Chat Interface

class ChatInterface:
    """
    Complete chat interface component with message feed and input area.
    
    Parameters:
    - callback: Function to handle new messages
    - callback_user: User identifier for callback function
    - callback_exception: How to handle callback exceptions ('summary', 'verbose', 'ignore')
    - show_rerun: Whether to show rerun button for messages
    - show_undo: Whether to show undo button for messages
    - show_clear: Whether to show clear button
    - **params: Additional parameters
    """

class ChatFeed:
    """
    Message feed component for displaying chat messages.
    
    Parameters:
    - objects: List of message objects to display
    - load_buffer: Number of messages to load ahead for performance
    - scroll_button_threshold: Threshold for showing scroll-to-bottom button
    - auto_scroll_limit: Message limit for automatic scrolling
    - show_activity_dot: Whether to show activity indicator
    - **params: Additional parameters
    """

class ChatMessage:
    """
    Individual chat message component.
    
    Parameters:
    - object: Message content (text, HTML, or Panel object)
    - user: User name or identifier
    - avatar: User avatar image or initials
    - timestamp: Message timestamp
    - reactions: List of reaction emojis
    - show_reaction_icons: Whether to show reaction buttons
    - show_copy_icon: Whether to show copy button
    - show_timestamp: Whether to show message timestamp
    - **params: Additional parameters
    """

class ChatStep:
    """
    Chat step component for multi-step conversations.
    
    Parameters:
    - object: Step content
    - title: Step title
    - status: Step status ('pending', 'running', 'complete', 'failed')
    - **params: Additional parameters
    """

class ChatAreaInput:
    """
    Chat input area with send button and formatting options.
    
    Parameters:
    - value: Current input text
    - placeholder: Placeholder text for input
    - max_rows: Maximum number of visible rows
    - auto_grow: Whether input area grows with content
    - disabled: Whether input is disabled
    - **params: Additional parameters
    """

class ChatReactionIcons:
    """
    Reaction icons component for message reactions.
    
    Parameters:
    - value: Currently selected reactions
    - options: Available reaction options
    - **params: Additional parameters
    """

import panel as pn

def respond_to_message(contents, user, instance):
    """Callback function to handle new messages"""
    if "hello" in contents.lower():
        return "Hello! How can I help you today?"
    else:
        return f"You said: {contents}"

# Create chat interface
chat = pn.chat.ChatInterface(
    callback=respond_to_message,
    callback_user="Assistant",
    show_rerun=True,
    show_undo=True
)

chat.servable()

# Create messages
messages = [
    pn.chat.ChatMessage(
        "Welcome to our support chat!",
        user="Support Agent",
        avatar="🎧"
    ),
    pn.chat.ChatMessage(
        "Hi, I need help with my account.",
        user="Customer",
        avatar="👤"
    ),
    pn.chat.ChatMessage(
        "I'd be happy to help! What specific issue are you experiencing?",
        user="Support Agent", 
        avatar="🎧"
    )
]

# Create chat feed
chat_feed = pn.chat.ChatFeed(
    *messages,
    load_buffer=50,
    scroll_button_threshold=5,
    show_activity_dot=True
)

# Add input area
input_area = pn.chat.ChatAreaInput(
    placeholder="Type your message here...",
    max_rows=5
)

# Combine into layout
chat_layout = pn.Column(
    chat_feed,
    input_area,
    sizing_mode='stretch_both',
    height=600
)

# Create step-based conversation
steps = [
    pn.chat.ChatStep(
        "Analyzing your request...",
        title="Step 1: Analysis",
        status="complete"
    ),
    pn.chat.ChatStep(
        "Fetching relevant data...",
        title="Step 2: Data Retrieval", 
        status="running"
    ),
    pn.chat.ChatStep(
        "Generating response...",
        title="Step 3: Response Generation",
        status="pending"
    )
]

workflow_chat = pn.chat.ChatFeed(*steps)

# Create message with reactions
message_with_reactions = pn.chat.ChatMessage(
    "This feature is really useful! 🎉",
    user="User",
    avatar="https://example.com/avatar.jpg",
    reactions=["👍", "❤️", "🎉"],
    show_reaction_icons=True,
    show_copy_icon=True,
    show_timestamp=True
)

# Create reaction icons component
reaction_icons = pn.chat.ChatReactionIcons(
    options=["👍", "👎", "❤️", "😂", "😮", "😢", "🎉"],
    value=["👍", "❤️"]
)

# Create styled chat interface
styled_chat = pn.chat.ChatInterface(
    callback=respond_to_message,
    callback_user="AI Assistant",
    width=800,
    height=600,
    margin=(10, 10),
    styles={
        'background': '#f8f9fa',
        'border': '1px solid #dee2e6',
        'border-radius': '8px'
    }
)

# Customize message appearance
custom_message = pn.chat.ChatMessage(
    "This is a custom styled message",
    user="User",
    avatar="👤",
    styles={
        'background': '#e3f2fd',
        'border-left': '4px solid #2196f3',
        'padding': '10px',
        'margin': '5px 0'
    }
)

import param

class PersistentChat(param.Parameterized):
    messages = param.List(default=[])
    
    def __init__(self, **params):
        super().__init__(**params)
        self.chat_interface = pn.chat.ChatInterface(
            callback=self.handle_message,
            callback_user="Assistant"
        )
        self.load_history()
    
    def handle_message(self, contents, user, instance):
        # Process message and generate response
        response = self.generate_response(contents)
        
        # Save to history
        self.messages.extend([
            {'user': user, 'message': contents},
            {'user': 'Assistant', 'message': response}
        ])
        self.save_history()
        
        return response
    
    def load_history(self):
        # Load previous messages from storage
        for msg in self.messages:
            self.chat_interface.send(
                msg['message'], 
                user=msg['user'], 
                respond=False
            )
    
    def save_history(self):
        # Save messages to persistent storage
        pass

persistent_chat = PersistentChat()

import pandas as pd

def data_analysis_chat(contents, user, instance):
    """Chat interface for data analysis queries"""
    query = contents.lower()
    
    if "show data" in query:
        return pn.pane.DataFrame(df.head())
    elif "plot" in query:
        import matplotlib.pyplot as plt
        fig, ax = plt.subplots()
        df.plot(ax=ax)
        return pn.pane.Matplotlib(fig)
    elif "summary" in query:
        return pn.pane.Str(str(df.describe()))
    else:
        return "I can help you with data analysis. Try 'show data', 'plot', or 'summary'."

data_chat = pn.chat.ChatInterface(
    callback=data_analysis_chat,
    callback_user="Data Assistant"
)

def file_processing_chat(contents, user, instance):
    """Chat interface with file processing capabilities"""
    if contents.startswith("/upload"):
        file_input = pn.widgets.FileInput(accept='.csv,.xlsx')
        return pn.Column(
            "Please select a file to upload:",
            file_input
        )
    elif contents.startswith("/analyze"):
        # Process uploaded file
        return "File analysis complete! Here are the results..."
    else:
        return "Available commands: /upload, /analyze"

file_chat = pn.chat.ChatInterface(
    callback=file_processing_chat,
    callback_user="File Assistant"
)