Happy Horse 1.1 is Alibaba Cloud's video generation model with highly realistic, fluid, and detailed motion. It automatically routes to text-to-video, image-to-video, or reference-to-video based on the inputs you provide.
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
post
Body
modelstring · enumRequiredPossible values:
promptstringRequired
The text description of the scene, subject, or action to generate in the video.
image_urlstring · uriOptional
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.
Array of image URLs for multi-image-to-video generation.
aspect_ratiostring · enumOptional
The aspect ratio of the generated video.
Default: 16:9Possible values:
resolutionstring · enumOptional
An enumeration where the short side of the video frame determines the resolution.
Default: 1080pPossible values:
durationinteger · enumOptional
The length of the output video in seconds.
Default: 10Possible values:
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.
watermarkbooleanOptional
Whether the video contains a watermark.
Default: false
Responses
200
Successful response.
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
200
Successful response.
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 generation_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.
The code below creates a video generation task, then automatically polls the server every 15 seconds until it finally receives the video URL.
Response
Code Example #2: References-to-Video
The code below creates a video generation task using reference images, then automatically polls the server every 15 seconds until it finally receives the video URL.
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": "alibaba/happyhorse-1.1",
"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."
}'
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": "alibaba/happyhorse-1.1",
"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": 7,
}
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: "alibaba/happyhorse-1.1",
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: 7,
});
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: rLCxsu-1_rTBBGbBC6JFJ
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.
Processing complete:
{'id': 'rLCxsu-1_rTBBGbBC6JFJ', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/generations/alligator/1777398123542-525ef81e-4568-4e38-97bd-cf2e2ee5c2aa.mp4'}}
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": "alibaba/happyhorse-1.1",
"prompt": "Combine the images so the T-Rex is wearing a business suit, sitting in a cozy small café, drinking from the mug. Blur the background slightly to create a bokeh effect.",
"reference_image_urls": [
"https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/t-rex.png",
"https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/coffee-mug.jpg",
],
"duration": 8,
}
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: "alibaba/happyhorse-1.1",
prompt: "Combine the images so the T-Rex is wearing a business suit, sitting in a cozy small café, drinking from the mug. Blur the background slightly to create a bokeh effect.",
reference_image_urls: [
"https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/t-rex.png",
"https://raw.githubusercontent.com/aimlapi/api-docs/main/reference-files/coffee-mug.jpg",
],
duration: 8,
});
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: uDXFoifRMu4rpMBtxSn3Q
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.
Processing complete:
{'id': 'uDXFoifRMu4rpMBtxSn3Q', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/generations/alligator/1777422401287-d8a3ae7a-fbe8-4a1e-93b1-3acb6c27c125.mp4'}}
