Canopy: A New RAG Framework for Easy Top-Tier Performance

Explore the new retrieval augmented generation (RAG) framework Canopy, developed by the Pinecone GenAI team, in this 15-minute video tutorial. Learn how to achieve top-tier RAG performance easily without needing to understand every component in the pipeline. Follow along as the tutorial covers Canopy setup, data input formatting, upserting process, and using the Canopy CLI for chatting. Compare RAG performance to LLM-only approaches and discover techniques for handling complex queries in RAG. Access the provided GitHub repository for code examples and further exploration of the Canopy framework.

Canopy RAG Framework
Canopy Setup
Data Input to Canopy
Upserting with Canopy
Chatting with Canopy CLI
RAG vs. LLM only
Handling Complex Queries in RAG