dockai-cli 2.1.1

The Customizable AI Dockerfile Generation Framework

DockAI

AI-Powered Dockerfile Generation Framework

Generate production-ready Dockerfiles from first principles using AI agents

Quick Start • Features • Docs • CI/CD • Contributing

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🎯 What is DockAI?

DockAI is an agentic AI framework that analyzes your codebase and generates optimized, production-ready Dockerfiles. Unlike template-based tools, DockAI uses first-principles reasoning to understand your application and create Dockerfiles from scratch—handling everything from standard stacks to legacy systems.

pip install dockai-cli
dockai build /path/to/project

That's it. DockAI handles the rest.

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✨ Features

🧠 First-Principles AI No templates. Analyzes file structures, dependencies, and code patterns to deduce the optimal containerization strategy.	🔄 Self-Correcting Workflow Builds and tests Dockerfiles in a sandbox. If something fails, AI reflects, learns, and retries with a new approach.
🛡️ Security-First Built-in Trivy integration scans for vulnerabilities. Enforces non-root users, minimal base images, and hardened configs.	🤖 10 Specialized Agents Each agent handles a specific task: analysis, planning, generation, review, and more. All fully customizable.
⚡ Multi-Provider LLMs Supports OpenAI, Azure OpenAI, Google Gemini, and Anthropic Claude. Mix models per agent for cost optimization.	🔧 Fully Customizable Override prompts, instructions, and model selection per agent. Use .dockai files for repo-specific configs.

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🚀 Quick Start

Installation

pip install dockai-cli

Configuration

Create a .env file:

# Required: Choose your LLM provider and add the API key
OPENAI_API_KEY=sk-your-api-key

# Optional: Use a different provider (openai, azure, gemini, anthropic)
# DOCKAI_LLM_PROVIDER=openai

Usage

# Generate Dockerfile for your project
dockai build /path/to/project

# With verbose output
dockai build /path/to/project --verbose

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🏗️ How It Works

graph TD
    Start([▶ Start]) --> Scan[📂 Scanner]
    Scan --> Analyze[🧠 Analyzer]
    Analyze --> Read[📖 Reader]
    Read --> Health[🏥 Health Detector]
    Health --> Ready[⏱️ Readiness Detector]
    Ready --> Plan[📝 Planner]
    Plan --> Generate[⚙️ Generator]
    Generate --> Review[🔒 Security Reviewer]
    
    Review -- Secure --> Validate[✅ Validator]
    Review -- Issues & Can Retry --> Reflect[🤔 Reflector]
    Review -- Critical & Max Retries --> Fail([❌ Fail])
    
    Validate -- Success --> End([🏁 Finish])
    Validate -- Failure --> Reflect
    
    Reflect --> Increment[🔄 Increment Retry]
    
    Increment -- Fix Code --> Generate
    Increment -- New Strategy --> Plan
    Increment -- Re-Analyze --> Analyze
    Increment -- Max Retries --> Fail

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🤖 The 10 AI Agents

Agent	Role	Model Type
Analyzer	Project discovery & stack detection	Fast
Planner	Strategic build planning	Fast
Generator	Dockerfile creation	Powerful
Generator (Iterative)	Debugging failed Dockerfiles	Powerful
Reviewer	Security audit & hardening	Fast
Reflector	Failure analysis & learning	Powerful
Health Detector	Health endpoint discovery	Fast
Readiness Detector	Startup pattern analysis	Fast
Error Analyzer	Error classification	Fast
Iterative Improver	Targeted fix application	Powerful

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⚙️ Configuration

Environment Variables

Variable	Description	Default
OPENAI_API_KEY	OpenAI API key	Required*
GOOGLE_API_KEY	Google Gemini API key	Required*
ANTHROPIC_API_KEY	Anthropic Claude API key	Required*
AZURE_OPENAI_API_KEY	Azure OpenAI API key	Required*
DOCKAI_LLM_PROVIDER	Provider (openai, azure, gemini, anthropic)	openai
MAX_RETRIES	Maximum retry attempts	3
DOCKAI_SKIP_SECURITY_SCAN	Skip Trivy scanning	false

*Only one API key required for your chosen provider.

Repository-Level Configuration

Create a .dockai file in your project root:

[instructions_analyzer]
This is a Django application with Celery workers.

[instructions_generator]
Use gunicorn as the WSGI server.
Run database migrations at container start.

[instructions_reviewer]
All containers must run as non-root (UID >= 10000).

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🔗 GitHub Actions

name: Auto-Dockerize

on:
  push:
    branches: [main]

jobs:
  dockai:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: itzzjb/dockai@v2
        with:
          openai_api_key: ${{ secrets.OPENAI_API_KEY }}

Multi-Provider Example

- uses: itzzjb/dockai@v2
  with:
    llm_provider: gemini
    google_api_key: ${{ secrets.GOOGLE_API_KEY }}
    max_retries: 5
    strict_security: true

See GitHub Actions Guide for all options.

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📖 Documentation

Document	Description
Getting Started	Installation, configuration, first run
Architecture	Deep dive into the agentic workflow
Configuration	All environment variables and options
Customization	Tuning agents for your organization
API Reference	Module and function documentation
GitHub Actions	CI/CD integration guide
FAQ	Frequently asked questions

💡 Platform Engineers: DockAI is ideal for embedding into Internal Developer Platforms, CI/CD pipelines, and self-service portals to auto-generate Dockerfiles at scale.

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🛠️ Tech Stack

Technology	Purpose
Python 3.10+	Core runtime
LangGraph	Stateful agent workflow orchestration
LangChain	LLM provider integration
Pydantic	Structured output validation
Rich + Typer	Beautiful CLI interface
Trivy	Security vulnerability scanning

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🤝 Contributing

Contributions are welcome! Feel free to open issues and pull requests.

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📄 License

MIT License - see LICENSE for details.

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_{Built with ❤️ by itzzjb}