QuizWiz

QuizWiz is an advanced, AI-powered chatbot creation platform that enables users to build, deploy, and interact with custom chatbots. Leveraging cutting-edge natural language processing technologies, QuizWiz offers a user-friendly interface for creating intelligent conversational agents tailored to specific domains or purposes.

Table of Contents

1. Features
2. Demo
3. Prerequisites
4. Installation
5. Configuration
6. Usage
7. Project Structure
8. Technologies Used
9. API Reference
10. Deployment
11. Contributing
12. Support
13. License

Features

• Custom Chatbot Creation: Design chatbots with unique personalities and knowledge bases.
• Document Processing: Upload and process various document types (PDF, TXT, DOCX, etc.) to train your chatbot.
• Web-based Interface: User-friendly interface for bot creation and interaction.
• Advanced AI Integration: Utilizes state-of-the-art AI models for natural language understanding and generation.
• Scalable Architecture: Built on PostgreSQL for efficient data storage and retrieval.
• Cloud Integration: Seamless integration with Cloudinary for image and file management.
• Customizable Responses: Fine-tune your chatbot's responses for specific use cases.
• Multi-language Support: Create chatbots in various languages.
• Analytics Dashboard: Track chatbot performance and user interactions.

Demo

• Free Usage: Experience QuizWiz in action at HuggingFace Space
• Official Website: Learn more about QuizWiz at Official Website

Prerequisites

Ensure you have the following installed:

• Python 3.8+
• PostgreSQL 12+
• Node.js 14+ (for frontend development)
• Git

Installation

1. Clone the repository:

   git clone https://github.com/shahdivax/QuizWiz.git
   cd QuizWiz/custombot
   

2. Set up a Python virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
   

3. Install required Python packages:

   pip install -r requirements.txt
   

4. Set up the PostgreSQL database:

   createdb quizwiz_bot_data
   

5. Install frontend dependencies (if applicable):

   cd frontend
   npm install
   

Configuration

1. Create a .env file in the root directory with the following variables:

   POSTGRESQL_URI=postgresql://username:password@localhost:5432/quizwiz_bot_data
   CLOUDINARY_NAME=your_cloudinary_name
   CLOUDINARY_API=your_cloudinary_api_key
   CLOUDINARY_SECRET=your_cloudinary_secret
   FLASK_SECRET_KEY=your_secret_key
   AI_MODEL_API_KEY=your_ai_model_api_key
   

2. Update config.py with any additional settings specific to your deployment.

Usage

Running the Application

1. Start the Flask development server:

   python run.py
   

2. Access the QuizWiz interface at http://localhost:5000

Creating a Chatbot

1. Navigate to the "Create Bot" page.
2. Provide a name and description for your chatbot.
3. Upload a logo (optional).
4. Upload training documents (PDF, TXT, DOCX, etc.).
5. Configure any additional settings (language, response style, etc.).
6. Click "Create Bot" to generate your custom chatbot.

Interacting with Your Chatbot

1. Go to the chat interface.
2. Select your chatbot from the list of available bots.
3. Start chatting! Your bot will respond based on its training.

Managing Your Chatbots

1. Access the bot management dashboard.
2. View analytics, update training data, and adjust settings for your bots.

Project Structure

QuizWiz/
├── custombot/
│   ├── app/
│   │   ├── __init__.py
│   │   ├── models.py
│   │   ├── routes.py
│   │   └── utils.py
│   ├── bots/
│   ├── data/
│   ├── static/
│   │   ├── css/
│   │   ├── images/
│   │   └── js/
│   ├── templates/
│   │   ├── home.html
│   │   └── index.html
│   ├── tests/
│   ├── .env
│   ├── config.py
│   ├── requirements.txt
│   └── run.py
├── frontend/  # If separate frontend exists
│   ├── src/
│   ├── public/
│   └── package.json
├── docs/
├── .gitignore
├── LICENSE
└── README.md

Technologies Used

• Backend: Flask, SQLAlchemy, psycopg2
• Database: PostgreSQL
• AI/ML: LlamaIndex, Gemini Embedding, Gemini LLM
• Frontend: HTML, CSS, JavaScript (potentially React or Vue.js)
• Cloud Services: Cloudinary, Render (for deployment)
• Version Control: Git

API Reference

Document your API endpoints here, for example:

• POST /api/create-bot: Create a new chatbot
• GET /api/bots: List all chatbots
• POST /api/chat: Send a message to a chatbot

Refer to the full API documentation for detailed information on request/response formats.

Deployment

QuizWiz is deployed on Render. To deploy your own instance:

1. Create a Render account and set up a new Web Service.
2. Connect your GitHub repository to Render.
3. Configure environment variables in Render dashboard.
4. Deploy the application.

For detailed deployment instructions, refer to the Deployment Guide.

Contributing

We welcome contributions to QuizWiz! Please follow these steps:

1. Fork the repository
2. Create a new branch (git checkout -b feature/AmazingFeature)
3. Make your changes
4. Commit your changes (git commit -m 'Add some AmazingFeature')
5. Push to the branch (git push origin feature/AmazingFeature)
6. Open a Pull Request

Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

Support

For support, please open an issue in the GitHub repository or contact our support team at support@quizwiz.com.

License

This project is licensed under the MIT License - see the LICENSE file for details.