import gradio as gr # Example inference function def model_inference(message): # Example logic for processing user messages return f"You said: {message}" # Example chatbot configuration (if needed) chatbot = None # Example inputs EXAMPLES = ["Hello!", "How are you?", "Tell me a joke."] # Define Gradio theme theme = gr.themes.Soft( primary_hue="indigo", secondary_hue="emerald", neutral_hue="gray", font=["Rubik"] # Font as a list ) # Create Gradio blocks with custom CSS for enhanced UI with gr.Blocks( css=""" .gradio-container {background-color: #f0f4f8; padding: 20px;} h1, h2, h3, h4, h5, h6 {color: #4a5568;} .chat-message {background-color: #edf2f7; border-radius: 8px; padding: 10px;} """, ) as chat: gr.Markdown("### 💬 SuperChat - A Chatbot Interface") gr.ChatInterface( fn=model_inference, # Defined above chatbot=chatbot, # Set to None for now examples=EXAMPLES, # Example inputs multimodal=True, cache_examples=False, autofocus=False, concurrency_limit=10, ) # Create Gradio blocks with custom CSS for enhanced UI with gr.Blocks(theme=theme, title="RocketGPT - AI-Powered Chatbot") as demo: # Define individual tabs with gr.Blocks() as voice: gr.Markdown("### 🎙️ Speech Generator") gr.HTML("") with gr.Blocks() as image: gr.Markdown("### 🖼️ Image Generator") gr.HTML("") with gr.Blocks() as video: gr.Markdown("### 📹 Video Engine") gr.HTML("") with gr.Blocks() as tryon: gr.Markdown("### 🖼️ Finegrain") gr.HTML("") # Create a tabbed interface gr.TabbedInterface( interface_list=[chat, voice, image, video, tryon], tab_names=["💬 SuperChat", "🗣️ Speech Generator", "🖼️ Image Generator", "🎥 Video Generator", "🖼️ Finegrain"] ) # Launch the app demo.queue(max_size=300) demo.launch()