dockerbrain 1.0

AI-powered Docker container monitoring, analysis, and optimization CLI.

DockerBrain

AI-powered Docker container monitoring, optimization, and Dockerfile generation CLI.

DockerBrain monitors your Docker containers in real time, detects resource issues, and uses LLMs to generate actionable optimizations for running containers and Dockerfiles. Supports Gemini, Groq, and Ollama. All configuration lives in a single .dockerbrainrc file.

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Features

Feature	Command	LLM Required
Real-time container monitoring	dockerb monitor	No
AI optimization suggestions	dockerb suggest	Yes
Auto-fix containers & Dockerfiles	dockerb fix	Yes
AI Dockerfile generation from project	dockerb dockerize	Yes
Curated Dockerfile templates	dockerb template	No
Environment & config diagnostics	dockerb env	No

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Installation

Requirements: Python 3.10+ and a running Docker daemon.

pip install dockerbrain

Verify:

dockerb --version

Configure an LLM Provider

dockerb init

This creates .dockerbrainrc in your project directory. Open it and set your provider and key:

[llm]
provider = "gemini"
model    = "gemini-3.1-flash-lite-preview"
api_key  = "your_key_here"

Provider	API Key	Link
Gemini	Required	aistudio.google.com
Groq	Required	console.groq.com/keys
Ollama	Not Required	ollama.com

monitor, template, and env commands work without an API key.

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Usage

DockerBrain exposes all functionality through the dockerb CLI. Run the following to see all available commands and options:

dockerb --help

Each command also has its own help page, for example dockerb suggest --help, dockerb fix --help, etc.

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Pre-commit Hook

DockerBrain can run as a pre-commit hook to lint Dockerfiles on every commit:

# .pre-commit-config.yaml 
repos:
  - repo: https://github.com/iamPulakesh/DockerBrain
    rev: v1.0
    hooks:
      - id: dockerbrain-fix

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Development

git clone https://github.com/iamPulakesh/DockerBrain.git
cd DockerBrain
pip install -e ".[dev]"

make test                              
make lint                              
make clean                    

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See Changelog.md for the full release history.

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Contributing

1. Fork the repository
2. Contribute
3. Open a Pull Request

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License

Apache-2.0 — see LICENSE for details.