Building an Open LLM App Using Hermes 2 Pro Deployed Locally

In my previous tutorial, I showed you how to bring real-time data to LLMs through function calling, using OpenAI’s latest LLM GPT-4o. In this followup, I will look at function calling using Hermes 2 Pro – Llama-3 8B, a powerful LLM developed by Nous Research and based on Meta’s Llama 3 architecture, with 8 billion parameters. It’s an open model and we will run it on Hugging Face’s Text Generation Inference.

As with the previous post, we will integrate the API from Flightaware.com — with the LLM to track flight status in real-time.

FlightAware’s AeroAPI is a perfect tool for developers to gain access to comprehensive flight information. It enables real-time flight tracking, historical and future flight data, and flight searches by various criteria. The API presents data in a user-friendly JSON format, making it highly usable and integrable. We will invoke the REST API to get the real-time status of a flight based on the prompt sent to an LLM by the user.

What Is Hermes 2 Pro?

Hermes 2 Pro – Llama-3 8B excels at natural language processing tasks, creative writing, coding assistance, and more. One of its standout features is its exceptional function-calling capability, which allows it to execute external functions and retrieve information related to stock prices, company fundamentals, financial statements, and more.

Read the entire article at?The New Stack

Janakiram MSV?is an analyst, advisor, and architect. Follow him on?Twitter,??Facebook?and?LinkedIn.