# Veo 2 (Image-to-Video)

{% columns %}
{% column width="66.66666666666666%" %}
{% hint style="info" %}
This documentation is valid for the following list of our models:

* `veo2/image-to-video`
  {% endhint %}
  {% endcolumn %}

{% column width="33.33333333333334%" %} <a href="https://aimlapi.com/app/veo2/image-to-video" class="button primary">Try in Playground</a>
{% endcolumn %}
{% endcolumns %}

An advanced multimodal (image + text) AI model that transforms static images into high-quality, dynamic video content. It builds upon the success of Google's [Veo2 text-to-video](https://docs.aimlapi.com/api-references/video-models/google/veo2-text-to-video) model, offering unprecedented control and realism in video generation from still images, faithful content preservation from source images, and intuitive motion generation with physics-aware movement.

## How to Make a Call

<details>

<summary>Step-by-Step Instructions</summary>

Generating a video using this model involves sequentially calling two endpoints:

* The first one is for creating and sending a video generation task to the server (returns a generation ID).
* The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.

Below, you can find both corresponding API schemas.

</details>

## API Schemas

{% hint style="success" %}
Now, all of our API schemas for video models use our new universal short URL — `https://api.aimlapi.com/v2/video/generations`.\
However, you can still call this model using the legacy URL that includes the vendor name.
{% endhint %}

### Create a video generation task and send it to the server

You can generate a video using this API.

## POST /v2/video/generations

>

```json
{"openapi":"3.0.0","info":{"title":"AIML API","version":"1.0.0"},"servers":[{"url":"https://api.aimlapi.com"}],"paths":{"/v2/video/generations":{"post":{"operationId":"_v2_video_generations","requestBody":{"required":true,"content":{"application/json":{"schema":{"type":"object","properties":{"model":{"type":"string","enum":["veo2/image-to-video"]},"prompt":{"type":"string","description":"The text description of the scene, subject, or action to generate in the video."},"image_url":{"type":"string","format":"uri","description":"A direct link to an online image or a Base64-encoded local image that will serve as the visual base or the first frame for the video."},"tail_image_url":{"type":"string","format":"uri","description":"A direct link to an online image or a Base64-encoded local image to be used as the last frame of the video."},"duration":{"type":"integer","description":"The length of the output video in seconds.","enum":[5,6,7,8],"default":"5"},"aspect_ratio":{"type":"string","enum":["16:9","9:16"],"description":"The aspect ratio of the generated video."},"negative_prompt":{"type":"string","description":"The description of elements to avoid in the generated video."},"seed":{"type":"integer","description":"Varying the seed integer is a way to get different results for the same other request parameters. Using the same value for an identical request will produce similar results. If unspecified, a random number is chosen."},"enhance_prompt":{"type":"boolean","default":true,"description":"Whether to enhance the video generation."}},"required":["model","prompt","image_url"],"title":"veo2/image-to-video"}}}},"responses":{"200":{"content":{"application/json":{"schema":{"type":"object","properties":{"id":{"type":"string","description":"The ID of the generated video."},"status":{"type":"string","enum":["queued","generating","completed","error"],"description":"The current status of the generation task."},"video":{"type":"object","nullable":true,"properties":{"url":{"type":"string","format":"uri","description":"The URL where the file can be downloaded from."}},"required":["url"]},"error":{"type":"object","nullable":true,"properties":{"name":{"type":"string"},"message":{"type":"string"}},"required":["name","message"],"description":"Description of the error, if any."},"meta":{"type":"object","nullable":true,"properties":{"usage":{"type":"object","nullable":true,"properties":{"credits_used":{"type":"number","description":"The number of tokens consumed during generation."}},"required":["credits_used"]}},"description":"Additional details about the generation."}},"required":["id","status"]}}}}}}}}}
```

### Fetch the video

After sending a request for video generation, this task is added to the queue. This endpoint lets you check the status of a video generation task using its `id`, obtained from the endpoint described above.\
If the video generation task status is `completed`, the response will include the final result — with the generated video URL and additional metadata.

