Kubectl OpenAI plugin ✨
This project is a kubectl plugin to generate and apply Kubernetes manifests using OpenAI GPT.
My main motivation is to avoid finding and collecting random manifests when dev/testing things.
Demo
Installation
Homebrew
Add to brew tap and install with:
brew tap sozercan/kubectl-ai https://github.com/sozercan/kubectl-ai
brew install kubectl-aiKrew
Add to krew index and install with:
kubectl krew index add kubectl-ai https://github.com/sozercan/kubectl-ai
kubectl krew install kubectl-ai/kubectl-aiGitHub release
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Download the binary from GitHub releases.
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If you want to use this as a
kubectlplugin, then copykubectl-aibinary to yourPATH. If not, you can also use the binary standalone.
Usage
Prerequisites
kubectl-ai requires an OpenAI API key or an Azure OpenAI Service API key and endpoint, and a valid Kubernetes configuration.
For both OpenAI and Azure OpenAI, you can use the following environment variables:
export OPENAI_API_KEY=<your OpenAI key>
export OPENAI_DEPLOYMENT_NAME=<your OpenAI deployment/model name. defaults to "gpt-3.5-turbo-0301">Following models are supported:
code-davinci-002text-davinci-003gpt-3.5-turbogpt-3.5-turbo-0301(default)gpt-4-0314gpt-4-32k-0314
For Azure OpenAI Service, you can use the following environment variables:
export AZURE_OPENAI_ENDPOINT=<your Azure OpenAI endpoint, like "https://my-aoi-endpoint.openai.azure.com">If AZURE_OPENAI_ENDPOINT variable is set, then it will use the Azure OpenAI Service. Otherwise, it will use OpenAI API.
Azure OpenAI service does not allow certain characters, such as ., in the deployment name. Consequently, kubectl-ai will automatically replace gpt-3.5-turbo to gpt-35-turbo for Azure. However, if you use an Azure OpenAI deployment name completely different from the model name, you can set AZURE_OPENAI_MAP environment variable to map the model name to the Azure OpenAI deployment name. For example:
export AZURE_OPENAI_MAP="gpt-3.5-turbo=my-deployment"Flags and environment variables
-
--require-confirmationflag orREQUIRE_CONFIRMATIONenvironment varible can be set to prompt the user for confirmation before applying the manifest. Defaults to true. -
--temperatureflag orTEMPERATUREenvironment variable can be set between 0 and 1. Higher temperature will result in more creative completions. Lower temperature will result in more deterministic completions. Defaults to 0.
Use with external editors
If you want to use an external editor to edit the generated manifest, you can set the --raw flag and pipe to the editor of your choice. For example:
# Visual Studio Code
$ kubectl ai "create a foo namespace" --raw | code -
# Vim
$ kubectl ai "create a foo namespace" --raw | vim -Examples
Creating objects with specific values
$ kubectl ai "create an nginx deployment with 3 replicas"
✨ Attempting to apply the following manifest:
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx-deployment
labels:
app: nginx
spec:
replicas: 3
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 80
Use the arrow keys to navigate: ↓ ↑ → ←
? Would you like to apply this? [Reprompt/Apply/Don't Apply]:
+ Reprompt
▸ Apply
Don't ApplyReprompt to refine your prompt
...
Reprompt: update to 5 replicas and port 8080
✨ Attempting to apply the following manifest:
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx-deployment
labels:
app: nginx
spec:
replicas: 5
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 8080
Use the arrow keys to navigate: ↓ ↑ → ←
? Would you like to apply this? [Reprompt/Apply/Don't Apply]:
+ Reprompt
▸ Apply
Don't ApplyMultiple objects
$ kubectl ai "create a foo namespace then create nginx pod in that namespace"
✨ Attempting to apply the following manifest:
apiVersion: v1
kind: Namespace
metadata:
name: foo
---
apiVersion: v1
kind: Pod
metadata:
name: nginx
namespace: foo
spec:
containers:
- name: nginx
image: nginx:latest
Use the arrow keys to navigate: ↓ ↑ → ←
? Would you like to apply this? [Reprompt/Apply/Don't Apply]:
+ Reprompt
▸ Apply
Don't ApplyOptional --require-confirmation flag
$ kubectl ai "create a service with type LoadBalancer with selector as 'app:nginx'" --require-confirmation=false
✨ Attempting to apply the following manifest:
apiVersion: v1
kind: Service
metadata:
name: nginx-service
spec:
selector:
app: nginx
ports:
- port: 80
targetPort: 80
type: LoadBalancerPlease note that the plugin does not know the current state of the cluster (yet?), so it will always generate the full manifest.