---------------------- The best way to teach LLM programming using LlamaIndex is to start with the Understanding LlamaIndex series of tutorials. This series provides bite-sized tutorials on every stage of building an LLM application, making it a great starting point for both beginners and experienced programmers new to LlamaIndex source ().
LlamaIndex provides a unified interface for defining LLM modules, whether it’s from OpenAI, Hugging Face, or LangChain. This interface supports text completion and chat endpoints, streaming and non-streaming endpoints, and synchronous and asynchronous endpoints source ().
LlamaIndex also comes with a set of built-in, battle-tested prompts that handle the tricky work of getting a specific LLM to correctly handle and format data. These prompts can be customized as needed source ().
For more advanced users, LlamaIndex provides tools for fine-grained evaluation and experiment tracking to systematically diagnose issues source ().
Finally, LlamaIndex offers a guide on how to create a unified query framework over your indexes, which can be useful for handling complex queries source (). ---------------------- Note: you can ask me a follow up question by @ mentioning me again :speech_balloon: ----------------------
