Text to video
curl --request POST \
--url https://gengen.farm/api/gengen/v1/contents/generations/tasks \
--header 'Authorization: Bearer gengen_live_xxxxxxxxxxxxxxxx' \
--header 'Content-Type: application/json' \
--data '{
"model": "wonder-pro",
"mode": "text_to_video",
"prompt": "A paper spacecraft glides above a neon city at blue hour.",
"controls": {
"resolution": "1080p",
"ratio": "16:9",
"duration": 6,
"outputCount": 2
}
}'import requests
url = "https://gengen.farm/api/gengen/v1/contents/generations/tasks"
payload = {
"model": "wonder-pro",
"prompt": "A paper spacecraft glides above a neon city at blue hour."
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
model: 'wonder-pro',
prompt: 'A paper spacecraft glides above a neon city at blue hour.'
})
};
fetch('https://gengen.farm/api/gengen/v1/contents/generations/tasks', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));{
"id": "wonderclip10:ag_123",
"model": "wonder-pro",
"status": "queued",
"outputs": {
"videos": [],
"images": []
}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}Video API
Create a WonderClip video task
Create a WonderClip text, frame-guided, or multimodal video generation task.
POST
/
contents
/
generations
/
tasks
Text to video
curl --request POST \
--url https://gengen.farm/api/gengen/v1/contents/generations/tasks \
--header 'Authorization: Bearer gengen_live_xxxxxxxxxxxxxxxx' \
--header 'Content-Type: application/json' \
--data '{
"model": "wonder-pro",
"mode": "text_to_video",
"prompt": "A paper spacecraft glides above a neon city at blue hour.",
"controls": {
"resolution": "1080p",
"ratio": "16:9",
"duration": 6,
"outputCount": 2
}
}'import requests
url = "https://gengen.farm/api/gengen/v1/contents/generations/tasks"
payload = {
"model": "wonder-pro",
"prompt": "A paper spacecraft glides above a neon city at blue hour."
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
model: 'wonder-pro',
prompt: 'A paper spacecraft glides above a neon city at blue hour.'
})
};
fetch('https://gengen.farm/api/gengen/v1/contents/generations/tasks', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));{
"id": "wonderclip10:ag_123",
"model": "wonder-pro",
"status": "queued",
"outputs": {
"videos": [],
"images": []
}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}{
"error_code": "<string>",
"error": "<string>",
"error_params": {}
}Authorizations
A workspace API key beginning with gengen_live_.
Body
application/json
Supported WonderClip public model IDs:
wonder-pro— WonderClip Prowonder-standard— WonderClip Standardwonder-happyhorse-1.1— Happy Horse 1.1 through WonderClipwonder-happyhorse-1.0— Happy Horse 1.0 through WonderClip
Available options:
wonder-pro, wonder-standard, wonder-happyhorse-1.1, wonder-happyhorse-1.0 Required generation instructions for every WonderClip mode.
Minimum string length:
1WonderClip generation mode. GENGEN can infer the mode from assets, but an explicit value is recommended.
Supported values:
text_to_video— generate from a text promptimage_first_frame— animate a first-frame imageimage_first_last_frame— interpolate between first and last framesmultimodal_reference— guide generation with reference media
Available options:
text_to_video, image_first_frame, image_first_last_frame, multimodal_reference Reference media is limited to 1–9 items in total. The
wonder-happyhorse-1.1 model accepts only image references in
multimodal_reference mode.
Show child attributes
Show child attributes
Show child attributes
Show child attributes