app.py

from shiny import App, ui, reactive, render
import uuid
from datetime import datetime
import os
import sys
from pathlib import Path
from chatbot import ask_question, clear_conversation
from shinyswatch import theme

# Define UI
app_ui = ui.page_fluid(
    ui.panel_title("American University Academic Advisor Chatbot"),
    
    # Use Bootstrap row/column layout
    ui.row(
        # Settings panel (left side)
        ui.column(3,
            ui.div(
                {"class": "card mb-3"},
                ui.div(
                    {"class": "card-header"},
                    ui.h4("Settings", class_="mb-0")
                ),
                ui.div(
                    {"class": "card-body"},
                    ui.tags.div(
                        {"class": "mb-3"},
                        ui.tags.label("Session ID:", class_="form-label"),
                        ui.tags.div(str(uuid.uuid4()), class_="form-text")
                    ),
                    ui.input_action_button("clear_chat", "Clear Chat History", 
                                          class_="btn btn-warning btn-block mb-3 w-100"),
                    # Export button                          
                    ui.download_button("download_chat", "Export Chat History",
                                      class_="btn btn-primary btn-block mb-3 w-100"),
                    ui.hr(),
                    ui.h5("Model Parameters"),
                    ui.input_slider("n_results", "Documents to retrieve", 
                                   min=0, max=16, value=8),
                    ui.input_slider("temperature", "Temperature", 
                                   min=0.1, max=1.0, value=0.7, step=0.1),
                    ui.hr(),
                    ui.h5("About/Warning"),
                    ui.p("This AI advisor is an on-going student research project using a RAG architecture with Python, a Chroma database and the Mistral 7B LLM. It provides answers to questions about American University's academic offerings related to the Math/Stat Department. While it draws from authoritative sources, it is known to produce some answers that are incomplete, inaccurate, or irrelevant. All responses should be checked with the references and one's human advisor.")
                )
            )
        ),
        
        # Chat area (right side)
        ui.column(9,
            ui.div(
                {"class": "card h-100"},
                ui.div(
                    {"class": "card-body"},
                    # Chat UI
                    ui.chat_ui("academic_chat", width="100%", height="75vh")
                )
            )
        )
    ),
    # Named parameters after all positional arguments
    title="American University Academic Advisor",
    theme=theme.flatly  # flatly is good for color-blind users (high contrast, distinguishable colors)
)

# Define server
def server(input, output, session):
    # Initialize the Shiny Chat UI
    chat = ui.Chat(
        id="academic_chat",
        messages=[{"role": "assistant", "content": "Hello! I'm your American University Academic Advisor. How can I help you today?"}]
    )
    
    # Handle clear chat button
    @reactive.Effect
    @reactive.event(input.clear_chat)
    async def _():
        # Clear Shiny chat UI
        await chat.clear()
        await chat.append_message({"role": "assistant", 
                                "content": "Chat history cleared. How can I help you today?"})
        # Clear internal chatbot conversation
        clear_conversation()
    
    # Define download handler for chat history
    @output
    @render.download
    def download_chat():
        # Get current chat messages
        messages = chat.messages()
        
        # Create filename with timestamp
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        filename = f"au_advisor_chat_{timestamp}.md"
        
        # Format as Markdown
        md_lines = []
        md_lines.append("# American University Academic Advisor Chat")
        md_lines.append(f"*Exported on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}*\n")
        
        for msg in messages:
            role = msg.get("role", "unknown")
            content = msg.get("content", "")
            
            if role == "user":
                md_lines.append(f"## User\n\n{content}\n")
            elif role == "assistant":
                md_lines.append(f"## Assistant\n\n{content}\n")
        
        content = "\n".join(md_lines)
        
        # Return as bytes
        return filename, "text/markdown", content.encode("utf-8")
    
    # Define callback for user input
    @chat.on_user_submit
    async def handle_user_input(user_input: str):
        # Process the query with the chatbot
        result = ask_question(
            query=user_input, 
            n_results=input.n_results(),
            temperature=input.temperature()
        )
        
        # Format the response with better source descriptions
        response = result["response"].strip()
        if result.get("contexts") and result.get("metadata"):
            sources = []
            for i, (context, meta) in enumerate(zip(result.get("contexts", []), result.get("metadata", []))):
                title = meta.get("title", "") if meta else ""
                url = meta.get("url", "")
                
                if title in ["Table Row", "Paragraph"] or not title:
                    content_preview = context.strip()[:50] + "..." if len(context) > 50 else context.strip()
                    description = content_preview
                else:
                    description = title
                
                if url:
                    sources.append(f"[{i+1}] <a href='{url}' target='_blank'>{description}</a>")
                else:
                    sources.append(f"[{i+1}] {description}")
            
            if sources and "Sources:" not in response:
                response += "<br><br><strong>Sources:</strong><br>" + "<br>".join(sources)
        
        # Add the response to the Shiny chat
        await chat.append_message({"role": "assistant", "content": response})

# Create and run the app
app = App(app_ui, server)

if __name__ == "__main__":
    # For Shiny apps, make sure to use the correct host/port
    import shiny
    shiny.run_app(
        host="0.0.0.0",  # Important to bind to 0.0.0.0, not localhost
        port=7860,       # Must match the exposed port
        launch_browser=False
    )