Run your first model

This example shows how to invoke an image-based model using the Norman SDK. You provide an input image, and the model returns the processed output as raw bytes. See all available models in the Models Library.

# Initialize the SDK with your API key
norman = Norman(api_key="nrm_sk_2a96b7b1a9f44b09b7c3f9f1843e93e2")

# Define the invocation configuration
invocation_config = {
    "model_name": "image_reverser_model",
    "inputs": [
        {
            "display_title": "Input",
            "data": "/Users/alice/Desktop/sample_image.png"
        }
    ]
}

# Invoke the model
response = await norman.invoke(invocation_config)

# Initialize the SDK with your API key
norman = Norman(api_key="nrm_sk_2a96b7b1a9f44b09b7c3f9f1843e93e2")

# Define the invocation configuration
invocation_config = {
    "model_name": "image_reverser_model",
    "inputs": [
        {
            "display_title": "Input",
            "data": "/Users/alice/Desktop/sample_image.png"
        }
    ]
}

# Invoke the model
response = await norman.invoke(invocation_config)

# Initialize the SDK with your API key
norman = Norman(api_key="nrm_sk_2a96b7b1a9f44b09b7c3f9f1843e93e2")

# Define the invocation configuration
invocation_config = {
    "model_name": "image_reverser_model",
    "inputs": [
        {
            "display_title": "Input",
            "data": "/Users/alice/Desktop/sample_image.png"
        }
    ]
}

# Invoke the model
response = await norman.invoke(invocation_config)

# Initialize the SDK with your API key
norman = Norman(api_key="nrm_sk_2a96b7b1a9f44b09b7c3f9f1843e93e2")

# Define the invocation configuration
invocation_config = {
    "model_name": "image_reverser_model",
    "inputs": [
        {
            "display_title": "Input",
            "data": "/Users/alice/Desktop/sample_image.png"
        }
    ]
}

# Invoke the model
response = await norman.invoke(invocation_config)

Example Response

{
  "output_image": <bytes>

{
  "output_image": <bytes>

{
  "output_image": <bytes>

{
  "output_image": <bytes>

Response Structure

Root object (dict):

output_image (bytes) — Binary output data representing the model’s generated result.

For image models, this contains the image bytes.
For text or audio models, it contains the corresponding binary data.

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