Delete decision-simulator.py

decision-simulator.py

@@ -1,321 +0,0 @@
-def render_decision_simulator(startup_data):
-    """
-    Render the AI-powered decision simulator page.
-    
-    This feature helps startup founders test the financial impact of business
-    decisions before implementing them, using AI to analyze risks and benefits.
-    """
-    st.markdown("<h1 class='main-header'>Decision Simulator</h1>", unsafe_allow_html=True)
-    st.markdown("<p class='sub-header'>AI-powered analysis of business decisions</p>", unsafe_allow_html=True)
-    
-    # How AI helps with decision-making
-    with st.expander("ℹ️ How AI enhances your decision-making"):
-        st.markdown("""
-        ### How AI Powers Your Decision Simulator
-        
-        The decision simulator uses AI to help you make better strategic decisions:
-        
-        - **Scenario Analysis**: Our AI model simulates multiple financial scenarios based on your input variables
-        - **Risk Assessment**: The system automatically evaluates risk levels based on your cash runway and growth metrics
-        - **Return Prediction**: AI algorithms predict potential returns on investments like hiring or marketing
-        - **Opportunity Cost Analysis**: The model compares different allocations of capital to maximize growth
-        - **Personalized Recommendations**: Based on your specific situation, the AI provides tailored alternatives
-        
-        This helps founders make data-driven decisions with less guesswork, avoid costly mistakes, and optimize resource allocation.
-        """)
-    
-    st.write("Test the financial impact of key business decisions before implementing them. Our AI advisor will analyze the risks and benefits.")
-    
-    # Quick decision templates
-    st.subheader("Common Scenarios")
-    
-    decision_templates = {
-        "Hiring Engineering Team": {
-            "description": "Evaluate the impact of growing your engineering team",
-            "new_hires": 3,
-            "new_marketing": 0,
-            "other_expenses": 2000,
-            "growth_impact": 0.02,
-            "question": "We're considering hiring 3 more engineers to accelerate product development. How will this affect our runway and what growth impact should we expect to justify this investment?"
-        },
-        "Marketing Expansion": {
-            "description": "Test increasing your marketing budget",
-            "new_hires": 0,
-            "new_marketing": 15000,
-            "other_expenses": 0,
-            "growth_impact": 0.04,
-            "question": "We want to increase our marketing spend by $15K/month to drive growth. What growth rate would we need to achieve to make this financially viable?"
-        },
-        "Office Expansion": {
-            "description": "Analyze the cost of moving to a larger office",
-            "new_hires": 0,
-            "new_marketing": 0,
-            "other_expenses": 8000,
-            "growth_impact": 0.01,
-            "question": "We're considering moving to a larger office space that would add $8K/month to our expenses. Is this justified at our current stage?"
-        },
-        "Custom Scenario": {
-            "description": "Create your own custom scenario",
-            "new_hires": 0,
-            "new_marketing": 0,
-            "other_expenses": 0,
-            "growth_impact": 0.0,
-            "question": ""
-        }
-    }
-    
-    # Template selection
-    template_cols = st.columns(4)
-    selected_template = None
-    
-    for i, (template_name, template) in enumerate(decision_templates.items()):
-        with template_cols[i]:
-            if st.button(f"{template_name}\n{template['description']}", key=f"template_{i}"):
-                selected_template = template_name
-    
-    # Initialize form values based on selected template
-    if selected_template and selected_template != "Custom Scenario":
-        new_hires = decision_templates[selected_template]["new_hires"]
-        new_marketing = decision_templates[selected_template]["new_marketing"]
-        other_expenses = decision_templates[selected_template]["other_expenses"]
-        growth_impact = decision_templates[selected_template]["growth_impact"]
-        question = decision_templates[selected_template]["question"]
-    else:
-        new_hires = 0
-        new_marketing = 0
-        other_expenses = 0
-        growth_impact = 0.0
-        question = ""
-    
-    # Decision input form
-    with st.form("decision_form"):
-        st.subheader("Scenario Parameters")
-        
-        col1, col2 = st.columns(2)
-        
-        with col1:
-            new_hires = st.number_input("New Engineering Hires", min_value=0, max_value=10, value=new_hires, 
-                                       help=f"Each engineer costs ${ENGINEER_SALARY:,} per month")
-            st.caption(f"Monthly Cost: ${new_hires * ENGINEER_SALARY:,}")
-            
-            new_marketing = st.number_input("Additional Monthly Marketing Budget", 
-                                           min_value=0, max_value=50000, value=new_marketing, step=1000,
-                                           help="Additional marketing spend per month")
-        
-        with col2:
-            other_expenses = st.number_input("Other Additional Monthly Expenses", 
-                                            min_value=0, max_value=50000, value=other_expenses, step=1000,
-                                            help="Any other additional monthly expenses")
-            
-            growth_impact = st.slider("Estimated Impact on Monthly Growth Rate", 
-                                     min_value=0.0, max_value=0.10, value=growth_impact, step=0.01, 
-                                     format="%.2f",
-                                     help="Estimated increase in monthly growth rate due to these investments")
-            st.caption(f"New Growth Rate: {(startup_data['growth_rate'] + growth_impact) * 100:.1f}% (current: {startup_data['growth_rate'] * 100:.1f}%)")
-        
-        question = st.text_area("Describe your decision scenario", 
-                               value=question,
-                               height=100, 
-                               placeholder="E.g., We're considering hiring two more engineers and increasing our marketing budget...")
