Merge branch 'main' of https://github.com/AI-Maker-Space/Beyond-ChatGPT

README.md

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 # 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
+
+Navigate inside this repo
+
+### Install requirements using `pip install -r requirements.txt`?????????
+
+Add your OpenAI Key to `.env` file and save the file.
+
+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.
+
+It works! Let's ship it!
+
+
+### Deploy to Huggingface Spaces
+
+Login to Huggingface Spaces CLI
+
+``` bash
+huggingface-cli login
+```
+
+Follow the prompts to authenticate.
+
+
+
+Push Docker Image to Huggingface Container Registry
+
+```
+docker tag llm-app:latest huggingface/your-username/llm-app:latest
+docker push huggingface/your-username/llm-app:latest
+```
+
+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.