dockerfile-assistant 1.0.0

AI-powered Dockerfile generation and analysis

Dockerfile Assistant

AI-powered CLI tool that generates production-ready Dockerfiles and .dockerignore files for Python and Node.js projects.

Features

• Multi-Provider LLM Support - OpenAI, Google (Gemini), Anthropic (Claude), and Ollama (local)
• Automatic Stack Detection - Detects Python/Node.js, package managers, entry points, and ports
• Production-Ready Templates - Multi-stage builds, non-root users, health checks
• Filesystem MCP Integration - Optional AI-powered file exploration and generation
• Interactive CLI - Chat-based interface with multi-turn conversations

Installation

pip install dockerfile-assistant

From Source

git clone https://github.com/giulianotesta7/dockerfile-assistant.git
cd dockerfile-assistant
pip install -e .

Configuration

Create a .env file in your working directory:

# Required
LLM_PROVIDER=openai # ollama/google/anthropic
MODEL_NAME=gpt-4o-mini

# API Key (based on provider)
OPENAI_API_KEY=sk-...
# GOOGLE_API_KEY=...
# ANTHROPIC_API_KEY=...
# OLLAMA_BASE_URL=http://localhost:11434/v1

# Optional - Enable filesystem access for AI
USE_FS_MCP=false 
# Only if USE_FS_MCP is set on true
PROJECT_PATH=/path/to/your/project
OUTPUT_PATH=/path/to/output 

Supported Providers

Provider	Model Examples	Required Variable
openai	gpt-4	OPENAI_API_KEY
google	gemini-pro	GOOGLE_API_KEY
anthropic	claude-sonnet	ANTHROPIC_API_KEY
ollama	llama3.1:8b	OLLAMA_BASE_URL

Usage

dockerfile-assistant

Mode Comparison

Feature	Basic Mode	MCP Mode
User provides project info	Yes	Optional
Auto-detects stack	No	Yes
Auto-detects dependencies	No	Yes
Reads project files	No	Yes
Saves files to disk	No	Yes
Required env vars	LLM_PROVIDER, MODEL_NAME, API key	+ PROJECT_PATH, OUTPUT_PATH

Basic Mode

Required input: Describe your project to the agent (stack, package manager, port, start command).

If there is missing information, AI will ask you for:

• Stack (Python or Node.js)
• Package manager (pip, poetry, npm, yarn, pnpm)
• Container port
• Start command

Then generates a Dockerfile and .dockerignore.

Note: For Ollama, llama3.1:8b was used during development testing. The OLLAMA_BASE_URL must include /v1 (e.g., http://localhost:11434/v1).

MCP Mode (USE_FS_MCP=true)

Required input: Just ask "Generate a Dockerfile for my project" - the AI explores your project automatically.

When enabled, the AI can:

• Explore your project directory automatically (PROJECT_PATH)
• Detect stack from file signatures (package.json, requirements.txt, etc.)
• Find entry points and ports from configuration
• Save generated files directly to OUTPUT_PATH (Dockerfile, .dockerignore)

# Set in .env
USE_FS_MCP=true
PROJECT_PATH=/path/to/your/project
OUTPUT_PATH=/path/to/your/project

Important: MCP mode requires a model that supports tool/function calling.

Note: Ollama with small models (< 30B parameters) is not recommended for MCP mode. Small local models may struggle with tool calling and file exploration, leading to unexpected behavior. For MCP mode, use larger models or cloud providers (OpenAI, Google, Anthropic).

Security: The AI cannot read or write .env files. Access is blocked for security reasons.

Generated Dockerfile Features

All generated Dockerfiles include:

• Multi-stage builds for optimized image size
• Non-root user for security
• Health checks for container orchestration
• Optimized base images (python:3.12-slim, node:20-alpine)

Supported Stacks

Stack	Package Managers
Python	pip, poetry
Node.js	npm, yarn, pnpm

Environment Variables Reference

Variable	Required	Description
LLM_PROVIDER	Yes	Provider: openai, google, anthropic, ollama
MODEL_NAME	Yes	Model identifier for the provider
OPENAI_API_KEY	If openai	OpenAI API key
GOOGLE_API_KEY	If google	Google AI API key
ANTHROPIC_API_KEY	If anthropic	Anthropic API key
OLLAMA_BASE_URL	If ollama	Ollama server URL
USE_FS_MCP	No	Enable filesystem MCP (true/false)
PROJECT_PATH	If MCP	Path to project directory
OUTPUT_PATH	If MCP	Path for output files

Requirements

• Python 3.10+
• Node.js (only if using MCP filesystem features)

License

MIT License - see LICENSE for details.

Author

Giuliano Testa (@giulianotesta7)

Acknowledgments

• System prompts were crafted with the assistance of Claude (Anthropic)
• Built with Pydantic AI