Update app.py

app.py

@@ -5,17 +5,41 @@ import gradio as gr
 import pandas as pd
 import plotly.graph_objects as go
 import plotly.express as px
+from datetime import datetime, timedelta
 from geo_macro import UnifiedMarketDataDownloader, FRED_API_KEY
 from feature_engineering import IntegratedTheoryFeatures
 
 
+# ==================== COLOR PALETTE ====================
+COLORS = {
+    'primary': '#2E5EAA',      # Deep blue
+    'secondary': '#4A90E2',    # Light blue
+    'success': '#52B788',      # Green
+    'warning': '#F4A261',      # Orange
+    'danger': '#E63946',       # Red
+    'purple': '#9D4EDD',       # Purple
+    'teal': '#06AED5',         # Teal
+    'gray': '#6C757D',         # Gray
+    'light_bg': '#F8F9FA',     # Light background
+    'border': '#DEE2E6',       # Border
+}
 
-# Cache to avoid re-downloading data
+REGIME_COLORS = {
+    'CRISIS': COLORS['danger'],
+    'INEQUALITY_TRAP': COLORS['warning'],
+    'GEOPOLITICAL_SHOCK': COLORS['purple'],
+    'TECH_MONOPOLY': COLORS['success'],
+    'TRANSITION': COLORS['gray']
+}
+
+
+# ==================== DATA CACHING ====================
 _cached_df = None
 _cached_dates = (None, None)
 
 
 def get_data(start_date: str, end_date: str):
+    """Fetch market data with caching"""
     global _cached_df, _cached_dates
     if _cached_df is not None and _cached_dates == (start_date, end_date):
         return _cached_df.copy()
@@ -29,147 +53,510 @@ def get_data(start_date: str, end_date: str):
     return df
 
 
+# ==================== VISUALIZATION FUNCTIONS ====================
+
 def create_composite_bar(latest):
-    """Bar chart of the 4 core normalized scores"""
+    """Enhanced bar chart of the 4 core normalized scores"""
     scores = {
-        "Dalio Composite": latest['dalio_composite_norm'],
-        "Stevenson Inequality": latest['stevenson_inequality_norm'],
-        "Thiel Monopoly": latest['thiel_monopoly_norm'],
-        "Gundlach Reckoning": latest['gundlach_reckoning_norm'],
+        "Dalio\nComposite": latest['dalio_composite_norm'],
+        "Stevenson\nInequality": latest['stevenson_inequality_norm'],
+        "Thiel\nMonopoly": latest['thiel_monopoly_norm'],
+        "Gundlach\nReckoning": latest['gundlach_reckoning_norm'],
     }
-    colors = ["#1f77b4", "#ff7f0e", "#2ca02c", "#d62728"]
+    
+    colors = [COLORS['primary'], COLORS['warning'], COLORS['success'], COLORS['danger']]
+    
     fig = go.Figure(go.Bar(
         x=list(scores.keys()),
         y=list(scores.values()),
-        marker_color=colors,
-        text=[f"{v:.3f}" for v in scores.values()],
-        textposition='auto',
+        marker=dict(
+            color=colors,
+            line=dict(color='white', width=2)
+        ),
+        text=[f"{v:.2f}" for v in scores.values()],
+        textposition='outside',
+        textfont=dict(size=14, color='#2C3E50'),
+        hovertemplate='<b>%{x}</b><br>Score: %{y:.3f}<extra></extra>'
     ))
+    
     fig.update_layout(
-        title="Core Theory Scores (Normalized)",
-        yaxis_range=[-1, 1],
-        height=350
+        title=dict(
+            text="<b>Core Theory Scores</b>",
+            font=dict(size=18, color='#2C3E50'),
+            x=0.5,
+            xanchor='center'
+        ),
+        yaxis=dict(
+            range=[-1, 1],
+            title="Normalized Score",
+            gridcolor=COLORS['border'],
+            zeroline=True,
+            zerolinecolor=COLORS['gray'],
+            zerolinewidth=2
+        ),
+        xaxis=dict(
+            title="",
+            tickfont=dict(size=11)
+        ),
+        height=400,
+        plot_bgcolor='white',
+        paper_bgcolor='white',
+        margin=dict(t=60, b=40, l=60, r=40),
+        font=dict(family="Arial, sans-serif")
     )
+    
     return fig
 
