Bootcamp
LLM Function Calling

LLM Function Calling (Tool Use)

What happens when you give the power of function calling to your LLM?

How LLMs use Tools

How LLMs use Tools

When you want your LLM to do more than just text completion, you need to understand function calling. This powerful feature lets you interact with your application in a meaningful way. By teaching your models what your application (domain) can do and how to use it, you can unlock a lot of potential.

This tutorial will cover:

Tutorial Goals

In this tutorial you will:

  • Pick an LLM that can handle function calling effectively
  • Define functions (tools) that your model can understand
  • Map complex function types to simpler ones
  • Understand the complete process of prompting models for tool use

While you can get function calling to work using libraries like LangChain and LlamaIndex, understanding the underlying principles is crucial. This tutorial aims to give you a deeper understanding of function calling with LLMs and help you make your AI applications more powerful. Trust me, it's worth it!

LLMs and Function Calling

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References

Footnotes

  1. Introducing Llama-3-Groq-Tool-Use Models (opens in a new tab)

  2. Berkeley Function-Calling Leaderboard (opens in a new tab)