Kling O3 Image Edit API: AI Image Editing

Kling O3 Image Edit API Reference

Endpoint

POST https://api.muapi.ai/api/v1/kling-o3-image-edit

Submit 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.

Parameters

Name	Type	Required	Description
prompt	string	Yes	Text instructions describing the desired transformation. Maximum 2,000 characters.
images_list	array	Yes	Upload or provide reference images to transform. Up to 10 images supported.
aspect_ratio	string	No	Output image aspect ratio. Use 'auto' to follow the reference image.Options: auto, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 21:9Default: "auto"
resolution	string	No	Output image resolution.Options: 1K, 2K, 4KDefault: "1K"
num_images	int	No	How many images to generate per request.Default: 1

cURL example

REQUEST_ID=$(curl -s -X POST https://api.muapi.ai/api/v1/kling-o3-image-edit \
  -H "x-api-key: $MUAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"<prompt>","images_list":[]}' | jq -r .request_id)

curl -s https://api.muapi.ai/api/v1/predictions/$REQUEST_ID/result -H "x-api-key: $MUAPI_API_KEY"

Python example

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}/kling-o3-image-edit", headers=headers, json={"prompt":"<prompt>","images_list":[]})
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.