Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import random
+
+# Initialize models
+text_generator = pipeline("text-generation", model="gpt2")
+image_captioner = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
+
+def generate_content():
+    # Generate text content
+    text_prompt = "This website is unique because"
+    generated_text = text_generator(text_prompt, max_length=100, num_return_sequences=1)[0]['generated_text']
+    
+    # Generate a random color for demonstration purposes
+    color = "#{:06x}".format(random.randint(0, 0xFFFFFF))
+    
+    # For now, we'll just return a placeholder for the image
+    image_description = "A placeholder for a generated image"
+    
+    html_content = f"""
+    <div style="background-color: {color}; padding: 20px; border-radius: 10px;">
+        <h2>Welcome to Your Dynamic AI Website!</h2>
+        <p>{generated_text}</p>
+        <p><em>Image concept: {image_description}</em></p>
+    </div>
+    """
+    
+    return html_content
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=generate_content,
+    inputs=[],
+    outputs=gr.HTML(),
+    title="AI-Driven Dynamic Website",
+    description="Click the button to generate new content!",
+    theme="huggingface"
+)
+
+# Launch the app
+iface.launch()