# video-01-live2d {% columns %} {% column width="66.66666666666666%" %} {% hint style="info" %} This documentation is valid for the following list of our models: * `video-01-live2d` {% endhint %} {% endcolumn %} {% column width="33.33333333333334%" %} Try in Playground {% endcolumn %} {% endcolumns %} An innovative AI model designed for generating high-quality videos from text prompts or image. 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](https://docs.aimlapi.com/quickstart/setting-up). ## 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 both corresponding API schemas.
## API Schemas {% hint style="success" %} Now, all of our API schemas for video models use our new universal short URL — `https://api.aimlapi.com/v2/video/generations`.\ However, you can still call this model using the legacy URL that includes the vendor name. {% endhint %} ### Create a video generation task and send it to the server ## POST /v2/video/generations > ```json {"openapi":"3.0.0","info":{"title":"AIML API","version":"1.0.0"},"servers":[{"url":"https://api.aimlapi.com"}],"paths":{"/v2/video/generations":{"post":{"operationId":"_v2_video_generations","requestBody":{"required":true,"content":{"application/json":{"schema":{"type":"object","properties":{"model":{"type":"string","enum":["video-01-live2d"]},"prompt":{"type":"string","maxLength":2000,"description":"The text description of the scene, subject, or action to generate in the video."},"image_url":{"type":"string","format":"uri","description":"A direct link to an online image or a Base64-encoded local image that will serve as the first frame for the video.\nImage specifications: \n- format must be JPG, JPEG, or PNG; \n- aspect ratio should be greater than 2:5 and less than 5:2; \n- the shorter side must exceed 300 pixels; \n- file size must not exceed 20MB.","required":true},"enhance_prompt":{"type":"boolean","default":true,"description":"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."}},"required":["model","prompt","image_url"],"title":"video-01-live2d"}}}},"responses":{"200":{"content":{"application/json":{"schema":{"type":"object","properties":{"id":{"type":"string","description":"The ID of the generated video."},"status":{"type":"string","enum":["queued","generating","completed","error"],"description":"The current status of the generation task."},"video":{"type":"object","nullable":true,"properties":{"url":{"type":"string","format":"uri","description":"The URL where the file can be downloaded from."}},"required":["url"]},"error":{"type":"object","nullable":true,"properties":{"name":{"type":"string"},"message":{"type":"string"}},"required":["name","message"],"description":"Description of the error, if any."},"meta":{"type":"object","nullable":true,"properties":{"usage":{"type":"object","nullable":true,"properties":{"credits_used":{"type":"number","description":"The number of tokens consumed during generation."}},"required":["credits_used"]}},"description":"Additional details about the generation."}},"required":["id","status"]}}}}}}}}} ``` ### 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 `completed`, the response will include the final result — with the generated video URL and additional metadata. ## GET /v2/video/generations > ```json {"openapi":"3.0.0","info":{"title":"AI/ML Gateway","version":"1.0"},"servers":[{"url":"https://api.aimlapi.com"}],"paths":{"/v2/video/generations":{"get":{"operationId":"VideoControllerV2_pollVideo_v2","parameters":[{"name":"generation_id","required":true,"in":"query","schema":{"type":"string"}}],"responses":{"200":{"description":"Successfully generated video","content":{"application/json":{"schema":{"$ref":"#/components/schemas/Video.v2.PollVideoResponseDTO"}}}}},"tags":["Video Models"]}}},"components":{"schemas":{"Video.v2.PollVideoResponseDTO":{"type":"object","properties":{"id":{"type":"string","description":"The ID of the generated video."},"status":{"type":"string","enum":["queued","generating","completed","error"],"description":"The current status of the generation task."},"video":{"type":"object","nullable":true,"properties":{"url":{"type":"string","format":"uri","description":"The URL where the file can be downloaded from."},"duration":{"type":"number","nullable":true,"description":"The duration of the video."}},"required":["url"]},"duration":{"type":"number","nullable":true,"description":"The duration of the video."