import gradio as gr

# Custom CSS for gradient background and styling
custom_css = """
.gradio-container {
    background: linear-gradient(135deg, #ffecd2 0%, #fcb69f 25%, #fbc2eb 50%, #a6c1ee 75%, #c2e9fb 100%);
    background-size: 400% 400%;
    animation: gradient-animation 15s ease infinite;
    min-height: 100vh;
}
@keyframes gradient-animation {
    0% { background-position: 0% 50%; }
    50% { background-position: 100% 50%; }
    100% { background-position: 0% 50%; }
}
.dark .gradio-container {
    background: linear-gradient(135deg, #2a2a3e 0%, #3a3a5e 25%, #4a4a6e 50%, #5a5a7e 75%, #6a6a8e 100%);
    background-size: 400% 400%;
    animation: gradient-animation 15s ease infinite;
}
/* Style for content areas */
.main-container {
    background-color: rgba(255, 255, 255, 0.92);
    backdrop-filter: blur(10px);
    border-radius: 20px;
    padding: 20px;
    box-shadow: 0 4px 20px 0 rgba(31, 38, 135, 0.15);
    border: 1px solid rgba(255, 255, 255, 0.3);
    margin: 10px;
}
.dark .main-container {
    background-color: rgba(40, 40, 40, 0.95);
    border: 1px solid rgba(255, 255, 255, 0.1);
}
"""

def chat_fn(message, history, model_choice):
    """Placeholder chat function"""
    return f"Response from {model_choice}: {message}"

with gr.Blocks(fill_height=True, theme="soft", css=custom_css) as demo:
    # State variable to track current model
    current_model = gr.State("openai/gpt-oss-120b")
    
    with gr.Row():
        # Sidebar
        with gr.Column(scale=1):
            with gr.Group(elem_classes="main-container"):
                gr.Markdown("# 🚀 Inference Provider")
                gr.Markdown(
                    "This Space showcases OpenAI GPT-OSS models, served by the Cerebras API. "
                    "Sign in with your Hugging Face account to use this API."
                )
                
                # Model selection
                model_dropdown = gr.Dropdown(
                    choices=[
                        "openai/gpt-oss-120b",
                        "openai/gpt-oss-20b"
                    ],
                    value="openai/gpt-oss-120b",
                    label="📊 Select Model",
                    info="Choose between different model sizes"
                )
                
                # Login button
                login_button = gr.LoginButton("Sign in with Hugging Face", size="lg")
                
                # Additional options
                with gr.Accordion("⚙️ Advanced Options", open=False):
                    gr.Markdown("*These options will be available after model implementation*")
                    temperature = gr.Slider(
                        minimum=0,
                        maximum=2,
                        value=0.7,
                        step=0.1,
                        label="Temperature"
                    )
                    max_tokens = gr.Slider(
                        minimum=1,
                        maximum=4096,
                        value=512,
                        step=1,
                        label="Max Tokens"
                    )
        
        # Main chat area
        with gr.Column(scale=3):
            with gr.Group(elem_classes="main-container"):
                gr.Markdown("## 💬 Chat Interface")
                
                # Display current model
                model_display = gr.Markdown(f"### Model: openai/gpt-oss-120b")
                
                # Single chat interface that works with both models
                chatbot = gr.Chatbot(
                    height=400,
                    show_label=False,
                    elem_classes="main-container"
                )
                
                with gr.Row():
                    msg = gr.Textbox(
                        placeholder="Type your message here...",
                        show_label=False,
                        scale=9
                    )
                    submit_btn = gr.Button("Send", variant="primary", scale=1)
                
                clear_btn = gr.Button("🗑️ Clear Chat", variant="secondary")
    
    # Update model display when dropdown changes
    def update_model_display(model_choice):
        return f"### Model: {model_choice}", model_choice
    
    model_dropdown.change(
        fn=update_model_display,
        inputs=[model_dropdown],
        outputs=[model_display, current_model]
    )
    
    # Chat functionality
    def respond(message, chat_history, model):
        if not message:
            return "", chat_history
        
        # Add user message to history
        chat_history = chat_history + [[message, None]]
        
        # Generate bot response (placeholder - replace with actual model call)
        bot_response = f"[{model.split('/')[-1]}]: This is a placeholder response. In production, this would connect to the {model} via Fireworks AI API."
        
        # Update the last message with bot response
        chat_history[-1][1] = bot_response
        
        return "", chat_history
    
    # Submit message on button click or enter
    submit_btn.click(
        fn=respond,
        inputs=[msg, chatbot, current_model],
        outputs=[msg, chatbot]
    )
    
    msg.submit(
        fn=respond,
        inputs=[msg, chatbot, current_model],
        outputs=[msg, chatbot]
    )
    
    # Clear chat
    clear_btn.click(
        fn=lambda: (None, ""),
        inputs=[],
        outputs=[chatbot, msg]
    )
    
    # Show info message on login
    login_button.click(
        fn=lambda: gr.Info("Please authenticate with Hugging Face to access the models"),
        inputs=[],
        outputs=[]
    )

demo.launch()