Django Ollama Chat App

This Django project showcases the power of building local AI-powered chat applications using the Ollama library and Meta's Llama 3 model

Accompanying post with additional info here

Key Features

• Local AI : Leverages Ollama to run the Llama 3 model locally
• Django Framework: Built on the Django web framework
• Real-time Streaming: Chat interface displays AI responses as they are generated
• Open Source: Fully open-source code, allowing you to explore, modify, and extend the project to your liking

Getting Started

1. Clone the Repository:

   git clone https://github.com/scoutapp/ollama-django
   cd your-repo-name
   

2. Start Ollama: (If you haven't already)

   docker pull ollama/ollama
   docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
   docker exec -it ollama ollama run llama3
   

3. Set Up Virtual Environment:

   python3 -m venv env
   source env/bin/activate
   

4. Install Dependencies:

   pip install -r requirements.txt 
   

5. Run the Server:

   python manage.py runserver
   

Chat Away: Open your browser and visit http://localhost:8000/chat/ to start chatting with your AI

Project Structure

chat/: Contains the Django app for the chat interface and Ollama interaction. templates/: HTML template for the chat interface. requirements.txt: Lists the project dependencies.

Future Enhancements

Improved Styling: CSS enhancements for a more visually appealing chat interface. Reduced Latency: Optimization techniques to minimize response delays. Additional Models: Integration of other Ollama-supported models. Multimodal AI: Exploration of combining text with images and audio.

Contributing

Contributions are welcome! Feel free to open issues, submit pull requests, or share your feedback to help improve this project.

Acknowledgements

Ollama: For providing a powerful library for local AI model execution.

Django: For the excellent web development framework.

Llama 3: The open-source AI model that powers this chat app.