Delete app.py

app.py

@@ -1,71 +0,0 @@
-
-from gradio_client import Client
-import gradio as gr
-
-# Initialize Gradio Client
-client = Client("prithivMLmods/FireRed-Image-Edit-1.0-Fast")
-
-# Define Prediction Function
-def predict_image(images, prompt, seed, randomize_seed, guidance_scale, steps):
-    """
-    Calls the external model's /infer endpoint using the Gradio client
-    and returns the prediction result.
-
-    Args:
-        images: Input image(s).
-        prompt: Text prompt for image editing.
-        seed: Random seed.
-        randomize_seed: Boolean to randomize seed.
-        guidance_scale: Guidance scale for the model.
-        steps: Number of inference steps.
-
-    Returns:
-        The prediction result from the model (e.g., an image).
-    """
-    try:
-        result = client.predict(
-            images,
-            prompt,
-            seed,
-            randomize_seed,
-            guidance_scale,
-            steps,
-            api_name='/infer'
-        )
-        return result
-    except Exception as e:
-        print(f"Error during prediction: {e}")
-        return None
-
-# Define input components
-input_images = gr.Image(type="filepath", label="Input Image")
-input_prompt = gr.Textbox(label="Prompt")
-input_seed = gr.Slider(minimum=0, maximum=2147483647, step=1, label="Seed", value=0)
-input_randomize_seed = gr.Checkbox(label="Randomize Seed", value=False)
-input_guidance_scale = gr.Slider(minimum=0.0, maximum=20.0, step=0.1, label="Guidance Scale", value=7.5)
-input_steps = gr.Slider(minimum=1, maximum=100, step=1, label="Inference Steps", value=20)
-
-# Create a list of input components
-input_components = [
-    input_images,
-    input_prompt,
-    input_seed,
-    input_randomize_seed,
-    input_guidance_scale,
-    input_steps
-]
-
-# Define the output component
-output_image = gr.Image(label="Edited Image")
-
-# Create the Gradio interface
-iface = gr.Interface(
-    fn=predict_image,
-    inputs=input_components,
-    outputs=output_image,
-    title="FireRed Image Editor"
-)
-
-# Launch the Gradio app (optional for local testing, not needed for Spaces deployment if app.py is run directly)
-if __name__ == "__main__":
-    iface.launch()