| # 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._ | |
| ## Lab3: Enabling Load PDF to Chainlit App | |
| Building on top of the current simplified version of ChatGPT using Chainlit, we now going to add loading PDF capabilities into the application. | |
| NowNow we have a web interface working, we will now add an LLM to our Chainlit app to have our simplified version of ChatGPT. We will be using [Langchain](https://python.langchain.com/docs/get_started/introduction) as the framework for this course. It provides easy abstractions and a wide varieties of data connectors and interfaces for everything LLM app development. | |
| In this lab, we will be adding an Chat LLM to our Chainlit app using Langchain. | |
| ## Exercises | |
| We will build on top of our existing chainlit app code in `app/app.py` in the `app` folder. As in our previous app, we added some template code and instructions in `app/app.py` | |
| 1. Please go through the exercises in `app/app.py`. | |
| 2. Please lanuch the application by running the following command on the Terminal: | |
| ```bash | |
| chainlit run app/app.py -w | |
| ``` | |
| ## Solution | |
| Please see `app/app.py`. | |
| Alternatively, to launch the application, please run the following command on the Terminal: | |
| ```bash | |
| chainlit run app/app.py -w | |
| ``` | |
| ## References | |
| - [Langchain's Prompt Template](https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/#chatprompttemplate) | |
| - [Langchain documentation](https://python.langchain.com/docs/modules/chains/foundational/llm_chain#legacy-llmchain) | |
| - [Chainlit's documentation](https://docs.chainlit.io/get-started/pure-python) | |