HappyHorse 1.1 Text-to-Video

HappyHorse 1.1 Text-to-Video is Alibaba's next-generation AI text-to-video model. Built on an integrated audio-video joint generation architecture, it generates native 720P/1080P HD videos directly from text, supporting up to 15 seconds of rendering. It natively supports multilingual lip-sync, ambient sound effects, and audio-visual synchronization without extra dubbing, while delivering exceptional motion smoothness, subject consistency, and camera control—ideal for short dramas, commercial ads, and social media video production.

HappyHorse 1.1 Text-to-Video

Base URL

https://api.icreat.ai

Authentication

All API requests must be authenticated with an API Key. You can obtain an API Key from the console.

export ICREAT_API_KEY="your-api-key-here"

HTTP Request Headers

import os

API_KEY = os.environ.get("ICREAT_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer " + API_KEY,
}

Protect your API Key

Never expose your API Key in client-side code or public repositories. Use environment variables or a backend proxy.

Code Examples

Image and video generation uses a three-step async flow: submit to get task_id, poll status, then fetch results when status is SUCCEEDED.

1. Submit Task

Send a generation request to the submit endpoint.

POST/v1/task/submit/ali/happyhorse-1-1/text-to-video

curl --fail-with-body --connect-timeout 10 --max-time 60 \
  -X POST https://api.icreat.ai/v1/task/submit/ali/happyhorse-1-1/text-to-video \
  -H "Authorization: Bearer ${ICREAT_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "input": {
      "prompt": "A running kitten",
      "negative_prompt": "The kitten should not run in a straight line"

    },
    "parameters": {
      "resolution": "720P",
      "ratio": "1:1",
      "duration": 5,
      "watermark": false
    }
  }'

2. Poll Status

Poll with task_id. Response contains only status.

POST/v1/task/query-status

curl --connect-timeout 10 --max-time 60 \
  -X POST "https://api.icreat.ai/v1/task/query-status" \
  -H "Authorization: Bearer ${ICREAT_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "task_id": "task-xxx"
  }'

3. Get Result

Fetch output when the task succeeds.

POST/v1/task/get-result

curl --connect-timeout 10 --max-time 60 \
  -X POST "https://api.icreat.ai/v1/task/get-result" \
  -H "Authorization: Bearer ${ICREAT_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "task_id": "task-xxx"
  }'

Input Schema

Submit Task — Input

Total: 2 Required: 2 Optional: 0

inputobjectrequired

Generation input payload.

:::

parametersobjectrequired

Generation parameters.

Poll Status — Input

Total: 1 Required: 1 Optional: 0

task_idstringrequired

Task ID from the submit endpoint.

Get Result — Input

Total: 1 Required: 1 Optional: 0

task_idstringrequired

Task ID from the submit endpoint.

Output Schema

Submit Task — Output

Total: 1

task_idstring

Async task identifier.

Poll Status — Output

Total: 1

statusstring

Current task status. Fetch results when SUCCEEDED.

Get Result — Output

Top-level array of resource objects.

Total: 3

typestring

Resource type; Video for this model.

urlstring

Preview/access URL.

download_urlstring

Download URL.

LLM Prompt

The Markdown below is an LLM-friendly prompt you can paste into AI assistants (e.g. Cursor, ChatGPT) to help them understand this model's API, call flow, and key parameters. Use Copy for AI or copy from the code block below.

# ali/happyhorse-1-1/text-to-video

> HappyHorse 1.1 Text-to-Video is Alibaba's next-generation AI text-to-video model.

## Overview

Use the iCreat three-step async task API: submit a generation request, poll status, then fetch the video URL on success.

## API Info

- **Base URL**：`https://api.icreat.ai`
- **Submit endpoint (POST)**：`/v1/task/submit/ali/happyhorse-1-1/text-to-video`
- **Poll endpoint (POST)**：`/v1/task/query-status`
- **Get result endpoint (POST)**：`/v1/task/get-result`
- **Model ID**：`ali/happyhorse-1-1/text-to-video`
- **Auth**：`Authorization: Bearer ${ICREAT_API_KEY}`

## Call Flow

1. **Submit**: POST submit path with body per Input Notes; response `{ "task_id": "..." }`
2. **Poll**: POST `/v1/task/query-status` with `{ "task_id": "..." }`; response contains **only** `{ "status": "SUBMITTED|SUCCEEDED|FAILED" }`
3. **Get result**: when `status` is `SUCCEEDED`, POST `/v1/task/get-result`; top-level array; read `url` or `download_url` when `type` is `Video`

### Input Notes

- Top-level body: `input` (object) + `parameters` (object) as siblings
- `input.prompt` (required): Prompt describing the video to generate.
- `input.negative_prompt` (optional): Content that should not appear in the video.
- `parameters.resolution` (required): Video resolution.
- `parameters.ratio` (required): Video aspect ratio.
- `parameters.duration` (required): Video duration in seconds.
- `parameters.watermark` (optional): Whether to add a watermark.

### Output Notes

- Poll: read `status` only
- Result: top-level `[{ "type": "Video", "url": "...", "download_url": "..." }]`

## Notes

- Use the same `task_id` across all three steps; do not skip polling
- `FAILED` is terminal — check request parameters or reference media
- `input` and `parameters` are sibling top-level fields; do not nest them