# x-ai/grok-imagine-image-quality/edit

> xAI Grok Imagine Image Quality Edit is a fast AI image editing model that edits and enhances images with high-quality visual output using a dedicated RunPod workflow. Ready-to-use REST inference API for photo retouching, creative image edits, product image enhancement, marketing assets, social media visuals, and professional AI image editing workflows with simple integration, no coldstarts, and affordable pricing.

## Overview

- **Endpoint**: `https://api.wavespeed.ai/api/v3/x-ai/grok-imagine-image-quality/edit`
- **Polling/result URL**: `https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result`
- **Model ID**: `x-ai/grok-imagine-image-quality/edit`
- **Category**: image-to-image

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
The API is asynchronous: submit a prediction, then poll its result URL until it completes.

### Input Schema

The API accepts the following input parameters:

- **`prompt`** (`string`, _required_):
  The prompt for image generation or editing.

- **`images`** (`array of string`, _required_):
  The images to edit. A maximum of 3 reference images can be uploaded.

- **`aspect_ratio`** (`string`, _optional_):
  Aspect ratio of the generated image.
  - Default: `"auto"`
  - Options: "auto", "1:1", "16:9", "9:16", "4:3", "3:4", "3:2", "2:3"

- **`resolution`** (`string`, _optional_):
  Output resolution tier.
  - Default: `"1k"`
  - Options: "1k", "2k"

- **`num_images`** (`integer`, _optional_):
  Number of images to generate. Range: 1-4.
  - Default: `1`
  - Range: `1` to `4`

- **`output_format`** (`string`, _optional_):
  Output image format.
  - Default: `"jpeg"`
  - Options: "jpeg", "png", "webp"

- **`enable_base64_output`** (`boolean`, _optional_):
  If set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "images": []
}
```

**Full Example**:

```json
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "images": [],
  "aspect_ratio": "auto",
  "resolution": "1k",
  "num_images": 1,
  "output_format": "jpeg"
}
```

### Result Data Schema

The `data` object returned by the API has the following fields:

- **`created_at`** (`string (date-time)`, _optional_):
  ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array of string | object`, _optional_):
  Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example `data` Object**:

```json
{
  "created_at": "example",
  "id": "example",
  "model": "example",
  "outputs": [],
  "status": "example",
  "urls": {}
}
```

## Usage Examples

The examples use `jq` to read JSON. Set your API key first:

```bash
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
```

### 1. Submit a prediction

```bash
REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "images": []
}
JSON
)

SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --request POST \
  --url https://api.wavespeed.ai/api/v3/x-ai/grok-imagine-image-quality/edit \
  --header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  --header "Content-Type: application/json" \
  --data "${REQUEST_BODY}")

printf '%s\n' "${SUBMIT_RESPONSE}" | jq .
```

The response contains the prediction ID in `data.id`.

### 2. Poll until complete and read `outputs`

```bash
PREDICTION_ID=$(printf '%s' "${SUBMIT_RESPONSE}" | jq -r '.data.id')
if [ -z "${PREDICTION_ID}" ] || [ "${PREDICTION_ID}" = "null" ]; then
  printf 'Submission response did not contain data.id\n' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    --request GET \
    --url "${RESULT_URL}" \
    --header "Authorization: Bearer ${WAVESPEED_API_KEY}")

  RESULT=$(printf '%s' "${RESPONSE}" | jq -e '.data')
  STATUS=$(printf '%s' "${RESULT}" | jq -er '.status')
  case "${STATUS}" in
    completed)
      # Generated files are returned in the outputs array.
      printf '%s\n' "${RESULT}" | jq '.outputs'
      break
      ;;
    failed|cancelled|timeout|deleted)
      printf '%s\n' "${RESULT}" | jq '{status, error, code}'
      exit 1
      ;;
    *)
      sleep 2
      ;;
  esac
done
```

## Additional Resources

### Documentation

- [Model Playground](https://wavespeed.ai/models/x-ai/grok-imagine-image-quality/edit)
- [API Documentation](https://wavespeed.ai/docs/docs-api/x-ai/x-ai-grok-imagine-image-quality-edit)