MonkWarrior08 / Model_Router

Dynamically route tasks to the best AI model and configuration using an LLM-powered intelligent selection system.

AI Model Router

An intelligent routing system that automatically selects the optimal AI model and configuration for any given task using LLM-powered analysis.

🎯 What It Does

The AI Model Router analyzes your prompts and automatically:

• Selects the best AI provider (OpenAI, Anthropic, Google)
• Chooses the optimal model for your specific task type
• Configures ideal parameters (temperature, thinking levels, reasoning effort)
• Applies specialized instructions tailored to your task category

Instead of manually deciding between GPT-4, Claude, or Gemini for each task, the router uses AI to make these decisions intelligently.

✨ Key Features

🧠 Intelligent Task Analysis

• Uses Gemini Flash 2.0 to analyze and categorize your prompts
• Automatically detects task types: coding, creative writing, tutoring, conversation
• Selects optimal model configurations based on task requirements

🔄 Multi-Provider Support

• OpenAI: GPT models with reasoning effort controls
• Anthropic: Claude models with temperature tuning
• Google: Gemini models with thinking budgets and temperature controls

🎛️ Dynamic Parameter Optimization

• Temperature Control: Automatically adjusts creativity vs precision
• Thinking Levels: Configures reasoning depth for complex tasks
• Specialized Instructions: Applies task-specific system prompts

💻 Dual Interface

• CLI Tool: Interactive terminal interface for developers
• Web App: Modern streaming chat interface with real-time model selection display

⚙️ Configurable Architecture

• JSON-based configuration system
• Hot-reloadable settings
• Built-in backup system for configuration changes
• Easy to add new models and task categories

🚀 Quick Start

Prerequisites

• Python 3.8+
• API keys for at least one provider (OpenAI, Anthropic, or Google)

Installation

1. Clone the repository

   git clone <repository-url>
   cd Model_Router

2. Install dependencies

   pip install -r requirements.txt

3. Set up environment variables

   cp env_template.txt .env
   # Edit .env and add your API keys

4. run the web interface

   python app.py
   # Open http://localhost:5000 in your browser

🏗️ Architecture

Core Components

1. Router (router.py)

   • LLM-powered prompt analysis
   • Model and parameter selection logic
   • Configuration validation

2. CLI Interface (main.py)

   • Interactive terminal chat
   • Conversation history management
   • Multi-provider execution

3. Web Interface (app.py)

   • Flask-based streaming API
   • Real-time model selection display
   • Configuration management UI

4. Configuration (model_prompt.json)

   • Task category definitions
   • Model mappings and parameters
   • Specialized instruction templates

Task Categories (Default)

• Conversational AI: General chat with Gemini Flash Lite
• Creative Writing: Storytelling and poetry with Gemini Flash
• Professional Coding: Development tasks with Gemini Pro + thinking budget
• Tutoring: Educational content with OpenAI o4-mini + reasoning effort

🔧 API Keys Setup

Get your API keys from:

• OpenAI: https://platform.openai.com/api-keys
• Anthropic: https://console.anthropic.com/
• Google: https://makersuite.google.com/app/apikey

Add them to your .env file:

OPENAI_API_KEY=your_key_here
ANTHROPIC_API_KEY=your_key_here
GOOGLE_API_KEY=your_key_here

🙋‍♂️ Support

For questions, suggestions, or issues, please open a GitHub issue or reach out to the maintainers.