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Chlorobiota - Plant Identification & Research Assistant System

An AI system that identifies plants by scientific, local, and family names using image inputs. Includes a research assistant chat interface where users can ask questions about taxonomy, plant traits and more.


📌 Overview

Built to support researchers with fast classification, structured data outputs, and contextual insights. Designed to improve plant identification accuracy and streamline research workflows.


✨ Features

  • User authentication
  • Responsive UI
  • Real-time notifications
  • REST API integration
  • Plant Identification
  • Research assistant

🛠 Tech Stack

Frontend

  • React
  • Tailwind CSS
  • Typescript

Backend

  • Node.js
  • Next.js
  • Python
  • Fast API

Database

  • Postgresql

Deployment

  • Vercel / Render

📷 Screenshots

Home Page

image

Login Page

image

Dashboard

image

Main Page

image

🚀 Installation

Clone the repository:

git clone https://github.com/Muhozgu/chlorobiota.git

Go to the project folder:

cd chlorobiota/frontend

Install dependencies:

npm install

Start the development server:

npm start
npm run dev

Run the backend:

cd chlorobiota/backend
python -m uvicorn main:app --reload --host 127.0.0.1 --port 8000

📖 Usage

  1. Sign up or log in
  2. Create navigate to the loggin page
  3. Upload an plant image that you would like to identifier
  4. Navigate to the research assistant interface
  5. Start asking any plant related question based on your goals

📂 Project Structure

CHLOROBIOTA
│
├── backend/
│   ├── __pycache__/
│   ├── .venv/
│   ├── venv/
│   ├── .env
│   ├── .gitignore
│   ├── main.py
│   └── requirements.txt
│
├── frontend/
│   ├── node_modules/
│   ├── src/
│   ├── .env
│   ├── ATTRIBUTIONS.md
│   ├── default_theme.css
│   ├── index.html
│   ├── package-lock.json
│   ├── package.json
│   ├── pnpm-workspace.yaml
│   ├── postcss.config.mjs
│   ├── README.md
│   └── vite.config.ts

⚙️ Environment Variables

Create a .env file in the root directory:

PORT=8000
GROQ-API-KEY=your_qroq_api_key

🧪 Testing

Run tests using:

npm test

🔮 Future Improvements

  • Add mobile app
  • Add a RAG for 200+ pages book
  • Add Online Learning features

🤝 Contributing

Contributions are welcome!

Steps:

  1. Fork the repository
  2. Create a new branch
  3. Commit your changes
  4. Open a Pull Request

📜 License

This project is licensed under the MIT License.


👨‍💻 Author

Guy Muhoza


⭐ Support

If you like this project, give it a star and a follow!

About

An AI system that identifies plants by scientific, local, and family names using image and text inputs. Includes a research assistant chat interface where users can ask questions about taxonomy and plant traits. Built to support researchers with fast classification and structured data output. ⚠️Qwen API is broken- being fixed !!!

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