Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import random
 import os
 
-# Load all models
+
 models = {
     "Face Projection": gr.load("models/Purz/face-projection"),
     "Flux LoRA Uncensored": gr.load("models/prashanth970/flux-lora-uncensored"),
@@ -10,35 +10,19 @@ models = {
     "NSFW Master": gr.load("models/pimpilikipilapi1/NSFW_master")
 }
 
-def generate_image(text, seed, width, height, guidance_scale, num_inference_steps):
-    if seed is not None:
-        random.seed(seed)
-
+def generate_image(text, num_inference_steps):
     result_images = {}
     for model_name, model in models.items():
         result_images[model_name] = model(text)
 
-    print(f"Width: {width}, Height: {height}, Guidance Scale: {guidance_scale}, Inference Steps: {num_inference_steps}")
+    print(f"Inference Steps: {num_inference_steps}")
     
     return [result_images[model_name] for model_name in models]
 
-def randomize_parameters():
-    seed = random.randint(0, 999999)
-    width = random.randint(512, 2048)
-    height = random.randint(512, 2048)
-    guidance_scale = round(random.uniform(0.1, 20.0), 1)
-    num_inference_steps = random.randint(1, 40)
-    
-    return seed, width, height, guidance_scale, num_inference_steps
-
 interface = gr.Interface(
     fn=generate_image,
     inputs=[
         gr.Textbox(label="Type here your imagination:", placeholder="Type or click an example..."),
-        gr.Slider(label="Seed", minimum=0, maximum=999999, step=1),
-        gr.Slider(label="Width", minimum=512, maximum=2048, step=64, value=1024),
-        gr.Slider(label="Height", minimum=512, maximum=2048, step=64, value=1024),
-        gr.Slider(label="Guidance Scale", minimum=0.1, maximum=20.0, step=0.1, value=3.0),
         gr.Slider(label="Number of inference steps", minimum=1, maximum=40, step=1, value=28),
     ],
     outputs=[gr.Image(label=model_name) for model_name in models],