AI Coding Tools Orchestrator | Multi-Agent Collaboration Platform

Overview

🤝

Multi-Agent Collaboration

Coordinate Claude, Codex, Gemini, and Copilot to work together on your code with intelligent workflows.

💻

Interactive CLI & Web UI

Choose between a powerful command-line interface or modern web UI with real-time updates.

⚙️

Configurable Workflows

Define custom collaboration patterns or use built-in workflows for different scenarios.

🛡️

Production Ready

Security, monitoring, rate limiting, retry logic, and comprehensive test coverage built-in.

How It Works

graph LR
    A[User Request] --> B[AI Orchestrator]
    B --> C[Codex: Implementation]
    C --> D[Gemini: Review]
    D --> E[Claude: Refinement]
    E --> F[Quality Code]

    style A fill:#667eea,stroke:#667eea,color:#fff
    style B fill:#764ba2,stroke:#764ba2,color:#fff
    style C fill:#f093fb,stroke:#f093fb,color:#fff
    style D fill:#4facfe,stroke:#4facfe,color:#fff
    style E fill:#00f2fe,stroke:#00f2fe,color:#fff
    style F fill:#43e97b,stroke:#43e97b,color:#fff

4

AI Agents

14+

Python Files

5

Workflows

80%+

Test Coverage

Core Features

🤖

Multi-Agent Collaboration

Coordinate multiple AI assistants with specialized roles:

Codex: Initial implementation
Gemini: Code review & analysis
Claude: Refinement & documentation
Copilot: Alternative suggestions

💬

Interactive Shell

REPL-style conversation interface
Smart follow-up detection
Full readline support & history
Session save/restore
Colored output with Rich

🌐

Modern Web UI

Vue 3 with Composition API
Real-time updates via Socket.IO
Monaco code editor (VS Code)
File management & downloads
Conversation mode toggle

📊

Monitoring & Metrics

Prometheus metrics integration
Structured logging (structlog)
Health & readiness checks
Performance tracking
Error rate monitoring

🛡️

Security Features

Input validation & sanitization
Rate limiting (token bucket)
Audit logging
Secret management
Security scanning (Bandit)

⚡

Performance

Async execution support
Multi-layer caching
Connection pooling
Retry logic with backoff
Circuit breaker pattern

🚢

Deployment Options

Docker & Docker Compose
Kubernetes manifests
Systemd service files
CI/CD with GitHub Actions
Multi-environment configs

🔧

Code Quality

Type hints with Pydantic
80%+ test coverage (pytest)
Black code formatting
Flake8 linting
MyPy type checking

System Architecture

The AI Orchestrator follows a modular, layered architecture with clear separation of concerns. It's designed for extensibility, reliability, and production-grade performance.

flowchart TB
    subgraph "User
Interfaces"
        CLI[CLI Shell
Click + Rich]
        WebUI[Web UI
Vue 3 + Socket.IO]
    end

    subgraph "Core
Orchestrator"
        Engine[Orchestration
Engine]
        Workflow[Workflow
Manager]
        Config[Config
Manager]
        Session[Session
Manager]
    end

    subgraph "Cross-Cutting
Concerns"
        Metrics[Prometheus
Metrics]
        Cache[Response
Cache]
        Retry[Retry
Logic]
        Security[Security
Layer]
    end

    subgraph "AI
Adapters"
        Claude[Claude
Adapter]
        Codex[Codex
Adapter]
        Gemini[Gemini
Adapter]
        Copilot[Copilot
Adapter]
    end

    subgraph "External AI
Tools"
        ClaudeCLI[Claude Code
CLI]
        CodexCLI[OpenAI Codex
CLI]
        GeminiCLI[Google Gemini
CLI]
        CopilotCLI[GitHub Copilot
CLI]
    end

