Update app.py

app.py

@@ -14,6 +14,7 @@ import warnings
 
 warnings.filterwarnings("ignore")
 
+
 def analyze_stock(symbol, prediction_days=30):
     try:
         if not symbol.strip():
@@ -32,19 +33,25 @@ def analyze_stock(symbol, prediction_days=30):
         signals = generate_trading_signals(data, indicators)
         fundamental_info = get_fundamental_data(stock)
         predictions = predict_prices(data, prediction_days=prediction_days)
+
         fig_price = create_price_chart(data, indicators)
         fig_technical = create_technical_chart(data, indicators)
         fig_prediction = create_prediction_chart(data, predictions)
 
         return fundamental_info, indicators, signals, fig_price, fig_technical, fig_prediction, predictions
+
     except Exception as e:
         print(f"Error analyzing {symbol}: {e}")
         empty_fig = gr.Plot.update(value=None)
         empty_predictions = {
-            'high_30d': 0, 'low_30d': 0, 'change_pct': 0, 'summary': 'Prediction unavailable.'
+            "high_30d": 0,
+            "low_30d": 0,
+            "change_pct": 0,
+            "summary": "Prediction unavailable.",
         }
         return {}, {}, {}, empty_fig, empty_fig, empty_fig, empty_predictions
 
+
 def update_analysis(symbol, prediction_days):
     (
         fundamental_info,
@@ -58,16 +65,20 @@ def update_analysis(symbol, prediction_days):
 
     if not fundamental_info:
         return (
-            "❌ Unable to fetch stock data.",
+            "Unable to fetch stock data.",
+            "No technical signals available.",
             gr.Plot.update(value=None),
             gr.Plot.update(value=None),
             gr.Plot.update(value=None),
-            "",
-            "0", "0", "0", ""
+            "0",
+            "0",
+            "0",
+            "No prediction data available.",
         )
 
     fundamentals = f"""
-### 🏢 {fundamental_info.get('name', 'N/A')} ({symbol.upper()})
+#### COMPANY FUNDAMENTALS
+**Name:** {fundamental_info.get('name', 'N/A')} ({symbol.upper()})  
 **Current Price:** Rp{fundamental_info.get('current_price', 0):,.2f}  
 **Market Cap:** {fundamental_info.get('market_cap', 0):,}  
 **P/E Ratio:** {fundamental_info.get('pe_ratio', 0):.2f}  
@@ -76,24 +87,24 @@ def update_analysis(symbol, prediction_days):
 """
 
     trading_signal = f"""
-### 📊 Technical Signal Summary
+#### TECHNICAL SIGNAL SUMMARY
 **Overall Trend:** {signals.get('overall', 'N/A')}  
 **Signal Strength:** {signals.get('strength', 0):.2f}%  
-**Support:** {signals.get('support', 0):,.2f}  
-**Resistance:** {signals.get('resistance', 0):,.2f}  
-**Stop Loss:** {signals.get('stop_loss', 0):,.2f}  
+**Support:** Rp{signals.get('support', 0):,.2f}  
+**Resistance:** Rp{signals.get('resistance', 0):,.2f}  
+**Stop Loss:** Rp{signals.get('stop_loss', 0):,.2f}  
 
-**Detailed Insights:**
+**Detailed Signals:**
 {signals.get('details', '')}
 """
 
     prediction = f"""
-### 🤖 30-Day AI Forecast (Amazon Chronos-Bolt)
+#### 30-DAY AI FORECAST (CHRONOS-BOLT)
 **Predicted High:** Rp{predictions.get('high_30d', 0):,.2f}  
 **Predicted Low:** Rp{predictions.get('low_30d', 0):,.2f}  
 **Expected Change:** {predictions.get('change_pct', 0):.2f}%  
 
-🧠 **Model Insight:**  
+**Model Insight:**  
 {predictions.get('summary', 'No analysis available')}
 """
 
@@ -109,41 +120,76 @@ def update_analysis(symbol, prediction_days):
         prediction,
     )
 
