update requirements

requirements.txt

@@ -1,43 +1,42 @@
-gradio>=4.0.0
-yfinance>=0.2.18
-pandas>=1.5.0
-numpy>=1.24.0
-plotly>=5.15.0
-scikit-learn>=1.3.0
-transformers>=4.35.0
-torch>=2.0.0
-accelerate>=0.24.0
-safetensors>=0.4.0
-```
-
-This application provides a comprehensive IDX stock prediction system with the following features:
-
-## Key Features:
-
-1. **Stock Selection**: Dropdown with 35+ major Indonesian stocks from various sectors
-2. **Flexible Parameters**: Adjustable historical period and forecast horizon
-3. **Advanced Model**: Uses Google's TimesFM-2.0-500M for time series forecasting
-4. **Interactive Visualizations**: Plotly charts with historical data, forecasts, and confidence intervals
-5. **Volume Analysis**: Option to include trading volume in predictions
-6. **Summary Statistics**: Key metrics and trend indicators
-7. **Stock Information**: Additional details like market cap, 52-week highs/lows
-8. **Examples**: Pre-configured examples for quick testing
-
-## Technical Implementation:
-
-- **Multi-file structure** for better maintainability
-- **Error handling** with fallback prediction methods
-- **Data preprocessing** with scaling and missing value handling
-- **Model loading optimization** with lazy loading
-- **Interactive UI** with tabs and responsive design
-- **Real-time data fetching** from Yahoo Finance
-
-## How to Use:
-
-1. Install dependencies: `pip install -r requirements.txt`
-2. Run the application: `python app.py`
-3. Select a stock from the dropdown
-4. Adjust parameters if needed
-5. Click "Analyze Stock" to generate predictions
-
+gradio>=4.0.0
+yfinance>=0.2.18
+pandas>=1.5.0
+numpy>=1.24.0
+plotly>=5.15.0
+scikit-learn>=1.3.0
+transformers>=4.35.0
+torch>=2.0.0
+accelerate>=0.24.0
+safetensors>=0.4.0
+
+This application provides a comprehensive IDX stock prediction system with the following features:
+
+## Key Features:
+
+1. **Stock Selection**: Dropdown with 35+ major Indonesian stocks from various sectors
+2. **Flexible Parameters**: Adjustable historical period and forecast horizon
+3. **Advanced Model**: Uses Google's TimesFM-2.0-500M for time series forecasting
+4. **Interactive Visualizations**: Plotly charts with historical data, forecasts, and confidence intervals
+5. **Volume Analysis**: Option to include trading volume in predictions
+6. **Summary Statistics**: Key metrics and trend indicators
+7. **Stock Information**: Additional details like market cap, 52-week highs/lows
+8. **Examples**: Pre-configured examples for quick testing
+
+## Technical Implementation:
+
+- **Multi-file structure** for better maintainability
+- **Error handling** with fallback prediction methods
+- **Data preprocessing** with scaling and missing value handling
+- **Model loading optimization** with lazy loading
+- **Interactive UI** with tabs and responsive design
+- **Real-time data fetching** from Yahoo Finance
+
+## How to Use:
+
+1. Install dependencies: `pip install -r requirements.txt`
+2. Run the application: `python app.py`
+3. Select a stock from the dropdown
+4. Adjust parameters if needed
+5. Click "Analyze Stock" to generate predictions
+
 The application will fetch historical data, apply the TimesFM model for forecasting, and display results with interactive charts and detailed statistics.