https://github.com/hellorge/abika
ABIKA (Ambient Behavioral Intelligence with Knowledge Analysis) is a dual-realm (two language) AI assistant designed for Linux systems, focusing on silent input processing and predictive assistance.
https://github.com/hellorge/abika
Last synced: 2 months ago
JSON representation
ABIKA (Ambient Behavioral Intelligence with Knowledge Analysis) is a dual-realm (two language) AI assistant designed for Linux systems, focusing on silent input processing and predictive assistance.
- Host: GitHub
- URL: https://github.com/hellorge/abika
- Owner: Hellorge
- Created: 2024-11-10T14:51:02.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-11-10T15:07:12.000Z (over 1 year ago)
- Last Synced: 2025-01-25T14:43:12.011Z (over 1 year ago)
- Size: 6.84 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
Awesome Lists containing this project
README
# ABIKA (अभिका)
## Ambient Behavioral Intelligence with Knowledge Analysis
ABIKA is an intelligent Linux assistant designed to understand and predict user behavior through silent observation and pattern recognition. It employs a unique dual-realm architecture for optimal performance and functionality.
### Dual-Realm Architecture
```
+--------------------+ +--------------------+ +--------------------+
| Mortal Realm | | | | Spiritual Realm |
| (Python) | | Bridge Layer | | (C++) |
| | | - ZeroMQ | | |
| - Input Monitor | <---> | - Shared Memory | <---> | - Pattern Engine |
| - System Tray | | | | - Predictor |
| - Configuration | | | | - Analytics |
+--------------------+ +--------------------+ +--------------------+
```
#### Mortal Realm (Python)
- System integration
- User interface
- Configuration management
- Input monitoring
- High-level orchestration
#### Spiritual Realm (C++)
- Pattern recognition
- Real-time analysis
- Predictive processing
- Performance-critical operations
The realms communicate via a high-performance bridge using ZeroMQ and shared memory, combining Python's rapid development capabilities with C++'s processing power.
### Key Features
- Silent input prediction
- Pattern learning
- Context-aware assistance
- System resource optimization
- Secure authentication
### Development Status
🚧 Currently in active development
### Requirements
- Python 3.8+
- C++17 compatible compiler
- ZeroMQ
- Qt6
- Linux system
### License
MIT