Beyond-ChatGPT

Chainlit App using Python streaming for Level 0 MLOps

LLM Application with Chainlit, Docker, and Huggingface Spaces In this guide, we'll walk you through the steps to create a Language Learning Model (LLM) application using Chainlit, then containerize it using Docker, and finally deploy it on Huggingface Spaces.

Prerequisites A GitHub account Docker installed on your local machine A Huggingface Spaces account

Building our App

Clone this repo.

git clone https://github.com/AI-Maker-Space/Beyond-ChatGPT.git

Navigate inside this repo

cd Beyond-ChatGPT

Install the packages required for this python envirnoment in requirements.txt.

pip install -r requirements.txt

Open your .env file. Replace the ### in your .env file with your OpenAI Key and save the file.

OPENAI_API_KEY=sk-###

Let's try deploying it locally. Make sure you're in the python environment where you installed Chainlit and OpenAI.

Run the app using Chainlit

chainlit run app.py -w

Great work! Let's see if we can interact with our chatbot.

Time to throw it into a docker container a prepare it for shipping

Build the Docker image. We'll tag our image as llm-app using the -t parameter. The . at the end means we want all of the files in our current directory to be added to our image.

docker build -t llm-app .

Run and test the Docker image locally using the run command. The -pparameter connects our host port # to the left of the : to our container port # on the right.

docker run -p 7860:7860 llm-app

Visit http://localhost:7860 in your browser to see if the app runs correctly.

Great! Time to ship!

Deploy to Huggingface Spaces

Make sure you're logged into Huggingface Spaces CLI

huggingface-cli login

Follow the prompts to authenticate.

Deploy to Huggingface Spaces

Deploying on Huggingface Spaces using a custom Docker image involves using their web interface. Go to Huggingface Spaces and create a new space, then set it up to use your Docker image from the Huggingface Container Registry.

Access the Application

Once deployed, access your app at:

ruby Copy code https://huggingface.co/spaces/your-username/llm-app Conclusion You've successfully created an LLM application with Chainlit, containerized it with Docker, and deployed it on Huggingface Spaces. Visit the link to interact with your deployed application.