# Happy Horse 1.1 Image to Video

> Animate a still photo into a 3-15 second video at 720P or 1080P, with audio generated alongside the picture and the output frame shape taken straight from your image.

## Overview

- **Endpoint**: `https://queue.modelrunner.run/alibaba/happy-horse/v1.1/image-to-video`
- **Model ID**: `alibaba/happy-horse/v1.1/image-to-video`
- **Category**: image-to-video
- **Kind**: inference
- **Tags**: happy-horse, happyhorse, alibaba, image-to-video, photo-to-video, animate-photo, video-generation, video, audio

## Pricing

- **720P**: $0.14 per output second
- **1080P**: $0.18 per output second

## Request Lifecycle

This model runs on the ModelRunner **asynchronous queue API** — a single POST does not return the output. Every call requires an `Authorization: Key $MODEL_RUNNER_KEY` header. Run three steps:

1. **Submit** — `POST https://queue.modelrunner.run/alibaba/happy-horse/v1.1/image-to-video` with a JSON body holding the input fields at the top level. The body may also include a reserved top-level `metadata` object — a flat string map (max 16 keys, key ≤64 / value ≤512 chars) stored on the request for your own tagging. It is never sent to the model; filter your request history with `GET https://queue.modelrunner.run/requests?metadata=<url-encoded JSON>` (exact key=value matches, AND-ed). The response carries request handles only (no output yet):

```json
{
  "status": "IN_QUEUE",
  "request_id": "<21-char id>",
  "status_url": "https://queue.modelrunner.run/alibaba/happy-horse/v1.1/image-to-video/requests/<request_id>/status",
  "response_url": "https://queue.modelrunner.run/alibaba/happy-horse/v1.1/image-to-video/requests/<request_id>",
  "cancel_url": "https://queue.modelrunner.run/alibaba/happy-horse/v1.1/image-to-video/requests/<request_id>/cancel"
}
```

2. **Poll status** — `GET <status_url>` until `status` is `COMPLETED`. Possible values are `IN_QUEUE`, `IN_PROGRESS`, `COMPLETED`, `FAILED`, `CANCELLED`. A `FAILED` request responds with HTTP 400 and an `error` field.

3. **Read result** — `GET <response_url>`. Returns the finished request, including the generated `output`:

```json
{ "id": "<request_id>", "status": "COMPLETED", "output": ..., "input": ... }
```

The JavaScript and Python SDKs below perform steps 2–3 for you. In any language without an SDK (Swift, Go, Kotlin, etc.) you must implement the polling loop and the final result fetch yourself — see the cURL example for the full flow.

### Input Schema

- **`seed`** (`integer`, _optional_):
  Random seed for reproducible results. Omit for a different clip each run.
  - Range: `0` to `2147483647`

- **`prompt`** (`string`, _optional_):
  Optional. Describe what happens next - the movement, the camera, any spoken line, and the sound you want. The scene is already fixed by the image, so describe the action rather than re-describing the picture. Any language, up to 5000 characters (2500 for Chinese). Leave it empty to let the model animate the image on its own.

- **`duration`** (`integer`, _optional_):
  Length of the generated video in whole seconds (3-15). Cost scales directly with this value.
  - Default: `5`
  - Range: `3` to `15`

- **`resolution`** (`ResolutionEnum`, _optional_):
  Output video resolution. 720P bills at $0.14 per second of finished video; 1080P (default) bills at $0.18 per second.
  - Default: `"1080P"`
  - Options: `"720P"`, `"1080P"`

- **`start_image_url`** (`string`, _required_):
  The photo to animate. It becomes the opening frame, and the finished clip takes its frame shape from this image, so upload it already cropped to the proportions you want. JPEG, JPG, PNG or WEBP; at least 300 px on each side, aspect ratio between 1:2.5 and 2.5:1, up to 20 MB.

### Output Schema

_No `Output` schema properties are available._

## Default Example

**Input**

```json
{
  "prompt": "She lifts the pot of mint to her face and breathes in, then looks to camera and says 'gel, çay hazır' — a warm smile as gulls call over the rooftops and a distant ferry horn sounds on the water.",
  "duration": 5,
  "resolution": "1080P",
  "start_image_url": "https://media.modelrunner.ai/un2tpPpD15tTkv1AHosEm.jpeg"
}
```

**Output**

```json
"https://media.modelrunner.ai/REs3B1ebTexgJ0HRWboRH.mp4"
```
## Usage Examples

### cURL

The queue API is asynchronous: submit the request, poll `status_url` until it is `COMPLETED`, then read the result from `response_url`. Requires `jq`.

```bash
# 1. Submit the request (returns request handles, not the output)
SUBMIT=$(curl --silent --request POST \
  --url https://queue.modelrunner.run/alibaba/happy-horse/v1.1/image-to-video \
  --header "Authorization: Key $MODEL_RUNNER_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "prompt": "She lifts the pot of mint to her face and breathes in, then looks to camera and says '\''gel, çay hazır'\'' — a warm smile as gulls call over the rooftops and a distant ferry horn sounds on the water.",
  "duration": 5,
  "resolution": "1080P",
  "start_image_url": "https://media.modelrunner.ai/un2tpPpD15tTkv1AHosEm.jpeg"
}')

STATUS_URL=$(echo "$SUBMIT" | jq -r '.status_url')
RESPONSE_URL=$(echo "$SUBMIT" | jq -r '.response_url')

# 2. Poll until the request leaves the queue / in-progress state
while true; do
  STATUS=$(curl --silent --url "$STATUS_URL" \
    --header "Authorization: Key $MODEL_RUNNER_KEY" | jq -r '.status')
  echo "Status: $STATUS"
  case "$STATUS" in
    COMPLETED) break ;;
    FAILED|CANCELLED) echo "Request $STATUS"; exit 1 ;;
  esac
  sleep 1
done

# 3. Read the finished request, including the generated output
curl --silent --url "$RESPONSE_URL" \
  --header "Authorization: Key $MODEL_RUNNER_KEY"
```

### JavaScript

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

const result = await modelrunner.subscribe("alibaba/happy-horse/v1.1/image-to-video", {
  input: {
  "prompt": "She lifts the pot of mint to her face and breathes in, then looks to camera and says 'gel, çay hazır' — a warm smile as gulls call over the rooftops and a distant ferry horn sounds on the water.",
  "duration": 5,
  "resolution": "1080P",
  "start_image_url": "https://media.modelrunner.ai/un2tpPpD15tTkv1AHosEm.jpeg"
}
});

console.log(result.data);
```

### Python

```python
import asyncio
import modelrunner_ai

async def main():
    response = await modelrunner_ai.submit_async(
        "alibaba/happy-horse/v1.1/image-to-video",
        arguments={
  "prompt": "She lifts the pot of mint to her face and breathes in, then looks to camera and says 'gel, çay hazır' — a warm smile as gulls call over the rooftops and a distant ferry horn sounds on the water.",
  "duration": 5,
  "resolution": "1080P",
  "start_image_url": "https://media.modelrunner.ai/un2tpPpD15tTkv1AHosEm.jpeg"
}
    )
    result = await response.get()
    print(result["output"])

asyncio.run(main())
```

## Additional Resources

- [Playground](https://modelrunner.ai/models/alibaba/happy-horse/v1.1/image-to-video)
- [OpenAPI Schema](https://modelrunner.ai/models/alibaba/happy-horse/v1.1/image-to-video/openapi.json)
- [LLM Instructions](https://modelrunner.ai/models/alibaba/happy-horse/v1.1/image-to-video/llms.txt)