import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
# (Import other necessary libraries for visualization and Gemini API interaction)

# Define Color Palette
primary_color = "#3498db"  # Example: Bright blue
secondary_color = "#e74c3c"  # Example: Vibrant red
background_color = "#f0f0f0"  # Example: Light gray
text_color = "#2c3e50"  # Example: Dark gray

# Apply Styling
st.markdown(
    f"""
<style>
.stApp {{
    background-color: {background_color};
    color: {text_color};
}}
.sidebar .sidebar-content {{
    background-color: {primary_color};
    color: white;
}}
.stButton button {{
    background-color: {secondary_color};
    color: white;
}}
</style>
""",
    unsafe_allow_html=True,
)

st.title("Event Management Financial Forecaster")

# Sidebar
gemini_api_key = st.sidebar.text_input("Google Gemini API Key")

# Sliders for Revenue Variables
st.sidebar.subheader("Revenue")
ticket_sales = st.sidebar.slider("Ticket Sales", 0, 100000, 50000)
# (Add sliders for other revenue variables)

# Sliders for Expense Variables
st.sidebar.subheader("Expenses")
venue_rental = st.sidebar.slider("Venue Rental", 0, 50000, 25000)
# (Add sliders for other expense variables)

# Calculate Financial Metrics
# (Implement the logic to calculate P&L, cash flow, sensitivity, KPIs based on slider values)

# Main Area
st.subheader("Projected P&L Statement")

# Visualization Styling for P&L
fig_pl, ax_pl = plt.subplots()
# ... (plot P&L data)
ax_pl.set_facecolor(background_color)
plt.grid(color="white", linestyle="--", linewidth=0.5)
# ... (other plot customizations)
st.pyplot(fig_pl)

st.subheader("Cash Flow Forecast")

# Visualization Styling for Cash Flow
fig_cf, ax_cf = plt.subplots()
# ... (plot cash flow data)
ax_cf.set_facecolor(background_color)
plt.grid(color="white", linestyle="--", linewidth=0.5)
# ... (other plot customizations)
st.pyplot(fig_cf)

# (Add other visualizations for sensitivity analysis and KPIs with similar styling)

# Optional: AI-Powered Insights (using Gemini API)
if gemini_api_key:
    st.subheader("AI-Powered Insights")
    # (Integrate Gemini API to generate analysis and scenario simulations based on input data)