/Chatbot-with-Google-Gemini-LLM-Model

Welcome to my project, LLM-Model-using-Google-Gemin, where I merge advanced Large Language Models (LLM) with Google's Gemini framework to create a versatile chatbot. This bot excels in delivering conversational experiences that mimic human interaction, suitable for everything from customer service to education.

Primary LanguagePython

LLM-Model-using-Google-Gemini

Welcome to my project, LLM-Model-using-Google-Gemin, where I merge advanced Large Language Models (LLM) with Google's Gemini framework to create a versatile chatbot. This bot excels in delivering conversational experiences that mimic human interaction, suitable for everything from customer service to education.

#To get API KEY #Follow this link to get your own API Key and it's absolutely free. https://aistudio.google.com/app/apikey

Adding API KEY Add your API key into the .env file

  1. Download the neccessary pacakages by running pip install -r requirements.txt

  2. Run the app using streamlit

streamlit run Gemini_Pro_Vision.py ##To run the pro vision model (Images).

streamlit run Gemini_Pro.py ##To run the Pro model (Text).

streamlit run Gemini_QA.py ##To run the Q&A Model.

##You can use your any favourite IDE to run this project.

Building the docker image

(Note: Run as administrator on Windows and remove "sudo" in commands)

  1. Important - Make sure you have installed Docker on your PC:
  • Linux: Docker
  • Windows/Mac: Docker Desktop
  1. Start Docker:
  • Linux (Home Directory): 
    sudo systemctl start docker
  • Windows: You can start Docker engine from Docker Desktop.
  1. Build Docker image from the project directory:
docker build -t Image_name .

(Note: Rerun the Docker build command if you want to make any changes to the code files and redeploy.)

Running the container & removing it

  1. witch to Home Directory:
cd ~

List the built Docker images

docker images
  1. Start a container:
docker run -p 80:80 Image_ID

  1. This will display the URL to access the Streamlit app (http://0.0.0.0:80). Note that this URL may not work on Windows. For Windows, go to http://localhost/.

  2. In a different terminal window, you can check the running containers with:

docker ps
  1. Stop the container:
  • Use ctrl + c or stop it from Docker Desktop.
  1. Check all containers:
docker ps -a
  1. Delete the container if you are not going to run this again:
docker container prune

Pushing the docker image to Docker Hub

  1. Sign up on Docker Hub.

  2. Create a repository on Docker Hub.

  3. Log in to Docker Hub from the terminal. You can log in with your password or access token.

docker login
  1. Tag your local Docker image to the Docker Hub repository:
docker tag Image_ID username/repo-name:tag
  1. Push the local Docker image to the Docker Hub repository:
docker push username/repo-name:tag

(If you want to delete the image, you can delete the repository in Docker Hub and force delete it locally.)

  1. Command to force delete an image (but don't do this yet):
docker rmi -f IMAGE_ID