## GET /v2/video/generations

>

```json
{"openapi":"3.0.0","info":{"title":"AIML API","version":"1.0.0"},"servers":[{"url":"https://api.aimlapi.com"}],"security":[{"access-token":[]}],"components":{"securitySchemes":{"access-token":{"scheme":"bearer","bearerFormat":"<YOUR_AIMLAPI_KEY>","type":"http","description":"Bearer key","in":"header"}}},"paths":{"/v2/video/generations":{"get":{"operationId":"_v2_video_generations","parameters":[{"name":"generation_id","required":true,"in":"query","schema":{"type":"string"}}],"responses":{"200":{"content":{"application/json":{"schema":{"type":"object","properties":{"id":{"type":"string","description":"The ID of the generated video."},"status":{"type":"string","enum":["queued","generating","completed","error"],"description":"The current status of the generation task."},"video":{"type":"object","nullable":true,"properties":{"url":{"type":"string","format":"uri","description":"The URL where the file can be downloaded from."}},"required":["url"]},"error":{"type":"object","nullable":true,"properties":{"name":{"type":"string"},"message":{"type":"string"}},"required":["name","message"],"description":"Description of the error, if any."},"meta":{"type":"object","nullable":true,"properties":{"usage":{"type":"object","nullable":true,"properties":{"credits_used":{"type":"number","description":"The number of tokens consumed during generation."}},"required":["credits_used"]}},"description":"Additional details about the generation."}},"required":["id","status"]}}}}}}}}}
```

## Full Example: Generating and Retrieving the Video From the Server

We have a classic [reproduction](https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg) of the famous da Vinci painting. Let's ask the model to generate a video where the Mona Lisa puts on glasses.

{% hint style="info" %}
Generation may take around 40-50 seconds for a 5-second video.
{% endhint %}

{% tabs %}
{% tab title="Python" %}
{% code overflow="wrap" %}

```python
import requests
import time

# replace <YOUR_AIMLAPI_KEY> with your actual AI/ML API key
api_key = "<YOUR_AIMLAPI_KEY>"
base_url = "https://api.aimlapi.com/v2"


# Creating and sending a video generation task to the server
def generate_video():
    url = f"{base_url}/generate/video/google/generation"
    headers = {
        "Authorization": f"Bearer {api_key}", 
    }

    data = {
        "model": "veo2/image-to-video",
        "prompt": "Mona Lisa puts on glasses with her hands.",
        "image_url": "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
        "duration": "5",       
    }
 
    response = requests.post(url, json=data, headers=headers)
    
    if response.status_code >= 400:
        print(f"Error: {response.status_code} - {response.text}")
    else:
        response_data = response.json()
        return response_data
    

# Requesting the result of the task from the server using the generation_id
def get_video(gen_id):
    url = f"{base_url}/generate/video/google/generation"
    params = {
        "generation_id": gen_id,
    }
    
    # Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
    headers = {
        "Authorization": f"Bearer {api_key}", 
        "Content-Type": "application/json"
        }

    response = requests.get(url, params=params, headers=headers)
    # print("Generation:", response.json())
    return response.json()



def main():
     # Running video generation and getting a task id
    gen_response = generate_video()
    gen_id = gen_response.get("id")
    print("Generation ID:  ", gen_id)

    # Trying to retrieve the video from the server every 10 sec
    if gen_id:
        start_time = time.time()

        timeout = 600
        while time.time() - start_time < timeout:
            response_data = get_video(gen_id)

            if response_data is None:
                print("Error: No response from API")
                break
        
            status = response_data.get("status")
            
            if status in ["queued", "generating"]:
                print(f"Status: {status}. Checking again in 15 seconds.")
                time.sleep(15)
            else:
                print("Processing complete:\n", response_data)
                return response_data
   
        print("Timeout reached. Stopping.")
        return None     


if __name__ == "__main__":
    main()
```

