## Basic model info

- Model name: xai/xai grok-imagine-video
- Model description: Generate high-quality videos from text, images, reference images, or existing videos with xAI's Grok Imagine Video model.
- Endpoint name: reference-to-video


## Model schema

The model schema is defined in the OpenAPI schema: [OpenAPI Schema](https://oapi.sunra.ai/main/xai/grok-imagine-video/latest.json)

### Model input schema

The model input schema is:



```json
{
  "description": "Input model for reference-to-video generation using Grok Imagine Video.",
  "properties": {
    "prompt": {
      "description": "Text description of the desired video.",
      "maxLength": 4096,
      "minLength": 1,
      "title": "Prompt",
      "type": "string",
      "x-sr-order": 201
    },
    "aspect_ratio": {
      "default": "16:9",
      "description": "Aspect ratio of the generated video.",
      "enum": [
        "16:9",
        "4:3",
        "3:2",
        "1:1",
        "2:3",
        "3:4",
        "9:16"
      ],
      "title": "Aspect Ratio",
      "type": "string",
      "x-sr-order": 402
    },
    "duration": {
      "default": 8,
      "description": "Video duration in seconds.",
      "maximum": 10,
      "minimum": 1,
      "title": "Duration",
      "type": "integer",
      "x-sr-order": 401
    },
    "reference_images": {
      "description": "URLs of reference images used to guide the video generation.",
      "items": {
        "anyOf": [
          {
            "format": "uri",
            "maxLength": 2083,
            "minLength": 1,
            "type": "string"
          },
          {
            "type": "string"
          }
        ]
      },
      "minItems": 1,
      "title": "Reference Images",
      "type": "array",
      "x-sr-order": 301
    },
    "resolution": {
      "default": "480p",
      "description": "Resolution of the output video.",
      "enum": [
        "480p",
        "720p"
      ],
      "title": "Resolution",
      "type": "string",
      "x-sr-order": 403
    }
  },
  "required": [
    "prompt",
    "reference_images"
  ],
  "title": "ReferenceToVideoInput",
  "type": "object"
}
```



### Model output schema

The model output schema is:



```json
{
  "properties": {
    "video": {
      "properties": {
        "content_type": {
          "description": "The mime type of the file.",
          "title": "Content Type",
          "type": "string"
        },
        "file_name": {
          "description": "The name of the file. It will be auto-generated if not provided.",
          "title": "File Name",
          "type": "string"
        },
        "file_size": {
          "description": "The size of the file in bytes.",
          "title": "File Size",
          "type": "integer"
        },
        "url": {
          "description": "The URL where the file can be downloaded from.",
          "title": "Url",
          "type": "string"
        }
      },
      "required": [
        "content_type",
        "file_name",
        "file_size",
        "url"
      ],
      "title": "SunraFile",
      "type": "object"
    }
  },
  "required": [
    "video"
  ],
  "title": "VideoOutput",
  "type": "object"
}
```



## Example inputs and outputs

Use the following example inputs and outputs to understand the model.

### Input example



```json
{
  "prompt": "",
  "aspect_ratio": "16:9",
  "duration": 8,
  "reference_images": [
  ],
  "resolution": "480p"
}
```



### Output example



```json
{
}
```



## Model code examples

### JavaScript



```javascript
import { sunra } from "@sunra/client";

const result = await sunra.subscribe("xai/grok-imagine-video/reference-to-video", {
  input: {
  	prompt: '',
  	reference_images: [],
  	duration: 8,
  	aspect_ratio: '16:9',
  	resolution: '480p'
  },
  logs: true,
  onQueueUpdate: (update) => {
    console.log(`Status Update: ${update.status}, Request ID: ${update.request_id}`);
  },
});
console.log(result.data);
console.log(result.requestId);
```



### Python



```python
import sunra_client

result = sunra_client.subscribe(
    "xai/grok-imagine-video/reference-to-video",
    arguments={
        "prompt": "",
        "reference_images": [],
        "duration": 8,
        "aspect_ratio": "16:9",
        "resolution": "480p"
    },
    with_logs=True,
    on_enqueue=print,
    on_queue_update=print,
)
print(result)
```



### Java



```java
import ai.sunra.client.*;
import java.util.Map;
import com.google.gson.JsonObject;

var client = SunraClient.withEnvCredentials();

var response = client.subscribe(
    "xai/grok-imagine-video/reference-to-video",
    SubscribeOptions.<JsonObject>builder()
        .input(Map.of(
            "prompt", "",
            "reference_images", ,
            "duration", 8,
            "aspect_ratio", "16:9",
            "resolution", "480p"))
        .resultType(JsonObject.class)
        .onQueueUpdate(update -> System.out.printf(
            "\nStatus Update: %s, Request ID: %s%n",
            update.getStatus(),
            update.getRequestId()
        ))
        .logs(true)
        .build()
);

System.out.println("Completed!");
System.out.println(response.getData());
  
```



### Kotlin



```kotlin
import ai.sunra.client.kt.*
import com.google.gson.JsonObject

val client = createSunraClient()

val response = client.subscribe<JsonObject>(
    endpointId = "xai/grok-imagine-video/reference-to-video",
    input = mapOf(
            "prompt" to "",
            "reference_images" to ,
            "duration" to 8,
            "aspect_ratio" to "16:9",
            "resolution" to "480p"),
    options = ai.sunra.client.kt.SubscribeOptions(logs = true),
    onUpdate = { update ->
        println("\nStatus Update: ${update.status}, Request ID: ${update.requestId}")
    }
)

println("Completed!")
println(response.data)
  
```



### Curl



```bash

curl --request POST \
  --url https://api.sunra.ai/v1/queue/xai/grok-imagine-video/reference-to-video \
  --header "Authorization: Key $SUNRA_KEY" \
  --header "Content-Type: application/json" \
  --data '{"prompt":"","reference_images":[],"duration":8,"aspect_ratio":"16:9","resolution":"480p"}'
    
```



## Model readme

>