Z-Image Turbo LoRA API: Lora Support

Z-Image Turbo LoRA API Reference

Endpoint

POST https://api.muapi.ai/api/v1/z-image-turbo-text-to-image-lora

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	The positive prompt for the generation.
loras	array	No	List of LoRAs to apply (maximum 3).
aspect_ratio	string	No	Output aspect ratio, automatically mapped to pixel dimensions.Options: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 21:9, 9:21Default: "1:1"
output_format	string	No	Format of the generated image.Options: jpeg, png, webpDefault: "jpeg"

cURL example

REQUEST_ID=$(curl -s -X POST https://api.muapi.ai/api/v1/z-image-turbo-text-to-image-lora \
  -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"

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}/z-image-turbo-text-to-image-lora", 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.