Vector Database | Pinecone Create Index Tutorial Part2 - API Key, Metric...

Vector Database | Pinecone Create Index Tutorial Part2 - API Key, Metric, Dimension, Index Functions

📝 YouTube Description: In this Part of our Pinecone Vector Database Tutorial Series, we dive hands-on into setting up and managing a vector index in Pinecone — the cloud-native database for AI search!

🎯 What you'll learn in this video: 

  ✅ How to sign up and generate your Pinecone API Key

  ✅ What is an Index and why it’s crucial in vector search

  ✅ What is Dimension in a vector — and how to choose the right size

  ✅ How Metrics like cosine, dotproduct, and euclidean affect similarity search

  ✅ Embedding model compatibility and choosing correct dimensions (e.g., OpenAI vs HuggingFace)

  ✅ Full Python code walkthrough to create, connect, and manage Pinecone indexes

  ✅ What pinecone.Index() really does behind the scenes

  ✅ How to use the Pinecone Dashboard to track index creation, deletion, and status

  ✅ All major Python functions available to manipulate indexes:

    • create_index()

    • list_indexes()

    • delete_index()

    • Index().upsert()

    • Index().query()

    • Index().fetch()

    • Index().delete()

💡 Whether you're building AI-powered search, chatbots, or recommendation systems — understanding this step is foundational.

https://www.youtube.com/watch?v=fSN28mpYS70