    CLI --> Engine
    WebUI --> Engine
    Engine --> Workflow
    Engine --> Config
    Engine --> Session
    Workflow --> Metrics
    Workflow --> Cache
    Workflow --> Retry
    Workflow --> Security
    Workflow --> Claude
    Workflow --> Codex
    Workflow --> Gemini
    Workflow --> Copilot
    Claude --> ClaudeCLI
    Codex --> CodexCLI
    Gemini --> GeminiCLI
    Copilot --> CopilotCLI

    style CLI fill:#667eea,stroke:#667eea,color:#fff
    style WebUI fill:#667eea,stroke:#667eea,color:#fff
    style Engine fill:#4facfe,stroke:#4facfe,color:#fff
    style Workflow fill:#43e97b,stroke:#43e97b,color:#fff

1. Interface Layer

User-facing interfaces: CLI and Web UI

2. Orchestration Layer

Core business logic and workflow management

3. Cross-Cutting Layer

Security, caching, metrics, and logging

4. Adapter Layer

AI agent integrations with uniform interface

5. External Services

Third-party AI CLI tools

Design Patterns

Adapter Pattern

Uniform interface to different AI CLIs

Strategy Pattern

Configurable workflow strategies

Observer Pattern

Real-time UI updates via Socket.IO

Factory Pattern

Agent and workflow creation

Singleton Pattern

Config and metrics managers

Decorator Pattern

Retry, cache, and logging decorators

Quick Start

1

Clone Repository

git clone <repository-url>
cd AI-Coding-Tools-Collaborative

2

Install Dependencies

pip install -r requirements.txt
chmod +x ai-orchestrator

3

Verify Installation

./ai-orchestrator --help
./ai-orchestrator agents

4

Start Interactive Shell

./ai-orchestrator shell

Prerequisites

Python 3.8+ - Core runtime
Node.js 20+ - For Web UI (optional)
At least one AI CLI - Claude, Codex, Gemini, or Copilot
Docker - For containerized deployment (optional)

Example Usage

# Start interactive shell
./ai-orchestrator shell

orchestrator (default) > create a REST API for user management
✓ Task completed successfully!
📁 Generated Files:
  📄 api/routes.py
  📄 api/models.py

orchestrator (default) > add JWT authentication
💡 Detected as follow-up to previous task
✓ Authentication added!

orchestrator (default) > /save user-api-project
✓ Session saved!

Available Workflows

Workflow	Agents	Iterations	Use Case
default	Codex → Gemini → Claude	3	Production-quality code with review
quick	Codex only	1	Fast prototyping and iteration
thorough	Codex → Copilot → Gemini → Claude → Gemini	5	Mission-critical or security-sensitive
review-only	Gemini → Claude	2	Analyzing existing code
document	Claude → Gemini	2	Generating documentation

Workflow Execution Flow

graph TD
    START([Start]) --> LOAD[Load Workflow Config]
    LOAD --> VALIDATE[Validate Configuration]
    VALIDATE --> INIT[Initialize Agents]
    INIT --> ITER{Iteration < Max?}

    ITER -->|Yes| EXEC[Execute Workflow Steps]
    EXEC --> AGENT1[Agent 1]
    AGENT1 --> AGENT2[Agent 2]
    AGENT2 --> AGENT3[Agent 3]

    AGENT3 --> COLLECT[Collect Feedback]
    COLLECT --> CHECK{Sufficient
Suggestions?}

    CHECK -->|Yes| UPDATE[Update Context]
    UPDATE --> ITER

    CHECK -->|No| AGG[Aggregate Results]
    ITER -->|No| AGG

    AGG --> REPORT[Generate Report]
    REPORT --> END([End])

    style START fill:#667eea,stroke:#667eea,color:#fff
    style END fill:#43e97b,stroke:#43e97b,color:#fff

Custom Workflows

Define your own workflows in config/agents.yaml:

workflows:
  custom:
    max_iterations: 4
    min_suggestions_threshold: 5
    steps:
      - agent: "codex"
        task: "implement"
      - agent: "gemini"
        task: "security_review"
      - agent: "claude"
        task: "refine"

Documentation

📖

README

Project overview and getting started guide

🏗️

Architecture

System design, patterns, and components

✨

Features

Comprehensive feature documentation

🚀

Setup Guide

Detailed installation and configuration

🔌

Add Agents

Guide for integrating new AI agents

☁️

Deployment

Production deployment strategies

Technology Stack

Core

Python 3.8+
Click (CLI)
Rich (Terminal)
Pydantic (Validation)

