Rume is a comprehensive, AI-driven ecosystem designed to facilitate seamless interactions between users and smart devices. The project is modular, consisting of three main components: Aiml, Device, and Mobile, each responsible for different aspects of the system. This architecture ensures scalability, maintainability, and ease of development.
Rume follows a microservices architecture, with each component encapsulating specific functionalities. This separation of concerns allows each module to be developed, tested, and deployed independently, enhancing the overall robustness and flexibility of the system.
Rume Ecosystem
├── Rume AI/ML
├── Rume Device
└── Rume Mobile
Rume Aiml is responsible for the artificial intelligence and machine learning functionalities of the Rume ecosystem. It handles tasks such as natural language processing, speech recognition, and response generation.
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Features:
- Speech-to-Text (STT)
- Text-to-Speech (TTS)
- Language Model Integration (e.g., GPT-4)
- AI Response Generation
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Technologies Used:
- FastAPI
- Uvicorn
- OpenAI API
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Repository: rume_aiml
Rume Device manages the hardware interactions and backend services that power the smart device functionalities. It orchestrates communication between various modules and ensures seamless operation of sensors, multimedia, and communication interfaces.
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Features:
- Sensor Data Handling
- Multimedia Management
- Real-Time Communication
- API Gateway
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Technologies Used:
- Docker Compose
- Python
- FastAPI
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Repository: rume_device
Rume Mobile provides the user interface through a mobile application, allowing users to interact with the Rume ecosystem. It communicates with the Rume Device backend to send commands and receive responses.
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Features:
- User Interface for Device Control
- Real-Time Notifications
- Command Execution
- Multimedia Playback
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Technologies Used:
- React Native
- WebSockets
- Bluetooth Integration
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Repository: rume_mobile
- Rume AI/ML: Maintained by @ayoung206
- Rume Device: Maintained by @jhwanchoi, @JinJis
- Rume Mobile: Maintained by @jhwanchoi, @JinJis
This project is licensed under the MIT License.
We welcome contributions from the community! Please see our Contributing Guidelines for more information.
For questions, suggestions, or support, please contact:
- Email: david.jeong0724@gmail.com