Seedance 1.0 pro (Image-to-Video)

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

• bytedance/seedance-1-0-pro-i2v

Model Overview

Generate professional video content (1080p) from a reference image and text prompt in a minute — with the option to keep the camera fixed throughout the entire clip.

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 both corresponding API schemas.

API Schemas

Create a video generation task and send it to the server

You can generate a video using this API. In the basic setup, you only need a reference image and a prompt. This endpoint creates and sends a video generation task to the server — and returns a generation ID.

model*	string enum: [ bytedance/seedance-1-0-pro-i2v ]
image_url*	string($uri) A direct link to an online image or a Base64-encoded local image that will serve as the visual base or the first frame for the video.
prompt*	string The text description of the scene, subject, or action to generate in the video.
resolution	string default: 1080p An enumeration where the short side of the video frame determines the resolution. enum: [ 480p, 720p, 1080p ]
duration	integer The length of the output video in seconds. enum: [ 5, 10 ]
watermark	boolean default: false Whether the video contains a watermark
seed	integer Varying the seed integer is a way to get different results for the same other request parameters. Using the same value for an identical request will produce similar results. If unspecified, a random number is chosen.
camerafixed	boolean default: false Whether to fix the camera position. true: Fix the camera position. The platform will append instructions to fix the camera position in the user's prompt, but the actual effect is not guaranteed. false: Do not fix the camera position.

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 generation_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

Responses

200Success

get

HTTPcURLJavaScriptPython

GET /v2/generate/video/bytedance/generation HTTP/1.1
Host: api.aimlapi.com
Authorization: Bearer <YOUR_AIMLAPI_KEY>
Accept: */*

200Success

No content

Full Example: Generating and Retrieving the Video From the Server

The code below creates a video generation task, then automatically polls the server every 10 seconds until it finally receives the video URL.

Python

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/bytedance/generation"
    headers = {
        "Authorization": f"Bearer {api_key}", 
    }

    data = {
        "model": "bytedance/seedance-1-0-pro-i2v",
        "prompt": "Mona Lisa puts on glasses with her hands.",
        "image_url": "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
        "resolution": "1080p"      
    }
 
    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/bytedance/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("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()

JavaScript

const https = require("https");
const { URL } = require("url");

// Replace <YOUR_AIMLAPI_KEY> with your actual AI/ML API key
const apiKey = "<YOUR_AIMLAPI_KEY>";
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: "bytedance/seedance-1-0-pro-i2v",
    prompt: "Mona Lisa puts on glasses with her hands.",
    image_url: "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
    duration: "5",
  });

  const url = new URL(`${baseUrl}/generate/video/bytedance/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/bytedance/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 seconds until completion or timeout
function main() {
  generateVideo((genResponse) => {
    if (!genResponse || !genResponse.id) {
      console.error("Failed to start generation");
      return;
    }

    const genId = genResponse.id;
    console.log("Gen_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();

Response

{'id': 'cgt-20250721143112-kkm5n', 'status': 'queued'}
Generation ID:   cgt-20250721143112-kkm5n
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': 'cgt-20250721143112-kkm5n', 'status': 'completed', 'video': {'url': 'https://ark-content-generation-ap-southeast-1.tos-ap-southeast-1.volces.com/seedance-1-0-pro/02175307947305300000000000000000000ffffc0a840664c87c7.mp4?X-Tos-Algorithm=TOS4-HMAC-SHA256&X-Tos-Credential=AKLTYjg3ZjNlOGM0YzQyNGE1MmI2MDFiOTM3Y2IwMTY3OTE%2F20250721%2Fap-southeast-1%2Ftos%2Frequest&X-Tos-Date=20250721T063202Z&X-Tos-Expires=86400&X-Tos-Signature=2d18ca9f23a2b12baac84d7cc9b56b4db77b6215f42a336aa170b666b3126324&X-Tos-SignedHeaders=host'}}

Processing time: ~56 sec (and ~38 sec for the 480p resolution).

Original: 1248x1664

Low-res GIF preview:

"Mona Lisa puts on glasses with her hands."