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import streamlit as st
import os
from dotenv import load_dotenv
# Import local modules
from src.pages import dashboard, decision_simulator, fund_monitoring, financial_advisor
from src.utils.data_processing import (
generate_sample_startup_data,
generate_sample_cash_flow_data,
generate_sample_transactions_data
)
# Load environment variables
load_dotenv()
# Constants
DEFAULT_GROWTH_RATE = 0.08 # 8% monthly growth
DEFAULT_BURN_RATE = 85000 # $85,000 monthly burn
ENGINEER_SALARY = 10000 # $10,000 monthly cost per engineer ($120K/year)
def main():
"""
Main application entry point for Startup Finance Pilot
"""
# App configuration
st.set_page_config(
page_title="StartupFinancePilot",
page_icon="💰",
layout="wide",
initial_sidebar_state="expanded"
)
# Custom CSS (you might want to move this to a separate file in a larger project)
st.markdown("""
<style>
/* Your existing CSS styles from previous implementation */
.main-header { font-size: 2.5rem; color: #0066cc; }
.sub-header { font-size: 1.5rem; color: #5c5c5c; }
/* Add more styles as needed */
</style>
""", unsafe_allow_html=True)
# Initialize session state
if 'startups' not in st.session_state:
st.session_state.startups = {}
if 'current_startup' not in st.session_state:
st.session_state.current_startup = None
if 'current_page' not in st.session_state:
st.session_state.current_page = 'upload'
if 'insights_cache' not in st.session_state:
st.session_state.insights_cache = {}
# Add sample data for demonstration
sample_startup = generate_sample_startup_data()
st.session_state.startups[sample_startup['name']] = {
'profile': sample_startup,
'cash_flow': generate_sample_cash_flow_data(),
'transactions': generate_sample_transactions_data()
}
st.session_state.current_startup = sample_startup['name']
# Sidebar navigation
with st.sidebar:
st.title("💰 StartupFinancePilot")
st.write("AI-powered financial assistant for startups")
# Startup selector
if st.session_state.startups:
startup_names = list(st.session_state.startups.keys())
selected_startup = st.selectbox(
"Choose Startup",
startup_names,
index=startup_names.index(st.session_state.current_startup)
)
st.session_state.current_startup = selected_startup
# Show basic startup info
startup_data = st.session_state.startups[selected_startup]['profile']
st.markdown(f"""
**Stage:** {startup_data['stage']}
**Cash:** ${startup_data['cash']:,}
**Monthly Burn:** ${startup_data['burn_rate']:,}
**Monthly Revenue:** ${startup_data['revenue']:,}
""")
# Navigation buttons
st.markdown("<hr>", unsafe_allow_html=True)
page_options = {
"📊 Financial Dashboard": "dashboard",
"🔮 Decision Simulator": "simulator",
"🕵️ Fund Monitoring": "monitoring",
"🤖 AI Financial Advisor": "advisor"
}
for label, page_key in page_options.items():
if st.button(label, use_container_width=True):
st.session_state.current_page = page_key
st.experimental_rerun()
# Render the correct page
if st.session_state.current_page == 'dashboard':
dashboard.render_financial_dashboard(
st.session_state.startups[st.session_state.current_startup]['profile'],
st.session_state.startups[st.session_state.current_startup]['cash_flow']
)
elif st.session_state.current_page == 'simulator':
decision_simulator.render_decision_simulator(
st.session_state.startups[st.session_state.current_startup]['profile']
)
elif st.session_state.current_page == 'monitoring':
fund_monitoring.render_fund_monitoring(
st.session_state.startups[st.session_state.current_startup]['transactions']
)
elif st.session_state.current_page == 'advisor':
financial_advisor.render_ai_financial_advisor(
st.session_state.startups[st.session_state.current_startup]['profile']
)
def validate_gemini_api_key():
"""
Validate the Google Generative AI API key
Returns:
bool: True if API key is valid, False otherwise
"""
try:
import google.generativeai as genai
api_key = os.getenv('GOOGLE_API_KEY')
if not api_key:
st.error("🚨 Google API Key not found. Please set GOOGLE_API_KEY in your .env file.")
return False
genai.configure(api_key=api_key)
model = genai.GenerativeModel('gemini-pro')
# Try a simple test generation
test_response = model.generate_content("Hello, can you confirm the API is working?")
return True
except Exception as e:
st.error(f"🚨 Error validating API key: {e}")
return False
if __name__ == "__main__":
# Check API key before running
if validate_gemini_api_key():
main()
else:
st.warning("Please set up your Google Generative AI API key to use the application.")
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