Using LlamaIndex for RAG in Python: Setting Up & Coding Indexing
Skills:
RAG Basics90%
Key Takeaways
Demonstrates setting up and coding LlamaIndex for RAG in Python
Original Description
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This is a preview of the video course, "Using LlamaIndex for RAG in Python". Discover how to use LlamaIndex with practical examples. This framework helps you build retrieval-augmented generation (RAG) apps using Python. LlamaIndex lets you load your data and documents, create and persist searchable indexes, and query an LLM using your data as context.
In this course, you’ll learn the basics of installing the package, setting AI providers, spinning up a query engine, and running queries against remote or local models.
This is a portion of the complete course, which you can find here: https://realpython.com/courses/using-llamaindex-for-rag-in-python/
The rest of the course covers:
- Coding Querying
- Examining the Code Output
- Exercise: Build a RAG Query Pipeline
- Refactoring Code
- Persisting
- Persisting Functionality
- Testing the Output
- Exercise: Persist or Rebuild an Index
- Looking at Next Steps
- Investigating Documents and Index
- Using LlamaIndex for RAG in Python (Quiz)
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