Update app.py

app.py

@@ -1,6 +1,29 @@
 import gradio as gr
+from huggingface_hub import InferenceClient
 
-gr.load(
-   "models/tryonlabs/FLUX.1-dev-LoRA-Lehenga-Generator",
-   provider="hf-inference",
-).launch()
+# Define the inference function
+def generate_image(prompt, seed, denoise):
+    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
+    )
+    return image
+
+# Create the Gradio interface with advanced options
+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)")
+    ],
+    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.",
+)
+
+# Launch the interface
+interface.launch()