/fal-ai/flux-lora

var myHeaders = new Headers();
myHeaders.append("Authorization", "Bearer YOUR_API_KEY");
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
  "prompt": "Extreme close-up of a single tiger eye, direct frontal view. Detailed iris and pupil. Sharp focus on eye texture and color. Natural lighting to capture authentic eye shine and depth. The word \"FLUX\" is painted over it in big, white brush strokes with visible texture.",
  "image_size": "landscape_4_3",
  "num_inference_steps": 28,
  "guidance_scale": 3.5,
  "num_images": 1,
  "enable_safety_checker": true,
  "output_format": "jpeg"
});

var requestOptions = {
  method: 'POST',
  headers: myHeaders,
  body: raw,
  redirect: 'follow'
};

fetch("https://api.quickrouter.ai/fal-ai/flux-lora", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

import http.client
import json

conn = http.client.HTTPSConnection("api.quickrouter.ai")
payload = json.dumps({
  "prompt": "Extreme close-up of a single tiger eye, direct frontal view. Detailed iris and pupil. Sharp focus on eye texture and color. Natural lighting to capture authentic eye shine and depth. The word \"FLUX\" is painted over it in big, white brush strokes with visible texture.",
  "image_size": "landscape_4_3",
  "num_inference_steps": 28,
  "guidance_scale": 3.5,
  "num_images": 1,
  "enable_safety_checker": True,
  "output_format": "jpeg"
})
headers = {
  'Authorization': 'Bearer YOUR_API_KEY',
  'Content-Type': 'application/json'
}
conn.request("POST", "/fal-ai/flux-lora", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))