This model transforms static images into dynamic video clips. Offers more advanced camera controls than v1 Standard model, including options for tilt, pan, zoom, and roll movements. Results in richer details and more stable camera movements, enhancing the overall visual quality of the generated videos. Enhanced animations make elements like water flow and character movements appear more natural and engaging.
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
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.
Create a video generation task and send it to the server
The aspect ratio of the generated video is solely determined by the aspect ratio of the input reference image.
post
Body
modelstring · enumRequiredPossible values:
image_urlstring · uriRequired
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.
promptstringOptional
The text description of the scene, subject, or action to generate in the video.
tail_image_urlstring · uriOptional
A direct link to an online image or a Base64-encoded local image to be used as the last frame of the video.
durationinteger · enumOptional
The length of the output video in seconds.
Default: 5Possible values:
negative_promptstringOptional
The description of elements to avoid in the generated video.
cfg_scalenumber · max: 1Optional
The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt.
static_maskstring · uriOptional
URL of the image for Static Brush Application Area (Mask image created by users using the motion brush).
Responses
200Success
application/json
idstringRequired
The ID of the generated video.
Example: 60ac7c34-3224-4b14-8e7d-0aa0db708325
statusstring · enumRequired
The current status of the generation task.
Example: completedPossible values:
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 — with the generated video URL and additional metadata.
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. The code below creates a video generation task, then automatically polls the server every 15 seconds until it finally receives the video URL.
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": "kling-video/v1/pro/image-to-video",
"prompt": "Mona Lisa puts on glasses with her hands.",
"image_url": "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/mona_lisa_extended.jpg",
"duration": "5",
}
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 # 1000 sec = 16 min 40 sec
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: "kling-video/v1/pro/image-to-video",
prompt: "Mona Lisa puts on glasses with her hands.",
image_url: "https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/mona_lisa_extended.jpg",
duration: "5",
});
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 = 16 min 40 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: gg6lldgKC2tRmvJwBjK7-
Status: queued. 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': 'gg6lldgKC2tRmvJwBjK7-', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/kangaroo/bs2/upload-ylab-stunt-sgp/muse/784256485483880450/VIDEO/20260122/d40612cb5e896d7522b879ef1df858d9-a9d6cd03-e7c7-436f-a5ea-8e4a0436905a.mp4?cacheKey=ChtzZWN1cml0eS5rbGluZy5tZXRhX2VuY3J5cHQSsAHb-cd6E1sNt1khQt00KZDlKKywMoWCcZZpN20KDMWKJ2KpOPIvyEvdZGxo6Pq2ZdfroGNpC8qzkfsQ5NKoUYw3eMISmzkZUGfsxQoGf1s62zOVo8DgLcWTcSVjBrPWDiINCRcRfPLhDcpBBo0nxg5Y4okHO7NlLCxkO5GEezRFVR_DKVVo2STvgP67QWtHz3CzfT8rUhcGCYs1XkQTMJhUxaBjWmmBYRx3p4wutoKr3hoSYF8ADrg3uvuiuzhTSVrQUvw0IiAsCh1HKrgcKo6_JboDCYiKlWjo6KJpZr1TjTMcg3vWAigFMAE&x-kcdn-pid=112781&ksSecret=0de731a5285509eb9c9eb89da6e10bd0&ksTime=6999d288'}}
