Update app.py

app.py

@@ -9,6 +9,7 @@ from model_handler import ModelHandler
 from trading_logic import TradingLogic
 import io
 import base64
+import plotly.graph_objects as go
 
 # Global instances
 data_processor = DataProcessor()
@@ -164,62 +165,45 @@ def analyze_sentiment(asset_name):
     """Analyze market sentiment for selected asset"""
     try:
         ticker = asset_map[asset_name]
-        sentiment_score, news_summary = sentiment_analyzer.analyze_sentiment(ticker)
-        
-        # --- Modifikasi untuk tampilan Gauge yang lebih baik ---
-        
-        # Create sentiment gauge using matplotlib
-        fig, ax = plt.subplots(figsize=(6, 4), facecolor='white')
-        fig.patch.set_facecolor('white')
-        
-        # Setup Gauge limits
-        ax.set_xlim(-1.1, 1.1) # Diperluas sedikit untuk label
-        ax.set_ylim(-0.2, 1.1) # Diperluas sedikit ke bawah untuk skor
-        ax.set_aspect('equal')
-        
-        # Draw gauge background segments
-        theta = np.linspace(np.pi, 0, 100)
-        x, y = np.cos(theta), np.sin(theta)
-        
-        # Segments: Red (-1.0 to -0.5), Gray/Yellow (-0.5 to 0.5), Green (0.5 to 1.0)
-        ax.fill_between(x[75:], y[75:], 0, where=x[75:]<=-0.5, color='#F08080', alpha=0.9, linewidth=0) # Red (Bearish)
-        ax.fill_between(x[25:75], y[25:75], 0, color='#D3D3D3', alpha=0.9, linewidth=0) # Gray (Neutral)
-        ax.fill_between(x[:25], y[:25], 0, where=x[:25]>=0.5, color='#90EE90', alpha=0.9, linewidth=0) # Green (Bullish)
-
-        # Draw main arc line
-        ax.plot(x, y, color='#D3D3D3', linewidth=10, solid_capstyle='round', zorder=1)
-        
-        # Draw needle (using a small triangle/arrow)
-        needle_angle = np.pi * (1 - (sentiment_score + 1) / 2) # Angle from pi (180 deg) to 0 (0 deg)
-        needle_x = 0.8 * np.cos(needle_angle)
-        needle_y = 0.8 * np.sin(needle_angle)
-        
-        # Draw a line/needle for the pointer
-        ax.plot([0, needle_x], [0, needle_y], color='black', linewidth=3, zorder=3)
-        ax.plot([0], [0], marker='o', color='black', markersize=6, zorder=4)
-        
-        # Draw score number (similar to the image)
-        score_color = 'red' if sentiment_score < 0 else 'green' if sentiment_score > 0 else 'black'
-        ax.text(0, -0.15, f"{sentiment_score:+.3f}", ha='center', va='center', 
-               fontsize=24, color=score_color, weight='bold', zorder=5)
-        
-        # Add labels for the scale
-        ax.text(-1, 0, "-1", ha='center', va='top', fontsize=10, color='black')
-        ax.text(-0.5, 0.5, "-0.5", ha='center', va='center', fontsize=10, color='black')
-        ax.text(0, 1.05, "0", ha='center', va='bottom', fontsize=10, color='black')
-        ax.text(0.5, 0.5, "0.5", ha='center', va='center', fontsize=10, color='black')
-        ax.text(1, 0, "1", ha='center', va='top', fontsize=10, color='black')
-        
-        # Add Title
-        ax.set_title(f'{ticker} Market Sentiment (Simulated)', color='black', pad=20)
-        
-        # Remove axes
-        ax.axis('off')
+        # FIX: Menggunakan fungsi yang benar dari sentiment_analyzer.py
+        sentiment_score, news_summary = sentiment_analyzer.analyze_market_sentiment(ticker)
+        
+        # --- Implementasi Plotly Gauge (sesuai referensi pengguna) ---
+        
+        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 (Simulated)"},
+            delta={'reference': 0},
+            gauge={
+                'axis': {'range': [-1, 1]},
+                'bar': {'color': "#FFD700"},
+                'steps': [
+                    {'range': [-1, -0.5], 'color': "rgba(255,0,0,0.5)"}, # Merah (Bearish)
+                    {'range': [-0.5, 0.5], 'color': "rgba(100,100,100,0.3)"}, # Abu-abu (Neutral)
+                    {'range': [0.5, 1], 'color': "rgba(0,255,0,0.5)"} # Hijau (Bullish)
+                ],
+                'threshold': {
+                    'line': {'color': "black", 'width': 4},
+                    'thickness': 0.75,
+                    'value': 0
+                }
+            }
+        ))
+        
+        fig.update_layout(
+            template='plotly_white',
+            height=300,
+            paper_bgcolor='white', 
+            plot_bgcolor='white',
+            font=dict(color='black')
+        )
         
         return fig, news_summary
         
     except Exception as e:
-        # Return error plot
+        # Return error plot (menggunakan Matplotlib untuk error fallback)
         fig, ax = plt.subplots(figsize=(6, 4), facecolor='white')
         fig.patch.set_facecolor('white')
         ax.text(0.5, 0.5, f'Sentiment Error: {str(e)}', ha='center', va='center', 
@@ -328,10 +312,8 @@ with gr.Blocks(
         
         with gr.TabItem("Sentiment Analysis"):
             with gr.Row():
-                with gr.Column(scale=1):
-                    sentiment_gauge = gr.Plot(label="Sentiment Score")
-                with gr.Column(scale=1):
-                    news_display = gr.HTML(label="Market News")
+                sentiment_gauge = gr.Plot(label="Sentiment Score")
+                news_display = gr.HTML(label="Market News")
         
         with gr.TabItem("Fundamentals"):
             with gr.Row():