From the course: Hands-On AI: Building LLM-Powered Apps

Unlock the full course today

Join today to access over 25,200 courses taught by industry experts.

Challenge: Adding an LLM to the Chainlit app

Challenge: Adding an LLM to the Chainlit app - Python Tutorial

From the course: Hands-On AI: Building LLM-Powered Apps

Start my 1-month free trial Buy for my team

Challenge: Adding an LLM to the Chainlit app

“

- [Instructor] Now we have an API key, let's try to add large language model to our chat with PDF application. First, let's make a copy of .env.sample, rename it to.env like here and put your API key inside this quote. Now, to build a large language model application, we will use a framework called Langchain. Langchain is the most likely used framework to develop large language model applications. It orchestrates models, prompts, data sources, and outputs. The central idea here is a chain. A chain is an execution step in a large language model application. So it is the equivalent of a Lego block. So with Langchain, we turn building large language model applications into putting together many Lego blocks to make a castle to build an app. So go to app slash app.py and follow the instruction here. There are a series of exercises from creating a model, defining a prompt, building a chain, to integrating the chain into our chainlit application. Good luck.

Contents