README.md

# 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)