POST https://api.muapi.ai/api/v1/ovi-text-to-videoSubmit a job with your MuApi API key in the x-api-key header, then poll https://api.muapi.ai/api/v1/predictions/{request_id}/result until status is completed.
| Name | Type | Required | Description |
|---|---|---|---|
| prompt | string | Yes | Text prompt describing the video. |
| aspect_ratio | string | No | Aspect ratio of the output video.Options: 16:9, 9:16Default: "16:9" |
REQUEST_ID=$(curl -s -X POST https://api.muapi.ai/api/v1/ovi-text-to-video \
-H "x-api-key: $MUAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{"prompt":"<prompt>"}' | jq -r .request_id)
curl -s https://api.muapi.ai/api/v1/predictions/$REQUEST_ID/result -H "x-api-key: $MUAPI_API_KEY"import os, time, requests
API = "https://api.muapi.ai/api/v1"
headers = {"x-api-key": os.environ["MUAPI_API_KEY"]}
r = requests.post(f"{API}/ovi-text-to-video", headers=headers, json={"prompt":"<prompt>"})
request_id = r.json()["request_id"]
while True:
res = requests.get(f"{API}/predictions/{request_id}/result", headers=headers).json()
if res["status"] == "completed":
print(res["outputs"]); break
if res["status"] == "failed":
raise RuntimeError(res.get("error"))
time.sleep(3)Full docs and agent/MCP integration: llms.txt. Get an API key at muapi.ai/access-keys.