The model generates realistic 8-second 720p and 1080p videos with detailed visuals and audio. Optimized for speed and cost compared to the Veo 3 (Image-to-Video) model.
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 two corresponding API schemas and examples for both endpoint calls.
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
You can generate a video using this API.
post
Body
modelstring · enumRequiredPossible values:
promptstringRequired
The text description of the scene, subject, or action to generate in the video.
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.
The description of elements to avoid in the generated video.
seedintegerOptional
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.
enhance_promptbooleanOptional
Whether to enhance the video generation.
Default: true
generate_audiobooleanOptional
Whether to generate audio for the video.
Default: true
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
Fetch the video
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.
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/google/generation"
headers = {
"Authorization": f"Bearer {api_key}",
}
data = {
"model": "google/veo-3.0-i2v-fast",
"prompt": "The woman puts on glasses with her hands and then sighs and says slowly: 'Well...'.",
"image_url": "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/google/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()
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: "google/veo-3.0-i2v-fast",
prompt: "The woman puts on glasses with her hands and then sighs and says slowly: 'Well...'.",
image_url: "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
duration: "5",
});
const url = new URL(`${baseUrl}/generate/video/google/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/google/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.id) {
console.error("Failed to start generation");
return;
}
const genId = genResponse.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();
Generation ID: e0ab34a6-1d6b-4b60-99cc-de15e210dbfc:veo-3.0-fast-generate-001
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 {'status': 'completed', 'id': 'e0ab34a6-1d6b-4b60-99cc-de15e210dbfc:veo-3.0-fast-generate-001', 'video': {'url': 'https://cdn.aimlapi.com/generations/guepard/1754988463411-e17d66b5-57c1-4813-a4ed-3a7aa41723f9.mp4'}}
