Your Automation Powerhouse

1. Prerequisites

- An LLM API Key: Zrb needs an API key to talk to an AI model (OpenAI is default, but others are supported).

    export OPENAI_API_KEY="your-key-here"
    

    npm install -g @mermaid-js/mermaid-cli
    

Set up the dependency: the image task runs after the script is created

make_mermaid_script >> make_mermaid_image ```

prepare-env runs first, then build-app, then deploy-app

prepare_env >> build_app >> deploy_app ```

⚙️ Installation & Configuration

Ready to dive deeper into getting Zrb set up and customized? Our comprehensive guides cover everything you need:

• Installation Guide: Details on pip install, the automated install.sh script, Docker images, and even running Zrb on Android (Termux/Proot).
• Environment Variables & Overrides: An exhaustive list of all general environment variables to customize Zrb's behavior.
• LLM & Rate Limiter Configuration: Everything you need to configure your LLM provider, manage token budgets, and fine-tune AI behavior.

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🚀 Quickstart Part 1: Your First Basic Pipeline in < 2 Minutes

Let's start with the absolute basics: defining simple units of work and chaining them together. You only need Python installed.

🚀 Quickstart Part 2: Your First AI-Powered Workflow in < 5 Minutes

Now that you understand the basics, let's unleash Zrb's full power. This example uses an LLM to analyze your code and generate a Mermaid diagram, then converts that diagram into a PNG image.

🎥 Demo Video

Watch a video demonstration of Zrb in action:

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V. Configuration

• Environment Variables & Overrides
• LLM & Rate Limiter Configuration

2. Run Your First Pipeline!

Now, open your terminal and run:

zrb deploy-app

Zrb will see that deploy-app depends on build-app, which depends on prepare-env. It will automatically run them in the correct sequential order:

[prepare-env] Environment prepared!
[build-app] Building application in pure Python...
[build-app] Build complete.
[deploy-app] Deploying app to the cloud ☁️

Congratulations! You've just built and run your first Zrb automation pipeline.

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3. Run Your AI-Powered Workflow!

Navigate to any project with source code (e.g., a Python project). For instance, if you've cloned a repository:

git clone https://github.com/someuser/my-python-project.git
cd my-python-project

Now, run your new task:

zrb mermaid make-image

Zrb will interactively ask for the directory and diagram name. Just press Enter to accept the defaults (./ and state-diagram). The AI will analyze your code, generate the Mermaid script, and mmdc will convert it to a PNG. In moments, you'll have a beautiful diagram of your code!

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🤝 CI/CD Integration

Integrate Zrb into your Continuous Integration/Continuous Deployment pipelines for robust, automated workflows. See the CI/CD Integration Guide for examples with GitHub Actions, GitLab CI, and Bitbucket Pipelines.

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III. LLM & AI Integration

• LLM Assistant & AI Tasks — LLMTask, tools, sub-agents, context management
• LLMChatTask API Reference — builder API, TUI configuration
• LLM Chat Request Lifecycle — end-to-end tour: CLI → agent run → UI → history persistence
• Hook System (Claude Code Compatible)
• MCP Support (Model Context Protocol)
• LSP Support (Language Server Protocol)
• Technical Spec: LLM Journal System
• Claude Code Compatibility