app.py

import gradio as gr
import random
import time
from typing import List, Tuple

# Mock AI responses for demonstration
def get_ai_response(user_message: str, chat_history: List[Tuple[str, str]]) -> Tuple[str, List[Tuple[str, str]]]:
    """
    Simulates an AI chatbot response.
    In a real application, you would connect this to an actual AI model.
    """
    # Simple pattern matching for demonstration
    user_message_lower = user_message.lower()
    
    if "hello" in user_message_lower or "hi" in user_message_lower:
        responses = [
            "Hello there! How can I assist you today?",
            "Hi! Nice to meet you!",
            "Greetings! What can I help you with today?"
        ]
    elif "how are you" in user_message_lower:
        responses = [
            "I'm doing great! Just here ready to chat with you.",
            "I'm functioning perfectly! How about you?",
            "All systems operational! What's on your mind?"
        ]
    elif "weather" in user_message_lower:
        responses = [
            "I don't have real-time weather data, but I hope it's pleasant wherever you are!",
            "I'm an AI, so I don't experience weather, but I can discuss it with you!"
        ]
    elif "help" in user_message_lower:
        responses = [
            "I'm here to help! You can ask me about various topics, or we can just have a friendly conversation!"
        ]
    elif "bye" in user_message_lower or "goodbye" in user_message_lower:
        responses = [
            "Goodbye! It was nice chatting with you!",
            "Farewell! Hope to talk with you again soon!",
            "See you later! Don't hesitate to come back if you have more questions!"
        ]
    else:
        responses = [
            "That's interesting! Tell me more about that.",
            "I appreciate you sharing that with me.",
            "That's fascinating! I'd love to hear more."
        ]
    
    # Add some randomness and thinking simulation
    thinking_time = random.uniform(0.5, 2.0)
    time.sleep(thinking_time)
    
    return random.choice(responses), chat_history + [(user_message, random.choice(responses))]

def stream_ai_response(user_message: str, chat_history: List[Tuple[str, str]]):
    """
    Streams AI responses character by character for a more natural feel.
    """
    full_response, chat_history = get_ai_response(user_message, chat_history)
    for i in range(len(full_response)):
        partial_response = full_response[:i+1]
        yield partial_response, chat_history + [(user_message, partial_response)]

def handle_user_input(user_message: str, chat_history: List[Tuple[str, str]]):
    """Process user input and update chat history."""
    if not user_message.strip():
        return "", chat_history
    
    # Get AI response
    ai_response, chat_history = get_ai_response(user_message, chat_history)
    
    return "", chat_history

def clear_chat():
    """Clear the chat history."""
    return [], []

def like_message():
    """Handle message liking."""
    gr.Info("Thanks for the feedback!")

def retry_message():
    """Handle message retry."""
    gr.Warning("Retrying the last response...")

# Create custom theme for the chatbot
custom_theme = gr.themes.Soft(
    primary_hue="indigo",
    secondary_hue="blue",
    neutral_hue="slate",
    font=gr.themes.GoogleFont("Inter"),
    text_size="lg",
    spacing_size="lg",
    radius_size="md"
).set(
    button_primary_background_fill="*primary_600",
    button_primary_background_fill_hover="*primary_700",
    block_title_text_weight="600",
)

with gr.Blocks() as demo:
    # Header with title and anycoder link
    with gr.Row():
        gr.Markdown("# 🤖 AI Chatbot")
        gr.HTML(
            '<div style="text-align: right; font-size: 0.8em;">'
            '<a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" style="color: #6B7280; text-decoration: none;">'
            'Built with anycoder'
            '</a>'
            '</div>'
        )
    
    # Description
    gr.Markdown(
        "Welcome to your AI assistant! I'm here to help with questions, "
        "have conversations, or just chat about whatever's on your mind."
    )
    
    # Chat interface
    with gr.Row():
        with gr.Column(scale=3):
            chatbot = gr.Chatbot(
                label="Chat",
                height=500,
                show_copy_button=True,
                show_share_button=True,
                placeholder="Type your message here...",
            show_clear_button=True,
            )
    
    with gr.Column(scale=2):
        # Input controls
        with gr.Group():
            user_input = gr.Textbox(
                label="Your Message",
                placeholder="Type your message here and press Enter...",
                lines=2,
                max_lines=5,
                )
            
            with gr.Row():
                send_btn = gr.Button("Send", variant="primary")
                clear_btn = gr.Button("Clear Chat", variant="secondary")
        
        # Additional controls
        with gr.Accordion("Advanced Options", open=False):
            with gr.Row():
                like_btn = gr.Button("👍 Like", size="sm")
                retry_btn = gr.Button("🔄 Retry", size="sm")
        
        # Status indicators
        with gr.Row():
            gr.Markdown("**Status:** Ready")
    
    # Event handling
    send_btn.click(
        fn=handle_user_input,
        inputs=[user_input, chatbot],
        outputs=[user_input, chatbot],
        api_visibility="public"
        )
        
        user_input.submit(
            fn=handle_user_input,
            inputs=[user_input, chatbot],
        outputs=[user_input, chatbot],
        api_visibility="public"
        )
    
    clear_btn.click(
        fn=clear_chat,
        inputs=None,
        outputs=[chatbot, user_input],
        api_visibility="public"
        )
    
    like_btn.click(
        fn=like_message,
        inputs=None,
        outputs=None,
        api_visibility="private"
        )
    
    retry_btn.click(
        fn=retry_message,
        inputs=None,
        outputs=None,
        api_visibility="private"
        )
    
    # Streaming example
    with gr.Group(visible=False) as streaming_section:
        gr.Markdown("### Streaming Response Demo")
        streaming_input = gr.Textbox(label="Streaming test message")
        streaming_output = gr.Textbox(label="Streaming response", interactive=False)
    
    # Examples
    gr.Examples(
        examples=[
            "Hello, how are you today?",
            "What's the weather like?",
            "Can you help me with something?",
            "Tell me a fun fact!",
            "What can you do as an AI assistant?"
        ],
        inputs=user_input
        )

# Launch the application with modern Gradio 6 syntax
demo.launch(
    theme=custom_theme,
    footer_links=[
        {"label": "API Documentation", "url": "/docs"},
        {"label": "About", "url": "/about"}
    ],
    share=False,  # Set to True for public sharing
    show_error=True,
    )