curl

Test your agentgateway Kubernetes deployment using curl.

Before you begin

  1. Set up an agentgateway proxy.
  2. Set up access to the OpenAI LLM provider.

Get the gateway URL

export INGRESS_GW_ADDRESS=$(kubectl get svc -n agentgateway-system agentgateway-proxy \
  -o jsonpath='{.status.loadBalancer.ingress[0].ip}')

echo "Gateway address: $INGRESS_GW_ADDRESS"
export INGRESS_GW_ADDRESS=$(kubectl get svc -n agentgateway-system agentgateway-proxy \
  -o jsonpath='{.status.loadBalancer.ingress[0].hostname}')

echo "Gateway address: $INGRESS_GW_ADDRESS"

After port-forwarding, the gateway is accessible at http://localhost:8080. Use localhost:8080 wherever the instructions reference $INGRESS_GW_ADDRESS.

kubectl port-forward -n agentgateway-system svc/agentgateway-proxy 8080:80

Send a request

Replace <route-path> with the path configured in your HTTPRoute (for example, /openai).

curl "http://$INGRESS_GW_ADDRESS/<route-path>" \
  -H "content-type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [
      {"role": "user", "content": "Hello from Kubernetes!"}
    ]
  }' | jq

Example output:

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "gpt-4o-mini",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I help you today?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 11,
    "completion_tokens": 10,
    "total_tokens": 21
  }
}

Authentication

If agentgateway requires authentication, include an Authorization header.

curl "http://$INGRESS_GW_ADDRESS/<route-path>" \
  -H "content-type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [{"role": "user", "content": "Hello"}]
  }' | jq
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