Update app.py

app.py

@@ -1,4 +1,73 @@
-import subprocess
+import gradio as gr
+from gradio_client import Client
+from PIL import Image
 import os
+import time
+import traceback
 
-os.system("apt-cache search openblas")
+# Create a Client instance to communicate with the Hugging Face space
+client = Client("https://huggingface.co/spaces/hsuwill000/LCM_SoteMix_OpenVINO_CPU_Space_TAESD")
+
+# Counter for image filenames to avoid overwriting
+count = 0
+
+# Gradio Interface Function to handle image generation
+def infer_gradio(prompt: str):
+    global count
+
+    # Prepare the inputs for the prediction
+    inputs = {
+        "prompt": prompt,
+        "num_inference_steps": 10  # Number of inference steps for the model
+    }
+
+    try:
+        # Send the request to the model and receive the image
+        result = client.predict(inputs, api_name="/infer")
+        
+        # Open the resulting image
+        image = Image.open(result)
+        
+        # Create a unique filename to save the image
+        filename = f"img_{count:08d}.jpg"
+        while os.path.exists(filename):
+            count += 1
+            filename = f"img_{count:08d}.jpg"
+        
+        # Save the image locally
+        image.save(filename)
+        print(f"Saved image as {filename}")
+        
+        # Return the image to be displayed in Gradio
+        return image
+    
+    except Exception as e:
+        # Handle any errors that occur
+        print(f"An exception occurred: {str(e)}")
+        print("Stack trace:")
+        traceback.print_exc()  # Print stack trace for debugging
+        return None  # Return nothing if an error occurs
+
+# Define Gradio Interface
+with gr.Blocks() as demo:
+    with gr.Column():
+        gr.Markdown("# LCMSoteMix Image Generator")
+        
+        # Prompt input field for the user
+        prompt_input = gr.Textbox(
+            label="Enter Your Prompt", 
+            placeholder="Type your prompt for image generation here",
+            lines=4,  # Allow multi-line input for the prompt
+            interactive=True  # Allow user to interact with the textbox
+        )
+        
+        # Button to trigger the generation
+        run_button = gr.Button("Generate Image")
+        
+        # Output image display area
+        output_image = gr.Image(label="Generated Image")
+        
+        # Connecting the button click to the image generation function
+        run_button.click(infer_gradio, inputs=prompt_input, outputs=output_image)
+
+demo.launch()