# Happy Horse 1.0

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

* `alibaba/happyhorse-1-0`
  {% endhint %}
  {% endcolumn %}

{% column width="33.33333333333334%" %} <a href="https://aimlapi.com/app/happyhorse-1-0" class="button primary">Try in Playground</a>
{% endcolumn %}
{% endcolumns %}

Advanced video generation and editing model supporting text-to-video, image-to-video, video-to-video, and references-to-video workflows. Handles multi-shot scenes and supports synchronized audio. Ideal for video generation, image animation, video editing, and media content pipelines.

## Setup your API Key

If you don’t have an API key for the AI/ML API yet, feel free to use our [Quickstart guide](https://docs.aimlapi.com/quickstart/setting-up).

## 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

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

## 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":["alibaba/happyhorse-1-0"]},"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."},"reference_image_urls":{"type":"array","items":{"type":"string","format":"uri"},"maxItems":9,"description":"Array of image URLs for multi-image-to-video generation."},"video_url":{"type":"string","format":"uri","description":"A HTTPS URL pointing to a video or a data URI containing a video. This video will be used as a reference during generation."},"aspect_ratio":{"type":"string","enum":["16:9","9:16","1:1","4:3","3:4"],"default":"16:9","description":"The aspect ratio of the generated video."},"resolution":{"type":"string","enum":["720p","1080p"],"default":"1080p","description":"An enumeration where the short side of the video frame determines the resolution."},"duration":{"type":"integer","description":"The length of the output video in seconds. \nThe option does not work if a video reference is provided. \n- If the input video is 15 seconds or shorter, the output video has the same duration as the input.\n- If the input video is longer than 15 seconds, the system automatically uses only the first 15 seconds, so the maximum output duration is 15 seconds.","enum":[3,4,5,6,7,8,9,10,11,12,13,14,15],"default":"10"},"audio_setting":{"type":"string","enum":["auto","origin"],"default":"auto","description":"Audio control. Works only if a video reference is provided.\n- auto (default): Determined by the model.\n- origin: Preserves the original audio from the input 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."},"watermark":{"type":"boolean","default":false,"description":"Whether the video contains a watermark."}},"required":["model","prompt"],"title":"alibaba/happyhorse-1-0"}}}},"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."},"usd_spent":{"type":"number","description":"The total amount of money spent by the user in USD."}},"required":["credits_used","usd_spent"]}},"description":"Additional details about the generation."}},"required":["id","status"]}}}}}}}}}
```

### Retrieve the generated video from the server

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 `generation_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"]}}}}}}}}}
```

## Code Example: Image-to-Video

The code below creates a video generation task, then automatically polls the server every **15** seconds until it finally receives the video URL.

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

```python
import requests
import time

# Insert your AIML API Key instead of <YOUR_AIMLAPI_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}/video/generations"
    headers = {
        "Authorization": f"Bearer {api_key}", 
    }

    data = {
        "model": "alibaba/happyhorse-1-0",
        "prompt": "Mona Lisa puts on glasses with her hands.",
        "image_url": "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/mona_lisa_extended.jpg",
        "duration": "7",
    }
 
    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}/video/generations"
    params = {
        "generation_id": gen_id,
    }
    
    headers = {
        "Authorization": f"Bearer {api_key}", 
        "Content-Type": "application/json"
        }

    response = requests.get(url, params=params, headers=headers)
    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)

    # Try to retrieve the video from the server every 15 sec
    if gen_id:
        start_time = time.time()

        timeout = 1000
        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="JS" %}
{% 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: "alibaba/happyhorse-1-0",
    prompt: "Mona Lisa puts on glasses with her hands.",
    image_url: "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/mona_lisa_extended.jpg",
    duration: "7",
  });

  const url = new URL(`${baseUrl}/video/generations`);
  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}/video/generations`);
  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 15 seconds until completion or timeout
function main() {
    generateVideo((genResponse) => {
        if (!genResponse || !genResponse.id) {
            console.error("No generation ID received.");
            return;
        }

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

        const timeout = 1000 * 1000; // 1000 sec
        const interval = 15 * 1000; // 15 sec
        const startTime = Date.now();

        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;
        
                if (["queued", "generating"].includes(status)) {
                    console.log(`Status: ${status}. Checking again in 15 seconds.`);
                    setTimeout(checkStatus, interval);
                } else {
                    console.log("Processing complete:\n", responseData);
                }
            });
        };
        checkStatus();
    })
}

main();
```

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

<details>

<summary>Response</summary>

{% code overflow="wrap" %}

```json5
Generation ID:   rLCxsu-1_rTBBGbBC6JFJ
Status: queued. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Processing complete:
 {'id': 'rLCxsu-1_rTBBGbBC6JFJ', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/generations/alligator/1777398123542-525ef81e-4568-4e38-97bd-cf2e2ee5c2aa.mp4'}}
```

{% endcode %}

</details>

**Processing time**: \~ 2 min 36 sec.

**Generated video** (1920x1080, with sound):

{% embed url="<https://drive.google.com/file/d/1-zE_NsJAaPYGqYkmH-9U--hXz_5BNuYR/view?usp=sharing>" %}

## Code Example #2: Video-to-Video

The code below creates a video generation task, then automatically polls the server every **15** seconds until it finally receives the video URL.

