The model that performs video-to-video editing by applying a reference style or identity to source footage, enabling appearance transfer across clips while preserving motion and structure from the original video. The model is well-suited for maintaining consistent characters, branding elements, or artistic style over multiple outputs derived from related source videos.
How to Make a Call
Step-by-Step Instructions
1ď¸Setup You Canât Skip
âŞď¸Create an Account: Visit the AI/ML API website and create an account (if you donât have one yet).
âŞď¸Generate an API Key: After logging in, navigate to your account dashboard and generate your API key. Ensure the key is enabled on the UI.
2ď¸Copy the code example
At the bottom of this page, you'll find a code example that shows how to structure the request. Choose the code snippet in your preferred programming language and copy it into your development environment.
3ď¸Modify the code example
âŞď¸ Replace <YOUR_AIMLAPI_KEY> with your actual AI/ML API key.
âŞď¸ Adjust the input field used by this model (for example, prompt, input text, instructions, media source, or other model-specific input) to match your request.
4ď¸(Optional)Adjust other optional parameters if needed
Only the required parameters shown in the example are needed to run the request, but you can include optional parameters to fine-tune behavior. Below, you can find the corresponding API schema, which lists all available parameters and usage notes.
5ď¸Run your modified code
Run your modified code inside your development environment. Response time depends on many factors, but for simple requests it rarely exceeds a few seconds.
If you need a more detailed walkthrough for setting up your development environment and making a request step-by-step, feel free to use our Quickstart guide.
API Schemas
Create a video generation task and send it to the server
post
Body
modelstring ¡ enumRequiredPossible values:
promptstring ¡ max: 2500Required
The text description of the scene, subject, or action to generate in the video.
video_urlstring ¡ uriRequired
A HTTPS URL pointing to a video or a data URI containing a video. This video will be used as a reference during generation.
Array of image URLs for multi-image-to-video generation.
aspect_ratiostring ¡ enumOptional
The aspect ratio of the generated video.
Default: 16:9Possible values:
durationinteger ¡ enumOptional
The length of the output video in seconds.
Default: 5Possible values:
keep_audiobooleanOptional
Whether to keep the original audio from the video.
Default: false
Responses
200Success
application/json
post
/v2/video/generations
200Success
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 â with the generated video URL and additional metadata.
curl -L \
--request POST \
--url 'https://api.aimlapi.com/v2/video/generations' \
--header 'Authorization: Bearer <YOUR_AIMLAPI_KEY>' \
--header 'Content-Type: application/json' \
--data '{
"model": "klingai/video-o1-video-to-video-reference",
"video_url": "https://zovi0.github.io/public_misc/kling-v2-master-t2v-racoon.mp4",
"prompt": "Add a small fairy as a rider on the raccoonâs back. She must have a black-and-golden face and a cloak in the colors of a dark emerald tropical butterfly with bright blue shimmering spots."
}'
import requests
import time
# Insert your AIML API Key instead of <YOUR_AIMLAPI_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}/video/generations"
headers = {
"Authorization": f"Bearer {api_key}",
}
data = {
"model": "klingai/video-o1-video-to-video-reference",
"prompt":'''
Add a small fairy as a rider on the raccoonâs back. She must have a black-and-golden face and a cloak in the colors of a dark emerald tropical butterfly with bright blue shimmering spots.
''',
"video_url": "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/racoon-in-the-forest.mp4"
}
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()
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}/video/generations"
params = {
"generation_id": gen_id,
}
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
}
response = requests.get(url, params=params, headers=headers)
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)
# Try to retrieve the video from the server every 15 sec
if gen_id:
start_time = time.time()
timeout = 1000
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 ["waiting", "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()
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: "klingai/video-o1-video-to-video-reference",
prompt: `
Add a small fairy as a rider on the raccoonâs back. She must have a black-and-golden face and a cloak in the colors of a dark emerald tropical butterfly with bright blue shimmering spots.`,
video_url: "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/racoon-in-the-forest.mp4",
});
const url = new URL(`${baseUrl}/video/generations`);
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}/video/generations`);
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 15 seconds until completion or timeout
function main() {
generateVideo((genResponse) => {
if (!genResponse || !genResponse.id) {
console.error("No generation ID received.");
return;
}
const genId = genResponse.id;
console.log("Generation ID:", genId);
const timeout = 1000 * 1000; // 1000 sec
const interval = 15 * 1000; // 15 sec
const startTime = Date.now();
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;
if (["waiting", "queued", "generating"].includes(status)) {
console.log(`Status: ${status}. Checking again in 15 seconds.`);
setTimeout(checkStatus, interval);
} else {
console.log("Processing complete:\n", responseData);
}
});
};
checkStatus();
})
}
main();
Generation ID: 6a3ada23-8eb3-4e29-948a-59e5bc2074c5:klingai/video-o1-video-to-video-reference
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Processing complete:
{'id': '6a3ada23-8eb3-4e29-948a-59e5bc2074c5:klingai/video-o1-video-to-video-reference', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/flamingo/files/b/0a878546/2Wt0iDavlysQHFuP3_8I5_output.mp4'}}
