Update app.py

app.py

@@ -1,172 +1,230 @@
 import gradio as gr
+import pandas as pd
 import yfinance as yf
 from utils import (
     calculate_technical_indicators,
     generate_trading_signals,
     get_fundamental_data,
+    predict_prices,
     create_price_chart,
     create_technical_chart,
     create_prediction_chart,
-    predict_prices,
 )
-import numpy as np
+import warnings
+
+warnings.filterwarnings("ignore")
 
 
-def analyze_stock(symbol, mode, pred_days):
+def analyze_stock(symbol, prediction_days=30):
     try:
+        if not symbol.strip():
+            raise ValueError("Please enter a valid stock symbol.")
+
+        if not symbol.endswith(".JK"):
+            symbol = symbol.upper() + ".JK"
+
         stock = yf.Ticker(symbol)
-        data = stock.history(period="1y")
+        data = stock.history(period="6mo", interval="1d")
 
         if data.empty:
-            msg = f"No data found for {symbol}. Check the symbol or try adding .JK (e.g., ADRO.JK)"
-            return (
-                {"name": "N/A", "current_price": 0, "market_cap": 0, "pe_ratio": 0, "dividend_yield": 0, "volume": 0},
-                {"overall": "N/A", "strength": 0, "support": 0, "resistance": 0, "stop_loss": 0, "details": msg},
-                None, None, None, None
-            )
+            raise ValueError("No price data available for this stock.")
 
         indicators = calculate_technical_indicators(data)
         signals = generate_trading_signals(data, indicators)
-        fundamentals = get_fundamental_data(stock)
+        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)
+
+        # kalkulasi TP1, TP2, SL
+        last_price = data['Close'].iloc[-1]
+        tp1 = last_price * (1 + (predictions.get("change_pct", 0) / 200))
+        tp2 = last_price * (1 + (predictions.get("change_pct", 0) / 100))
+        sl = last_price * 0.95
 
-        if mode == "AI Prediction":
-            prediction = predict_prices(data, prediction_days=pred_days)
-            fig_prediction = create_prediction_chart(data, prediction)
-            return fundamentals, signals, fig_price, fig_technical, fig_prediction, prediction
-        else:
-            return fundamentals, signals, fig_price, fig_technical, None, None
+        predictions["tp1"] = tp1
+        predictions["tp2"] = tp2
+        predictions["sl"] = sl
+
+        return fundamental_info, indicators, signals, fig_price, fig_technical, fig_prediction, predictions
 
     except Exception as e:
-        msg = f"Error analyzing {symbol}: {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.",
+        }
+        return {}, {}, {}, empty_fig, empty_fig, empty_fig, empty_predictions
+
+
+def update_analysis(symbol, prediction_days):
+    (
+        fundamental_info,
+        indicators,
+        signals,
+        fig_price,
+        fig_technical,
+        fig_prediction,
+        predictions,
+    ) = analyze_stock(symbol, prediction_days)
+
+    if not fundamental_info:
         return (
-            {"name": "N/A", "current_price": 0, "market_cap": 0, "pe_ratio": 0, "dividend_yield": 0, "volume": 0},
-            {"overall": "Error", "strength": 0, "support": 0, "resistance": 0, "stop_loss": 0, "details": msg},
-            None, None, None, None
+            "Unable to fetch stock data.",
+            "No technical signals available.",
+            "No prediction data available.",
+            gr.Plot.update(value=None),
+            gr.Plot.update(value=None),
+            gr.Plot.update(value=None),
         )
 
-
-def format_fundamental_output(f):
-    return f"""
-    <div class="card">
-    <h3>COMPANY FUNDAMENTALS</h3>
-    <p><b>Name:</b> {f['name']}</p>
-    <p><b>Current Price:</b> Rp{f['current_price']:,.2f}</p>
-    <p><b>Market Cap:</b> {f['market_cap']:,}</p>
-    <p><b>P/E Ratio:</b> {f['pe_ratio']:.2f}</p>
-    <p><b>Dividend Yield:</b> {f['dividend_yield']:.2f}%</p>
-    <p><b>Volume:</b> {f['volume']:,}</p>
-    </div>
+    fundamentals = f"""
+    <h4>COMPANY FUNDAMENTALS</h4>
+    <b>Name:</b> {fundamental_info.get('name', 'N/A')} ({symbol.upper()})<br>
+    <b>Current Price:</b> Rp{fundamental_info.get('current_price', 0):,.2f}<br>
+    <b>Market Cap:</b> {fundamental_info.get('market_cap', 0):,}<br>
+    <b>P/E Ratio:</b> {fundamental_info.get('pe_ratio', 0):.2f}<br>
+    <b>Dividend Yield:</b> {fundamental_info.get('dividend_yield', 0):.2f}%<br>
+    <b>Volume:</b> {fundamental_info.get('volume', 0):,}<br>
     """
 
