CKAD Agent

A powerful AI-powered agent. This tool leverages large language models to help you understand, debug, and generate Kubernetes configurations.

Features

• 🐛 Debug Kubernetes YAML manifests
• 📚 Explain Kubernetes concepts and best practices
• ✨ Generate valid Kubernetes YAML from requirements
• ✅ Validate and improve existing configurations

Installation

1. Install the package:

   pip install ckad-agent
   

2. Create a .env file with your OpenAI API key:

   cp .env.example .env
   # Edit .env and add your OpenAI API key
   

Usage

Command Line Interface

The CKAD Agent provides a convenient CLI for common tasks:

# Debug issues in read-only mode
ckad debug "My pod in namespace default keeps crashing, fix it" --read-only

# Debug and correct issues (Project in development be carefull, do not use it in production environment)
ckad debug "My pod in namespace default keeps crashing, fix it" --no-read-only

# Explain a Kubernetes concept
ckad explain "How do I configure liveness and readiness probes?"

# Validate a YAML file
ckad validate deployment.yaml --resource Deployment

Python API

from ckad_agent import CkadAgent, CKADRequest, TaskType, KubernetesResourceType
import asyncio

async def main():
    agent = CkadAgent()
    
    # Example: Debug a YAML
    request = CKADRequest(
        task_type=TaskType.DEBUG,
        resource_type=KubernetesResourceType.POD,
        yaml_content="""
        apiVersion: v1
        kind: Pod
        metadata:
          name: my-pod
        spec:
          containers:
          - name: nginx
            image: nginx:latest
        """,
        question="Why isn't this pod starting?"
    )
    
    response = await agent.process_request(request)
    print(response.solution)

asyncio.run(main())

Development with uv

Prerequisites

• Install uv (if not already installed):

  curl -LsSf https://astral.sh/uv/install.sh | sh
  

  Or install via pip:

  pip install uv
  

Setup and Development

1. Clone the repository
2. Create and activate a virtual environment:

   uv venv
   source .venv/bin/activate  # On macOS/Linux
   # .\.venv\Scripts\activate  # On Windows
   

3. Install the package in development mode with all dependencies:

   uv pip install -e ".[dev]"
   

4. Run tests:

   pytest
   

License

MIT