},"error":{"nullable":true,"description":"Description of the error, if any."},"meta":{"type":"object","nullable":true,"properties":{"usage":{"type":"object","nullable":true,"properties":{"tokens_used":{"type":"number","description":"The number of tokens consumed during generation."}},"required":["tokens_used"]}},"description":"Additional details about the generation."}},"required":["id","status"]}}}} ``` ## Full Example: Generating and Retrieving the Video From the Server We have a classic [reproduction](https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg) of the famous da Vinci painting. Let's ask the model to generate a video where the Mona Lisa puts on glasses. Generation may take around 3 minutes for a 6-second video. {% tabs %} {% tab title="Python" %} {% code overflow="wrap" %} ```python import requests import time # replace with your actual AI/ML API key api_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 : 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 15 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") if status in ["queued", "generating"]: print(f"Status: {status}. Checking again in 15 seconds.") time.sleep(15) else: print("Processing complete:\n", response_data) return response_data print("Timeout reached. Stopping.") return None if __name__ == "__main__": main() ``` {% endcode %} {% endtab %} {% tab title="JavaScript" %} {% code overflow="wrap" %} ```javascript const https = require("https"); const { URL } = require("url"); // Replace with your actual AI/ML API key const apiKey = ""; const baseUrl = "https://api.aimlapi.com/v2"; // Creating and sending a video generation task to the server function generateVideo(callback) { const data = JSON.stringify({ 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", }); const url = new URL(`${baseUrl}/generate/video/minimax/generation`); const options = { method: "POST", headers: { "Authorization": `Bearer ${apiKey}`, "Content-Type": "application/json", "Content-Length": Buffer.byteLength(data), }, }; const req = https.request(url, options, (res) => { let body = ""; res.on("data", (chunk) => body += chunk); res.on("end", () => { if (res.statusCode >= 400) { console.error(`Error: ${res.statusCode} - ${body}`); callback(null); } else { const parsed = JSON.parse(body); callback(parsed); } }); }); req.on("error", (err) => console.error("Request error:", err)); req.write(data); req.end(); } // Requesting the result of the task from the server using the generation_id function getVideo(genId, callback) { const url = new URL(`${baseUrl}/generate/video/minimax/generation`); url.searchParams.append("generation_id", genId); const options = { method: "GET", headers: { "Authorization": `Bearer ${apiKey}`, "Content-Type": "application/json", }, }; const req = https.request(url, options, (res) => { let body = ""; res.on("data", (chunk) => body += chunk); res.on("end", () => { const parsed = JSON.parse(body); callback(parsed); }); }); req.on("error", (err) => console.error("Request error:", err)); req.end(); } // Initiates video generation and checks the status every 10 s until completion or timeout function main() { generateVideo((genResponse) => { if (!genResponse || !genResponse.generation_id) { console.error("Failed to start generation"); return; } const genId = genResponse.generation_id; console.log("Generation ID:", genId); const startTime = Date.now(); const timeout = 600000; const checkStatus = () => { if (Date.now() - startTime > timeout) { console.log("Timeout reached. Stopping."); return; } getVideo(genId, (responseData) => { if (!responseData) { console.error("Error: No response from API"); return; } const status = responseData.status; console.log("Status:", status); if (["waiting", "active", "queued", "generating"].includes(status)) { console.log("Still waiting... Checking again in 10 seconds."); setTimeout(checkStatus, 10000); } else { console.log("Processing complete:\n", responseData); } }); }; checkStatus(); }); } main(); ``` {% endcode %} {% endtab %} {% endtabs %}
Response {% code overflow="wrap" %} ```json5 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'}} ``` {% endcode %}
Generated Video **Original**: [720x1072](https://drive.google.com/file/d/1AnWhtqf-_DI9f7B3wkhIKAa1YmbE06ns/view?usp=sharing) **Low-res GIF preview**:
--- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.aimlapi.com/api-references/video-models/minimax/video-01-live2d.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.