+    details_list = "".join(
+        [f"<li>{line.strip()}</li>" for line in signals.get("details", "").split("\n") if line.strip()]
+    )
 
-def format_signal_output(s):
-    details = s.get("details", "")
-    detail_list = details.split("\n") if details else []
-    formatted_details = "<ul>" + "".join(f"<li>{d}</li>" for d in detail_list) + "</ul>"
-    return f"""
-    <div class="card">
-    <h3>TECHNICAL SIGNAL SUMMARY</h3>
-    <p><b>Overall Trend:</b> {s.get('overall','N/A')}</p>
-    <p><b>Signal Strength:</b> {s.get('strength',0):.2f}%</p>
-    <p><b>Support:</b> Rp{s.get('support',0):,.2f}</p>
-    <p><b>Resistance:</b> Rp{s.get('resistance',0):,.2f}</p>
-    <p><b>Stop Loss:</b> Rp{s.get('stop_loss',0):,.2f}</p>
-    <h4>Detailed Signals:</h4>
-    {formatted_details}
-    </div>
+    trading_signal = f"""
+    <h4>TECHNICAL SIGNAL SUMMARY</h4>
+    <b>Overall Trend:</b> {signals.get('overall', 'N/A')}<br>
+    <b>Signal Strength:</b> {signals.get('strength', 0):.2f}%<br>
+    <b>Support:</b> Rp{signals.get('support', 0):,.2f}<br>
+    <b>Resistance:</b> Rp{signals.get('resistance', 0):,.2f}<br>
+    <b>Stop Loss:</b> Rp{signals.get('stop_loss', 0):,.2f}<br><br>
+    <b>Detailed Signals:</b>
+    <ul style="margin-top: 8px; padding-left: 20px; line-height: 1.6;">
+    {details_list}
+    </ul>
     """
 
+    prediction = f"""
+    <h4>30-DAY AI FORECAST (CHRONOS-BOLT)</h4>
+    <b>Predicted High:</b> Rp{predictions.get('high_30d', 0):,.2f}<br>
+    <b>Predicted Low:</b> Rp{predictions.get('low_30d', 0):,.2f}<br>
+    <b>Expected Change:</b> {predictions.get('change_pct', 0):.2f}%<br><br>
+    <b>TP1:</b> Rp{predictions.get('tp1', 0):,.2f}<br>
+    <b>TP2:</b> Rp{predictions.get('tp2', 0):,.2f}<br>
+    <b>Stop Loss:</b> Rp{predictions.get('sl', 0):,.2f}<br><br>
+    <b>Model Insight:</b><br>{predictions.get('summary', 'No analysis available')}
+    """
 
-def format_ai_output(p):
-    if p is None or not isinstance(p, dict) or "values" not in p or len(p["values"]) == 0:
-        return """
-        <div class="card">
-        <h3>30-DAY AI FORECAST (CHRONOS-BOLT)</h3>
-        <p>No AI prediction data available.</p>
+    return (
+        f"""
+        <div class='triple-panel'>
+            <div class='panel-box'>{fundamentals}</div>
+            <div class='panel-box'>{trading_signal}</div>
+            <div class='panel-box'>{prediction}</div>
         </div>
-        """
-    tp1 = p["mean_30d"] * 0.97
-    tp2 = p["mean_30d"] * 1.02
-    sl = p["low_30d"] * 0.95
-    return f"""
-    <div class="card">
-    <h3>30-DAY AI FORECAST (CHRONOS-BOLT)</h3>
-    <p><b>Predicted High:</b> Rp{p['high_30d']:,.2f}</p>
-    <p><b>Predicted Low:</b> Rp{p['low_30d']:,.2f}</p>
-    <p><b>Expected Change:</b> {p['change_pct']:.2f}%</p>
-    <p><b>TP1:</b> Rp{tp1:,.2f}</p>
-    <p><b>TP2:</b> Rp{tp2:,.2f}</p>
-    <p><b>Stop Loss:</b> Rp{sl:,.2f}</p>
-    <h4>Model Insight:</h4>
-    <p style="font-size:13px;line-height:1.4;">{p['summary']}</p>
-    </div>
-    """
+        """,
+        fig_price,
+        fig_technical,
+        fig_prediction,
+    )
 