-        
-        decision_summary = f"""
-        - {new_hires} new engineers: ${new_hires * ENGINEER_SALARY:,}/month
-        - Marketing increase: ${new_marketing:,}/month
-        - Other expenses: ${other_expenses:,}/month
-        - Total additional burn: ${new_hires * ENGINEER_SALARY + new_marketing + other_expenses:,}/month
-        - Growth impact: +{growth_impact * 100:.1f}% monthly growth
-        """
-        
-        st.markdown(f"**Decision Summary:**\n{decision_summary}")
-        
-        submitted = st.form_submit_button("Simulate Decision")
-    
-    if submitted:
-        # Calculate current and new runway
-        current_runway, new_runway, current_df, new_df = simulate_decision(
-            startup_data['cash'],
-            startup_data['burn_rate'],
-            startup_data['revenue'],
-            startup_data['growth_rate'],
-            other_expenses,
-            new_hires,
-            new_marketing,
-            growth_impact
-        )
-        
-        # Display results
-        st.markdown("<h3>Decision Impact Analysis</h3>", unsafe_allow_html=True)
-        
-        # Summary metrics
-        col1, col2, col3 = st.columns(3)
-        
-        with col1:
-            st.metric("Current Runway", f"{current_runway} months")
-        with col2:
-            runway_change = new_runway - current_runway
-            st.metric("New Runway", f"{new_runway} months", 
-                     delta=f"{runway_change} months", 
-                     delta_color="off" if runway_change == 0 else ("normal" if runway_change > 0 else "inverse"))
-        with col3:
-            new_burn = startup_data['burn_rate'] + other_expenses + (new_hires * ENGINEER_SALARY) + new_marketing
-            burn_change = new_burn - startup_data['burn_rate']
-            burn_percentage = burn_change / startup_data['burn_rate'] * 100
-            st.metric("New Monthly Burn", f"${new_burn:,}", 
-                     delta=f"${burn_change:,} ({burn_percentage:.1f}%)", 
-                     delta_color="inverse")
-        
-        # Cash projection comparison
-        st.subheader("Cash Projection Comparison")
-        
-        # Combine dataframes for comparison
-        current_df['Scenario'] = 'Current'
-        new_df['Scenario'] = 'After Decision'
-        
-        combined_df = pd.concat([current_df, new_df])
-        combined_df = combined_df.reset_index()
-        combined_df = combined_df.rename(columns={'index': 'Date'})
-        
-        # Plot comparison
-        fig = px.line(combined_df, x='Date', y='Cumulative_Cash', color='Scenario',
-                     title="Cash Runway Comparison",
-                     labels={'Cumulative_Cash': 'Remaining Cash'},
-                     color_discrete_sequence=['#4c78a8', '#f58518'])
-        
-        fig.add_hline(y=0, line_dash="dash", line_color="red", annotation_text="Out of Cash")
-        
-        fig.update_layout(
-            height=400,
-            plot_bgcolor='rgba(240,247,255,0.8)',
-            xaxis_title="Date",
-            yaxis_title="Cash Balance ($)",
-            font=dict(family="Arial, sans-serif", size=12),
-            margin=dict(l=20, r=20, t=40, b=20),
-        )
-        
-        st.plotly_chart(fig, use_container_width=True)
-        
-        # Get AI analysis
-        if question:
-            decision_params = {
-                "new_hires": new_hires,
-                "new_marketing": new_marketing,
-                "other_expenses": other_expenses,
-                "growth_impact": growth_impact
-            }
-            
-            analysis = get_decision_analysis(question, startup_data, decision_params)
-            
-            st.markdown("<div class='advisor-card'>", unsafe_allow_html=True)
-            st.markdown("<span class='ai-badge'>AI Decision Analysis</span>", unsafe_allow_html=True)
-            st.markdown(f"<p class='advice-text'>{analysis}</p>", unsafe_allow_html=True)
-            st.markdown("</div>", unsafe_allow_html=True)
-            
-            # Break down impacts of each component
-            st.subheader("Component Impact Analysis")
-            
-            # Calculate the impact of each component in isolation
-            _, hiring_runway, _, _ = simulate_decision(
-                startup_data['cash'],
-                startup_data['burn_rate'],
