Update app.py

app.py

@@ -2,6 +2,9 @@ import gradio as gr
 import pandas as pd
 import plotly.graph_objects as go
 import numpy as np
+
+# ASUMSI: Komponen-komponen berikut sudah ada dan berfungsi
+# dari file data_processor.py, sentiment_analyzer.py, model_handler.py, dan trading_logic.py
 from data_processor import DataProcessor
 from sentiment_analyzer import SentimentAnalyzer
 from model_handler import ModelHandler
@@ -69,6 +72,7 @@ def update_analysis(interval):
         
     except Exception as e:
         error_msg = f"Error: {str(e)}"
+        # Mengembalikan nilai yang dapat di-update untuk semua 7 output
         return [gr.update(value=error_msg)] * 7
 
 def create_candlestick_chart(df, interval):
@@ -199,8 +203,109 @@ def create_sentiment_gauge(score):
     
     return fig
 
+# --- FUNGSI YANG DIPERBAIKI ---
 def create_fundamentals_gauge(fundamentals):
     """Create fundamentals gauge"""
     value = fundamentals.get('Gold Strength Index', 50)
     
-    fig = go.Figure(go
+    # PERBAIKAN: Melengkapi go.Figure(go.Indicator(...)) dan menutup tanda kurung
+    fig = go.Figure(go.Indicator( 
+        mode="gauge+number",
+        value=value,
+        domain={'x': [0, 1], 'y': [0, 1]},
+        title={'text': "Fundamentals Strength"},
+        gauge={
+            'axis': {'range': [0, 100]},
+            '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)"}
+            ]
+        }
+    ))
+    
+    fig.update_layout(
+        template='plotly_dark',
+        height=300,
+        paper_bgcolor='black',
+        plot_bgcolor='black',
+        font=dict(color='white')
+    )
+    
+    return fig
+# --- AKHIR FUNGSI YANG DIPERBAIKI ---
+
+# --- Gradio UI definition (Tambahan untuk kode lengkap) ---
+
+with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
+    gr.Markdown("<h1><center>📈 Gold Trading Dashboard</center></h1>")
+    
+    with gr.Row():
+        interval_selector = gr.Dropdown(
+            ['1h', '4h', '1d'], 
+            label="Data Interval", 
+            value='1d', 
+            interactive=True
+        )
+    
+    with gr.Row():
+        chart_output = gr.Plot(label="Candlestick Chart", scale=3)
+        
+        with gr.Column(scale=1):
+            metrics_output = gr.Dataframe(
+                headers=["Metric", "Value"],
+                row_count=(8, "fixed"),
+                col_count=(2, "fixed"),
+                label="Key Metrics",
+                interactive=False
+            )
+            
+            fundamentals_fig_output = gr.Plot(label="Fundamentals Gauge")
+            fundamentals_df_output = gr.Dataframe(
+                headers=["Metric", "Value"],
+                label="Fundamental Data",
+                interactive=False,
+                visible=False
+            )
+
+    with gr.Row():
+        pred_output = gr.Plot(label="Price Prediction")
+        sentiment_fig_output = gr.Plot(label="Market Sentiment Gauge")
+        
+    news_output = gr.HTML(label="Latest Sentiment News")
+
+    interval_selector.change(
+        fn=update_analysis,
+        inputs=[interval_selector],
+        outputs=[
+            chart_output,
+            metrics_output,
+            pred_output,
+            sentiment_fig_output,
+            news_output,
+            fundamentals_fig_output,
+            fundamentals_df_output
+        ]
+    )
+    
+    # Initial load
+    demo.load(
+        fn=update_analysis,
+        inputs=[interval_selector],
+        outputs=[
+            chart_output,
+            metrics_output,
+            pred_output,
+            sentiment_fig_output,
+            news_output,
+            fundamentals_fig_output,
+            fundamentals_df_output
+        ]
+    )
+
+if __name__ == "__main__":
+    # Catatan: Anda perlu memastikan file data_processor.py, sentiment_analyzer.py, 
+    # model_handler.py, dan trading_logic.py tersedia di direktori yang sama 
+    # dan memiliki implementasi kelas yang diperlukan.
+    demo.launch()