Update app.py

app.py

@@ -1,99 +1,100 @@
 import gradio as gr
 from gradio_client import Client
+import random
 
-# Initialize the Hugging Face client with the specific model
+# Initialize the client for the Hugging Face Space
 client = Client("ByteDance/Hyper-FLUX-8Steps-LoRA")
 
-def generate_image(prompt, height, width, steps, scale, seed):
+def generate_image(prompt, height, width, steps, scales, seed):
     """
-    Function to generate an image based on the provided prompt and parameters.
-    
-    Args:
-        prompt (str): The text prompt to generate the image.
-        height (int): The height of the generated image.
-        width (int): The width of the generated image.
-        steps (int): Number of inference steps.
-        scale (float): Guidance scale for the image generation.
-        seed (int): Seed for random number generator to ensure reproducibility.
-    
+    Generates an image based on the provided parameters by calling the Hugging Face Space API.
+
+    Parameters:
+    - prompt (str): The text prompt for image generation.
+    - height (int): The height of the generated image.
+    - width (int): The width of the generated image.
+    - steps (int): The number of steps for the image generation process.
+    - scales (float): The scaling factor.
+    - seed (int): The seed for random number generation to ensure reproducibility.
+
     Returns:
-        Image: Generated image based on the prompt and parameters.
+    - result (str or Image): The generated image or a link to it.
     """
+    # Generate a random seed if not provided
+    if not seed:
+        seed = random.randint(0, 100000)
+
     try:
-        # Call the predict method of the client with provided parameters
         result = client.predict(
-            height=height,
-            width=width,
-            steps=steps,
-            scales=scale,
+            height=int(height),
+            width=int(width),
+            steps=int(steps),
+            scales=float(scales),
             prompt=prompt,
-            seed=seed,
+            seed=int(seed),
             api_name="/process_image"
         )
         return result
     except Exception as e:
         return f"An error occurred: {e}"
 
-# Define the Gradio interface using the updated API
+# Define the Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# Hyper-FLUX-8Steps-LoRA Image Generator")
-    gr.Markdown(
-        """
-        Enter a text prompt and adjust the parameters to generate an image using the Hyper-FLUX-8Steps-LoRA model.
-        """
-    )
-    
+    gr.Markdown("Generate images based on your text prompts using the Hyper-FLUX-8Steps-LoRA model.")
+
     with gr.Row():
         with gr.Column():
             prompt = gr.Textbox(
                 label="Prompt",
-                placeholder="Enter your image description here...",
+                placeholder="Enter your descriptive text here...",
                 lines=2
             )
-            height = gr.Slider(
+            height = gr.Number(
                 label="Height",
-                minimum=256,
-                maximum=2048,
-                step=64,
-                value=1024
+                value=1024,
+                precision=0,
+                interactive=True
             )
-            width = gr.Slider(
+            width = gr.Number(
                 label="Width",
-                minimum=256,
-                maximum=2048,
-                step=64,
-                value=1024
+                value=1024,
+                precision=0,
+                interactive=True
             )
-            steps = gr.Slider(
+            steps = gr.Number(
                 label="Steps",
-                minimum=1,
-                maximum=50,
-                step=1,
-                value=8
+                value=8,
+                precision=0,
+                interactive=True
             )
-            scale = gr.Slider(
+            scales = gr.Number(
                 label="Scale",
-                minimum=1.0,
-                maximum=10.0,
-                step=0.1,
-                value=3.5
+                value=3.5,
+                precision=1,
+                interactive=True
             )
             seed = gr.Number(
                 label="Seed",
                 value=3413,
-                precision=0
+                precision=0,
+                interactive=True
             )
-            generate_btn = gr.Button("Generate Image")
-        
+            generate_button = gr.Button("Generate Image")
+
         with gr.Column():
-            output = gr.Image(label="Generated Image")
-    
-    generate_btn.click(
+            output_image = gr.Image(label="Generated Image", interactive=False)
+
+    # Define the button click action
+    generate_button.click(
         fn=generate_image,
-        inputs=[prompt, height, width, steps, scale, seed],
-        outputs=output
+        inputs=[prompt, height, width, steps, scales, seed],
+        outputs=output_image
     )
 
+    # Optional: Add a footer or additional information
+    gr.Markdown("© 2024 Your Name. All rights reserved.")
+
 # Launch the Gradio app
 if __name__ == "__main__":
     demo.launch()