 
-with gr.Blocks(css="""
-    body { font-family: 'Inter', sans-serif; background-color: #f9fafc; color: #222; }
-    .gradio-container { max-width: 1300px; margin: auto; }
-    h1 { text-align:center; color:#003366; margin-bottom:20px; }
-    h3 { color:#003366; margin-bottom:8px; }
-    .card {
-        background: #ffffff;
-        border-radius: 10px;
-        box-shadow: 0 2px 4px rgba(0,0,0,0.08);
-        padding: 18px;
-        margin: 5px;
-        flex: 1;
-        min-width: 0;
-    }
-    .row-flex {
-        display: flex;
-        flex-wrap: wrap;
-        justify-content: space-between;
-        gap: 10px;
-    }
-    ul { margin: 6px 0 0 20px; padding: 0; }
-    li { margin-bottom: 4px; font-size: 14px; }
-""") as demo:
-
-    gr.HTML("<h1>STOCK ANALYSIS DASHBOARD</h1>")
+with gr.Blocks(
+    title="REXPRO FINANCIAL AI DASHBOARD",
+    theme=gr.themes.Soft(primary_hue="blue", secondary_hue="gray"),
+    css="""
+        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap');
+        body {
+            background-color: #f9fafb;
+            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;
+            margin-bottom: 6px;
+        }
+        .gr-button {
+            background-color: #2563eb !important;
+            color: white !important;
+            font-weight: 600;
+            border-radius: 8px;
+            padding: 10px 18px;
+        }
+        .panel-box {
+            background-color: #ffffff;
+            border-radius: 10px;
+            border: 1px solid #e2e8f0;
+            padding: 16px;
+            flex: 1;
+            min-width: 30%;
+        }
+        .triple-panel {
+            display: flex;
+            flex-direction: row;
+            justify-content: space-between;
+            gap: 16px;
+            width: 100%;
+        }
+        ul { margin: 0; padding: 0 0 0 18px; }
+        li { margin-bottom: 4px; }
+        .gr-plot {
+            background-color: #ffffff;
+            border: 1px solid #e2e8f0;
+            border-radius: 10px;
+        }
+    """,
+) as app:
+    gr.Markdown("# REXPRO FINANCIAL AI DASHBOARD")
+    gr.Markdown(
+        "Comprehensive stock analytics powered by **AI forecasting and technical analysis.**"
+    )
 
     with gr.Row():
-        stock_input = gr.Textbox(label="Enter Stock Symbol (e.g. BBCA.JK, ADRO.JK)", placeholder="Type stock symbol...")
-        mode_input = gr.Radio(["Technical Analysis", "AI Prediction"], label="Select Analysis Mode", value="Technical Analysis")
-        pred_days_input = gr.Slider(7, 60, value=30, step=1, label="Prediction Days (AI only)")
-        analyze_button = gr.Button("Analyze", variant="primary")
-
-    gr.HTML("<hr style='margin:20px 0;'>")
-
-    with gr.Row(elem_classes="row-flex"):
-        fundamentals_output = gr.HTML()
-        signal_output = gr.HTML()
-        ai_output = gr.HTML()
-
-    gr.HTML("<hr style='margin:20px 0;'>")
+        symbol = gr.Textbox(
+            label="STOCK SYMBOL (IDX)",
+            value="BBCA",
+            placeholder="Example: BBCA, TLKM, ADRO, BMRI",
+            interactive=True,
+        )
+        prediction_days = gr.Slider(
+            label="FORECAST PERIOD (DAYS)",
+            minimum=5,
+            maximum=60,
+            step=5,
+            value=30,
+            interactive=True,
+        )
+        analyze_button = gr.Button("RUN ANALYSIS")
 
-    with gr.Row():
-        chart_price = gr.Plot(label="Price Chart")
-        chart_technical = gr.Plot(label="Technical Chart")
-        chart_prediction = gr.Plot(label="AI Prediction Chart")
+    gr.Markdown("---")
+    report_section = gr.HTML()
+    gr.Markdown("---")
 
-    def run_analysis(symbol, mode, pred_days):
-        fundamentals, signals, fig_price, fig_technical, fig_prediction, prediction = analyze_stock(symbol, mode, pred_days)
-        return (
-            format_fundamental_output(fundamentals),
-            format_signal_output(signals),
-            format_ai_output(prediction) if mode == "AI Prediction" else "",
-            fig_price,
-            fig_technical,
-            fig_prediction if mode == "AI Prediction" else None,
-        )
+    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")
 
     analyze_button.click(
-        fn=run_analysis,
-        inputs=[stock_input, mode_input, pred_days_input],
-        outputs=[fundamentals_output, signal_output, ai_output, chart_price, chart_technical, chart_prediction]
+        fn=update_analysis,
+        inputs=[symbol, prediction_days],
+        outputs=[report_section, price_chart, technical_chart, prediction_chart],
     )
 
-demo.launch(server_name="0.0.0.0", server_port=7860)
+if __name__ == "__main__":
+    app.launch(server_name="0.0.0.0", server_port=7860, ssr_mode=True)