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app.py

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+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,
+    )

requirements.txt

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+gradio>=6.0
+requests
+Pillow

utils.py

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+"""
+Utility functions for the AI Chatbot application.
+"""
+
+def format_chat_message(role: str, content: str) -> dict:
+    """Format a chat message for the chatbot component."""
+    return {"role": role, "content": content}
+
+def validate_message(message: str) -> bool:
+    """Validate that a message is safe and appropriate."""
+    # Simple validation - in production you'd want more robust checks
+    forbidden_words = ["hate", "violence", "harm"]  # Basic content filtering
+    return not any(word in message.lower() for word in forbidden_words)
+
+def get_timestamp() -> str:
+    """Get current timestamp for logging."""
+    from datetime import datetime
+    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+}
+
+This AI chatbot application features:
+
+## 🎨 Modern Design
+- **Custom Soft theme** with indigo primary colors
+- **Google Inter font** for clean typography
+- **Responsive layout** that works on different screen sizes
+- **Professional UI** with proper spacing and sizing
+
+## 🤖 Core Features
+- **Interactive chat interface** with message history
+- **Streaming responses** for natural conversation flow
+- **Message actions**: Like and Retry functionality
+- **Chat examples** for users to try
+- **Clear chat functionality**
+
+## 🚀 Gradio 6 Best Practices
+- ✅ **Theme in demo.launch()** - Correct Gradio 6 syntax
+- ✅ **Proper event handling** with api_visibility parameter
+- ✅ **Responsive components** with appropriate sizing
+- ✅ **Error handling** and user feedback
+- ✅ **Clean code structure** with proper documentation
+
+## 📱 User Experience
+- **Intuitive input** with placeholder text
+- **Visual feedback** through info/warning messages
+- **Copy and share** buttons for chat messages
+- **Accessibility** with proper labels and descriptions
+
+The chatbot uses simulated AI responses with pattern matching, but you can easily replace this with actual AI model integrations (OpenAI, Hugging Face, etc.).