alibaba/happyhorse-1.1/reference-to-video

參考生影片

HappyHorse 1.1 Reference-to-Video API by Alibaba

alibaba/happyhorse-1.1/reference-to-video

Reference-to-video

Generates videos from one to nine reference images and a text prompt, supporting 480P, 720P, or 1080P output, flexible aspect ratios, and durations from 3 to 15 seconds.

HappyHorse 1.1 Reference-to-Video 由 Alibaba 開發。Atlas Cloud（由 Atlas Cloud AI LLC 營運）僅提供接取服務，並不擁有該模型。所有商標均歸其各自所有者所有。

輸入

提示詞 *

圖片 *(0/9)

可拖曳檔案至此，或點擊上傳

MAX:9

解析度

畫面比例

時長

種子

輸出

閒置

生成的影片將在這裡顯示

設定參數後點擊執行開始生成

每次執行將花費 $0.07。$10 可執行約 142 次。

你可以繼續：

Seedance 2.0 Kling v3 Vidu Wan2.7

參數

程式碼範例
import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "alibaba/happyhorse-1.1/reference-to-video",  # Required. Model name. options: alibaba/happyhorse-1.1/reference-to-video
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # Required. Text prompt describing the desired video and how the reference images should be used
    "images": [
        "https://example.com/image1.jpg"
    ],  # Required. Reference image URLs
    "resolution": "1080p",  # Output video resolution. options: 480p | 720p | 1080p
    "ratio": "16:9",  # Aspect ratio of the generated video
    "duration": 5,  # Video duration in seconds. (min: 3, max: 15)
    "seed": -1,  # Random seed for video generation. (min: -1, max: 2147483647)
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

安裝

安裝所需的相依套件。

pip install requests

驗證

所有 API 請求都需要透過 API Key 進行認證。您可以在 Atlas Cloud 控制台取得 API Key。

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

HTTP 標頭

import os

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

保護好您的 API Key

切勿在客戶端程式碼或公開儲存庫中暴露您的 API Key。請使用環境變數或後端代理。

提交請求

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

提交請求

提交一個非同步生成請求。API 會傳回一個 prediction ID，您可以用它來檢查狀態與取得結果。

POST/api/v1/model/generateVideo

請求主體

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "alibaba/happyhorse-1.1/reference-to-video",
    "prompt": "A beautiful sunset over the ocean with gentle waves"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

回應

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

檢查狀態

輪詢 prediction 端點以檢查請求的當前狀態。

GET/api/v1/model/prediction/{prediction_id}

輪詢範例

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

狀態值

processing請求仍在處理中。

completed生成完成，輸出可用。

succeeded生成成功，輸出可用。

failed生成失敗，請檢查 error 欄位。

完成回應

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

上傳檔案

將檔案上傳到 Atlas Cloud 儲存空間，取得可在 API 請求中使用的 URL。使用 multipart/form-data 上傳。

POST/api/v1/model/uploadMedia

上傳範例

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

回應

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

以下參數在請求主體中被接受。

總計: 7必填: 3選填: 4

modelstringrequired

Model name.

Default: "alibaba/happyhorse-1.1/reference-to-video"

alibaba/happyhorse-1.1/reference-to-video

promptstringrequired

Text prompt describing the desired video and how the reference images should be used. Maximum length is 2500 characters.

imagesarray[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: 1Max items: 9

resolutionstring

Output video resolution.

Default: "1080p"

480p720p1080p

ratiostring

Aspect ratio of the generated video.

Default: "16:9"

16:99:161:14:33:44:55:49:2121:9

durationinteger

Video duration in seconds.

Default: 5Min: 3Max: 15

seedinteger

Random seed for video generation. Use -1 for a random seed.

Default: -1Min: -1Max: 2147483647

範例請求主體

{
  "model": "alibaba/happyhorse-1.1/reference-to-video",
  "prompt": "A beautiful landscape",
  "images": [
    "https://example.com/file.jpg"
  ],
  "resolution": "1080p",
  "ratio": "16:9",
  "duration": 5,
  "seed": -1
}

Output Schema

API 傳回包含生成輸出 URL 的 prediction 回應。

codeinteger

messagestring

dataunknown

範例回應

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills 將 400+ AI 模型直接整合到您的 AI 程式碼助手中。一條命令安裝，即可用自然語言生成圖片、影片，以及與 LLM 對話。

支援的客戶端

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ 支援的客戶端

安裝

npx skills add AtlasCloudAI/atlas-cloud-skills

設定 API Key

從 Atlas Cloud 控制台取得 API Key，並將其設定為環境變數。

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

功能

安裝完成後，您可以在 AI 助手中使用自然語言存取所有 Atlas Cloud 模型。

圖片生成使用 Nano Banana 2、Z-Image 等模型生成圖片。

影片創作使用 Kling、Vidu、Veo 等從文字或圖片創建影片。

LLM 對話與 Qwen、DeepSeek 及其他大型語言模型對話。

媒體上傳上傳本機檔案用於圖片編輯和圖生影片工作流程。

MCP Server

Atlas Cloud MCP Server 透過 Model Context Protocol 將您的 IDE 與 400+ AI 模型連接。支援任何相容 MCP 的客戶端。

