Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from diffusers import StableDiffusionPipeline
 import torch
+import random
 
 # Function to load the selected Stable Diffusion model
 def load_model(model_id):
@@ -24,9 +25,14 @@ def switch_model(selected_model):
     pipeline = load_model(selected_model)
     return f"Model switched to: {selected_model}"
 
-def generate_image(prompt, num_inference_steps=50, guidance_scale=7.5):
+def generate_image(prompt, num_inference_steps=20, guidance_scale=7.5, seed=None):
     """Generate an image from a text prompt using Stable Diffusion."""
-    image = pipeline(prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale).images[0]
+    if seed is not None:
+        generator = torch.manual_seed(seed)
+    else:
+        generator = None
+
+    image = pipeline(prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale, generator=generator).images[0]
     return image
 
 # Define the Gradio app layout
@@ -43,8 +49,9 @@ with gr.Blocks() as app:
             )
             model_switch_status = gr.Textbox(label="Model Status", value=f"Current model: {current_model_id}", interactive=False)
             prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here", lines=2)
-            num_inference_steps = gr.Slider(label="Inference Steps", minimum=10, maximum=100, value=50, step=5)
+            num_inference_steps = gr.Slider(label="Inference Steps", minimum=10, maximum=30, value=20, step=1)
             guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=20.0, value=7.5, step=0.5)
+            seed = gr.Number(label="Seed (Optional)", value=None)
             generate_btn = gr.Button("Generate Image")
 
         with gr.Column():
@@ -58,7 +65,7 @@ with gr.Blocks() as app:
 
     generate_btn.click(
         generate_image, 
-        inputs=[prompt, num_inference_steps, guidance_scale], 
+        inputs=[prompt, num_inference_steps, guidance_scale, seed], 
         outputs=output_image
     )