/fal-ai/flux-lora/image-to-image

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

var raw = JSON.stringify({
  "prompt": "A photo of a lion sitting on a stone bench",
  "num_inference_steps": 28,
  "guidance_scale": 3.5,
  "num_images": 1,
  "enable_safety_checker": true,
  "output_format": "jpeg",
  "image_url": "https://storage.googleapis.com/falserverless/example_inputs/dog.png",
  "strength": 0.85
});

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

fetch("https://api.quickrouter.ai/fal-ai/flux-lora/image-to-image", 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": "A photo of a lion sitting on a stone bench",
  "num_inference_steps": 28,
  "guidance_scale": 3.5,
  "num_images": 1,
  "enable_safety_checker": True,
  "output_format": "jpeg",
  "image_url": "https://storage.googleapis.com/falserverless/example_inputs/dog.png",
  "strength": 0.85
})
headers = {
  'Authorization': 'Bearer YOUR_API_KEY',
  'Content-Type': 'application/json'
}
conn.request("POST", "/fal-ai/flux-lora/image-to-image", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))