modified app.py

app.py

@@ -1,38 +1,3 @@
 import gradio as gr
-from transformers import pipeline
-import random
 
-# Load the model
-text_to_image_pipeline = pipeline("text-to-image", model="models/Shakker-Labs/FLUX.1-dev-LoRA-add-details")
-
-def generate_image(prompt, cfg_scale, steps, width, height, randomize_seed, seed_value, lora_scale):
-    # Randomize seed if checkbox is checked
-    if randomize_seed:
-        seed_value = random.randint(0, 10000)
-    
-    # Use the model to generate an image based on the input parameters
-    # Here we assume `text_to_image_pipeline` can accept these parameters
-    return text_to_image_pipeline(prompt, cfg_scale=cfg_scale, steps=steps, width=width, height=height, seed=seed_value, lora_scale=lora_scale)
-
-# Define the Gradio interface
-interface = gr.Interface(
-    fn=generate_image,
-    inputs=[
-        gr.Textbox(label="Enter your text prompt"),
-        gr.Slider(minimum=0, maximum=100, step=0.1, default=7.5, label="CFG Scale"),
-        gr.Slider(minimum=1, maximum=100, step=1, default=25, label="Steps"),
-        gr.Slider(minimum=64, maximum=1024, step=8, default=512, label="Width"),
-        gr.Slider(minimum=64, maximum=1024, step=8, default=512, label="Height"),
-        gr.Checkbox(label="Randomize Seed"),
-        gr.Slider(minimum=0, maximum=10000, step=1, default=1234, label="Seed"),
-        gr.Slider(minimum=0, maximum=10, step=0.1, default=1.0, label="Lora Scale")
-    ],
-    outputs=gr.Image(label="Generated Image"),
-    title="Advanced Text-to-Image Generation",
-    description="Enter a text prompt and adjust the settings to generate an image.",
-    theme="dark",
-    layout="vertical"
-)
-
-# Launch the interface
-interface.launch()
+gr.load("models/Shakker-Labs/FLUX.1-dev-LoRA-add-details").launch()