G.O.D. (Generalized Omni-dimensional Development)
Overview G.O.D. is a versatile and scalable AI framework, seamlessly blending advanced functionalities to tackle complex challenges in anomaly detection, automated data pipelines, clustering, AI model lifecycle management, and more. Designed with cutting-edge principles, G.O.D. empowers developers to create reliable, efficient, and innovative AI solutions. Whether you're a researcher, developer, or engineer, G.O.D. offers unparalleled flexibility to turn ambitious AI concepts into reality.
Key Features - Advanced Anomaly Detection: Leverage AI to identify outliers and irregularities for robust data quality control. - Automated Data Pipelines: Streamline the entire data lifecycle with configurable and reusable pipelines for ingestion, preprocessing, and transformation. - Dynamic Clustering and AI Model Management: Gain insights into your data through clustering algorithms and maintain optimal AI model performance. - Framework for Universal AI Integration: Modular design enables easy integration of AI tasks across diverse domains and applications. - Robust Testing & Monitoring: Ensure system reliability and scalability with built-in tests, live monitoring, and performance metrics.
🛠️ Getting Started
📋 Prerequisites Before using G.O.D., ensure you have the following:
- Python 3.8 or higher.
- A virtual environment manager (
venv,conda, etc.). - Required dependencies listed in
requirements.txt.
📥 Installation Getting started is as easy as 1-2-3:
- Clone the Repository:
git clone https://github.com/AutoBotSolutions/Aurora.git
- Navigate to the Directory:
cd g_o_d - Set Up the Environment:
Create and activate a virtual environment:
Install dependencies:
python3 -m venv .venv source .venv/bin/activate # On Linux/Unix .venv\Scripts\activate # On Windows
pip install -r requirements.txt
python main.pyTesting Ensure your framework is functioning as expected by running the test suite:
pytest tests/