String | Input parameter. The namespace for the index. |
| distance_strategy | String | Input parameter. The strategy for calculating distance between vectors. |
| pinecone_api_key | SecretString | Input parameter. The API key for Pinecone. |
| text_key | String | Input parameter. The key in the record to use as text. |
| search_query | String | Input parameter. The query for similarity search. |
| ingest_data | JSON | Input parameter. The data to be ingested into the vector store. |
| embedding | Embeddings | Input parameter. The embedding function to use. |
| number_of_results | Integer | Input parameter. The number of results to return in search. |