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Overview

AI video generation is the hottest AI technology trend in 2024-2025. Through Ace Data Cloud, you can use various video generation models such as Sora, Luma, and Kling to build an automated video production pipeline.

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Involved Services

  • Sora: POST https://api.acedata.cloud/sora/videos
  • Luma: POST https://api.acedata.cloud/luma/videos
  • Kling: POST https://api.acedata.cloud/kling/videos

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Technical Solution

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Prerequisites

  1. Register an account at Ace Data Cloud
  2. Obtain an API Token
  3. Install Python 3.7+ and the requests library

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Implementation Steps

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Step 1: Choose a Video Model

Sora excels at movie-quality visuals, Luma supports control over the first and last frames, and Kling offers fast generation.

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Step 2: Submit a Generation Task

Sora uses /sora/videos, Luma uses /luma/videos, and Kling uses /kling/videos.

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Step 3: Query Task Status

All video APIs support querying task progress via the /tasks endpoint.

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Code Example

Below is a complete Python example using Sora: 
import requests

API_TOKEN = "YOUR_API_TOKEN"

def call_sora():
    response = requests.post(
        "https://api.acedata.cloud/sora/videos",
        headers={
            "Authorization": f"Bearer {API_TOKEN}",
            "Content-Type": "application/json",
        },
        json={
    "prompt": "A cat running across a sunny meadow",
    "model": "sora-2",
    "duration": 10,
    "orientation": "landscape"
},
    )
    return response.json()

result = call_sora()
print(result)

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Best Practices

  • Error Retry: Implement exponential backoff retries for 429 (rate limiting) and 5xx errors
  • Asynchronous Handling: For long-running tasks (image/video generation), use callback_url to receive results asynchronously
  • Cost Control: Monitor usage and expenses via the Ace Data Cloud console
  • Token Security: Store API Tokens in environment variables; avoid hardcoding them in code