🧠 MediGuru

MediGuru is an advanced web-based AI healthcare assistant that empowers users to speak their symptoms, upload medical images (like X-rays), and even analyze prescriptions—all through a simple, intuitive interface. Leveraging state-of-the-art speech-to-text, vision, and language models, MediGuru delivers:

• Professional, voice-based medical advice tailored to your symptoms and images
• Prescription analysis for uploaded prescriptions or medication lists
• Multi-modal AI that combines voice, text, and image understanding for holistic responses
• Natural, conversational interactions that feel like talking to a real doctor
• Instant audio feedback so you can listen to the AI doctor's response

Whether you need a quick check on your symptoms, a second opinion on a scan, or help understanding a prescription, MediGuru brings the power of modern AI to your healthcare journey—all from your browser.

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🖼️ Technical Architecture

Place the image file as technical_architecture.png in the project root or update the path as needed.

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🚀 Tech Stack

• Python 3.10+
• Gradio (web UI)
• gTTS (Google Text-to-Speech)
• Groq API (for transcription and LLM-based image analysis)
• pydub, scipy (audio processing)
• dotenv (environment variable management)
• Render (cloud deployment)

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✨ Features

• Voice Input: Speak your symptoms directly in the browser.
• Image Upload: Upload medical images (e.g., X-rays, scans).
• AI Diagnosis: Uses LLMs to analyze your symptoms and images, returning a concise, human-like doctor's response.
• Voice Output: Doctor's response is read aloud using gTTS.
• Web-based: No installation required for end users—just open the app in your browser.

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🛠️ Setup & Local Development

1. Clone the repository:

   git clone <your-repo-url>
   cd MediGuru

2. Create a virtual environment (recommended):

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

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   • Create a .env file in the project root:

     GROQ_API_KEY=your_groq_api_key_here

5. Run the app locally:

   python gradio_app.py

   • The app will be available at http://localhost:7860 by default.

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☁️ Deployment (Render)

1. Push your code to GitHub.
2. Create a new Web Service on Render:
   • Connect your GitHub repo.
   • Set the build command: pip install -r requirements.txt
   • Set the start command: python gradio_app.py
   • Add the environment variable GROQ_API_KEY in the Render dashboard.
3. Wait for deployment.
4. Access your app via the public Render URL!

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📝 Usage

• Speak your symptoms using the microphone input.
• Upload a medical image (optional).
• Receive a doctor's response in both text and voice.

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📁 Project Structure

MediGuru/
├── brain_of_the_doctor.py         # Image encoding & LLM analysis
├── gradio_app.py                 # Main Gradio web app
├── requirements.txt              # Python dependencies
├── render.yaml                   # Render deployment config
├── voice_of_the_doctor.py        # Text-to-speech (gTTS)
├── voice_of_the_patient.py       # Audio transcription (Groq)
└── ...

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👤 Author

Subhranil Mondal

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📜 License

This project is licensed under the GNU GPL v3.