Update Gradio app with multiple files

app.py

@@ -2,9 +2,6 @@ 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
@@ -72,7 +69,6 @@ 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):
@@ -203,27 +199,26 @@ 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)
     
-    # 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 = go.Figure(
+        go.Indicator(
+            mode="gauge+number",
+            value=value,
+            title={'text': "Gold Strength Index"},
+            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',
@@ -234,78 +229,90 @@ def create_fundamentals_gauge(fundamentals):
     )
     
     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>")
+# Gradio Interface
+with gr.Blocks(
+    title="Gold Trading Analysis",
+    theme=gr.themes.Default(
+        primary_hue="yellow",
+        secondary_hue="yellow",
+        neutral_hue="black"
+    ),
+    css="""
+        body {background: #000000; color: #FFFFFF}
+        .gradio-container {background: #000000}
+        .gr-button-primary {background: #FFD700 !important; color: #000000 !important}
+        .gr-padded {padding: 20px}
+    """
+) as demo:
+    
+    gr.HTML("""
+        <div style="text-align: center; padding: 20px; background: black;">
+            <h1 style="color: #FFD700; margin: 0;">Gold Trading Analysis & Prediction</h1>
+            <p style="color: white; margin: 10px 0;">AI-powered analysis for Gold Futures (GC=F)</p>
+            <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" 
+               style="color: #FFD700; text-decoration: none; font-weight: bold;">
+                Built with anycoder
+            </a>
+        </div>
+    """)
     
     with gr.Row():
-        interval_selector = gr.Dropdown(
-            ['1h', '4h', '1d'], 
-            label="Data Interval", 
-            value='1d', 
-            interactive=True
+        interval = gr.Dropdown(
+            choices=["5m", "15m", "30m", "1h", "4h", "1d", "1wk", "1mo", "3mo"],
+            value="1d",
+            label="Time Interval",
+            info="Select analysis timeframe"
         )
+        refresh_btn = gr.Button("🔄 Refresh Analysis", variant="primary")
     
-    with gr.Row():
-        chart_output = gr.Plot(label="Candlestick Chart", scale=3)
+    with gr.Tabs():
+        with gr.Tab("📊 Technical Analysis"):
+            with gr.Row():
+                chart = gr.Plot(label="Price Chart")
+                pred_chart = gr.Plot(label="Price Forecast")
+            metrics = gr.JSON(label="Trading Signals")
         
-        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")
+        with gr.Tab("📰 Market Sentiment"):
+            with gr.Row():
+                sentiment_chart = gr.Plot(label="Sentiment Gauge")
+                news_html = gr.HTML(label="Market News")
         
-    news_output = gr.HTML(label="Latest Sentiment News")
-
-    interval_selector.change(
+        with gr.Tab("📈 Fundamentals"):
+            with gr.Row():
+                fundamentals_chart = gr.Plot(label="Strength Index")
+                fundamentals_table = gr.Dataframe(
+                    headers=["Metric", "Value"],
+                    label="Key Fundamentals",
+                    interactive=False
+                )
+    
+    # Event handlers
+    refresh_btn.click(
         fn=update_analysis,
-        inputs=[interval_selector],
+        inputs=interval,
         outputs=[
-            chart_output,
-            metrics_output,
-            pred_output,
-            sentiment_fig_output,
-            news_output,
-            fundamentals_fig_output,
-            fundamentals_df_output
+            chart, metrics, pred_chart,
+            sentiment_chart, news_html,
+            fundamentals_chart, fundamentals_table
         ]
     )
     
-    # Initial load
     demo.load(
         fn=update_analysis,
-        inputs=[interval_selector],
+        inputs=interval,
         outputs=[
-            chart_output,
-            metrics_output,
-            pred_output,
-            sentiment_fig_output,
-            news_output,
-            fundamentals_fig_output,
-            fundamentals_df_output
+            chart, metrics, pred_chart,
+            sentiment_chart, news_html,
+            fundamentals_chart, fundamentals_table
         ]
     )
 
 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()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        show_api=True,
+        ssr_mode=False
+    )

requirements.txt

@@ -1,30 +1,34 @@
-plotly
+pandas
 numpy
+plotly
 gradio
-pandas
+openpyxl
+xlrd
+pyarrow
 kaleido
 requests
 Pillow
-matplotlib
-openpyxl
-xlrd
-python-docx
-PyPDF2
 scikit-learn
-scipy
-joblib
-git+https://github.com/huggingface/transformers
-sentencepiece
 torch
+git+https://github.com/huggingface/transformers
 accelerate
 tokenizers
 datasets
-yfinance
-ta-lib
-seaborn
 scipy
 joblib
+matplotlib
+seaborn
+yfinance
+ta-lib
+streamlit
+fastapi
+uvicorn
+pydantic
+python-dotenv
+jupyter
+ipykernel
 tqdm
-requests
-urllib3
-certifi
+click
+pytest
+black
+flake8