 
-def create_probabilities_bar(latest):
-    """Horizontal bar chart of scenario probabilities"""
-    probs = {
-        "Credit Collapse": latest['prob_credit_collapse'],
-        "Stagflation": latest['prob_stagflation'],
-        "Tech Boom": latest['prob_tech_boom'],
+def create_probabilities_gauge(latest):
+    """Three gauge charts for scenario probabilities"""
+    scenarios = {
+        "Credit Collapse": (latest['prob_credit_collapse'], COLORS['danger']),
+        "Stagflation": (latest['prob_stagflation'], COLORS['warning']),
+        "Tech Boom": (latest['prob_tech_boom'], COLORS['success']),
     }
-    fig = go.Figure(go.Bar(
-        x=list(probs.values()),
-        y=list(probs.keys()),
-        orientation='h',
-        marker_color=["#d62728", "#ff7f0e", "#2ca02c"],
-        text=[f"{v:.1%}" for v in probs.values()],
-        textposition='auto',
-    ))
+    
+    fig = go.Figure()
+    
+    positions = [(0, 0.5), (0.365, 0.5), (0.73, 0.5)]
+    
+    for i, (name, (value, color)) in enumerate(scenarios.items()):
+        x_pos, y_pos = positions[i]
+        
+        fig.add_trace(go.Indicator(
+            mode="gauge+number",
+            value=value * 100,
+            title={'text': f"<b>{name}</b>", 'font': {'size': 14}},
+            number={'suffix': "%", 'font': {'size': 20}},
+            gauge={
+                'axis': {'range': [0, 100], 'tickwidth': 1},
+                'bar': {'color': color, 'thickness': 0.75},
+                'bgcolor': "white",
+                'borderwidth': 2,
+                'bordercolor': COLORS['border'],
+                'steps': [
+                    {'range': [0, 30], 'color': '#E8F5E9'},
+                    {'range': [30, 70], 'color': '#FFF3E0'},
+                    {'range': [70, 100], 'color': '#FFEBEE'}
+                ],
+                'threshold': {
+                    'line': {'color': "#2C3E50", 'width': 3},
+                    'thickness': 0.75,
+                    'value': value * 100
+                }
+            },
+            domain={'x': [x_pos, x_pos + 0.27], 'y': [y_pos, y_pos + 0.5]}
+        ))
+    
     fig.update_layout(
-        title="Scenario Probabilities",
-        xaxis_tickformat='.0%',
-        xaxis_range=[0, 1],
-        height=250
+        height=300,
+        paper_bgcolor='white',
+        font={'family': "Arial, sans-serif", 'color': '#2C3E50'},
+        margin=dict(t=40, b=20, l=20, r=20)
     )
+    
     return fig
 
