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 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. :::

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 or inspect 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.