DockAI Documentation

Welcome to the comprehensive documentation for DockAI - The Customizable AI Dockerfile Generation Framework.

📚 Documentation Index

Getting Started

• Getting Started Guide - Installation, setup, and your first Dockerfile
• Configuration - Complete environment variable reference
• LLM Providers - Setting up OpenAI, Google Gemini, Anthropic, and more

Architecture & Design

• Architecture - Deep dive into v4.0 RAG multi-agent system
• API Reference - Code-level documentation

Integration

• GitHub Actions - Using DockAI in CI/CD pipelines
• MCP Integration - Model Context Protocol setup

Help

• FAQ - Common questions and troubleshooting

🚀 Quick Links

• Main Repository - Source code and issues
• PyPI Package - Install via pip
• GitHub Discussions - Community support

🎯 What is DockAI?

DockAI is an intelligent framework that generates production-ready Dockerfiles for any project using Large Language Models (LLMs). It goes beyond simple template generation by:

• Understanding your codebase through RAG (Retrieval-Augmented Generation)
• Analyzing your project architecture with AST code intelligence
• Iteratively improving Dockerfiles until they pass all security and validation checks

Key Features

• ✅ 15 Programming Languages - Python, JavaScript/TypeScript, Go, Rust, Ruby, PHP, Java, C#/.NET, Kotlin, Scala, Elixir, Haskell, Dart, Swift
• ✅ 80+ Frameworks - FastAPI, Flask, Django, Next.js, React, Express, Spring Boot, and many more
• ✅ Multi-Agent Architecture - 8 specialized AI agents orchestrated by LangGraph
• ✅ RAG-Powered - Semantic code search with sentence-transformers
• ✅ Security First - Hadolint linting, Trivy scanning, AI security review
• ✅ Adaptive Learning - AI-powered failure reflection and auto-fixes

📖 Documentation Structure

This documentation is organized to help you:

1. Get Started Quickly - Follow the getting started guide to install and run DockAI
2. Understand the Architecture - Learn how the RAG multi-agent system works
3. Configure for Your Needs - Customize LLM providers, models, and behavior
4. Integrate with Your Workflow - Use DockAI in GitHub Actions or as an MCP server
5. Troubleshoot Issues - Find answers in the FAQ

🤝 Contributing

We welcome contributions! See the Contributing Guide for details.

📄 License

DockAI is licensed under the MIT License. See LICENSE for details.

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Made with ❤️ by Januda Bethmin