-                startup_data['revenue'],
-                startup_data['growth_rate'],
-                0,
-                new_hires,
-                0,
-                0
-            )
-            
-            _, marketing_runway, _, _ = simulate_decision(
-                startup_data['cash'],
-                startup_data['burn_rate'],
-                startup_data['revenue'],
-                startup_data['growth_rate'],
-                0,
-                0,
-                new_marketing,
-                growth_impact
-            )
-            
-            _, expenses_runway, _, _ = simulate_decision(
-                startup_data['cash'],
-                startup_data['burn_rate'],
-                startup_data['revenue'],
-                startup_data['growth_rate'],
-                other_expenses,
-                0,
-                0,
-                0
-            )
-            
-            component_data = {
-                "Component": ["Engineering Hires", "Marketing Increase", "Other Expenses", "Combined Impact"],
-                "Runway Impact (months)": [
-                    hiring_runway - current_runway,
-                    marketing_runway - current_runway,
-                    expenses_runway - current_runway,
-                    new_runway - current_runway
-                ]
-            }
-            
-            component_df = pd.DataFrame(component_data)
-            
-            fig = px.bar(component_df, x='Component', y='Runway Impact (months)',
-                        title="Impact of Each Component on Runway",
-                        color='Runway Impact (months)',
-                        color_continuous_scale=['#dc3545', '#ffc107', '#28a745'],
-                        text='Runway Impact (months)')
-            
-            fig.update_layout(
-                height=400,
-                plot_bgcolor='rgba(240,247,255,0.8)',
-                font=dict(family="Arial, sans-serif", size=12),
-                margin=dict(l=20, r=20, t=40, b=20),
-            )
-            
-            fig.update_traces(texttemplate='%{text:.1f}', textposition='outside')
-            st.plotly_chart(fig, use_container_width=True)
-            
-            # Risk assessment
-            risk_level = "High" if new_runway < 3 else ("Medium" if new_runway < 6 else "Low")
-            risk_color = "danger-metric" if risk_level == "High" else ("warning-metric" if risk_level == "Medium" else "good-metric")
-            
-            st.markdown(f"""
-            <div class='metric-card'>
-                <p class='metric-label'>Risk Assessment</p>
-                <p class='metric-value {risk_color}'>{risk_level} Risk Decision</p>
-                <p>This decision would give you {new_runway} months of runway.</p>
-            </div>
-            """, unsafe_allow_html=True)
-            
-            # Recommendations
-            st.info("💡 **Want personalized guidance on this decision?** [Book a session](#book-a-session) with our AI financial advisor for detailed analysis.")
-
-def get_decision_analysis(question, financial_data, decision_params):
-    """Get AI analysis for a specific business decision."""
-    prompt = f"""
-    You are a financial advisor for startups. A founder asks:
-    "{question}"
-
-    Here's their current financial situation:
-    - Current cash: ${financial_data['cash']}
-    - Monthly burn rate: ${financial_data['burn_rate']}
-    - Monthly revenue: ${financial_data['revenue']}
-    - Monthly growth rate: {financial_data['growth_rate'] * 100}%
-    
-    They're considering these changes:
-    - Adding {decision_params['new_hires']} new engineers (${ENGINEER_SALARY}/month each)
-    - Increasing marketing budget by ${decision_params['new_marketing']}/month
-    - Adding ${decision_params['other_expenses']}/month in other expenses
-    - Expecting {decision_params['growth_impact'] * 100}% additional monthly growth
-
-    Analyze this decision thoroughly:
-    1. Quantify the impact on runway (exact calculation)
-    2. Assess the risk level (low, medium, high)
-    3. Compare the ROI potential
-    4. Provide 3 specific recommendations or alternatives
-    5. Suggest timeline and milestones for implementation if approved
-
-    Be direct and specific with numbers and timeframes.
-    """
-    
-    return generate_ai_response(prompt)