demirozAI Documentation
Complete guide to using demirozAI's artificial intelligence projects and APIs
Getting Started
Welcome to demirozAI! This documentation will help you understand and integrate our AI-powered projects into your applications.
Quick Start
To get started with any of our AI projects:
- Choose a project from our AI Portfolio
- Review the project-specific documentation below
- Follow the installation and setup instructions
- Explore the API reference and code examples
Prerequisites
- Basic understanding of AI/ML concepts
- Python 3.8+ (for most projects)
- Node.js 16+ (for web-based projects)
- Git for cloning repositories
AI Projects Overview
Our AI portfolio consists of cutting-edge projects designed for various applications:
PhoeniX
Advanced AI system with rebirth capabilities and adaptive learning algorithms for complex problem-solving scenarios.
View DocsmathPi
Advanced mathematical computing platform powered by AI for complex calculations, analysis, and mathematical modeling.
View DocssentinelAI
Intelligent monitoring and security system with advanced threat detection and autonomous response capabilities.
View Docsotocopit
Autonomous AI system with advanced self-learning capabilities and independent decision-making algorithms.
View DocsPhoeniX Documentation
PhoeniX is our flagship AI system featuring advanced rebirth capabilities and adaptive learning algorithms.
mathPi Documentation
mathPi is our advanced mathematical computing platform powered by AI for complex calculations and analysis.
sentinelAI Documentation
sentinelAI is our intelligent monitoring and security system with advanced threat detection capabilities.
kepler-62 Documentation
kepler-62 is our exoplanet exploration and analysis platform using AI for astronomical data processing.
otonomsAI Documentation
otonomsAI is our autonomous AI system with advanced self-learning capabilities and independent decision-making algorithms.
daiTurkishv1 Documentation
daiTurkishv1 is a series of AI models trained from scratch by daiTurkishv1, fully in Turkish.
Available Models
- DaiText: Turkish text generation and understanding
- DaiVision: Turkish image recognition and analysis
- DaiVoice: Turkish speech recognition and synthesis
- DaiCode: Turkish code generation and analysis
Usage
from daimodels import daiTurkishv1 ...
# Generate Turkish text
text = model.generate("Yapay zeka gelecekte...")
print(text)
Ollama Models Integration
We utilize various Ollama models across our projects to provide advanced AI capabilities. Our projects integrate with the following models from ollama.com:
Text and Embedding Models
- nomic-embed-text:latest - Used for text embeddings and semantic search
- embeddinggemma:latest - Advanced embedding model for natural language processing
Code Generation Models
- codegemma:2b - Specialized in code generation and analysis
- qwen2.5-coder:1.5b - Efficient code generation and completion
- qwen2.5-coder:0.5b - Lightweight coding assistant
- qwen2.5-coder:3b - Advanced code generation and understanding
Language Models
- gemma3:1b - General-purpose language model
- gemma3:270m - Efficient language processing
- gemma2:2b - Advanced language understanding
Specialized Models
- qwen2-math:1.5b - Mathematical problem solving
- qwen3:0.6b, 1.7b, 4b - Scalable language processing
- granite3.2-vision - Computer vision capabilities
- moondream - Advanced vision-language tasks
- daiTurkishv1 - Specialized Turkish language model
Model Integration in Projects
- PhoeniX: ...
- MathPi: ...
- SentinelAI: ...
- Kepler-62: ...
- OtonomsAI: ...
- DaiModels: ...