Ai Triad Model

AI Triad Model 🤖

A structured multi-agent AI framework with built-in oversight and transparent decision-making. Four specialized agents work together using proven architectural patterns for reliable AI coordination.

🌟 Features

• Four-Agent Architecture: Planner, Executor, Evaluator, and Oversight agents
• Structured Coordination: Clear separation of responsibilities and systematic workflows
• Built-in Oversight: Quality assurance and compliance checking at every step
• Transparent Processes: Complete audit trails and decision logging
• Modern Stack: Built with Pydantic AI, FastAPI, and Prisma
• Easy Integration: Simple Python SDK with comprehensive documentation

🚀 Quick Start

Prerequisites

• Python 3.11+
• pip package manager

Installation

# Clone the repository
git clone https://github.com/DamionR/ai-triad-model.git
cd ai-triad-model

# Create virtual environment
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Set up environment
cp .env.example .env
# Edit .env with your API keys

Run the Application

# Start the development server
python scripts/start.py

# Or use make
make run

Access the API at http://localhost:8000/docs

🏗️ Architecture

AI Triad Model
├── Planner Agent
│   ├── Strategic planning
│   ├── Workflow design
│   └── Task coordination
├── Executor Agent  
│   ├── Plan implementation
│   ├── Resource management
│   └── Operational tasks
├── Evaluator Agent
│   ├── Quality review
│   ├── Compliance checking
│   └── Performance evaluation
└── Oversight Agent
    ├── System monitoring
    ├── Crisis management
    └── Final approval

💡 Basic Usage

from triad import TriadFramework

# Initialize the framework
framework = TriadFramework()

# Process a request through all four agents
result = await framework.process_request(
    request="Analyze market trends f