changed to default

app.py

@@ -24,23 +24,9 @@ def infer(prompt, n_samples, steps, scale, seed):
     # generator = torch.Generator(device=device).manual_seed(seed)
     # print("Is GPU busy? ", is_gpu_busy)
     images = []
-    # if(not is_gpu_busy):
-    #    is_gpu_busy = True
-    #    images_list = pipe(
-    #        [prompt] * samples,
-    #        num_inference_steps=steps,
-    #        guidance_scale=scale,
-    # generator=generator,
-    #    )
-    #    is_gpu_busy = False
-    #    safe_image = Image.open(r"unsafe.png")
-    #    for i, image in enumerate(images_list["sample"]):
-    #       if(images_list["nsfw_content_detected"][i]):
-    #           images.append(safe_image)
-    #       else:
-    #           images.append(image)
-    # else:
-    url = os.getenv('BACKEND_URL')
+    images_default = []
+
+    url = os.getenv('BACKEND_URL_DEFAULT')
     response = requests.get(url.format(prompt, int(n_samples), max(50,int(steps)), f'{scale:.1f}', int(seed)))
     #response = requests.get(url.format('a%20naked%20girl', 2, 50, 7.5, 2))
     data = json.load(BytesIO(response.content))
@@ -51,12 +37,6 @@ def infer(prompt, n_samples, steps, scale, seed):
             im = Image.open(BytesIO(base64.b64decode(image['image_base64'])))
             images.append(im)
 
-    # payload = {'prompt': prompt}
-    # images_request = requests.post(url, json=payload)
-    # for image in images_request.json()["output"]['choices']:
-    #    image_b64 = (f"data:image/jpeg;base64,{image['image_base64']}")
-    #    images.append(image_b64)
-
     return images