docs.langflux.space
  • Welcome to LangFlux
  • Using LangFlux
    • API
    • Streaming
    • Embed
    • Variables
  • Configuration
    • Auth
      • Chatflow Level
    • Rate Limit
  • Integrations
    • Cache
      • InMemory Cache
    • Chains
      • Conversational Retrieval QA Chain
      • Vectara QA Chain
    • Document Loaders
      • S3 File Loader
      • PDF Files
    • Chat Models
      • Azure ChatOpenAI
      • ChatLocalAI
      • Google VertexAI
    • Embeddings
      • Azure OpenAI Embeddings
      • LocalAI Embeddings
    • Memory
      • Short Term Memory
      • Long Term Memory
        • Zep Memory
      • Threads
    • Text Splitters
      • Character Text Splitter
    • Tools
      • Custom Tool
    • Vector Stores
      • Chroma
      • Pinecone
      • Elastic
      • Qdrant
      • SingleStore
      • Supabase
      • Vectara
    • Utilities
      • Set/Get Variable
      • If Else
    • External Integrations
      • Zapier Zaps
  • Use Cases
    • Web Scrape QnA
    • Webhook Tool
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  • Prerequisite
  • Setup
  • Resources

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  1. Integrations
  2. Vector Stores

Pinecone

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Last updated 1 year ago

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Prerequisite

  1. Register an account for

  2. Click Create your first index

  1. Fill in required fields:

    • Index Name, name of the index to be created. (e.g. elon-musk)

    • 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 and Environment\

  2. 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 and Environment

  1. Start the upsert process:

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

Resources

Document can be connected with any node under category

Embeddings can be connected with any node under category

Document Loader
Embeddings
LangChain JS Pinecone
Pinecone Node.JS
Pinecone