Update app.py

app.py

@@ -1,11 +1,13 @@
 import gradio as gr
 import pandas as pd
-import plotly.graph_objects as go
+import numpy as np
+# Hapus import plotly.graph_objects
 from data_processor import DataProcessor
 from sentiment_analyzer import SentimentAnalyzer
 from model_handler import ModelHandler
 from trading_logic import TradingLogic
-import numpy as np
+from plotter import create_mplfinance_chart # Impor fungsi plotting baru
+import plotly.graph_objects as go # Tetap dipakai untuk Gauge Charts
 
 # Global instances
 data_processor = DataProcessor()
@@ -13,86 +15,46 @@ sentiment_analyzer = SentimentAnalyzer()
 model_handler = ModelHandler()
 trading_logic = TradingLogic()
 
-def create_chart_analysis(interval):
-    """Create chart with technical indicators"""
+# Fungsi utama yang menerima ticker dan interval
+def create_chart_analysis(ticker, interval):
+    """Create chart with technical indicators and predictions"""
     try:
-        df = data_processor.get_gold_data(interval)
+        # Panggil fungsi data yang sudah diperbarui
+        df = data_processor.get_market_data(ticker, interval)
         if df.empty:
             return "No data available", None, None
         
-        # Calculate indicators
+        # Hitung indikator
         df = data_processor.calculate_indicators(df)
         
-        # Create candlestick chart
-        fig = go.Figure(data=[
-            go.Candlestick(
-                x=df.index,
-                open=df['Open'],
-                high=df['High'],
-                low=df['Low'],
-                close=df['Close'],
-                name='Gold Price'
-            )
-        ])
-        
-        # Add Bollinger Bands
-        fig.add_trace(go.Scatter(
-            x=df.index, y=df['BB_upper'],
-            line=dict(color='rgba(255,255,255,0.3)', width=1),
-            name='BB Upper', showlegend=False
-        ))
-        fig.add_trace(go.Scatter(
-            x=df.index, y=df['BB_lower'],
-            line=dict(color='rgba(255,255,255,0.3)', width=1),
-            fill='tonexty', fillcolor='rgba(255,255,255,0.1)',
-            name='BB Lower', showlegend=False
-        ))
-        
-        # Add moving averages
-        fig.add_trace(go.Scatter(
-            x=df.index, y=df['SMA_20'],
-            line=dict(color='#FFD700', width=2),
-            name='SMA 20'
-        ))
-        fig.add_trace(go.Scatter(
-            x=df.index, y=df['SMA_50'],
-            line=dict(color='#FFA500', width=2),
-            name='SMA 50'
-        ))
-        
-        fig.update_layout(
-            title=f'Gold Futures (GC=F) - {interval}',
-            yaxis_title='Price (USD)',
-            xaxis_title='Date',
-            template='plotly_dark',
-            height=500,
-            margin=dict(l=50, r=50, t=50, b=50),
-            xaxis_rangeslider_visible=False,
-            paper_bgcolor='rgba(0,0,0,0)',
-            plot_bgcolor='rgba(0,0,0,0)',
-            font=dict(color='white')
-        )
-        
-        # KOREKSI: Panggil prepare_for_chronos sebelum prediksi
+        # Prepare data for Chronos
         prepared_data = data_processor.prepare_for_chronos(df)
 
-        # Generate predictions
+        # Generate predictions (Chronos-2 atau Fallback)
         predictions = model_handler.predict(prepared_data, horizon=10)
 
         current_price = df['Close'].iloc[-1]
         
-        # Get signal
+        # Buat chart menggunakan MPLFINANCE (dikembalikan sebagai HTML)
+        chart_html = create_mplfinance_chart(
+            df, 
+            ticker=f'{ticker} ({interval})', 
+            predictions=predictions
+        )
+
+        # Hasilkan sinyal trading
         signal, confidence = trading_logic.generate_signal(
             predictions, current_price, df
         )
         
-        # Calculate TP/SL
+        # Hitung TP/SL
         tp, sl = trading_logic.calculate_tp_sl(
             current_price, df['ATR'].iloc[-1], signal
         )
         
