Fast Prototyping of GenAI Apps with Streamlit

Welcome to the Fast Prototyping of GenAI Apps with Streamlit GitHub repository! This repository is designed to help you learn coding by working through various problems using the Avalanche dataset. Inside, you'll find all the necessary files and instructions to follow along with the accompanying video series.

Repository Structure

Upon opening this repository, you will find:

• data: Contains the Avalanche dataset needed for the course.

• Modules (M1, M2 and M3): There is a dedicated folder for each module of the course. Within these folders:

  • Code is organized by lessons.
  • Each lesson contains Python files or notebooks as used in the videos.
  • A lab folder is available with all necessary resources for lab activities.

• requirements.txt: Present where necessary to help you install all required dependencies for specific modules.

• Additional files:

  • .env.example: A sample environment file. Duplicate and rename to .env, then add your OpenAI API key.
  • README.md: This guide to help you get started.

Getting Started

To work with the course files, it's recommended to clone this repository to your local machine. This allows you to modify code as you proceed through the videos.

Instructions to Clone Repository

1. Sign in to your GitHub account.
2. Navigate to the main repo page.
3. Look for the green "Code" button near the top right.
4. Copy the repository address (it should start with "git...").
5. Using the command line, type: git clone [repository address] if you have git installed.
6. Alternatively, use GitHub Desktop by selecting File > Clone Repository.
7. After cloning, ensure your local copy of the repo is public to facilitate deployment on Snowflake later.

Utilizing the Course Files

This GitHub repository provides a straightforward project structure, pre-loaded with the necessary datasets and starter files. Each video corresponds to a file set under a naming convention like M1L1V1 (Module 1, Lesson 1, Video 1) for easy orientation.

You can either follow along with the provided files or write your own code as you progress. The video series typically builds upon previous sessions, allowing you to continue developing your solutions or refer to the provided working solutions within each lesson.

Happy coding!