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

1. 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)

1. Click Create Index

Setup

1. Get/Create your API Key

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

   • Pinecone Index

   • Pinecone namespace (optional)

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

1. 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

1. 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