#Resources

LlamaIndex APIs move quickly—prefer the official docs. This page lists primary documentation, usual entry points, and related courses on this site.

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#Official

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#Where this course maps onto official docs

Older defaults are often gpt-3.5-turbo and text-embedding-ada-002. This tutorial’s samples use gpt-4o-mini and text-embedding-3-small. Diff against the current starter page before you upgrade.

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#Related courses on this site

A useful order: RAG course for principles → LlamaIndex for the data layer → LangChain or CrewAI when you need a heavier agent harness.

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#Tutorial index

1. LlamaIndex tutorial
2. Introduction
3. Installation
4. Quick Start
5. Loaders and Nodes
6. Indexes
7. Query Engines
8. Retrieval
9. Workflows
10. Vector Stores
11. Practical Examples

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#Suggested exercises

1. Run example 1 on 3–5 of your own Markdown files; explain one source_nodes hit
2. Add a read-only tool (e.g. today’s date) and watch when the agent calls it
3. Replace the in-memory index with Chroma PersistentClient; query after restart
4. Move chunk_size from 256 to 1024; compare cited chunks for the same question
5. Read official JokeFlow; add retrieval as an @step using only documented parameters

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#Contribute

This tutorial lives in Kenhuang Academy. When APIs change, open an issue or PR and update both docs/zh/llamaindex/ and docs/en/llamaindex/.