video-01-live2d

This documentation is valid for the following list of our models:

  • video-01-live2d

Model Overview

An innovative AI model designed for generating high-quality videos from text prompts or image. Developed by Hailou AI, this model can produce visually striking content with cinematic qualities, allowing users to create engaging videos quickly and efficiently.

Setup your API Key

If you don’t have an API key for the AI/ML API yet, feel free to use our Quickstart guide.

How to Make a Call

Step-by-Step Instructions

Generating a video using this model involves sequentially calling two endpoints:

  • The first one is for creating and sending a video generation task to the server (returns a generation ID).

  • The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.

Below, you can find two corresponding API schemas.

API Schemas

Create a video generation task and send it to the server

post
Authorizations
Body
modelundefined · enumRequiredPossible values:
promptstring · max: 2000Required

The text description of the scene, subject, or action to generate in the video.

prompt_optimizerbooleanOptional

If True, the incoming prompt will be automatically optimized to improve generation quality when needed. For more precise control, set it to False — the model will then follow the instructions more strictly.

Default: true
first_frame_imagestring · uriRequired

The model will use the image passed in this parameter as the first frame to generate a video. Supported formats: - URL of the image; - base64 encoding of the image. Image specifications: - format must be JPG, JPEG, or PNG; - aspect ratio should be greater than 2:5 and less than 5:2; the shorter side must exceed 300 pixels; - file size must not exceed 20MB.

Responses
default
application/json
post
POST /v2/generate/video/minimax/generation HTTP/1.1
Host: api.aimlapi.com
Authorization: Bearer <YOUR_AIMLAPI_KEY>
Content-Type: application/json
Accept: */*
Content-Length: 109

{
  "model": "video-01-live2d",
  "prompt": "text",
  "prompt_optimizer": true,
  "first_frame_image": "https://example.com"
}
default
{
  "generation_id": "222226666699999",
  "status": "text"
}

Retrieve the generated video from the server

After sending a request for video generation, this task is added to the queue. This endpoint lets you check the status of a video generation task using its id, obtained from the endpoint described above. If the video generation task status is complete, the response will include the final result — with the generated video URL and additional metadata.

get
Authorizations
Query parameters
generation_idstringRequired

Generation ID

Example: 222226666699999
Responses
default
application/json
get
GET /v2/generate/video/minimax/generation HTTP/1.1
Host: api.aimlapi.com
Authorization: Bearer <YOUR_AIMLAPI_KEY>
Accept: */*
default
{
  "id": "222226666699999",
  "status": "queued",
  "video": {
    "url": "https://example.com"
  }
}

Full Example: Generating and Retrieving the Video From the Server

We have a classic reproduction of the famous da Vinci painting. Let's ask the model to generate a video where the Mona Lisa puts on glasses.

import requests
import time

# replace <YOUR_AIMLAPI_KEY> with your actual AI/ML API key
api_key = "<YOUR_AIMLAPI_KEY>"
base_url = "https://api.aimlapi.com/v2"


# Creating and sending a video generation task to the server
def generate_video():
    url = f"{base_url}/generate/video/minimax/generation"
    headers = {
        "Authorization": f"Bearer {api_key}", 
    }

    data = {
        "model": "video-01-live2d",
        "prompt": "Mona Lisa puts on glasses with her hands.",
        "first_frame_image": "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",      
    }
 
    response = requests.post(url, json=data, headers=headers)
    
    if response.status_code >= 400:
        print(f"Error: {response.status_code} - {response.text}")
    else:
        response_data = response.json()
        # print(response_data)
        return response_data
    

# Requesting the result of the task from the server using the generation_id
def get_video(gen_id):
    url = f"{base_url}/generate/video/minimax/generation"
    params = {
        "generation_id": gen_id,
    }
    
    # Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
    headers = {
        "Authorization": f"Bearer {api_key}", 
        "Content-Type": "application/json"
        }

    response = requests.get(url, params=params, headers=headers)
    # print("Generation:", response.json())
    return response.json()



def main():
     # Running video generation and getting a task id
    gen_response = generate_video()
    gen_id = gen_response.get("generation_id")
    print("Generation ID:  ", gen_id)

    # Trying to retrieve the video from the server every 10 sec
    if gen_id:
        start_time = time.time()

        timeout = 600
        while time.time() - start_time < timeout:
            response_data = get_video(gen_id)

            if response_data is None:
                print("Error: No response from API")
                break
        
            status = response_data.get("status")
            print("Status:", status)

            if status == "waiting" or status == "active" or  status == "queued" or status == "generating":
                print("Still waiting... Checking again in 10 seconds.")
                time.sleep(10)
            else:
                print("Processing complete:/n", response_data)
                return response_data
   
        print("Timeout reached. Stopping.")
        return None     


if __name__ == "__main__":
    main()
Response
Generation ID:   288439434137694
Status: queued
Still waiting... Checking again in 10 seconds.
Status: queued
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: generating
Still waiting... Checking again in 10 seconds.
Status: completed
Processing complete:/n {'id': '288439434137694', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/whale/inference_output%2Fvideo%2F2025-07-08%2Fd1626f4f-be9c-4aca-87da-5b749efcdef7%2Foutput.mp4?Expires=1752005613&OSSAccessKeyId=LTAI5tAmwsjSaaZVA6cEFAUu&Signature=5guXof04YOOgZPBhkeklSFY5gqM%3D'}}
Generated Video

Original: 720x1072

Low-res GIF preview:

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