A simple agent for operating large language models on Kubernetes.
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Kubernetes Operator Agent
This project uses Skaffold and Helm for development. Please make sure you have them installed on your machine.
The main code is written in Python, which may be formatted with either PyDantic or Black.
The process for this follows.
Build the agent image and push it to a public or local image repository.
docker build -t dockerhubuser/agent:0.0.1 .
Configure the redis-stack application's required storage class settings.
# values.yaml
# This is necessary only if you need to override the default `hostpath` storageClass.
redis-stack-server:
redis_stack_server:
storage_class: csi-lvm-linear
Configure the image repository and tag settings.
# values.yaml
image:
repository: dockerhubuser/agent
tag: 0.0.1
Obtain an OpenAPI API key and configure its value for the deployment.
# secrets/values.yaml
envVars:
OPENAI_API_KEY: base64-encoded-api-key
Create a namespace for the agent.
kubectl create ns agent
Deploy the agent with Helm using the values shown above.
helm upgrade --install -n agent agent deployment/helm/k8s-agent -f secrets/values.yaml -f values.yaml
Content type
Image
Digest
sha256:be10aeb80…
Size
505.6 MB
Last updated
about 2 years ago
docker pull edwardtheharris/agent:0.0.1