Inference Requests

Kubeflow serving can be inferenced and managed through its Inference APIs. Find out more about Kubeflow serving APIs in the official Inference API documentation.

Set HOST and PORT

The first step is to determine the ingress IP and ports and set INGRESS_HOST and INGRESS_PORT.
The following command assigns the IP address of the host where the Istio Ingress Gateway pod is running to the INGRESS_HOST variable:

export INGRESS_HOST=$(kubectl get po -l istio=ingressgateway -n istio-system -o jsonpath='{.items[0].status.hostIP}')

The following command assigns the node port used for the HTTP2 service of the Istio Ingress Gateway to the INGRESS_PORT variable:

export INGRESS_PORT=$(kubectl -n istio-system get service istio-ingressgateway -o jsonpath='{.spec.ports[?(@.name=="http2")].nodePort}')

Set Service Host Name

Next step is to determine service hostname. This command retrieves the hostname of a specific InferenceService in a Kubernetes environment by extracting it from the status.url field and assigns it to the SERVICE_HOSTNAME variable:

SERVICE_HOSTNAME=$(kubectl get inferenceservice <DEPLOYMENT_NAME> -o jsonpath='{.status.url}' | cut -d "/" -f 3)

Example:

SERVICE_HOSTNAME=$(kubectl get inferenceservice llm-deploy -o jsonpath='{.status.url}' | cut -d "/" -f 3)

Curl request to get inference

In the next step inference can be done on the deployed model. The following is the template command for inferencing with a json file:

curl -v -H "Host: ${SERVICE_HOSTNAME}" -H "Content-Type: application/json" http://${INGRESS_HOST}:${INGRESS_PORT}/v2/models/{model_name}/infer -d @{input_file_path}

Examples:

Curl request for MPT-7B model

curl -v -H "Host: ${SERVICE_HOSTNAME}" -H "Content-Type: application/json" http://${INGRESS_HOST}:${INGRESS_PORT}/v2/models/mpt_7b/infer -d @$WORK_DIR/data/qa/sample_text1.json

Curl request for Falcon-7B model

curl -v -H "Host: ${SERVICE_HOSTNAME}" -H "Content-Type: application/json" http://${INGRESS_HOST}:${INGRESS_PORT}/v2/models/falcon_7b/infer -d @$WORK_DIR/data/summarize/sample_text1.json

Curl request for Llama2-7B model

curl -v -H "Host: ${SERVICE_HOSTNAME}" -H "Content-Type: application/json" http://${INGRESS_HOST}:${INGRESS_PORT}/v2/models/llama2_7b/infer -d @$WORK_DIR/data/translate/sample_text1.json

Input data format

Input data should be in JSON format. The input should be a '.json' file containing the prompt in the format below:

{
  "id": "42",
  "inputs": [
      {
          "name": "input0",
          "shape": [-1],
          "datatype": "BYTES",
          "data": ["Capital of India?"]
      }
  ]
}