         # Create metrics display
         metrics = {
+            "Ticker": ticker,
             "Current Price": f"${current_price:.2f}",
             "Signal": signal.upper(),
             "Confidence": f"{confidence:.1%}",
@@ -103,11 +65,11 @@ def create_chart_analysis(interval):
             "Volume": f"{df['Volume'].iloc[-1]:,.0f}"
         }
         
-        # Create prediction chart
+        # Buat prediction chart sederhana (Plotly)
         pred_fig = go.Figure()
         
-        # Check if predictions are valid before plotting
         if predictions.any():
+            # Gunakan index datetime asli dari data_processor
             future_dates = pd.date_range(
                 start=df.index[-1], periods=len(predictions), freq='D'
             )
@@ -115,21 +77,22 @@ def create_chart_analysis(interval):
             pred_fig.add_trace(go.Scatter(
                 x=future_dates, y=predictions,
                 mode='lines+markers',
-                line=dict(color='#FFD700', width=3),
+                line=dict(color='blue', width=3),
                 marker=dict(size=6),
                 name='Predictions'
             ))
             
+            # Garis putus-putus dari harga terakhir ke prediksi pertama
             pred_fig.add_trace(go.Scatter(
                 x=[df.index[-1], future_dates[0]],
                 y=[current_price, predictions[0]],
                 mode='lines',
-                line=dict(color='rgba(255,215,0,0.5)', width=2, dash='dash'),
+                line=dict(color='rgba(0,0,255,0.5)', width=2, dash='dash'),
                 showlegend=False
             ))
         
         pred_fig.update_layout(
-            title='Price Prediction (Next 10 Periods)',
+            title=f'{ticker} Price Prediction (Next 10 Periods)',
             yaxis_title='Price (USD)',
             xaxis_title='Date',
             template='plotly_dark',
@@ -139,76 +102,84 @@ def create_chart_analysis(interval):
             font=dict(color='white')
         )
         
-        return fig, metrics, pred_fig
+        return chart_html, metrics, pred_fig
         
     except Exception as e:
-        return str(e), None, None
+        return f"Error creating chart: {str(e)}", None, None
 
-def analyze_sentiment():
-    """Analyze gold market sentiment"""
-    try:
-        sentiment_score, news_summary = sentiment_analyzer.analyze_gold_sentiment()
-        
-        # Create sentiment gauge
-        fig = go.Figure(go.Indicator(
-            mode="gauge+number+delta",
-            value=sentiment_score,
-            domain={'x': [0, 1], 'y': [0, 1]},
-            title={'text': "Gold Market Sentiment"},
-            delta={'reference': 0},
-            gauge={
-                'axis': {'range': [-1, 1]},
-                'bar': {'color': "#FFD700"},
-                'steps': [
-                    {'range': [-1, -0.5], 'color': "rgba(255,0,0,0.5)"},
-                    {'range': [-0.5, 0.5], 'color': "rgba(255,255,255,0.3)"},
-                    {'range': [0.5, 1], 'color': "rgba(0,255,0,0.5)"}
-                ],
-                'threshold': {
-                    'line': {'color': "white", 'width': 4},
-                    'thickness': 0.75,
-                    'value': 0
-                }
+def analyze_sentiment(ticker):
+    """Analyze gold/crypto market sentiment"""
+    # NOTE: Menggunakan sentiment_analyzer.py lama yang mock, tetapi sekarang berdasarkan ticker
+    sentiment_score, news_summary = sentiment_analyzer.analyze_gold_sentiment() # Fungsi ini masih mock, tidak menerima ticker
+
+    # ... (Logika Gauge Chart, tetap sama)
+    fig = go.Figure(go.Indicator(
+        mode="gauge+number+delta",
+        value=sentiment_score,
+        domain={'x': [0, 1], 'y': [0, 1]},
+        title={'text': f"{ticker} Market Sentiment (Mocked)"},
+        delta={'reference': 0},
+        gauge={
+            'axis': {'range': [-1, 1]},
+            'bar': {'color': "#FFD700"},
+            'steps': [
+                {'range': [-1, -0.5], 'color': "rgba(255,0,0,0.5)"},
+                {'range': [-0.5, 0.5], 'color': "rgba(255,255,255,0.3)"},
+                {'range': [0.5, 1], 'color': "rgba(0,255,0,0.5)"}
+            ],
+            'threshold': {
+                'line': {'color': "white", 'width': 4},
+                'thickness': 0.75,
+                'value': 0
             }
-        ))
-        
-        fig.update_layout(
-            template='plotly_dark',
-            height=300,
-            paper_bgcolor='rgba(0,0,0,0)',
-            plot_bgcolor='rgba(0,0,0,0)',
-            font=dict(color='white')
-        )
-        
-        return fig, news_summary
-        
-    except Exception as e:
-        return str(e), None
+        }
+    ))
+    
+    fig.update_layout(
+        template='plotly_dark',
+        height=300,
+        paper_bgcolor='rgba(0,0,0,0)',
+        plot_bgcolor='rgba(0,0,0,0)',
+        font=dict(color='white')
+    )
+    
+    return fig, news_summary
 
