Lesson 01: Introduction to RAG with LlamaIndex

In this lesson, you'll:

• Learn how to set up LlamaIndex
• Load documents and process them
• Create chunks and nodes for the index
• Create & Query the document using natural language
• Understand how RAG enhances LLM responses

🗺️ Roadmap

1. 🛠️ Hands-on: Load and process documents of a Wikipedia page (11_hands_on_problem.ipynb)
2. 🛠️ Hands-on: Create an index processing the Paul Graham essay (21_hands_on_problem.ipynb)
3. 🏆 Challenge: Process "complex" data and make an index (31_hands_on_challenge_problem.ipynb)

🎓 Key Concepts

• Document Loading
• Vector Indexing
• Query Processing
• Response Generation

🚀 Open the notebooks and let's get started!

Documentation: LlamaIndex.indexing