AI-AutoCoding-DAO (AIACD)

Orchestration Layer for AI-Assisted Development

Achieve 5-7x improvement in token efficiency through intelligent orchestration.

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Overview

AI-AutoCoding-DAO (AIACD) is a sophisticated framework for optimizing AI-assisted development through intelligent orchestration. This repository contains the Orchestration Layer (Layer 1) of the AIACD four-layer architecture, responsible for analyzing tasks, selecting optimal implementation approaches, and tracking token efficiency metrics.

Value Proposition

• Token Efficiency: Achieve 5-7x improvement in token utilization compared to direct AI usage
• Quality Assurance: Maintain 8.5+/10 implementation quality across various tasks
• Implementation Optimization: Intelligent template selection based on task characteristics
• Comprehensive Metrics: Track and visualize token usage and efficiency metrics
• Strategic Orchestration: Data-driven decision making for implementation approaches

Architecture

AIACD follows a comprehensive four-layer architecture designed to maximize token efficiency:

AI-AutoCoding-DAO Ecosystem
├── Layer 1: AIACD Core (Orchestration Layer) ← THIS REPOSITORY
│   ├── Task Analyzer
│   ├── Template Manager
│   ├── Token Tracker
│   ├── Quality Analyzer
│   ├── Metrics Dashboard
│   └── Integration Layer API Client
├── Layer 2: bolt.diy-impl (Integration Layer)
│   ├── API Endpoints
│   ├── Authentication System
│   ├── bolt.diy WSL Client
│   ├── Template Management
│   ├── Streaming Support
│   └── Token Metrics Service
├── Layer 3: bolt.diy-standalone (Implementation Environment)
│   ├── Full IDE Environment
│   ├── Web Container
│   ├── Code Execution Engine
│   ├── Error Detection
│   └── Deployment Pipeline
└── Layer 4: MetaGipsy (Interaction Analysis Layer)
    ├── Conversation Analyzer
    ├── Pattern Recognition
    ├── User Profiling
    └── Prediction Engine

Key Features

• Task Analysis: Sophisticated algorithm for determining task complexity and requirements
• Template Management: Intelligent selection and application of templates for different task types
• Token Tracking: Comprehensive metrics for measuring token consumption and efficiency
• Quality Assessment: Multi-dimensional evaluation of implementation quality
• Layer 2 Integration: Robust API client for communicating with the Integration Layer
• Streaming Support: Real-time updates during task implementation
• Metrics Dashboard: Visualization of token efficiency and performance metrics

Getting Started

Prerequisites

• Node.js 18+
• npm or pnpm
• TypeScript 5+

Installation

1. Clone the repository:

   git clone https://github.com/MaksimYurchanka/aiacd-source.git
   cd aiacd-source

2. Install dependencies:

   npm install
   # or
   pnpm install

3. Configure environment variables:

   cp .env.example .env

   Edit the .env file with your API credentials:

   AIACD_API_URL=your_layer2_api_url
   AIACD_API_KEY=your_api_key
   

4. Build the project:

   npm run build
   # or
   pnpm run build

Usage

Basic Example

import { AiacdCoreClient } from 'aiacd-source';

// Initialize the client
const client = new AiacdCoreClient({
  baseUrl: process.env.AIACD_API_URL,
  apiKey: process.env.AIACD_API_KEY,
  environment: 'production'
});

// Submit a task
async function processTask() {
  const result = await client.submitTask({
    prompt: 'Create a React button component with hover effects',
    type: 'ui',
    complexity: 'low'
  });
  
  console.log(`Task submitted with ID: ${result.taskId}`);
  console.log(`Status: ${result.status}`);
  
  // Connect to the task stream for real-time updates
  client.connectToTaskStream(result.taskId);
  
  // Register event handlers
  client.on('task.status', (data) => {
    console.log(`Status updated: ${data.status}`);
  });
  
  client.on('task.completion', (data) => {
    console.log(`Task completed!`);
    console.log(`Implementation: ${data.implementation}`);
  });
}

processTask().catch(console.error);

Template Management

// Get templates for UI components
const uiTemplates = await client.getTemplates('ui');

// Create a new template
const templateId = await client.createTemplate({
  name: 'React Button',
  type: 'ui',
  content: '# Button Component\n\n{description}\n\n## Props\n{props}',
  metadata: {
    version: '1.0',
    complexity: 'low'
  }
});

// Select the best template for a task
const bestTemplate = await client.selectBestTemplate({
  type: 'ui',
  complexity: 'medium'
});

Token Metrics

// Get efficiency metrics
const metrics = await client.getEfficiencyMetrics({
  templateType: 'ui',
  startDate: new Date('2025-01-01'),
  endDate: new Date()
});

// Get efficiency trend
const trend = await client.getEfficiencyTrend(30, 'ui');

API Reference

See the API Documentation for detailed information on all available methods.

Token Efficiency Methodology

AIACD achieves 5-7x token efficiency improvement through:

1. Intelligent Template Selection: Optimized templates for different task types
2. Strategic Task Decomposition: Breaking complex tasks into manageable components
3. Implementation Environment Optimization: Direct execution in Web Container
4. Continuous Improvement: Learning from successful implementations

For details on how token efficiency is measured and optimized, see Token Efficiency.

Contributing

Contributions are welcome! Please check out our Contributing Guide for guidelines on how to proceed.

Development

1. Fork the repository
2. Create your feature branch: git checkout -b feature/amazing-feature
3. Install development dependencies: npm install
4. Make your changes
5. Run tests: npm test
6. Commit your changes: git commit -m 'Add some amazing feature'
7. Push to the branch: git push origin feature/amazing-feature
8. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• Claude Sonnet - AI model used for orchestration
• bolt.diy - Implementation environment
• The AIACD community for continued support and contributions