 
 def create_regime_timeline(features):
-    """Timeline of regime over last 252 days"""
+    """Enhanced timeline with area fill and annotations"""
     tail = features[['regime']].tail(252).copy()
     tail['date'] = tail.index
-    color_map = {
-        'CRISIS': '#d62728',
-        'INEQUALITY_TRAP': '#ff7f0e',
-        'GEOPOLITICAL_SHOCK': '#9467bd',
-        'TECH_MONOPOLY': '#2ca02c',
-        'TRANSITION': '#7f7f7f'
+    
+    # Map regime to numeric value for plotting
+    regime_order = {
+        'CRISIS': 4,
+        'GEOPOLITICAL_SHOCK': 3,
+        'INEQUALITY_TRAP': 2,
+        'TECH_MONOPOLY': 1,
+        'TRANSITION': 0
     }
-    tail['color'] = tail['regime'].map(color_map)
-    fig = go.Figure(go.Scatter(
-        x=tail['date'],
-        y=tail['regime'],
-        mode='markers',
-        marker=dict(color=tail['color'], size=8),
-        showlegend=False
+    tail['regime_num'] = tail['regime'].map(regime_order)
+    tail['color'] = tail['regime'].map(REGIME_COLORS)
+    
+    fig = go.Figure()
+    
+    # Add colored area segments
+    for regime in regime_order.keys():
+        mask = tail['regime'] == regime
+        if mask.any():
+            fig.add_trace(go.Scatter(
+                x=tail[mask]['date'],
+                y=tail[mask]['regime_num'],
+                mode='markers',
+                name=regime,
+                marker=dict(
+                    color=REGIME_COLORS[regime],
+                    size=10,
+                    line=dict(color='white', width=1)
+                ),
+                hovertemplate=f'<b>{regime}</b><br>Date: %{{x|%Y-%m-%d}}<extra></extra>'
+            ))
+    
+    fig.update_layout(
+        title=dict(
+            text="<b>Regime Timeline (Last 12 Months)</b>",
+            font=dict(size=18, color='#2C3E50'),
+            x=0.5,
+            xanchor='center'
+        ),
+        height=350,
+        yaxis=dict(
+            title="Market Regime",
+            ticktext=['Transition', 'Tech Monopoly', 'Inequality Trap', 'Geo Shock', 'Crisis'],
+            tickvals=[0, 1, 2, 3, 4],
+            gridcolor=COLORS['border']
+        ),
+        xaxis=dict(
+            title="Date",
+            gridcolor=COLORS['border']
+        ),
+        plot_bgcolor='white',
+        paper_bgcolor='white',
+        margin=dict(t=60, b=40, l=80, r=40),
+        legend=dict(
+            orientation="h",
+            yanchor="bottom",
+            y=-0.3,
+            xanchor="center",
+            x=0.5
+        ),
+        font=dict(family="Arial, sans-serif")
+    )
+    
+    return fig
+
+
+def create_forces_radar(latest):
+    """Radar chart showing Dalio's five forces"""
+    forces = {
+        'Debt Cycle': latest['dalio_debt_cycle'],
+        'Internal Conflict': latest['dalio_internal_conflict'],
+        'External Conflict': latest['dalio_external_conflict'],
+        'Tech Force': latest['dalio_tech_force'],
+        'Nature Force': latest['dalio_nature_force']
+    }
+    
+    # Normalize to 0-1 for better visualization
+    categories = list(forces.keys())
+    values = [(v + 3) / 6 for v in forces.values()]  # Scale from [-3,3] to [0,1]
+    
+    fig = go.Figure()
+    
+    fig.add_trace(go.Scatterpolar(
+        r=values + [values[0]],  # Close the loop
+        theta=categories + [categories[0]],
+        fill='toself',
+        fillcolor=f'rgba(46, 94, 170, 0.3)',
+        line=dict(color=COLORS['primary'], width=2),
+        name='Current State',
+        hovertemplate='<b>%{theta}</b><br>Intensity: %{r:.2f}<extra></extra>'
     ))
+    
     fig.update_layout(
-        title="Regime Timeline (Last 12 Months)",
-        height=200,
-        yaxis_title="Regime",
-        xaxis_title="Date"
+        polar=dict(
+            radialaxis=dict(
+                visible=True,
+                range=[0, 1],
+                gridcolor=COLORS['border'],
+                tickformat='.1f'
+            ),
+            angularaxis=dict(
+                gridcolor=COLORS['border']
+            ),
+            bgcolor='white'
+        ),
+        title=dict(
+            text="<b>Dalio's Five Forces</b>",
+            font=dict(size=18, color='#2C3E50'),
+            x=0.5,
+            xanchor='center'
+        ),
+        height=350,
+        paper_bgcolor='white',
+        margin=dict(t=80, b=40, l=40, r=40),
+        font=dict(family="Arial, sans-serif"),
+        showlegend=False
     )
+    
     return fig
 
