Revert GKE demo (#1547)

- Revert "zijun/sdxl-gke-demo (#1546)" (a6a2546e48c1c5db7fd74180b1f4663aa9eb192d)

app.py

@@ -5,7 +5,6 @@ from datasets import load_dataset
 import base64
 import re
 import os
-import random
 import requests
 import time
 from PIL import Image
@@ -89,11 +88,10 @@ def infer(prompt, negative="low_quality", scale=7, style_name=None, profile: gr.
         if re.search(rf"\b{filter}\b", prompt):
             raise gr.Error("Please try again with a different prompt")
 
-    seed = random.randint(0,4294967295)
     prompt, negative = apply_style(style_name, prompt, negative)
     images = []
     url = os.getenv('JAX_BACKEND_URL')
-    payload = {'instances': [{ 'prompt': prompt, 'negative_prompt': negative, 'parameters':{ 'guidance_scale': scale, 'seed': seed } }] }
+    payload = {'prompt': prompt, 'negative_prompt': negative, 'guidance_scale': scale}
     start_time = time.time()
     images_request = requests.post(url, json = payload)
     print(time.time() - start_time)
@@ -102,23 +100,22 @@ def infer(prompt, negative="low_quality", scale=7, style_name=None, profile: gr.
     except requests.exceptions.JSONDecodeError:
         raise gr.Error("SDXL did not return a valid result, try again")
     
-    for prediction in json_data["predictions"]:
-        for image in prediction["images"]:
-            image_b64 = (f"data:image/jpeg;base64,{image}")
-            images.append(image_b64)
+    for image in json_data["images"]:
+        image_b64 = (f"data:image/jpeg;base64,{image}")
+        images.append(image_b64)
 
-            if profile is not None: # avoid conversion on non-logged-in users
-                pil_image = Image.open(BytesIO(base64.b64decode(image)))
-                user_history.save_image( # save images + metadata to user history
-                    label=prompt,
-                    image=pil_image,
-                    profile=profile,
-                    metadata={
-                        "prompt": prompt,
-                        "negative_prompt": negative,
-                        "guidance_scale": scale,
-                    },
-                )
+        if profile is not None: # avoid conversion on non-logged-in users
+            pil_image = Image.open(BytesIO(base64.b64decode(image)))
+            user_history.save_image( # save images + metadata to user history
+                label=prompt,
+                image=pil_image,
+                profile=profile,
+                metadata={
+                    "prompt": prompt,
+                    "negative_prompt": negative,
+                    "guidance_scale": scale,
+                },
+            )
     
     return images, gr.update(visible=True)