Bringing LLM's to Kubernetes.
Disclaimer: This project is still work in progress and is not ready for production use.
Introducing LLMNETES, a Kubernetes controller designed to simplify cluster management with a natural language interface. Powered by Large Language Models (LLM).
Whether it's creating deployments, deleting pods, or triggering chaos experiments, LLMNETES understands and tries executes your commands efficiently. It currently supports multiple LLM backends, including OpenAI's GPT-3 and a local model trained on a dataset. Additionally, users can integrate their own LLM backend by implementing the provided LLM interface.
| LLM backend | Supported | Notes |
|---|---|---|
| OpenAI GPT-X | Yes | |
| llama local model | WIP |
- A Kubernetes cluster
- helm installed and configured to access your cluster
- An OPENAI API key
helm install --create-namespace \
llmnetes oci://ghcr.io/llmnetes/llmnetes \
--version "0.0.1" \
--set=backned.openai.apiKey=<your-open-ai-key> \
--set=backend.customLLM.svc=To deploy new pods using llmnetes, you can deploy the following manifest:
apiVersion: llmnetes.dev/v1alpha1
kind: Command
metadata:
name: my-command
spec:
input: Create 3 nginx pods that will serve traffic on port 80.This will create 3 nginx pods that will serve traffic on port 80.
llmnetes can also be used to trigger chaos experiments. For example, to kill a pod in the default namespace, you can deploy the following manifest:
apiVersion: llmnetes.dev/v1alpha1
kind: ChaosSimulation
metadata:
name: chaos-simulation-cr
spec:
level: 10
command: break my cluster networking layer (or at least try to)Copyright 2023.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
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