tutorials

Tutorials Overview

The tutorials folder contains step‑by‑step guides to help you build your own LLM applications. These tutorials complement the code skeletons in the examples directory and cover core topics such as retrieval‑augmented generation, memory, conversational interfaces over custom data sources and fine‑tuning. Each subfolder includes a README with background concepts, setup instructions and links to relevant skeletons.

Available tutorials

• Quick Start – quickstart.md is a short guide on cloning the repository, installing dependencies and running your first agent.
• RAG Tutorials – rag_tutorials explains how to implement retrieval‑augmented generation pipelines, index documents and integrate retrieval into your agents.
• Memory Apps Tutorials – memory_apps introduces techniques for adding memory and state to your LLM applications.
• Chat with X Tutorials – chat_with_x_tutorials shows how to build conversational interfaces over data sources like GitHub, email, PDFs, research papers, Substack and YouTube.
• LLM Fine‑Tuning Tutorials – fine_tuning_tutorials covers when and how to fine‑tune models, including parameter‑efficient techniques and evaluation tips.

Feel free to contribute new tutorials or improve existing ones! Open an issue or pull request to share your ideas and help others learn.