DocPilot

DocPilot is a Flutter application designed to assist healthcare providers in recording, transcribing, and analyzing doctor-patient conversations. It leverages voice recognition, natural language processing, and AI to streamline medical documentation workflows.

Features

• Voice Recording: Capture doctor-patient conversations with a simple, intuitive interface
• Real-time Voice Transcription: Convert spoken conversations to text using Deepgram's Nova-2 model
• AI-Powered Analysis: Process transcribed conversations with Google's Gemini to generate:
  • Conversation summaries
  • Prescription suggestions
• Elegant UI: Beautiful gradient design with animated waveform visualization
• Export & Share: Save and share prescriptions with patients or other healthcare providers

Getting Started

For a detailed, step-by-step setup guide (including Windows, Android Studio, AVD, and common issues) see SETUP.md.

Prerequisites

• Flutter SDK 3.27+ (stable channel)
• Dart SDK 3.6+
• Android Studio (Hedgehog or newer) — needed for Android SDK and emulator
• API keys for:
  • Deepgram (speech-to-text)
  • Google Gemini (AI processing)

Installation

1. Clone the repository:

   git clone https://github.com/AOSSIE-Org/DocPilot.git
   cd DocPilot

2. Install dependencies:

   flutter pub get

3. Create a .env file in the root directory with your API keys:

   DEEPGRAM_API_KEY=your_deepgram_api_key
   GEMINI_API_KEY=your_gemini_api_key
   

   Important: Do NOT commit your .env file. It contains sensitive API keys. Use .env.example as a template and add .env to your .gitignore. For CI or shared environments, store secrets in your CI provider's secret management system or environment variables instead of committing them.

4. Run the app:

   flutter run

Project Structure

lib/
├── main.dart             # App entry point and main screen
├── screens/
│   ├── transcription_detail_screen.dart    # Displays raw transcription
│   ├── summary_screen.dart                 # Displays AI-generated summary
│   ├── prescription_screen.dart            # Displays AI-generated prescription
└── services/
    └── chatbot_service.dart                # Handles Gemini API integration

How It Works

1. Recording: The app uses the record package to capture audio from the device's microphone.
2. Transcription: Recorded audio is sent to Deepgram's API for accurate speech-to-text conversion.
3. AI Processing: The transcription is sent to Google's Gemini AI for:
   • Generating a concise summary of the medical conversation
   • Creating a prescription based on the conversation content
4. Visualization: Results are displayed in separate screens with Markdown formatting for better readability.
5. Export: Prescriptions can be saved and shared with the patient via various apps.

Dependencies

• flutter_dotenv: For managing environment variables
• record: For audio recording
• path_provider: For file management
• permission_handler: For handling device permissions
• http: For API requests
• flutter_markdown: For rendering formatted text
• share_plus: For sharing functionality

Permissions

The app requires the following permissions:

• Microphone: For recording audio
• Storage: For saving prescriptions (Android)

Customization

You can customize the app by:

• Modifying the theme colors in main.dart
• Adjusting the recording parameters in the _startRecording() method
• Changing the Gemini prompts in the _processWithGemini() method to get different outputs

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

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

Acknowledgments

• Deepgram for speech-to-text capabilities
• Google Gemini for AI processing
• Flutter team for the amazing framework

Future Enhancements

• Multi-language support
• Patient history integration
• Cloud synchronization
• Custom AI model fine-tuning for medical terminology
• Appointment scheduling integration
• Medical image analysis

Connect With AOSSIE

Stay connected and join the community:

• Website: https://aossie.org/
• GitHub: https://github.com/AOSSIE-Org
• X (Twitter): https://x.com/aossie_org
• YouTube: https://www.youtube.com/@AOSSIE-Org
• Discord: https://discord.com/invite/hjUhu33uAn