# Happy Horse 1.1 Text to Video

> Generate a short video with synchronized native audio from a text prompt, with spoken dialogue lip-synced on screen, at 720P or 1080P.

## Overview

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

## Pricing

- **Price**: $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/text-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/text-to-video/requests/<request_id>/status",
  "response_url": "https://queue.modelrunner.run/alibaba/happy-horse/v1.1/text-to-video/requests/<request_id>",
  "cancel_url": "https://queue.modelrunner.run/alibaba/happy-horse/v1.1/text-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`

- **`ratio`** (`RatioEnum`, _optional_):
  Frame shape (aspect ratio) of the generated video.
  - Default: `"16:9"`
  - Options: `"16:9"`, `"9:16"`, `"1:1"`, `"4:3"`, `"3:4"`, `"4:5"`, `"5:4"`, `"9:21"`, `"21:9"`

- **`prompt`** (`string`, _required_):
  Describe the scene, the action, the camera move, and any spoken lines or sound you want. Dialogue written into the prompt is spoken on screen and lip-synced to the character. Up to 5000 characters (2500 for Chinese); longer prompts are truncated.

- **`duration`** (`integer`, _optional_):
  Length of the generated video in whole seconds (3-15).
  - 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"`

### Output Schema

_No `Output` schema properties are available._

## Default Example

**Input**

```json
{
  "ratio": "16:9",
  "prompt": "Close-up of an elderly lighthouse keeper in a thick wool sweater, warm lamplight on his weathered face. He looks to camera and says warmly, 'Forty years I've kept this light burning.' Wind and distant surf behind him.",
  "duration": 5,
  "resolution": "1080P"
}
```

**Output**

```json
"https://media.modelrunner.ai/UhStvzgcQmWm8eJ9Tnv3L.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/text-to-video \
  --header "Authorization: Key $MODEL_RUNNER_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "ratio": "16:9",
  "prompt": "Close-up of an elderly lighthouse keeper in a thick wool sweater, warm lamplight on his weathered face. He looks to camera and says warmly, '\''Forty years I'\''ve kept this light burning.'\'' Wind and distant surf behind him.",
  "duration": 5,
  "resolution": "1080P"
}')

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/text-to-video", {
  input: {
  "ratio": "16:9",
  "prompt": "Close-up of an elderly lighthouse keeper in a thick wool sweater, warm lamplight on his weathered face. He looks to camera and says warmly, 'Forty years I've kept this light burning.' Wind and distant surf behind him.",
  "duration": 5,
  "resolution": "1080P"
}
});

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/text-to-video",
        arguments={
  "ratio": "16:9",
  "prompt": "Close-up of an elderly lighthouse keeper in a thick wool sweater, warm lamplight on his weathered face. He looks to camera and says warmly, 'Forty years I've kept this light burning.' Wind and distant surf behind him.",
  "duration": 5,
  "resolution": "1080P"
}
    )
    result = await response.get()
    print(result["output"])

asyncio.run(main())
```

## Additional Resources

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