# HappyHorse 1.1 Reference-to-Video — Atlas Cloud API

> Generates videos from one to nine reference images and a text prompt, supporting 720P or 1080P output, flexible aspect ratios, and durations from 3 to 15 seconds.

This is the machine-readable API reference for **HappyHorse 1.1 Reference-to-Video** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `alibaba/happyhorse-1.1/reference-to-video`
- **Built by**: Alibaba
- **Modality**: Video
- **Model page**: https://www.atlascloud.ai/models/alibaba/happyhorse-1.1/reference-to-video
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.14 per second of generated video
- Pay-as-you-go. No minimum spend, no subscription required.

> **These are the authoritative Atlas Cloud rates for this model.** Any price that
> appears in the vendor description further down refers to a different platform or
> a different model variant and does not apply here.

## Use this model from an AI agent

Atlas Cloud ships three first-party integration surfaces. All three authenticate
with the same API key via the `ATLASCLOUD_API_KEY` environment variable.

### MCP server

The official MCP server (`atlascloud-mcp`) exposes this model to any
MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose,
Claude Desktop. One-line install:

```bash
# Claude Code
claude mcp add atlascloud -- npx -y atlascloud-mcp

# OpenAI Codex CLI
codex mcp add atlascloud -- npx -y atlascloud-mcp

# Gemini CLI
gemini mcp add atlascloud -- npx -y atlascloud-mcp

export ATLASCLOUD_API_KEY="your-api-key"
```

Then ask in plain English; the agent calls `atlas_generate_video` with `model: "alibaba/happyhorse-1.1/reference-to-video"`.
The server fetches each model's schema and validates parameters before submitting,
so invalid requests fail fast without spending credits.

MCP docs: https://www.atlascloud.ai/docs/mcp-server

### Agent Skills

`atlas-cloud-skills` is a portable skill package (API reference, code templates in
Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and
12+ other agents:

```bash
npx skills add AtlasCloudAI/atlas-cloud-skills
export ATLASCLOUD_API_KEY="your-api-key"
```

Skills docs: https://www.atlascloud.ai/docs/skills

### CLI

The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs
are polled and downloaded automatically (use `--no-download` when a script only
needs the output URLs):

```bash
# Install (Homebrew, npm, or shell installer)
brew install AtlasCloudAI/tap/atlascloud
# npm install -g atlascloud-cli
# curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh

atlas auth login
atlas generate video alibaba/happyhorse-1.1/reference-to-video -p "Your prompt here"
```

CLI docs: https://www.atlascloud.ai/docs/cli

## HTTP API reference

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `alibaba/happyhorse-1.1/reference-to-video`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  Model name.
  - Default: `"alibaba/happyhorse-1.1/reference-to-video"`
  - Options: "alibaba/happyhorse-1.1/reference-to-video"

- **`prompt`** (`string`, _required_):
  Text prompt describing the desired video and how the reference images should be used. Maximum length is 2500 characters.

- **`images`** (`array[string]`, _required_):
  Reference image URLs. Provide 1 to 9 images. Supported formats are JPEG, JPG, PNG, and WEBP. Each image can be up to 20 MB, with the shorter side at least 400 px.
  - Min items: 1
  - Max items: 9

- **`resolution`** (`string`, _optional_):
  Output video resolution.
  - Default: `"1080p"`
  - Options: "720p", "1080p"

- **`ratio`** (`string`, _optional_):
  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"

- **`duration`** (`integer`, _optional_):
  Video duration in seconds.
  - Default: `5`
  - Min: 3
  - Max: 15

- **`seed`** (`integer`, _optional_):
  Random seed for video generation. Use -1 for a random seed.
  - Default: `-1`
  - Min: -1
  - Max: 2147483647



**Required Parameters Example**:

```json
{
  "model": "alibaba/happyhorse-1.1/reference-to-video",
  "prompt": "",
  "images": [
    ""
  ]
}
```


**Full Example**:

```json
{
  "model": "alibaba/happyhorse-1.1/reference-to-video",
  "prompt": "",
  "images": [
    ""
  ],
  "resolution": "1080p",
  "ratio": "16:9",
  "duration": 5,
  "seed": -1
}
```


### Output Schema

The API returns the following output format:


- **`code`** (`integer`, _optional_):

- **`message`** (`string`, _optional_):

- **`data`** (`string`, _optional_):



**Example Response**:

```json
{
  "code": 0,
  "message": "",
  "data": null
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "alibaba/happyhorse-1.1/reference-to-video",
  "prompt": "",
  "images": [
    ""
  ],
  "resolution": "1080p",
  "ratio": "16:9",
  "duration": 5,
  "seed": -1
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/alibaba/happyhorse-1.1/reference-to-video)

## About this model

_Vendor-supplied description. Any pricing or endpoint mentioned below refers to_
_other platforms — use the Atlas Cloud values above._

#### Alibaba HappyHorse 1.1 Reference-to-Video

**Alibaba HappyHorse 1.1 Reference-to-Video** creates short video clips from a text prompt and one or more reference images, helping preserve subjects, objects, or visual cues from the supplied images.

#### What makes it stand out?

- **Reference-guided generation:** Use 1 to 9 images to guide the people, objects, style, or scene elements in the output.
- **Prompt-directed motion:** Describe how the referenced elements should move, interact, or appear in the final clip.
- **Flexible framing:** Supports `16:9`, `9:16`, `1:1`, `4:3`, `3:4`, `4:5`, `5:4`, `9:21`, and `21:9`.
- **Two output resolutions:** Generate at `720P` or `1080P`.

#### Designed For

- Creators producing videos that need to keep a character, product, or prop recognizable.
- Teams building campaign visuals from approved reference material.
- Storyboard and concept workflows that need visual continuity across generated clips.

#### How to Use

1. Provide 1 to 9 reference image URLs.
2. Write a prompt that describes the desired action, composition, and style.
3. Choose the aspect ratio that matches your delivery surface.
4. Pick `720P` for faster iteration or `1080P` for higher-quality output.
5. Set a duration between 3 and 15 seconds.

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Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/alibaba/happyhorse-1.1/reference-to-video · Docs: https://www.atlascloud.ai/docs