> ## Documentation Index
> Fetch the complete documentation index at: https://developers.eyequant.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Run Multiple Prediction Types in a Single EyeQuant Call

> Request attention, clarity, and excitingness predictions together in one EyeQuant API call and retrieve all outputs in a single response.

By default, every EyeQuant analysis returns an attention heatmap — but the API supports several prediction types, and you can request more than one in a single call. By including a `predictions` object in your request body, you can ask for attention, clarity, and excitingness outputs simultaneously, receiving all results together once processing completes rather than making multiple separate requests.

## The `predictions` field

The `predictions` field is an optional top-level object in your request body. Each key corresponds to a prediction type (for example, `attention` or `clarity`), and its value is a configuration object with an `outputs` array that specifies exactly which output artifacts you want. If you omit `predictions` entirely, EyeQuant falls back to the default behaviour and returns only an attention heatmap.

## Example: requesting attention and clarity together

The following request analyzes a Base64-encoded image and asks for both an attention map and a perception map from the `attention` model, plus a clarity score and clarity map from the `clarity` model — all in one call.

```bash theme={null}
curl \
  -X POST \
  -H "Authorization: Bearer $apikey" \
  -H "Content-Type: application/json" \
  -d '{
        "input": {
          "type": "image",
          "content": "iVBORw0KGgoAAAANSUhE....FTkSuQmCC",
          "medium": "desktopWeb",
          "title": "Example"
        },
        "predictions": {
          "attention": {
            "outputs": ["attentionMap", "perceptionMap"]
          },
          "clarity": {
            "outputs": ["score", "map"]
          }
        }
      }' \
  https://api.eyequant.com/v2/analyses
```

After you poll the returned `location` URL and processing completes, the response body contains a unified `outputs` object with results from every requested prediction type:

```json theme={null}
{
  "id": "611457618c1d4283a830d10a9ad4f8ae",
  "status": "success",
  "outputs": {
    "attention": {
      "attentionMap": "https://s3.amazonaws.com/api-eyequant/attentionHeatmap.png",
      "perceptionMap": "https://s3.amazonaws.com/api-eyequant/perceptionMap.png"
    },
    "clarity": {
      "score": 87,
      "map": "https://s3.amazonaws.com/api-eyequant/clarityMap.png"
    }
  }
}
```

## Available prediction types and outputs

EyeQuant currently supports three prediction types. Include any combination of them in the `predictions` object:

| Prediction type | Available outputs                              |
| --------------- | ---------------------------------------------- |
| `attention`     | `attentionMap`, `perceptionMap`, `hotspotsMap` |
| `clarity`       | `score`, `map`                                 |
| `excitingness`  | `score`                                        |

**Attention** predicts where viewers' eyes are drawn on first glance. `attentionMap` is a heatmap overlay, `perceptionMap` shows predicted visual perception across the design, and `hotspotsMap` highlights the individual hot spots as discrete regions.

**Clarity** measures how visually clear and structured the design appears. The `score` is a numeric value from 0–100 and `map` is a spatial clarity heatmap.

**Excitingness** predicts the emotional arousal a design is likely to trigger. It returns a single numeric `score`.

### Example: requesting all three prediction types

```bash theme={null}
curl \
  -X POST \
  -H "Authorization: Bearer $apikey" \
  -H "Content-Type: application/json" \
  -d '{
        "input": {
          "type": "image",
          "content": "iVBORw0KGgoAAAANSUhE....FTkSuQmCC",
          "medium": "desktopWeb",
          "title": "Example"
        },
        "predictions": {
          "attention": {
            "outputs": ["attentionMap", "perceptionMap", "hotspotsMap"]
          },
          "clarity": {
            "outputs": ["score", "map"]
          },
          "excitingness": {
            "outputs": ["score"]
          }
        }
      }' \
  https://api.eyequant.com/v2/analyses
```

## Default configurations

If you include a prediction type in the `predictions` object but pass an empty configuration — for example, `"attention": {}` — EyeQuant uses that prediction's default outputs. You don't need to enumerate every output name if you're happy with the defaults.

<Warning>
  Currently, all available outputs for a given prediction type are returned regardless of which specific outputs you list in the `outputs` array. The array is accepted but not yet enforced. This behaviour may change in a future API version, so you should still pass the outputs you intend to use.
</Warning>

For the complete list of available prediction types and their supported outputs, see the [Predictions Model reference](/concepts/predictions-model).