Pinecone

Upsert embedded data and perform similarity search upon query using Pinecone, a leading fully managed hosted vector database.

Prerequisite

1. Register an account for Pinecone

2. Click Create index

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)

4. Click Create Index

Setup

1. Get/Create your API Key

2. Add a new Pinecone node to canvas and fill in the parameters:

   • Pinecone Index

   • Pinecone namespace (optional)

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

4. Add additional nodes to canvas and start the upsert process

   • Document can be connected with any node under Document Loader category

   • Embeddings can be connected with any node under Embeddings category

5. Verify from Pinecone dashboard to see if data has been successfully upserted:

Resources

• LangChain Pinecone vectorstore integrations

  • Python

  • NodeJS

• Pinecone LangChain integration

• Pinecone Flowise integration

• Pinecone official clients