QuantumData

QuantumData is an AI-based qualitative research tool designed to help researchers efficiently find and extract relevant information from their custom documents store for a smooth and efficient qualitative research experience using generative AI.

Please star ⭐ the repo if you want us to continue developing and improving the qualitative research tool! 😀

🥇 Features

• AI-powered document retrieval
• Natural language processing to understand user queries
• Retrieval Augmented Generation (RAG) based extractions
• Supports multiple file formats (PDF, DOCX, TXT)

➡️ Coming Soon

• Create Account
• Sign in with Email and Password
• User-friendly web interface
• Database integration
• Cloud Deployement Ready
• Sign in with Google [Setting up Google OAuth]
• Responsive UI
• Comet Haley

🖥️ Preview

See & Interact with Figma Prototype

🛠️ Getting Started

Prerequisites

• Node.js (v14 or later)
• npm (v6 or later)
• OpenAI API key

Installation

1. Clone the repository

   git clone https://github.com/ali-amaan/QuantumData.git
   cd QuantumData

2. Install dependencies

   npm install

3. Set up environment variables

   Create a .env file in the root directory and add your OpenAI API key:

   OPENAI_API_KEY=your_openai_api_key_here
   

4. Start the application

   npm start

   The application will be running at http://localhost:3000.

🚀 Usage

1. Upload your documents

   You can upload your research documents through the web interface. The application supports PDF, DOCX, and TXT formats.

2. Query the AI

   Enter your research question or query in natural language. The AI will process your query and retrieve relevant documents.

3. View results

   The AI will display the relevant documents along with extracted information related to your query.

✨ Contributing

Guidelines

Thanks for taking the time to contribute! Contributions make the open-source community a fantastic place to learn, inspire, and create. Any contributions you make are greatly appreciated.

Please try to create bug reports that are:

• Reproducible. Include steps to reproduce the problem.
• Specific. Include as much detail as possible: which version, what environment, etc.
• Unique. Do not duplicate existing opened issues.
• Scoped to a Single Bug. One bug per report.

See Contributing Guide

Contributors

Steps For Contributing

We welcome contributions from the community! Here’s how you can help:

1. Fork the repository

   Click the "Fork" button at the top-right corner of this repository.

2. Clone your fork

   git clone https://github.com/your-username/QuantumData.git
   cd QuantumData

3. Create a new branch

   git checkout -b feature-branch-name

4. Make your changes

   Implement your changes and commit them with a clear and descriptive commit message.

5. Push to your fork

   git push origin feature-branch-name

6. Create a pull request

   Open a pull request on the original repository to merge your changes.

🛡️ License

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

🙏 Acknowledgements

• Professor Henri Schildt for initial concept and ideation as well as a working prototype

Contact

For any questions or suggestions, feel free to reach out to us via email.

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Made with ❤️ in Helsinki