AI-Healthcare-Chatbot

🩺 AI Healthcare Chatbot

AI‑Healthcare‑Chatbot is a web‑based intelligent chatbot built using Python and Django. It offers 24/7 medical support, symptom checking, emergency assistance, and general healthcare guidance using Natural Language Processing (NLP). It is designed to improve accessibility, automate patient–chatbot interactions, and enhance digital health experiences.

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📚 Table of Contents

1. Features
2. Tech Stack
3. Architecture & Design
4. Installation & Setup
5. Usage
6. Configuration
7. API / Endpoints
8. Training / Data
9. Testing
10. Deployment
11. Future Enhancements
12. License
13. Contributing
14. Acknowledgments

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✨ Features

• ✅ Symptom checking: users describe symptoms and the chatbot gives likely causes or advice
• 🚨 Emergency assistance: guidance for urgent medical conditions
• 💡 Medical guidance & health tips
• 🌐 24/7 availability via web
• 🧠 Natural language understanding
• 💬 Web interface for users to interact with chatbot
• 📎 File upload and voice input options

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🛠️ Tech Stack

Layer	Technology
Backend	Python, Django
NLP / AI	Keyword Matching (optionally NLTK/spaCy)
Database	SQLite
Frontend	HTML, CSS, JavaScript (Django Templates)
APIs / Ext.	(Optional) Infermedica, Medline, etc.

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🧱 Architecture & Design

• MVC pattern via Django
• Chat Handler Module to:
  • Parse user input
  • Run NLP logic
  • Generate appropriate chatbot responses
• Data models:
  • Users, Sessions, Medical Knowledge Base, Logs
• Can be extended with:
  • API-based symptom databases (Infermedica, Healthwise)
  • ML model for response generation

User → Web UI → Django Views → Chat Handler → NLP Module → Response

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⚙️ Installation & Setup

Follow these steps to run the project locally:

# 1. Clone the repository
git clone https://github.com/devendrareddy2344/AI-Healthcare-Chatbot.git
cd AI-Healthcare-Chatbot

# 2. Create virtual environment
python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Apply migrations
python manage.py makemigrations
python manage.py migrate

# 5. (Optional) Load seed/sample data
# python manage.py loaddata initial_data.json

# 6. Start development server
python manage.py runserver

Open http://127.0.0.1:8000 in your browser.

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▶️ Usage

Once running:

• Enter symptoms like “I have a headache” or “chest pain”
• The chatbot will respond with predefined advice
• Voice and file upload options enhance the experience

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🔧 Configuration

• All chatbot logic is inside:
  healthcare_chatbot/views.py
• Add/edit keywords and responses in chatbot logic (or link to an API)
• Static assets are in the /static/ folder
• HTML templates in /templates/

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📡 API / Endpoints

This version does not use REST APIs but you can extend with:

Route	Method	Description
/	GET	Landing page
/chat/	POST	User sends message to chatbot
/upload/	POST	Upload medical reports (optional)
/voice/	POST	Capture speech input

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📁 Training / Data

Currently uses:

• Rule-based matching from symptom keywords
• No ML model or data training required
  Future enhancement can integrate:
• Custom intent classification model
• External symptom-checker APIs

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✅ Testing

To test:

python manage.py test

Add unit tests in healthcare_chatbot/tests.py

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🚀 Deployment

Free Deployment Options:

• Render
• Railway
• Heroku
• PythonAnywhere

These platforms support Django and offer free plans.

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🔮 Future Enhancements

• Integrate external symptom checker APIs (e.g. Infermedica)
• Add a trained ML model for better response generation
• Use spaCy/NLTK for NLP parsing
• User login and chat history
• Deploy with HTTPS and production DB (PostgreSQL)
• Chatbot UI upgrade with React or Vue

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🪪 License

This project is licensed under the MIT License.
Feel free to use, modify, and share with attribution.

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🤝 Contributing

Contributions are welcome!

To contribute:

• Fork this repo
• Create a new branch
• Make changes and commit
• Open a pull request

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🙏 Acknowledgments

• Django & Python Community
• OpenAI (for GPT inspiration)
• Infermedica API (for future integration)
• Bootstrap / Tailwind CSS (optional styling)

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📊 Dashboards & Screenshots

🏠 Welcome Page

Description: Intro page that welcomes users to the chatbot. Clear call-to-action to start consultation.

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🏠 Home Page

Description: Clean layout guiding users to chat. Navigation is simple and beginner-friendly.

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🗣️ Voice Input Feature

Description: Allows users to speak instead of typing. Helpful for elderly or visually impaired users.

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📄 File Upload – Add Files

Description: Option to upload reports, prescriptions, or files for context.

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📂 File Upload Confirmation

Description: Shows that a file was successfully uploaded and received by the system.

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👨‍💻 Author

Devendra Reddy
🔗 GitHub Profile

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📁 Repository Structure

AI-Healthcare-Chatbot/
├── chatbot-images/           # Project screenshots
├── healthcare_chatbot/       # Django app core
├── static/                   # CSS, JS
├── templates/                # HTML pages
├── db.sqlite3                # SQLite database
├── requirements.txt          # Dependencies
└── manage.py

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🎓 Ideal for students, healthcare hackathons, and prototyping real-world AI chatbot solutions.