 
+def create_summary_card(latest):
+    """HTML summary card with key metrics"""
+    regime = str(latest['regime'])
+    regime_color = REGIME_COLORS.get(regime, COLORS['gray'])
+    
+    html = f"""
+    <div style="
+        background: linear-gradient(135deg, {regime_color}15 0%, {regime_color}05 100%);
+        border-left: 5px solid {regime_color};
+        padding: 25px;
+        border-radius: 10px;
+        box-shadow: 0 2px 8px rgba(0,0,0,0.08);
+        font-family: Arial, sans-serif;
+    ">
+        <h2 style="margin: 0 0 20px 0; color: #2C3E50; font-size: 24px;">
+            📊 Current Market Regime
+        </h2>
+        <div style="
+            background: white;
+            padding: 15px;
+            border-radius: 8px;
+            margin-bottom: 15px;
+            text-align: center;
+        ">
+            <div style="font-size: 14px; color: #6C757D; margin-bottom: 5px;">Status</div>
+            <div style="
+                font-size: 28px;
+                font-weight: bold;
+                color: {regime_color};
+                text-transform: uppercase;
+                letter-spacing: 1px;
+            ">{regime.replace('_', ' ')}</div>
+        </div>
+        <div style="display: grid; grid-template-columns: 1fr 1fr; gap: 15px;">
+            <div style="background: white; padding: 15px; border-radius: 8px;">
+                <div style="font-size: 12px; color: #6C757D; margin-bottom: 5px;">Credit Collapse Risk</div>
+                <div style="font-size: 22px; font-weight: bold; color: {COLORS['danger']};">
+                    {latest['prob_credit_collapse']:.1%}
+                </div>
+            </div>
+            <div style="background: white; padding: 15px; border-radius: 8px;">
+                <div style="font-size: 12px; color: #6C757D; margin-bottom: 5px;">Tech Boom Probability</div>
+                <div style="font-size: 22px; font-weight: bold; color: {COLORS['success']};">
+                    {latest['prob_tech_boom']:.1%}
+                </div>
+            </div>
+            <div style="background: white; padding: 15px; border-radius: 8px;">
+                <div style="font-size: 12px; color: #6C757D; margin-bottom: 5px;">Stagflation Risk</div>
+                <div style="font-size: 22px; font-weight: bold; color: {COLORS['warning']};">
+                    {latest['prob_stagflation']:.1%}
+                </div>
+            </div>
+            <div style="background: white; padding: 15px; border-radius: 8px;">
+                <div style="font-size: 12px; color: #6C757D; margin-bottom: 5px;">Geopolitical Stress</div>
+                <div style="font-size: 22px; font-weight: bold; color: {COLORS['purple']};">
+                    {latest['geopolitical_risk_norm']:.2f}
+                </div>
+            </div>
+        </div>
+        <div style="
+            margin-top: 15px;
+            padding: 12px;
+            background: white;
+            border-radius: 8px;
+            font-size: 12px;
+            color: #6C757D;
+            text-align: center;
+        ">
+            Last Updated: {latest.name.strftime('%Y-%m-%d %H:%M') if hasattr(latest.name, 'strftime') else 'N/A'}
+        </div>
+    </div>
+    """
+    return html
+
+
+# ==================== MAIN PIPELINE ====================
+
 def run_pipeline(days_back: int = 1825):
+    """Execute the full analysis pipeline"""
     try:
         today = pd.Timestamp.today()
         start_date = (today - pd.Timedelta(days=days_back)).strftime('%Y-%m-%d')
         end_date = today.strftime('%Y-%m-%d')
         
+        # Fetch data
         df = get_data(start_date, end_date)
         if len(df) < 300:
-            return {"Error": "Insufficient data. Try increasing lookback window."}, None, None, None
+            error_html = """
+            <div style="padding: 30px; background: #FFEBEE; border-radius: 10px; border-left: 5px solid #E63946;">
+                <h3 style="color: #E63946; margin: 0 0 10px 0;">⚠️ Insufficient Data</h3>
+                <p style="margin: 0; color: #2C3E50;">
+                    Not enough data points for analysis. Try increasing the lookback window to at least 1000 days.
+                </p>
+            </div>
+            """
+            return error_html, None, None, None, None, None
         
+        # Build features
         engine = IntegratedTheoryFeatures(df)
         features = engine.build_all_features()
         latest = features.dropna(subset=['regime']).iloc[-1]
         
