alibaba/happyhorse-1.1/text-to-video

Text-zu-Video

HappyHorse 1.1 Text-to-Video API by Alibaba

alibaba/happyhorse-1.1/text-to-video

Text-to-video

Generates videos from text prompts with HappyHorse 1.1, supporting 480P, 720P, or 1080P output, flexible aspect ratios, and durations from 3 to 15 seconds.

Modelle vergleichen

HappyHorse 1.1 Text-to-Video wurde von Alibaba entwickelt. Atlas Cloud (betrieben von Atlas Cloud AI LLC) stellt lediglich den Zugang bereit und ist nicht Eigentümerin des Modells. Alle Marken sind Eigentum ihrer jeweiligen Inhaber.

Eingabe

Prompt *

Auflösung

Seitenverhältnis

Dauer

Seed

Ausgabe

Inaktiv

Ihre generierten Videos erscheinen hier

Konfigurieren Sie Parameter und klicken Sie auf Ausführen, um mit der Generierung zu beginnen

Jede Ausführung kostet $0.07. Für $10 können Sie ca. 142 Mal ausführen.

Sie können fortfahren mit:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parameter

Codebeispiel
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/text-to-video",  # Required. Model name. options: alibaba/happyhorse-1.1/text-to-video
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # Required. Text prompt describing the video content
    "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()

Installieren

Installieren Sie das erforderliche Paket für Ihre Programmiersprache.

pip install requests

Authentifizierung

Alle API-Anfragen erfordern eine Authentifizierung über einen API-Schlüssel. Sie können Ihren API-Schlüssel über das Atlas Cloud Dashboard erhalten.

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

HTTP-Header

import os

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

Schützen Sie Ihren API-Schlüssel

Geben Sie Ihren API-Schlüssel niemals in clientseitigem Code oder öffentlichen Repositories preis. Verwenden Sie stattdessen Umgebungsvariablen oder einen Backend-Proxy.

Anfrage senden

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())

Anfrage senden

Senden Sie eine asynchrone Generierungsanfrage. Die API gibt eine Vorhersage-ID zurück, mit der Sie den Status prüfen und das Ergebnis abrufen können.

POST/api/v1/model/generateVideo

Anfragekörper

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/text-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']}")

Antwort

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

Status prüfen

Fragen Sie den Vorhersage-Endpunkt ab, um den aktuellen Status Ihrer Anfrage zu überprüfen.

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

Abfrage-Beispiel

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)

Statuswerte

processingDie Anfrage wird noch verarbeitet.

completedDie Generierung ist abgeschlossen. Ergebnisse sind verfügbar.

succeededDie Generierung war erfolgreich. Ergebnisse sind verfügbar.

failedDie Generierung ist fehlgeschlagen. Überprüfen Sie das Fehlerfeld.

Abgeschlossene Antwort

{
  "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"
  }
}

Dateien hochladen

Laden Sie Dateien in den Atlas Cloud Speicher hoch und erhalten Sie eine URL, die Sie in Ihren API-Anfragen verwenden können. Verwenden Sie multipart/form-data zum Hochladen.

POST/api/v1/model/uploadMedia

Upload-Beispiel

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}")

Antwort

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

Eingabe-Schema

Die folgenden Parameter werden im Anfragekörper akzeptiert.

Gesamt: 6Erforderlich: 2Optional: 4

modelstringrequired

Model name.

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

alibaba/happyhorse-1.1/text-to-video

promptstringrequired

Text prompt describing the video content. Maximum length is 2500 characters.

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

Beispiel-Anfragekörper

{
  "model": "alibaba/happyhorse-1.1/text-to-video",
  "prompt": "A beautiful landscape",
  "resolution": "1080p",
  "ratio": "16:9",
  "duration": 5,
  "seed": -1
}

Ausgabe-Schema

Die API gibt eine Vorhersage-Antwort mit den generierten Ausgabe-URLs zurück.

codeinteger

messagestring

dataunknown

Beispielantwort

{
  "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 integriert über 400 KI-Modelle direkt in Ihren KI-Programmierassistenten. Ein Befehl zur Installation, dann generieren Sie per natürlicher Sprache Bilder und Videos und chatten mit LLMs.

Unterstützte Clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ unterstützte clients

Installieren

npx skills add AtlasCloudAI/atlas-cloud-skills

API-Schlüssel einrichten

Erhalten Sie Ihren API-Schlüssel über das Atlas Cloud Dashboard und setzen Sie ihn als Umgebungsvariable.

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

Funktionen

Nach der Installation können Sie natürliche Sprache in Ihrem KI-Assistenten verwenden, um auf alle Atlas Cloud Modelle zuzugreifen.

BildgenerierungGenerieren Sie Bilder mit Modellen wie Nano Banana 2, Z-Image und mehr.

VideoerstellungErstellen Sie Videos aus Text oder Bildern mit Kling, Vidu, Veo usw.

LLM-ChatChatten Sie mit Qwen, DeepSeek und anderen großen Sprachmodellen.

