Alibaba Happy Horse 1.0 (Video Edit) performs prompt-driven video editing with multi-image reference support, supporting 720p/1080p output. Ready-to-use REST API, best performance, no coldstarts, affordable pricing.
Chờ
$0.7cho mỗi lần chạy·~14 / $10
Change the setting in the video to a fashion runway.
Alibaba Happy Horse 1.0 Video Edit performs prompt-driven editing on existing videos, with optional multi-image reference support for stronger visual guidance and identity consistency. Upload a source video, describe the desired edits, and the model generates a transformed video clip in 720p or 1080p.
Prompt-driven video editing Edit existing videos using natural-language instructions for style, mood, action, and visual transformation.
Optional reference-image support Add up to multiple reference images to better guide character appearance, style consistency, and visual identity.
Consistent output workflow Keep the structure of the original video while transforming its look, atmosphere, or subject details.
Flexible resolution options
Choose 720p for lower-cost iteration or 1080p for higher-quality final outputs.
Production-ready API Access the model through a REST inference API with no cold starts for scalable creative workflows.
| Parameter | Required | Description |
|---|---|---|
| video | Yes | Source video to edit. |
| prompt | Yes | Text description of the desired edits. |
| images | No | Optional reference images. Supports 0–9 images. |
| resolution | No | Output resolution: 720p (default) or 1080p. |
| seed | No | Random seed for reproducibility. Range: 0–2147483647. |
0–9 images if you want stronger control over identity, styling, or visual direction.720p for lower-cost iteration or 1080p for higher-quality output.Transform this street video into a cinematic neo-noir scene with rainy atmosphere, stronger reflections on the ground, richer contrast, subtle slow-motion feeling, dramatic lighting, and a premium commercial look
| Resolution | Cost |
|---|---|
| 720p | $0.70 |
| 1080p | $1.40 |
| Resolution | 3s | 5s | 10s | 15s |
|---|---|---|---|---|
| 720p | $0.42 | $0.70 | $1.40 | $2.10 |
| 1080p | $0.84 | $1.40 | $2.80 | $4.20 |
720p costs $0.70 per 5 seconds1080p costs 2× the 720p rate3–15 seconds≤ 15s: output duration matches the input duration> 15s: the system automatically trims to the first 15stotal_price = 0.70 × (resolution == "1080p" ? 2 : 1) × clamp(output_duration, 3, 15) / 5720p for fast testing, then switch to 1080p for final-quality outputs.seed when you want more reproducible edits.video and prompt are required.images is optional and supports 0–9 reference images.3–15 seconds.15 seconds, the system automatically trims it to the first 15 seconds.1080p pricing is exactly 2× the 720p rate.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.0/video-edit with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Happyhorse 1.0 Video Edit below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"resolution": "720p"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.0/video-edit" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.0/video-edit";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"resolution": "720p"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"resolution": "720p"
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.0/video-edit", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout"}:
raise RuntimeError(result)
if status not in {"created", "processing"}:
raise RuntimeError(f"Unexpected status: {status}")
time.sleep(2)Happyhorse 1.0 Video Edit is a Alibaba model for video editing, exposed as a REST API on WaveSpeedAI. Alibaba Happy Horse 1.0 (Video Edit) performs prompt-driven video editing with multi-image reference support, supporting 720p/1080p output. Ready-to-use REST API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/alibaba/alibaba-happyhorse-1.0-video-edit.
Happyhorse 1.0 Video Edit starts at $0.70 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `images`, `video`, `resolution`, `seed`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/alibaba/alibaba-happyhorse-1.0-video-edit.
Median end-to-end generation time on WaveSpeedAI is around 369 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Alibaba). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.