-        # Format JSON
-        def fmt(x):
-            if pd.isna(x): return "N/A"
-            if isinstance(x, float) and -1 <= x <= 1: return f"{x:.3f}"
-            elif isinstance(x, float) and 0 <= x <= 1: return f"{x:.1%}"
-            else: return str(x)
+        # Create visualizations
+        summary_html = create_summary_card(latest)
+        composite_fig = create_composite_bar(latest)
+        prob_fig = create_probabilities_gauge(latest)
+        timeline_fig = create_regime_timeline(features)
+        radar_fig = create_forces_radar(latest)
         
+        # Create detailed JSON
         json_output = {
-            "Regime": str(latest["regime"]),
-            "Dalio Composite": fmt(latest['dalio_composite_norm']),
-            "Stevenson Inequality": fmt(latest['stevenson_inequality_norm']),
-            "Thiel Monopoly": fmt(latest['thiel_monopoly_norm']),
-            "Gundlach Reckoning": fmt(latest['gundlach_reckoning_norm']),
-            "Prob Credit Collapse": fmt(latest['prob_credit_collapse']),
-            "Prob Stagflation": fmt(latest['prob_stagflation']),
-            "Prob Tech Boom": fmt(latest['prob_tech_boom']),
+            "🎯 Current Regime": str(latest["regime"]),
+            "📊 Core Theories": {
+                "Dalio Composite": f"{latest['dalio_composite_norm']:.3f}",
+                "Stevenson Inequality": f"{latest['stevenson_inequality_norm']:.3f}",
+                "Thiel Monopoly": f"{latest['thiel_monopoly_norm']:.3f}",
+                "Gundlach Reckoning": f"{latest['gundlach_reckoning_norm']:.3f}",
+            },
+            "🎲 Scenario Probabilities": {
+                "Credit Collapse": f"{latest['prob_credit_collapse']:.1%}",
+                "Stagflation": f"{latest['prob_stagflation']:.1%}",
+                "Tech Boom": f"{latest['prob_tech_boom']:.1%}",
+            },
+            "🌍 Geopolitical": {
+                "Overall Risk": f"{latest['geopolitical_risk_norm']:.3f}",
+            },
+            "⚠️ Regime Flags": {
+                "Debt Unsustainable": bool(latest['debt_unsustainable']),
+                "Inequality Trap": bool(latest['inequality_trap']),
+                "Tech Monopoly": bool(latest['tech_monopoly']),
+                "Geopolitical Shock": bool(latest['geopolitical_shock']),
+            }
         }
         
-        # Create plots
-        composite_fig = create_composite_bar(latest)
-        prob_fig = create_probabilities_bar(latest)
-        timeline_fig = create_regime_timeline(features)
-        
-        return json_output, composite_fig, prob_fig, timeline_fig
+        return summary_html, json_output, composite_fig, prob_fig, timeline_fig, radar_fig
 
     except Exception as e:
-        error = {"Error": str(e)}
-        return error, None, None, None
+        error_html = f"""
+        <div style="padding: 30px; background: #FFEBEE; border-radius: 10px; border-left: 5px solid #E63946;">
+            <h3 style="color: #E63946; margin: 0 0 10px 0;">❌ Error</h3>
+            <p style="margin: 0; color: #2C3E50; font-family: monospace;">
+                {str(e)}
+            </p>
+        </div>
+        """
+        return error_html, {"Error": str(e)}, None, None, None, None
+
+
+# ==================== GRADIO UI ====================
+
+custom_css = """
+.gradio-container {
+    font-family: 'Arial', sans-serif !important;
+    max-width: 1400px !important;
+    margin: auto !important;
+}
+
+.header-text {
+    text-align: center;
+    padding: 20px;
+    background: linear-gradient(135deg, #2E5EAA 0%, #4A90E2 100%);
+    color: white;
+    border-radius: 10px;
+    margin-bottom: 20px;
+}
+
+.header-text h1 {
+    margin: 0;
+    font-size: 32px;
+    font-weight: bold;
+}
+
+.header-text p {
+    margin: 10px 0 0 0;
+    font-size: 16px;
+    opacity: 0.9;
+}
 