Web UI

Vue 3
Vite
TailwindCSS
Monaco Editor

Backend

Flask
Flask-SocketIO
Socket.IO
Pinia

Monitoring

Prometheus
Structlog
Grafana
Health Checks

Testing

Pytest
Coverage
MyPy
Black

Deployment

Docker
Kubernetes
GitHub Actions
Systemd

Community & Support

💬

GitHub Discussions

Ask questions, share ideas, and connect with other users

Join Discussions →

🐛

Issue Tracker

Report bugs, request features, and track development

View Issues →

🤝

Contributing

Help improve the project with code, docs, or ideas

Contribution Guide →

📧

Security

Report security vulnerabilities responsibly

Security Policy →

Quick Contribution Guide

Fork the repository
Create a feature branch: git checkout -b feature/your-feature
Make your changes with tests
Run checks: make all
Commit: git commit -m "feat: add amazing feature"
Push and create a Pull Request

Built With

Click Rich Pydantic Vue 3 Flask Monaco Editor Prometheus Docker Kubernetes

See It In Action

Interactive CLI Shell

$ ./ai-orchestrator shell

Welcome to AI Orchestrator v1.0.0
Type /help for available commands

orchestrator (default) > create a Python REST API with FastAPI

🤖 Executing workflow: default
📊 Step 1/3: Codex (Implementation)
⏳ Processing...

✓ Implementation complete!

📊 Step 2/3: Gemini (Review)
⏳ Analyzing code...

✓ Review complete! Found 3 suggestions:
  • Add input validation
  • Include error handling
  • Add API documentation

📊 Step 3/3: Claude (Refinement)
⏳ Implementing improvements...

✓ Task completed successfully!

📁 Generated Files:
  📄 app/main.py (FastAPI app)
  📄 app/models.py (Pydantic models)
  📄 app/routes.py (API routes)
  📄 app/schemas.py (Request/response schemas)
  📄 tests/test_api.py (Unit tests)
  📄 requirements.txt (Dependencies)

Workspace: ./workspace/session-abc123

orchestrator (default) > add authentication
💡 Detected as follow-up to previous task

Modern Web Interface

The Web UI provides a visual interface with:

Real-time progress tracking with live updates
Monaco code editor (same as VS Code)
File browser and management
Conversation mode for iterative development
Workflow and iteration visualization

Task Input

Multi-line textarea with syntax highlighting

Live Updates

Socket.IO for real-time progress

Code Editor

Full Monaco editor with IntelliSense

Workflow Execution

# Run with specific workflow
./ai-orchestrator run "Build authentication system" --workflow thorough

# Custom iterations
./ai-orchestrator run "Optimize database queries" --max-iterations 5

# With verbose output
./ai-orchestrator run "Add caching layer" --workflow default --verbose

# Dry run to preview
./ai-orchestrator run "Refactor code" --dry-run

# Load previous session
./ai-orchestrator shell --load my-project

Overview

Multi-Agent Collaboration

Interactive CLI & Web UI

Configurable Workflows

Production Ready

How It Works

Core Features

Multi-Agent Collaboration

Interactive Shell

Modern Web UI

Monitoring & Metrics

Security Features

Performance

Deployment Options

Code Quality

System Architecture

1. Interface Layer

2. Orchestration Layer

3. Cross-Cutting Layer

4. Adapter Layer

5. External Services

Design Patterns

Quick Start

Clone Repository

Install Dependencies

Verify Installation

Start Interactive Shell

Prerequisites

Example Usage

Available Workflows

Workflow Execution Flow

Custom Workflows

Documentation

README

Architecture

Features

Setup Guide

Add Agents

Deployment

Technology Stack

Core

Web UI

Backend

Monitoring

Testing

Deployment

Community & Support

GitHub Discussions

Issue Tracker

Contributing

Security

Quick Contribution Guide

Built With

See It In Action

Interactive CLI Shell

Modern Web Interface

Workflow Execution

Ready to Get Started?