{% endcode %}
{% endtab %}

{% tab title="JavaScript" %}
{% code overflow="wrap" %}

```javascript
const https = require("https");
const { URL } = require("url");

// Replace <YOUR_AIMLAPI_KEY> with your actual AI/ML API key
const apiKey = "<YOUR_AIMLAPI_KEY>";
const baseUrl = "https://api.aimlapi.com/v2";

// Creating and sending a video generation task to the server
function generateVideo(callback) {
  const data = JSON.stringify({
    model: "veo2/image-to-video",
    prompt: "Mona Lisa puts on glasses with her hands.",
    image_url: "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
    duration: "5",
  });

  const url = new URL(`${baseUrl}/generate/video/google/generation`);
  const options = {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${apiKey}`,
      "Content-Type": "application/json",
      "Content-Length": Buffer.byteLength(data),
    },
  };

  const req = https.request(url, options, (res) => {
    let body = "";
    res.on("data", (chunk) => body += chunk);
    res.on("end", () => {
      if (res.statusCode >= 400) {
        console.error(`Error: ${res.statusCode} - ${body}`);
        callback(null);
      } else {
        const parsed = JSON.parse(body);
        callback(parsed);
      }
    });
  });

  req.on("error", (err) => console.error("Request error:", err));
  req.write(data);
  req.end();
}

// Requesting the result of the task from the server using the generation_id
function getVideo(genId, callback) {
  const url = new URL(`${baseUrl}/generate/video/google/generation`);
  url.searchParams.append("generation_id", genId);

  const options = {
    method: "GET",
    headers: {
      "Authorization": `Bearer ${apiKey}`,
      "Content-Type": "application/json",
    },
  };

  const req = https.request(url, options, (res) => {
    let body = "";
    res.on("data", (chunk) => body += chunk);
    res.on("end", () => {
      const parsed = JSON.parse(body);
      callback(parsed);
    });
  });

  req.on("error", (err) => console.error("Request error:", err));
  req.end();
}

// Initiates video generation and checks the status every 10 s until completion or timeout
function main() {
  generateVideo((genResponse) => {
    if (!genResponse || !genResponse.id) {
      console.error("Failed to start generation");
      return;
    }

    const genId = genResponse.id;
    console.log("Gen_ID:", genId);

    const startTime = Date.now();
    const timeout = 600000;

    const checkStatus = () => {
      if (Date.now() - startTime > timeout) {
        console.log("Timeout reached. Stopping.");
        return;
      }

      getVideo(genId, (responseData) => {
        if (!responseData) {
          console.error("Error: No response from API");
          return;
        }

        const status = responseData.status;
        console.log("Status:", status);

        if (["waiting", "active", "queued", "generating"].includes(status)) {
          console.log("Still waiting... Checking again in 10 seconds.");
          setTimeout(checkStatus, 10000);
        } else {
          console.log("Processing complete:\n", responseData);
        }
      });
    };

    checkStatus();
  });
}

main();
```

{% endcode %}
{% endtab %}
{% endtabs %}

<details>

<summary>Response</summary>

{% code overflow="wrap" %}

```json5
Gen_ID:   9bf4e6f6-dae7-41c7-94aa-354443b300c6:veo2/image-to-video
Status: queued
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: completed
Processing complete:\n {'id': '812dbc37-f15a-46a4-a058-8477bd243f5a:veo2/image-to-video', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/eagle/files/rabbit/D7LD6oJwKMF9gk9KjqwDV_output.mp4', 'content_type': 'video/mp4', 'file_name': 'output.mp4', 'file_size': 6827705}}
```

{% endcode %}

</details>

**Original**: [1280x720](https://drive.google.com/file/d/19p8OlNOWJrJN9Z6KFTzloQ4ZAAmQIaDu/view?usp=sharing)

**Low-res GIF preview**:

<div align="left"><figure><img src="https://3927338786-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FROMd1X5PuqtikJ48n2N9%2Fuploads%2Fgit-blob-15d4edccb517a037246fc11f698f0800fd40ec06%2Fveo2-image-to-video-monalisa-preview.gif?alt=media" alt=""><figcaption></figcaption></figure></div>