-def get_fundamentals():
+def get_fundamentals(ticker):
     """Get fundamental analysis data"""
     try:
-        fundamentals = data_processor.get_fundamental_data()
+        # Panggil fungsi fundamental data yang sudah diperbarui
+        fundamentals = data_processor.get_fundamental_data(ticker)
         
-        # Create fundamentals table
+        # Buat fundamentals table
         table_data = []
         for key, value in fundamentals.items():
             table_data.append([key, value])
         
         df = pd.DataFrame(table_data, columns=['Metric', 'Value'])
         
+        # Ambil nilai kunci untuk gauge
+        if ticker == "BTC-USD":
+            gauge_title = "Crypto Volatility Index"
+            gauge_value = fundamentals.get(gauge_title, 100)
+            gauge_range = [0, 200]
+        else:
+            gauge_title = "Gold Strength Index"
+            gauge_value = fundamentals.get(gauge_title, 50)
+            gauge_range = [0, 100]
+            
         # Create fundamentals gauge chart
         fig = go.Figure(go.Indicator(
             mode="gauge+number",
-            value=fundamentals.get('Gold Strength Index', 50),
-            title={'text': "Gold Strength Index"},
+            value=gauge_value,
+            title={'text': gauge_title},
             gauge={
-                'axis': {'range': [0, 100]},
+                'axis': {'range': gauge_range},
                 'bar': {'color': "#FFD700"},
                 'steps': [
-                    {'range': [0, 30], 'color': "rgba(255,0,0,0.5)"},
-                    {'range': [30, 70], 'color': "rgba(255,255,255,0.3)"},
-                    {'range': [70, 100], 'color': "rgba(0,255,0,0.5)"}
+                    {'range': [gauge_range[0], gauge_range[1] * 0.3], 'color': "rgba(255,0,0,0.5)"},
+                    {'range': [gauge_range[1] * 0.3, gauge_range[1] * 0.7], 'color': "rgba(255,255,255,0.3)"},
+                    {'range': [gauge_range[1] * 0.7, gauge_range[1]], 'color': "rgba(0,255,0,0.5)"}
                 ]
             }
         ))
@@ -229,7 +200,7 @@ def get_fundamentals():
 # Create Gradio interface
 with gr.Blocks(
     theme=gr.themes.Default(primary_hue="yellow", secondary_hue="yellow"),
-    title="Gold Trading Analysis & Prediction",
+    title="Ultimate Market Analysis & Prediction",
     css="""
         .gradio-container {background-color: #000000; color: #FFFFFF}
         .gr-button-primary {background-color: #FFD700 !important; color: #000000 !important}
@@ -238,34 +209,47 @@ with gr.Blocks(
         .gr-tab button.selected {background-color: #FFD700 !important; color: #000000 !important}
         .gr-highlighted {background-color: #1a1a1a !important}
         .anycoder-link {color: #FFD700 !important; text-decoration: none; font-weight: bold}
+        /* Custom CSS to handle the mplfinance image block (since it returns HTML) */
+        .mpl-chart-container {
+            border: 1px solid #333333; 
+            border-radius: 5px; 
+            overflow: hidden; 
+            background: white; /* Ensure mplfinance chart background is visible */
+        }
     """
 ) as demo:
     
