https://github.com/drisskhattabi6/chat-with-llm-locally

This Repo contains "Chat with LLM Locally" Web Application, Using Django
https://github.com/drisskhattabi6/chat-with-llm-locally

chat-llm chat-with-ai chat-with-llm chatbot django django-application django-project huggingface llm local-llm web-application

Last synced: 3 months ago
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This Repo contains "Chat with LLM Locally" Web Application, Using Django

• Host: GitHub
• URL: https://github.com/drisskhattabi6/chat-with-llm-locally
• Owner: drisskhattabi6
• Created: 2024-11-06T21:10:55.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-12-31T20:31:34.000Z (9 months ago)
• Last Synced: 2024-12-31T21:24:17.822Z (9 months ago)
• Topics: chat-llm, chat-with-ai, chat-with-llm, chatbot, django, django-application, django-project, huggingface, llm, local-llm, web-application
• Language: CSS
• Homepage:
• Size: 803 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Chat with LLM Locally

A Django-based application that enables local interaction with language models (LLMs) like GPT-2. The app allows users to initiate conversations, interact with locally downloaded LLMs, and manage conversations efficiently. This project serves as a foundation for experimenting with natural language processing models in a user-friendly interface.

## Features

- **Interactive Chat Interface**: Users can chat with an LLM in real-time.

- **Model Selection**: Support for multiple locally downloaded models, with the ability to switch between them dynamically.

- **Conversation Management**: Start new conversations, view previous chats, and delete existing ones.

- **Model Management**: Download and manage models from Hugging Face directly within the app.

- **Error Handling**: User-friendly error messages for issues like missing models or corrupted downloads.

## Requirements

- Python 3.8 or above

- Django 4.2+

- Transformers library by Hugging Face

- Hugging Face Hub authentication token

## Installation

1. Clone the repository:

   ```bash

   git clone https://github.com/drisskhattabi6/Chat-with-LLM-Locally.git

   cd Chat-with-LLM-Locally

   ```

2. Install dependencies:

   ```bash

   pip install -r requirements.txt

   ```

3. Set up the database:

   ```bash

   python manage.py migrate

   ```

4. Create a superuser for admin access (Optional):

   ```bash

   python manage.py createsuperuser

   ```

5. Start the development server:

   ```bash

   python manage.py runserver

   ```

6. Access the application at `http://127.0.0.1:8000`.

## Configuration

- Add your Hugging Face authentication token in the `login()` function in `views.py`:

   ```python

   login(token="your_huggingface_token")

   ```

## Usage

1. **Download a Model**:

   - Go to the "Download LLM" page and provide the name of the model (e.g., `gpt2`) to download.

   ![](imgs/img3.png)

2. **Start a Conversation**:

   - Click "New Conversation" to initiate a chat.

   ![](imgs/img1.png)

3. **Chat**:

   - Enter your messages and receive responses from the selected LLM.

   ![](imgs/img2.png)

4. **Switch Models**:

   - Choose a different model from the dropdown menu.

   ![](imgs/img4.png)

5. **Delete Conversations**:

   - Delete old conversations to keep the interface clean.

## Future Additions

1. **Support for Additional Model Architectures**: 

   - Extend compatibility to include models like T5, BERT, or custom fine-tuned models.

2. **User Authentication**:

   - Enable user-specific conversation history and settings.

3. **Conversation Export**:

   - Add functionality to export conversations as JSON, CSV, or text files.

4. **UI Enhancements**:

   - Improve the user interface with better responsiveness and real-time interaction.

5. **Model Performance Insights**:

   - Display metrics such as inference time and memory usage for each model.

## Collaboration

We welcome contributions to this project! If you have ideas or enhancements, feel free to submit an issue or a pull request. 

To contribute:

1. Fork the repository.

2. Create a new branch for your feature:

   ```bash

   git checkout -b feature/your-feature-name

   ```

3. Commit your changes:

   ```bash

   git commit -m "Add your feature description"

   ```

4. Push to your branch:

   ```bash

   git push origin feature/your-feature-name

   ```

5. Open a pull request on GitHub.

Thank you for helping make **Chat with LLM Locally** better for everyone!

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.