• Original Model Card
• vLLM Documentation

Chat Completions API

Send Request

curl <AZUREML_ENDPOINT_URL> \
    -X POST \
    -H "Authorization: Bearer <AZUREML_TOKEN>" \
    -H "Content-Type: application/json" \
    -d '{"model":"Qwen/WebWorld-14B","messages":[{"role":"user","content":"What is Deep Learning?"}]}'

Supported Parameters

• model (string): Model ID used to generate the response, in this case since only a single model is deployed within the same endpoint you can either set it to Qwen/WebWorld-14B or leave it blank instead.
• messages (array): A list of messages comprising the conversation so far. Depending on the model you use, different message types (modalities) are supported, like text, images, and audio.

Example payload

{
  "model": "Qwen/WebWorld-14B",
  "messages": [
    {"role":"user","content":"What is Deep Learning?"}
  ],
  "max_completion_tokens": 256,
  "temperature": 0.6
}

Responses API

Send Request

curl <AZUREML_ENDPOINT_URL>/v1/responses \
    -X POST \
    -d '{"model":"Qwen/WebWorld-14B","input":"What is Deep Learning?","reasoning":{"effort":"medium"}}' \
    -H "Authorization: Bearer <AZUREML_TOKEN>" \
    -H "Content-Type: application/json"

Supported Parameters

• model (string): Model ID used to generate the response, in this case since only a single model is deployed within the same endpoint you can either set it to Qwen/WebWorld-14B or leave it blank instead.
• input (str or array): A text, image, or file inputs to the model, or even a list of messages comprising the conversation so far, used to generate the response. Depending on the model you use, different message types (modalities) are supported, like text, images, and audio; whilst in this case only text generation is supported so image and audio inputs are disallowed.

Example Payload

{
  "model": "Qwen/WebWorld-14B",
  "input": "What is Deep Learning?",
  "max_output_tokens": 1024,
  "temperature": 0.6,
  "reasoning": {
    "effort": "medium"
  }
}