> For the complete documentation index, see [llms.txt](https://docs.flowiseai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.flowiseai.com/integrations/langchain/vector-stores/pinecone.md).

# Pinecone

## Prerequisite

1. Register an account for [Pinecone](https://app.pinecone.io/)
2. Click **Create index**

<figure><img src="/files/wdiUazY23RHKx9gvjmMV" alt=""><figcaption></figcaption></figure>

3. Fill in required fields:
   * **Index Name**, name of the index to be created. (e.g. "flowise-test")
   * **Dimensions**, size of the vectors to be inserted in the index. (e.g. 1536)

<figure><img src="/files/sBO7qYeSlwyrTN0i7EpP" alt="" width="527"><figcaption></figcaption></figure>

4. Click **Create Index**

## Setup

1. Get/Create your **API Key**

<figure><img src="/files/SrDhIuLYSVUO1OhqySjX" alt=""><figcaption></figcaption></figure>

2. Add a new **Pinecone** node to canvas and fill in the parameters:
   * Pinecone Index
   * Pinecone namespace (optional)

<figure><img src="/files/cxzIwv6924mp4srowlmw" alt="" width="279"><figcaption></figcaption></figure>

3. Create new Pinecone credential -> Fill in **API Key**

<figure><img src="/files/Yql4M4gdlY7htc0uD7MK" alt="" width="563"><figcaption></figcaption></figure>

4. Add additional nodes to canvas and start the upsert process
   * **Document** can be connected with any node under [**Document Loader**](/integrations/langchain/document-loaders.md) category
   * **Embeddings** can be connected with any node under [**Embeddings** ](/integrations/langchain/embeddings.md)category

<figure><img src="/files/MO795gz1DW6hu46hFqxs" alt=""><figcaption></figcaption></figure>

<figure><img src="/files/UsVelqbzTh3z329WMOq0" alt=""><figcaption></figcaption></figure>

5. Verify from [Pinecone dashboard](https://app.pinecone.io) to see if data has been successfully upserted:

<figure><img src="/files/QMt2aXc2PWvyPVnOpaXw" alt=""><figcaption></figcaption></figure>

6.

## Resources

* LangChain Pinecone vectorstore integrations
  * [Python](https://python.langchain.com/v0.2/docs/integrations/providers/pinecone/)
  * [NodeJS](https://js.langchain.com/v0.2/docs/integrations/vectorstores/pinecone)
* [Pinecone LangChain integration](https://docs.pinecone.io/integrations/langchain)
* [Pinecone Flowise integration](https://docs.pinecone.io/integrations/flowise)
* [Pinecone official clients](https://docs.pinecone.io/reference/pinecone-clients)