Update app.py

app.py

@@ -1,45 +1,18 @@
-import gradio as gr
-from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
+from diffusers import StableDiffusionPipeline
 import torch
 import random
 
-# No token needed
-model_id = "stabilityai/stable-diffusion-2-1-base"  # ✅ New model ID
-pipe = StableDiffusionPipeline.from_pretrained(model_id)  # ✅ Simplified
-
-# Add before initializing the pipeline
-from diffusers import EulerDiscreteScheduler
-
-scheduler = EulerDiscreteScheduler.from_pretrained(
-    model_id, 
-    subfolder="scheduler"  # ✅ Required for SD v2
-)
-
-# Include in pipeline initialization
-pipe = StableDiffusionPipeline.from_pretrained(
-    model_id,
-    scheduler=scheduler,  # ✅ Add this
-    torch_dtype=torch.float32
-)
-
-# Old (might try to use GPU):
-pipe.to("cuda")  
-
-# New (force CPU):
-pipe.to("cpu")  # ✅ Explicit CPU usage
-
-pipe.enable_attention_slicing()  # ✅ Reduces RAM usage
-
 def generate_image(prompt):
-    seed = random.randint(0, 1000000)  # Random seed
-    generator = torch.Generator("cpu").manual_seed(seed)
+    # Load the model
+    pipe = StableDiffusionPipeline.from_pretrained(
+        "stabilityai/stable-diffusion-2-1",
+        use_auth_token="YOUR_HF_TOKEN"  # Replace with your token
+    )
+    
+    # Random seed for uniqueness
+    seed = random.randint(0, 1000000)
+    generator = torch.Generator().manual_seed(seed)
+    
+    # Generate image
     image = pipe(prompt, generator=generator).images[0]
     return image
-
-# Create interface
-gr.Interface(
-    fn=generate_image,
-    inputs=gr.Textbox(label="Type anything (e.g., 'dog')"),
-    outputs=gr.Image(label="Generated Image"),
-    title="Free AI Image Generator"
-).launch()