Medien-UploadLaden Sie lokale Dateien für Bildbearbeitung und Bild-zu-Video-Workflows hoch.

Mehr erfahren

github.com/AtlasCloudAI/atlas-cloud-skills

MCP-Server

Der Atlas Cloud MCP-Server verbindet Ihre IDE mit über 400 KI-Modellen über das Model Context Protocol. Funktioniert mit jedem MCP-kompatiblen Client.

Unterstützte Clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ unterstützte clients

Installieren

npx -y atlascloud-mcp

Konfiguration

Fügen Sie die folgende Konfiguration zur MCP-Einstellungsdatei Ihrer IDE hinzu.

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

Verfügbare Werkzeuge

atlas_generate_imageGenerieren Sie Bilder aus Textbeschreibungen.

atlas_generate_videoErstellen Sie Videos aus Text oder Bildern.

atlas_chatChatten Sie mit großen Sprachmodellen.

atlas_list_modelsDurchsuchen Sie über 400 verfügbare KI-Modelle.

atlas_quick_generateInhaltserstellung in einem Schritt mit automatischer Modellauswahl.

atlas_upload_mediaLaden Sie lokale Dateien für API-Workflows hoch.

Mehr erfahren

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/text-to-video",
            "enum": [
              "alibaba/happyhorse-1.1/text-to-video"
            ]
          },
          "prompt": {
            "description": "Text prompt describing the video content. Maximum length is 2500 characters.",
            "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"
        ],
        "x-order-properties": [
          "model",
          "prompt",
          "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-freundliche Prompt-Vorlage

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

> Generates videos from text prompts with HappyHorse 1.1, 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/text-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/text-to-video"`
  - Options: "alibaba/happyhorse-1.1/text-to-video"

- **`prompt`** (`string`, _required_):
  Text prompt describing the video content. Maximum length is 2500 characters.

- **`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/text-to-video",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "alibaba/happyhorse-1.1/text-to-video",
  "prompt": "",
  "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/text-to-video",
  "prompt": "",
  "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/text-to-video)

A solitary sports car travels through an endless empty landscape at sunset. No buildings, no people, only the sound of wind and the distant engine. The camera follows from behind as the car disappears toward the horizon, leaving a trail of dust illuminated by golden sunlight. Long shadows stretch across the ground while the sky gradually transitions from warm orange to deep blue. Themes of freedom, escape, and self-discovery. Cinematic road movie atmosphere, emotional storytelling, minimalist composition, ultra realistic, masterpiece.

Wird geladen...

Alibaba HappyHorse 1.1 Text-to-Video

Alibaba HappyHorse 1.1 Text-to-Video turns a text prompt into a short video clip with flexible framing, two output resolutions, and support for durations from 3 to 15 seconds.

What makes it stand out?

Prompt-first video generation: Start from a text description without preparing source media.
Flexible framing: Supports 16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21, and 21:9.
Two production-ready resolutions: Generate at 720P or 1080P.
Deterministic reruns: Reuse a seed when you want closer repeatability.

Designed For

Short-form video drafts for social, ads, and product teasers.
Creative teams iterating on scene ideas before moving into heavier production.
Prompt-based concept exploration where fast video feedback matters.

How to Use

Write a prompt that clearly describes subject, action, camera feel, and mood.
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.
Use a fixed seed when you want a more repeatable generation path.

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.

HappyHorse 1.1 Text-to-Video API by Alibaba

Eingabe

Ausgabe

Parameter

Codebeispiel

Installieren

Authentifizierung

HTTP-Header

Anfrage senden

Anfrage senden

Anfragekörper

Antwort

Status prüfen

Abfrage-Beispiel

Statuswerte

Abgeschlossene Antwort

Dateien hochladen

Upload-Beispiel

Antwort

Eingabe-Schema

Beispiel-Anfragekörper

Ausgabe-Schema

Beispielantwort

Atlas Cloud Skills

Unterstützte Clients

Installieren

API-Schlüssel einrichten

Funktionen

MCP-Server

Unterstützte Clients

Installieren

Konfiguration

Verfügbare Werkzeuge

API-Schema

LLM-freundliche Prompt-Vorlage

Alibaba HappyHorse 1.1 Text-to-Video

What makes it stand out?

Designed For

How to Use

Ähnliche Modelle Erkunden

HappyHorse-1.1 Reference-to-video

HappyHorse-1.1 Image-to-video

HappyHorse-1.0 Image-to-video

HappyHorse-1.0 Text-to-video

HappyHorse-1.0 Video-edit

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

Eine API für alle Media-KI.

Eingabe

Ausgabe

Parameter

Codebeispiel

Installieren

Authentifizierung

HTTP-Header

Anfrage senden

Anfrage senden

Anfragekörper

Antwort

Status prüfen

Abfrage-Beispiel

Statuswerte

Abgeschlossene Antwort

Dateien hochladen

Upload-Beispiel

Antwort

Eingabe-Schema

Beispiel-Anfragekörper

Ausgabe-Schema

Beispielantwort

Atlas Cloud Skills