| # Hands-On AI: Building and Deploying LLM-Powered Apps | |
| This is the repository for the LinkedIn Learning course `Hands-On AI: Building and Deploying LLM-Powered Apps`. The full course is available from [LinkedIn Learning][lil-course-url]. | |
| _See the readme file in the main branch for updated instructions and information._ | |
| ## Lab1: Introduction to Chainlit | |
| We will be using [Chainlit](https://docs.chainlit.io/get-started/overview) as the frontend framework to develop our LLM Powered applications. Chainlit is an open-source Python package that makes it incredibly fast to build Chat GPT like applications with your own business logic and data. | |
| In this lab, we will put up a very simple Chainlit application that echos a user's query. | |
| For example, if user says | |
| ``` | |
| hello | |
| ``` | |
| Our Chainlit app will respond with | |
| ``` | |
| Received: hello | |
| ``` | |
| The learning objective is to familiarize with Chainlit's framework and to launch the application. | |
| ## Exercises | |
| We have created some template code in `app/app.py` in the `app folder`. | |
| 1. Please go through [Chainlit's documentation](https://docs.chainlit.io/get-started/pure-python) and answer the questions in `app/app.py` | |
| 2. Please lanuch the application by running the following command on the Terminal: | |
| ```bash | |
| chainlit run app/app.py -w | |
| ``` | |