Veo3 (Text-to-Video)
Overview
The model generates high-quality short videos from text or image prompts with significant advancements over its predecessor, Veo2.
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
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.
API Schemas
Video Generation
You can generate a video using this API. In the basic setup, you only need a prompt.
The prompt will be automatically enhanced using AI. To disable this feature, set the parameter enhance_prompt to false.
Retrieve the generated video from the server
After sending a request for video generation, this task is added to the queue. Based on the service's load, the generation can be completed in a couple of minutes
or take a bit more.
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.
This model produces highly detailed and natural-looking videos, so generation may take around 2 minutes for a 8-second video with audio.
import requests
import time
base_url = "https://api.aimlapi.com/v2"
# Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
aimlapi_key = "<YOUR_AIMLAPI_KEY>"
# 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 {aimlapi_key}",
}
data = {
"model": "google/veo3",
"prompt": '''
A menacing evil dragon appears in a distance above the tallest mountain, then rushes toward the camera with its jaws open, revealing massive fangs. We see it's coming.
'''
}
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,
}
headers = {
"Authorization": f"Bearer {aimlapi_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("Gen_ID: ", gen_id)
# Trying to retrieve the video from the server every 10 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")
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()Original (with sound): 1280x720
Low-res GIF preview:
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