支援的客戶端

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ 支援的客戶端

安裝

npx -y atlascloud-mcp

設定

將以下設定新增到您的 IDE 的 MCP 設定檔中。

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

可用工具

atlas_generate_image根據文字提示生成圖片。

atlas_generate_video從文字或圖片創建影片。

atlas_chat與大型語言模型對話。

atlas_list_models瀏覽 400+ 可用 AI 模型。

atlas_quick_generate一步式內容創建，自動選擇最佳模型。

atlas_upload_media上傳本機檔案用於 API 工作流程。

了解更多

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "info": {
    "title": "AtlasCloud API",
    "version": "1.0.0",
    "description": "The AtlasCloud API."
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "components": {
    "schemas": {
      "Input": {
        "type": "object",
        "properties": {
          "model": {
            "type": "string",
            "description": "Model name.",
            "default": "alibaba/happyhorse-1.1/reference-to-video",
            "enum": [
              "alibaba/happyhorse-1.1/reference-to-video"
            ]
          },
          "prompt": {
            "description": "Text prompt describing the desired video and how the reference images should be used. Maximum length is 2500 characters.",
            "type": "string"
          },
          "images": {
            "description": "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.",
            "type": "array",
            "minItems": 1,
            "maxItems": 9,
            "items": {
              "type": "string"
            }
          },
          "resolution": {
            "default": "1080p",
            "description": "Output video resolution.",
            "enum": [
              "480p",
              "720p",
              "1080p"
            ],
            "type": "string"
          },
          "ratio": {
            "default": "16:9",
            "description": "Aspect ratio of the generated video.",
            "enum": [
              "16:9",
              "9:16",
              "1:1",
              "4:3",
              "3:4",
              "4:5",
              "5:4",
              "9:21",
              "21:9"
            ],
            "type": "string"
          },
          "duration": {
            "default": 5,
            "minimum": 3,
            "maximum": 15,
            "description": "Video duration in seconds.",
            "type": "integer"
          },
          "seed": {
            "default": -1,
            "minimum": -1,
            "maximum": 2147483647,
            "description": "Random seed for video generation. Use -1 for a random seed.",
            "type": "integer"
          }
        },
        "required": [
          "model",
          "prompt",
          "images"
        ],
        "x-order-properties": [
          "model",
          "prompt",
          "images",
          "resolution",
          "ratio",
          "duration",
          "seed"
        ]
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "code": {
            "type": "integer"
          },
          "message": {
            "type": "string"
          },
          "data": {
            "$ref": "#/components/schemas/PredictionData"
          }
        }
      },
      "PredictionData": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Unique ID of the generation task."
          },
          "model": {
            "type": "string",
            "description": "Model used for the generation."
          },
          "outputs": {
            "type": "array",
            "description": "Generated video results. Each item is a video URL.",
            "items": {
              "type": "string"
            }
          },
          "urls": {
            "type": "object",
            "properties": {
              "get": {
                "type": "string"
              }
            }
          },
          "status": {
            "type": "string",
            "description": "Current task status, such as created, processing, completed, unknown, or failed."
          },
          "created_at": {
            "type": "string",
            "format": "date-time"
          },
          "error": {
            "type": "string",
            "description": "Error message returned when the task fails."
          }
        }
      }
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM 友善的提示詞範本

# alibaba/happyhorse-1.1/reference-to-video

> Generates videos from one to nine reference images and a text prompt, supporting 480P, 720P, or 1080P output, flexible aspect ratios, and durations from 3 to 15 seconds.


## Overview

- **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: "480p", "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)

A tiny medieval knight stands alone on a weathered stone path, wearing a worn iron helmet and a dark leather cloak. Gentle wind blows across the scene, causing the cloak to sway softly and small dust particles to drift through the air. The knight slowly raises its head as if sensing a distant call. The camera begins with a close-up of the helmet visor, revealing scratches, rust, and detailed textures, then smoothly pulls back and circles around the character. Soft morning fog rolls across the ground while golden sunlight pierces through the mist, creating cinematic volumetric rays. In the distant background, ancient mountains and forgotten castle ruins gradually emerge from the haze. The knight takes a few determined steps forward, its cloak fluttering behind. Shallow depth of field, emotional storytelling, cinematic lighting, ultra-detailed textures, atmospheric fog, fantasy adventure mood, Pixar-quality animation, Unreal Engine 5, masterpiece, 4K.

載入中...

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

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

HappyHorse 1.1 Reference-to-Video API by Alibaba

輸入

輸出

參數

程式碼範例

安裝

驗證

HTTP 標頭

提交請求

提交請求

請求主體

回應

檢查狀態

輪詢範例

狀態值

完成回應

上傳檔案

上傳範例

回應

Input Schema

範例請求主體

Output Schema

範例回應

Atlas Cloud Skills

支援的客戶端

安裝

設定 API Key

功能

MCP Server

支援的客戶端

安裝

設定

可用工具

API Schema

LLM 友善的提示詞範本

Alibaba HappyHorse 1.1 Reference-to-Video

What makes it stand out?

Designed For

How to Use

探索類似模型

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HappyHorse-1.1 Text-to-video

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HappyHorse-1.0 Reference-to-video

Wan-2.7 Text-to-video

Wan-2.7 Image-to-video

Wan-2.7 Reference-to-video

Wan-2.7 Video-edit

Wan-2.2 Image-to-video

Wan-2.2 Image-to-video Lora

Wan-2.6 Image-to-video Flash

Wan-2.6 Video-to-video

Wan-2.6 Image-to-video

Wan-2.6 Text-to-video

一個 API，暢享全模態 AI。

輸入

輸出

參數

程式碼範例

安裝

驗證

HTTP 標頭

提交請求

提交請求

請求主體

回應

檢查狀態

輪詢範例

狀態值

完成回應

上傳檔案

上傳範例

回應

Input Schema

範例請求主體

Output Schema

範例回應

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