-    # Header with anycoder link
     gr.HTML("""
         <div style="text-align: center; padding: 20px;">
-            <h1 style="color: #FFD700;">Gold Trading Analysis & Prediction</h1>
-            <p>Advanced AI-powered analysis for Gold Futures (GC=F)</p>
+            <h1 style="color: #FFD700;">Ultimate Market Analysis & Prediction (Chronos-2)</h1>
+            <p>AI-powered analysis for Gold Futures (GC=F) and Bitcoin (BTC-USD)</p>
             <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" class="anycoder-link">Built with anycoder</a>
         </div>
     """)
     
     with gr.Row():
+        ticker_dropdown = gr.Dropdown(
+            choices=["GC=F", "BTC-USD"],
+            value="GC=F",
+            label="Market Ticker",
+            info="Select asset for analysis"
+        )
         interval_dropdown = gr.Dropdown(
             choices=[
-                "5m", "15m", "30m", "1h", "4h", "1d", "1wk", "1mo", "3mo"
+                "1d", "1wk", "1mo", "3mo"
             ],
             value="1d",
             label="Time Interval",
             info="Select analysis timeframe"
         )
-        refresh_btn = gr.Button("売 Refresh Data", variant="primary")
+        refresh_btn = gr.Button("売 Refresh Data & Predict", variant="primary")
     
     with gr.Tabs():
         with gr.TabItem("投 Chart Analysis"):
             with gr.Row():
-                chart_plot = gr.Plot(label="Price Chart")
-                pred_plot = gr.Plot(label="Predictions")
+                # Ganti gr.Plot dengan gr.HTML untuk menampilkan chart mplfinance
+                chart_html = gr.HTML(label="Price Chart & Indicators", elem_classes=["mpl-chart-container"])
+                pred_plot = gr.Plot(label="Price Predictions (Next 10 Periods)")
             
             with gr.Row():
                 metrics_output = gr.JSON(label="Trading Metrics")
@@ -277,7 +261,7 @@ with gr.Blocks(
         
         with gr.TabItem("嶋 Fundamentals"):
             with gr.Row():
-                fundamentals_gauge = gr.Plot(label="Strength Index")
+                fundamentals_gauge = gr.Plot(label="Strength Index Gauge")
                 fundamentals_table = gr.Dataframe(
                     headers=["Metric", "Value"],
                     label="Key Fundamentals",
@@ -285,28 +269,30 @@ with gr.Blocks(
                 )
     
     # Event handlers
-    def update_all(interval):
-        chart, metrics, pred = create_chart_analysis(interval)
-        sentiment, news = analyze_sentiment()
-        fund_gauge, fund_table = get_fundamentals()
+    def update_all(ticker, interval):
+        chart, metrics, pred = create_chart_analysis(ticker, interval)
+        sentiment, news = analyze_sentiment(ticker)
+        fund_gauge, fund_table = get_fundamentals(ticker)
         
         return chart, metrics, pred, sentiment, news, fund_gauge, fund_table
     
+    # Tambahkan ticker_dropdown ke inputs
     refresh_btn.click(
         fn=update_all,
-        inputs=interval_dropdown,
+        inputs=[ticker_dropdown, interval_dropdown],
         outputs=[
-            chart_plot, metrics_output, pred_plot,
+            chart_html, metrics_output, pred_plot,
             sentiment_gauge, news_display,
             fundamentals_gauge, fundamentals_table
         ]
     )
     
+    # Tambahkan ticker_dropdown ke inputs
     demo.load(
         fn=update_all,
-        inputs=interval_dropdown,
+        inputs=[ticker_dropdown, interval_dropdown],
         outputs=[
-            chart_plot, metrics_output, pred_plot,
+            chart_html, metrics_output, pred_plot,
             sentiment_gauge, news_display,
             fundamentals_gauge, fundamentals_table
         ]