Getting Started with LLM Apps Development for Python Enthusiasts

Welcome to your guide on diving into the world of Large Language Models (LLM) app development! Whether you’re a student or a professional with a background in Python, this guide will help you set up your development environment and explore various aspects of creating LLM applications. We’ll cover everything from setting up Visual Studio Code to advanced topics like OpenAI function calling and extracting structured information from audio files with Azure OpenAI. Let’s get started!

Step 1: Download and Set Up Visual Studio Code

Download Visual Studio Code

An Integrated Development Environment (IDE) like Visual Studio Code (VS Code) is crucial for coding efficiently and effectively. VS Code offers a powerful and flexible interface for coding, debugging, and running applications. It supports numerous extensions that make Python development seamless.

Step 2: Getting Started with Python in VS Code

Getting Started with Python in VS Code

Follow the tutorial to set up Python in VS Code. This guide will walk you through installing the Python extension, configuring the Python interpreter, and running your first Python script in VS Code. This step ensures you have a robust setup for Python development.

Step 3: Developing with OpenAI and Python

OpenAI Python Quickstart

Now that VS Code is configured for Python, let’s dive into developing applications using OpenAI. This quickstart guide introduces you to the OpenAI platform, showing you how to set up your environment and make your first API call. We recommend using VS Code to follow along with the sample code provided.

Step 4: Developing Azure Functions with Python in VS Code

Create Your First Python Azure Function

Azure Functions allow you to run event-driven serverless code. This guide will show you how to create your first Azure Function using Python in VS Code. By the end of this tutorial, you’ll have a basic understanding of how to deploy serverless functions on Azure, integrating them with your Python applications.

Step 5: Advanced Topic - OpenAI Function Calling

OpenAI Function Calling Video

Function calling in OpenAI is a powerful feature that allows you to integrate LLMs with external functions, enabling complex workflows and enhanced interactivity. This video provides an in-depth look at function calling, explaining its significance and demonstrating practical applications.

Step 6: Advanced Topic - Extracting Structured Information with Azure OpenAI Whisper and GPT-4

Extracting Information with Azure OpenAI Whisper and GPT-4

Extracting structured information from recorded conversations can revolutionize how you interact with and analyze data. This post explores the integration of Azure OpenAI Whisper and GPT-4 models, showing you how to leverage these technologies to extract and utilize structured information effectively.

Conclusion

By following this guide, you should now be equipped to create your first online LLM API. While this post provides the foundational steps, future updates will include the finalized API. In the meantime, you’re encouraged to experiment and build your applications, leveraging the powerful tools and resources at your disposal. Happy coding!