Update app.py

app.py

@@ -1,8 +1,9 @@
 import os
 import gradio as gr
 import torch
-from diffusers import StableDiffusion3Pipeline, AutoencoderKL, KDPM2AncestralDiscreteScheduler
-from huggingface_hub import snapshot_download
+import numpy as np
+import random
+from diffusers import StableDiffusion3Pipeline, SD3Transformer2DModel, FlowMatchEulerDiscreteScheduler
 import spaces
 from PIL import Image
 import requests
@@ -13,18 +14,7 @@ translator = Translator()
 HF_TOKEN = os.environ.get("HF_TOKEN", None)
 # Constants
 model = "stabilityai/stable-diffusion-3-medium"
-
-
-model_path = snapshot_download(
-    repo_id=model, 
-    revision="refs/pr/26",
-    repo_type="model", 
-    ignore_patterns=["*.md", "*..gitattributes"],
-    local_dir="model",
-    token=HF_TOKEN,
-    )
-
-
+MAX_SEED = np.iinfo(np.int32).max
 
 CSS = """
 .gradio-container {
@@ -47,7 +37,7 @@ JS = """function () {
 
 # Ensure model and scheduler are initialized in GPU-enabled function
 if torch.cuda.is_available():
-    pipe = StableDiffusion3Pipeline.from_pretrained(model_path, torch_dtype=torch.float16).to("cuda")
+    pipe = StableDiffusion3Pipeline.from_pretrained(model, torch_dtype=torch.float16, revision="refs/pr/26").to("cuda")
 
 
 # Function 
@@ -60,6 +50,10 @@ def generate_image(
     scale=1.5,
     steps=30,
     clip=3):
+
+    
+    seed = random.randint(0, MAX_SEED)
+    generator = torch.Generator().manual_seed(seed)
     
     prompt = str(translator.translate(prompt, 'English'))
 
@@ -73,6 +67,7 @@ def generate_image(
         guidance_scale=scale,
         num_inference_steps=steps,
         clip_skip=clip,
+        generator = generator,
     )
     return image.images[0]