Update app.py

app.py

@@ -2,27 +2,24 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 
 # Define the inference function
-def generate_image(prompt, seed, denoise):
+def generate_image(prompt, seed):
     client = InferenceClient(model="tryonlabs/FLUX.1-dev-LoRA-Lehenga-Generator")
-    # Assuming the model accepts these parameters; adjust based on actual API
     image = client.text_to_image(
         prompt=prompt,
-        seed=seed if seed >= 0 else None,  # Use -1 for random seed
-        denoise=denoise  # Denoising strength, typically between 0 and 1
+        seed=seed if seed >= 0 else None  # Use -1 for random seed
     )
     return image
 
-# Create the Gradio interface with advanced options
+# Create the Gradio interface
 interface = gr.Interface(
     fn=generate_image,
     inputs=[
         gr.Textbox(label="Prompt", placeholder="Enter your prompt here..."),
-        gr.Slider(label="Seed", minimum=-1, maximum=1000000, step=1, value=-1, info="Set to -1 for random seed"),
-        gr.Slider(label="Denoise Strength", minimum=0.0, maximum=1.0, step=0.01, value=0.8, info="Controls noise reduction (0 to 1)")
+        gr.Slider(label="Seed", minimum=-1, maximum=1000000, step=1, value=-1, info="Set to -1 for random seed")
     ],
     outputs=gr.Image(label="Generated Lehenga Image"),
     title="FLUX.1-dev Lehenga Generator",
-    description="Generate custom Lehenga designs using FLUX.1-dev with LoRA. Adjust seed and denoise for control.",
+    description="Generate custom Lehenga designs using FLUX.1-dev with LoRA. Adjust seed for control.",
 )
 
 # Launch the interface