+
 with gr.Blocks(
-    title="RexPro Financial AI Dashboard",
-    theme=gr.themes.Soft(primary_hue="cyan", secondary_hue="emerald"),
+    title="REXPRO FINANCIAL AI DASHBOARD",
+    theme=gr.themes.Soft(primary_hue="blue", secondary_hue="gray"),
     css="""
-        body {background-color: #0f172a; color: #e2e8f0; font-family: 'Inter', sans-serif;}
-        h1, h2, h3 {color: #22d3ee;}
-        .gr-markdown {background-color: #1e293b; border-radius: 12px; padding: 18px; color: #e2e8f0;}
-        .gr-button {background: linear-gradient(90deg, #06b6d4, #14b8a6); color: white !important; font-weight: 600; border-radius: 10px;}
-        .gr-textbox label, .gr-slider label {color: #a5f3fc;}
-        .gr-textbox input, .gr-slider {background-color: #1e293b; color: white;}
-        .gr-plot {background-color: #1e293b; border-radius: 12px;}
-    """
+        body {
+            background-color: #fafafa;
+            color: #1e293b;
+            font-family: 'Inter', 'Segoe UI', Arial, sans-serif;
+        }
+        h1 {
+            color: #1e40af;
+            text-align: center;
+            font-weight: 700;
+            letter-spacing: 0.5px;
+        }
+        h2, h3, h4 {
+            color: #1e3a8a;
+            font-weight: 600;
+        }
+        .gr-markdown {
+            background-color: #ffffff;
+            border-radius: 10px;
+            border: 1px solid #e2e8f0;
+            padding: 16px;
+        }
+        .gr-button {
+            background-color: #2563eb !important;
+            color: white !important;
+            font-weight: 600;
+            border-radius: 8px;
+            padding: 10px 18px;
+        }
+        .gr-textbox input {
+            background-color: #ffffff !important;
+            color: #1e293b !important;
+        }
+        .gr-slider {
+            background-color: #ffffff !important;
+        }
+        .gr-plot {
+            background-color: #ffffff;
+            border: 1px solid #e2e8f0;
+            border-radius: 10px;
+        }
+    """,
 ) as app:
-    gr.Markdown("# 💹 REXPRO FINANCIAL AI DASHBOARD")
-    gr.Markdown("Smart market insights powered by **Chronos-Bolt AI** — for serious investors and analysts.", elem_id="subheader")
+    gr.Markdown("# REXPRO FINANCIAL AI DASHBOARD")
+    gr.Markdown(
+        "A modern financial intelligence dashboard powered by **AI forecasting and technical analytics.**"
+    )
 
-    with gr.Row(equal_height=True):
+    with gr.Row():
         symbol = gr.Textbox(
-            label="Stock Symbol (IDX)",
+            label="STOCK SYMBOL (IDX)",
             value="BBCA",
-            placeholder="Example: BBCA, TLKM, ADRO, BMRI ...",
+            placeholder="Example: BBCA, TLKM, ADRO, BMRI",
             interactive=True,
-            lines=1,
         )
         prediction_days = gr.Slider(
-            label="Forecast Period (Days)",
+            label="FORECAST PERIOD (DAYS)",
             minimum=5,
             maximum=60,
             step=5,
             value=30,
             interactive=True,
         )
-        analyze_button = gr.Button("🚀 Run Analysis")
+        analyze_button = gr.Button("RUN ANALYSIS")
 
-    gr.Markdown("---")
+    gr.Markdown("___")
 
     with gr.Row():
         with gr.Column(scale=1):
@@ -151,21 +197,21 @@ with gr.Blocks(
         with gr.Column(scale=1):
             signal_output = gr.Markdown()
 
-    gr.Markdown("---")
+    gr.Markdown("___")
 
-    with gr.Tab("📈 Market Charts"):
+    with gr.Tab("MARKET CHARTS"):
         with gr.Row():
-            price_chart = gr.Plot(label="Price & Moving Averages")
-            technical_chart = gr.Plot(label="Technical Indicators Overview")
-        gr.Markdown("---")
-        prediction_chart = gr.Plot(label="AI Forecast Projection")
+            price_chart = gr.Plot(label="PRICE & MOVING AVERAGES")
+            technical_chart = gr.Plot(label="TECHNICAL INDICATORS OVERVIEW")
+        gr.Markdown("___")
+        prediction_chart = gr.Plot(label="AI FORECAST PROJECTION")
 
-    with gr.Tab("🤖 AI Forecast Summary"):
+    with gr.Tab("AI FORECAST SUMMARY"):
         with gr.Row():
-            predicted_high = gr.Textbox(label="Predicted High (30d)", interactive=False)
-            predicted_low = gr.Textbox(label="Predicted Low (30d)", interactive=False)
-            predicted_change = gr.Textbox(label="Expected Change (%)", interactive=False)
-        gr.Markdown("---")
+            predicted_high = gr.Textbox(label="PREDICTED HIGH (30D)", interactive=False)
+            predicted_low = gr.Textbox(label="PREDICTED LOW (30D)", interactive=False)
+            predicted_change = gr.Textbox(label="EXPECTED CHANGE (%)", interactive=False)
+        gr.Markdown("___")
         prediction_summary = gr.Markdown()
 
     analyze_button.click(