By analyzing movement in the video, the model automatically generates appropriate sound cues—footsteps, impacts, and object interactions—resulting in more immersive clips without manual audio design. You can also describe the required sounds (non-speech only) in the prompt parameter.
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
Create a video generation task and send it to the server
You can generate a video using this API. In the basic setup, you only need a prompt.
This endpoint creates and sends a video generation task to the server — and returns a generation ID.
post
Body
modelstring · enumRequiredPossible values:
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.
promptstringRequired
The text description of the scene, subject, or action to generate in the video.
negative_promptstringOptional
The description of elements to avoid in the generated video.
Number of inference steps for sampling. Higher values give better quality but take longer.
Default: 50
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.
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 complete, the response will include the final result — with the generated video URL and additional metadata.
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": "tencent/hunyuan-video-foley",
"prompt": "Sounds of the forest birds, gentle breathing from a small mammal, soft paws padding along a forest path.",
"negative_prompt": "Music",
"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: "tencent/hunyuan-video-foley",
prompt: `Sounds of the forest birds, gentle breathing from a small mammal, soft paws padding along a forest path.`,
negative_prompt: 'Music',
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: S3NWNIFxS20cW9TnYnb8W
Status: queued. Checking again in 15 seconds.
Processing complete:
{'id': 'S3NWNIFxS20cW9TnYnb8W', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/flamingo/files/b/0a8bf464/I5yDHjMQWi6wbGp4SQRcz_video_with_audio_1.mp4'}}
