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HealthAlly: AI-Powered Healthcare Chatbot for University Students �️

HealthAlly is an AI-powered healthcare chatbot designed to support university students by providing immediate assistance for physical & mental health concerns. Built with Python, Streamlit, and MongoDB, it offers personalized symptom diagnosis, first-aid room availability, mental health support, and doctor appointment booking—all tailored for campus life.

👉 Live Demo: Try HealthAlly Now

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✨ Key Features

Feature	Description
🤖 AI Symptom Checker	Diagnoses conditions based on symptoms using ML & suggests treatments.
💊 First-Aid Room Tracker	Checks medicine availability in campus first-aid rooms by department.
🧠 Mental Health Support	Provides stress-relief tips & connects to counseling services.
📅 Doctor Appointment Booking	Books consultations with campus doctors directly in-chat.
📚 Academic Wellness Tips	Advice on managing exam stress, sleep, and study habits.
24/7 Real-Time Assistance	Always available for urgent health queries.

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🎯 Target Audience

• University students needing quick health guidance.
• Those facing physical symptoms (fever, cough, headaches, etc.).
• Students struggling with stress, anxiety, or mental health challenges.
• Anyone seeking campus healthcare resources (medicines, first aid, doctors).

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🛠️ Installation

1. Clone the Repository

git clone https://github.com/AdesharaBrijesh/HealthAlly.git
cd HealthAlly

2. Set Up a Virtual Environment (Recommended)

python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Configure MongoDB

Create a config.py file:

# config.py
MONGO_URI = "your_mongodb_connection_url_here"  # Get this from MongoDB Atlas

⚠️ Never commit config.py to GitHub!

5. Run the App

streamlit run streamlit_app.py

Visit http://localhost:8501 in your browser.

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📂 Project Structure

HealthAlly/
├── data/                   # Health datasets (symptoms, treatments, etc.)
│   └── data.csv            
├── model/                  # AI models & embeddings
│   ├── llm.py              # Symptom diagnosis logic
│   ├── medicine.py         # Medicine search functions
│   └── *.pkl/.bin          # Pre-trained model files
├── pages/                  # Streamlit app pages
│   ├── 0_helthChat.py      # Main chat interface
│   ├── 1_appointment_booking.py  # Book doctors
│   └── ...                 # Other pages (history, profile, etc.)
├── styles/                 # Custom CSS
│   └── sidebar.css         
├── streamlit_app.py        # Main app entry point
├── config.py               # Secrets (ignored in Git)
└── requirements.txt        # Python dependencies

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🚀 How to Use

1. Select your department (e.g., Computer Science, Medicine).
2. Describe symptoms (e.g., "headache, fever for 2 days").
3. Get AI diagnosis with treatment & medicine suggestions.
4. Check first-aid room for medicine availability.
5. Book a doctor if symptoms persist.

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🤝 Contributing

We welcome contributions! Here’s how:

1. Fork the repo.
2. Create a branch: git checkout -b feature/your-idea
3. Commit changes: git commit -m "Add awesome feature"
4. Push: git push origin feature/your-idea
5. Open a Pull Request.

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📜 License

This project is licensed under the MIT License.

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🙏 Acknowledgements

• MongoDB Atlas for database hosting.
• Streamlit for the intuitive UI framework.
• Hugging Face for transformer models.
• FAISS for efficient similarity search.

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⚠️ Note: Always keep credentials (like MONGO_URI) private. Use .gitignore!