Code Editor for app.py

import streamlit as st
import pandas as pd
import plotly.express as px

# Initialize session state
if "authenticated" not in st.session_state:
    st.session_state.authenticated = False
if "messages" not in st.session_state:
    st.session_state.messages = []
if "data" not in st.session_state:
    # Load sample data
    st.session_state.data = pd.read_csv("https://raw.githubusercontent.com/mwaskom/seaborn-data/master/tips.csv")

# Sidebar for authentication
with st.sidebar:
    st.title("Login")
    with st.expander("Enter credentials"):
        username = st.text_input("Username")
        password = st.text_input("Password", type="password")
        if st.button("Login"):
            # This is a simple authentication. In a real app, you'd want to use
            # secure authentication methods
            if username == "admin" and password == "admin":
                st.session_state.authenticated = True
                st.success("Logged in successfully!")
            else:
                st.error("Invalid credentials")

if st.session_state.authenticated:
    # Main content area with tabs
    tab1, tab2 = st.tabs(["Data Visualization", "Chat"])
    
    with tab1:
        st.title("Data Analysis Dashboard")
        st.write("Sample data from tips dataset:")
        st.dataframe(st.session_state.data.head())
        
        # Create bar chart
        fig = px.bar(
            st.session_state.data,
            x="day",
            y="total_bill",
            color="time",
            title="Total Bill by Day and Time",
            barmode="group"
        )
        st.plotly_chart(fig)
        
    with tab2:
        st.title("Chat with your Data")
        
        # Display chat messages
        for message in st.session_state.messages:
            with st.chat_message(message["role"]):
                st.write(message["content"])
        
        # Chat input
        if prompt := st.chat_input("Ask about the data..."):
            # Add user message to chat history
            st.session_state.messages.append({"role": "user", "content": prompt})
            
            # Display user message
            with st.chat_message("user"):
                st.write(prompt)
            
            # Simulate assistant response
            with st.chat_message("assistant"):
                # Here you would typically integrate with a real LLM
                response = "I can help you analyze the tips dataset. You can ask questions about total bills, tips, day of week, or time of day distributions."
                st.write(response)
                
            # Add assistant response to chat history
            st.session_state.messages.append({"role": "assistant", "content": response})
            
else:
    st.title("Welcome to Data Chat Dashboard")
    st.write("Please login using the sidebar to access the dashboard.")