+.btn-primary {
+    background: linear-gradient(135deg, #2E5EAA 0%, #4A90E2 100%) !important;
+    border: none !important;
+    font-weight: bold !important;
+}
 
-# Gradio UI
-with gr.Blocks(title="🌍 Integrated Market Theory Dashboard") as demo:
-    gr.Markdown("# 🌍 Integrated Market Theory Dashboard")
-    gr.Markdown("Real-time macro regime detection using Dalio, Stevenson, Thiel & Gundlach frameworks")
+.panel {
+    background: white;
+    border-radius: 10px;
+    padding: 15px;
+    box-shadow: 0 2px 8px rgba(0,0,0,0.08);
+}
+"""
+
+with gr.Blocks(css=custom_css, title="🌍 Integrated Market Theory Dashboard", theme=gr.themes.Soft()) as demo:
+    
+    gr.HTML("""
+        <div class="header-text">
+            <h1>🌍 Integrated Market Theory Dashboard</h1>
+            <p>Real-time macro regime detection using Dalio, Stevenson, Thiel & Gundlach frameworks</p>
+        </div>
+    """)
     
     with gr.Row():
-        days = gr.Slider(365, 2500, value=1825, step=90, label="Lookback Window (days)")
-        run_btn = gr.Button("🔄 Update Analysis", variant="primary")
+        with gr.Column(scale=3):
+            days = gr.Slider(
+                365, 2500, 
+                value=1825, 
+                step=90, 
+                label="📅 Lookback Window (days)",
+                info="Minimum 1000 days recommended for stable results"
+            )
+        with gr.Column(scale=1):
+            run_btn = gr.Button(
+                "🔄 Update Analysis", 
+                variant="primary",
+                size="lg"
+            )
+    
+    gr.Markdown("---")
     
     with gr.Row():
-        json_output = gr.JSON(label="Current State")
-        composite_plot = gr.Plot(label="Core Theory Scores")
+        with gr.Column(scale=1):
+            summary_html = gr.HTML(label="Summary")
+        with gr.Column(scale=1):
+            json_output = gr.JSON(label="📋 Detailed Metrics", show_label=True)
+    
+    gr.Markdown("---")
+    gr.Markdown("## 📊 Theory Scores & Probabilities")
     
     with gr.Row():
+        composite_plot = gr.Plot(label="Core Theory Scores")
         prob_plot = gr.Plot(label="Scenario Probabilities")
+    
+    gr.Markdown("---")
+    gr.Markdown("## 📈 Historical Analysis")
+    
+    with gr.Row():
         timeline_plot = gr.Plot(label="Regime Timeline")
-
+        radar_plot = gr.Plot(label="Dalio's Five Forces")
+    
+    gr.Markdown("---")
+    gr.Markdown("""
+    <div style="text-align: center; padding: 20px; color: #6C757D; font-size: 14px;">
+        <p><b>Theoretical Framework:</b></p>
+        <p>
+            <b>Ray Dalio</b> - Five Forces (Debt, Internal/External Conflict, Technology, Nature) | 
+            <b>Betsey Stevenson</b> - Economic Inequality Dynamics | 
+            <b>Peter Thiel</b> - Zero to One Monopoly Theory | 
+            <b>Jeffrey Gundlach</b> - Debt Reckoning Framework
+        </p>
+        <p style="margin-top: 10px;">
+            Data Sources: Yahoo Finance, FRED Economic Data | 
+            All scores normalized to [-1, 1] range
+        </p>
+    </div>
+    """)
+    
+    # Event handler
     run_btn.click(
         run_pipeline,
-        inputs=days,
-        outputs=[json_output, composite_plot, prob_plot, timeline_plot]
+        inputs=[days],
+        outputs=[summary_html, json_output, composite_plot, prob_plot, timeline_plot, radar_plot]
     )
+    
+    # Auto-run on load
+    demo.load(
+        run_pipeline,
+        inputs=[days],
+        outputs=[summary_html, json_output, composite_plot, prob_plot, timeline_plot, radar_plot]
+    )
+
 
-demo.launch()
+if __name__ == "__main__":
+    demo.launch(
+        share=False,
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_error=True
+    )