The model transforms an input video according to a natural-language text prompt, altering style, visual attributes, or the overall look of the scene while preserving the original motion and structural layout of the footage.
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
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 and an example with both endpoint calls.
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.
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-edit",
"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-edit",
"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 ["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-edit",
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 (["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: 9177d714-9f53-4ce7-829f-b81e2223c48b:klingai/video-o1-video-to-video-edit
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.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Processing complete:
{'id': '9177d714-9f53-4ce7-829f-b81e2223c48b:klingai/video-o1-video-to-video-edit', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/flamingo/files/b/0a875051/Uce7GGCPuWbicbRrdaI4U_output.mp4'}}