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

```python
import requests
import time

# Insert your AIML API Key instead of <YOUR_AIMLAPI_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}/video/generations"
    headers = {
        "Authorization": f"Bearer {api_key}", 
    }

    data = {
        "model": "alibaba/happyhorse-1-0",
        "prompt": '''
            Replace the raccoon in the reference video with the dinosaur from the reference image. Match the dinosaur to the raccoon’s exact movement, position, scale, speed, and perspective throughout the entire scene. Seamlessly integrate the dinosaur into the environment with perfectly accurate shadows, lighting, ground contact, and motion blur. Preserve the original forest landscape, camera motion, framing, background, and all scene details without any changes. The result must look fully realistic and natural, as if the dinosaur was originally filmed in the video.
        ''',
        "reference_image_urls": ["https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/t-rex.png"],
        "video_url": "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/racoon-in-the-forest.mp4",
        "duration": "8",
    }
 
    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}/video/generations"
    params = {
        "generation_id": gen_id,
    }
    
    headers = {
        "Authorization": f"Bearer {api_key}", 
        "Content-Type": "application/json"
        }

    response = requests.get(url, params=params, headers=headers)
    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)

    # Try to retrieve the video from the server every 15 sec
    if gen_id:
        start_time = time.time()

        timeout = 1000
        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="JS" %}
{% 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: "alibaba/happyhorse-1-0",
    prompt: `
      Replace the raccoon in the reference video with the dinosaur from the reference image. Match the dinosaur to the raccoon’s exact movement, position, scale, speed, and perspective throughout the entire scene. Seamlessly integrate the dinosaur into the environment with perfectly accurate shadows, lighting, ground contact, and motion blur. Preserve the original forest landscape, camera motion, framing, background, and all scene details without any changes. The result must look fully realistic and natural, as if the dinosaur was originally filmed in the video.
    `,
    reference_image_url: ["https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/t-rex.png"],
    video_url: "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/racoon-in-the-forest.mp4",
    duration: "8",
  });

  const url = new URL(`${baseUrl}/video/generations`);
  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}/video/generations`);
  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 15 seconds until completion or timeout
function main() {
    generateVideo((genResponse) => {
        if (!genResponse || !genResponse.id) {
            console.error("No generation ID received.");
            return;
        }

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

        const timeout = 1000 * 1000; // 1000 sec
        const interval = 15 * 1000; // 15 sec
        const startTime = Date.now();

        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;
        
                if (["queued", "generating"].includes(status)) {
                    console.log(`Status: ${status}. Checking again in 15 seconds.`);
                    setTimeout(checkStatus, interval);
                } else {
                    console.log("Processing complete:\n", responseData);
                }
            });
        };
        checkStatus();
    })
}

main();
```

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

<details>

<summary>Response</summary>

{% code overflow="wrap" %}

```json5
Generation ID:   uDXFoifRMu4rpMBtxSn3Q
Status: queued. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Processing complete:
 {'id': 'uDXFoifRMu4rpMBtxSn3Q', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/generations/alligator/1777422401287-d8a3ae7a-fbe8-4a1e-93b1-3acb6c27c125.mp4'}}
```

{% endcode %}

</details>

**Processing time**: \~ 2 min 51 sec.

<details>

<summary>References</summary>

<table data-full-width="true"><thead><tr><th width="247.06683349609375" valign="top">Reference Image</th><th valign="top">Reference Video (GIF preview)</th></tr></thead><tbody><tr><td valign="top"><img src="https://content.gitbook.com/content/ROMd1X5PuqtikJ48n2N9/blobs/PPV2M1hqsCkKB9mAg212/t%20rex.png" alt="Image #1" data-size="original"></td><td valign="top"><img src="https://3927338786-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FROMd1X5PuqtikJ48n2N9%2Fuploads%2FDAGmmj8VSieRmKdLgk23%2Fracoon-forest-preview.gif?alt=media&#x26;token=8ea98621-85ca-4561-ae17-7b457a3c2b07" alt="&#x22;Combine the images so the T-Rex is wearing a business suit, sitting in a cozy small café, drinking from the mug. Blur the background slightly to create a bokeh effect.&#x22;" data-size="original"></td></tr></tbody></table>

</details>

**Generated video** (1920x1080, with sound):

{% embed url="<https://drive.google.com/file/d/1vxFpHbMZ83hgsc6cIpgmEzxtTlWNcPBd/view?usp=sharing>" %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.aimlapi.com/api-references/video-models/alibaba-cloud/happy-horse-1.0.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.