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| import gradio as gr | |
| import yfinance as yf | |
| import pandas as pd | |
| import numpy as np | |
| import torch | |
| from transformers import AutoModelForSeq2SeqLM, AutoTokenizer | |
| from datetime import datetime, timedelta | |
| import plotly.graph_objects as go | |
| import plotly.express as px | |
| from plotly.subplots import make_subplots | |
| import warnings | |
| warnings.filterwarnings('ignore') | |
| import spaces | |
| # Import utility functions | |
| from utils import ( | |
| get_indonesian_stocks, | |
| calculate_technical_indicators, | |
| generate_trading_signals, | |
| get_fundamental_data, | |
| format_large_number, | |
| predict_prices, | |
| create_price_chart, | |
| create_technical_chart, | |
| create_prediction_chart | |
| ) | |
| from config import IDX_STOCKS, TECHNICAL_INDICATORS, PREDICTION_CONFIG | |
| # Load Chronos-Bolt model | |
| def load_model(): | |
| """Load the Amazon Chronos-Bolt model for time series forecasting""" | |
| model = AutoModelForSeq2SeqLM.from_pretrained( | |
| "amazon/chronos-bolt-base", | |
| torch_dtype=torch.bfloat16, | |
| device_map="auto", | |
| trust_remote_code=True | |
| ) | |
| # CRITICAL FIX: Skip tokenizer loading | |
| tokenizer = None | |
| return model, tokenizer | |
| # Initialize model | |
| model, tokenizer = load_model() | |
| def get_stock_data(symbol, period="1y"): | |
| """Fetch historical stock data using yfinance""" | |
| try: | |
| stock = yf.Ticker(symbol) | |
| data = stock.history(period=period) | |
| if data.empty: | |
| return None, None | |
| return data, stock | |
| except Exception as e: | |
| print(f"Error fetching data for {symbol}: {e}") | |
| return None, None | |
| def analyze_stock(symbol, prediction_days=30): | |
| """Main analysis function""" | |
| # Get stock data | |
| data, stock = get_stock_data(symbol) | |
| if data is None or stock is None: | |
| return None, None, None, None, None, None | |
| # Get fundamental data | |
| fundamental_info = get_fundamental_data(stock) | |
| # Calculate technical indicators | |
| indicators = calculate_technical_indicators(data) | |
| # Generate trading signals | |
| signals = generate_trading_signals(data, indicators) | |
| # Make predictions using Chronos-Bolt | |
| predictions = predict_prices(data, model, tokenizer, prediction_days) | |
| # Create charts | |
| fig_price = create_price_chart(data, indicators) # RENAMED | |
| fig_technical = create_technical_chart(data, indicators) # RENAMED | |
| fig_prediction = create_prediction_chart(data, predictions) # RENAMED | |
| return fundamental_info, indicators, signals, fig_price, fig_technical, fig_prediction # Returning renamed local variables | |
| def create_ui(): | |
| """Create the Gradio interface""" | |
| with gr.Blocks( | |
| title="IDX Stock Analysis & Prediction", | |
| theme=gr.themes.Soft(), | |
| css=""" | |
| .header { | |
| text-align: center; | |
| padding: 20px; | |
| background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); | |
| color: white; | |
| border-radius: 10px; | |
| margin-bottom: 20px; | |
| } | |
| .metric-card { | |
| background: white; | |
| padding: 15px; | |
| border-radius: 8px; | |
| box-shadow: 0 2px 4px rgba(0,0,0,0.1); | |
| margin: 10px 0; | |
| } | |
| .positive { color: #10b981; font-weight: bold; } | |
| .negative { color: #ef4444; font-weight: bold; } | |
| .neutral { color: #6b7280; font-weight: bold; } | |
| """ | |
| ) as demo: | |
| with gr.Row(): | |
| gr.HTML(""" | |
| <div class="header"> | |
| <h1>📈 IDX Stock Analysis & Prediction</h1> | |
| <p>Advanced Technical Analysis & AI-Powered Predictions for Indonesian Stock Exchange</p> | |
| <p><a href="https://huggingface.co/spaces/akhaliq/anycoder" style="color: white;">Built with anycoder</a></p> | |
| </div> | |
| """) | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| stock_selector = gr.Dropdown( | |
| choices=list(IDX_STOCKS.keys()), | |
| value="BBCA.JK", | |
| label="📊 Select Indonesian Stock", | |
| info="Choose from top IDX stocks" | |
| ) | |
| with gr.Row(): | |
| prediction_days = gr.Slider( | |
| minimum=7, | |
| maximum=90, | |
| value=30, | |
| step=7, | |
| label="🔮 Prediction Days" | |
| ) | |
| analyze_btn = gr.Button( | |
| "🚀 Analyze Stock", | |
| variant="primary", | |
| size="lg" | |
| ) | |
| # Results sections | |
| with gr.Tabs() as tabs: | |
| # Tab 1: Stock Overview & Fundamentals | |
| with gr.TabItem("📊 Stock Overview"): | |
| with gr.Row(): | |
| company_name = gr.Textbox(label="Company Name", interactive=False) | |
| current_price = gr.Number(label="Current Price (IDR)", interactive=False) | |
| market_cap = gr.Textbox(label="Market Cap", interactive=False) | |
| with gr.Row(): | |
| pe_ratio = gr.Number(label="P/E Ratio", interactive=False) | |
| dividend_yield = gr.Number(label="Dividend Yield (%)", interactive=False) | |
| volume = gr.Number(label="Volume", interactive=False) | |
| fundamentals_text = gr.Textbox( | |
| label="📋 Company Information", | |
| lines=8, | |
| interactive=False | |
| ) | |
| # Tab 2: Technical Analysis | |
| with gr.TabItem("📈 Technical Analysis"): | |
| price_chart = gr.Plot(label="Price & Technical Indicators") | |
| technical_chart = gr.Plot(label="Technical Indicators Analysis") | |
| with gr.Row(): | |
| rsi_value = gr.Number(label="RSI (14)", interactive=False) | |
| macd_signal = gr.Textbox(label="MACD Signal", interactive=False) | |
| bb_position = gr.Textbox(label="Bollinger Band Position", interactive=False) | |
| # Tab 3: Trading Signals | |
| with gr.TabItem("🎯 Trading Signals"): | |
| with gr.Row(): | |
| overall_signal = gr.Textbox(label="🚦 Overall Signal", interactive=False, scale=2) | |
| signal_strength = gr.Slider( | |
| minimum=0, | |
| maximum=100, | |
| label="Signal Strength", | |
| interactive=False | |
| ) | |
| signals_text = gr.Textbox( | |
| label="📝 Detailed Signals", | |
| lines=10, | |
| interactive=False | |
| ) | |
| with gr.Row(): | |
| support_level = gr.Number(label="Support Level", interactive=False) | |
| resistance_level = gr.Number(label="Resistance Level", interactive=False) | |
| stop_loss = gr.Number(label="Recommended Stop Loss", interactive=False) | |
| # Tab 4: AI Predictions | |
| with gr.TabItem("🤖 AI Predictions"): | |
| prediction_chart = gr.Plot(label="Price Forecast (Chronos-Bolt)") | |
| with gr.Row(): | |
| predicted_high = gr.Number(label="Predicted High (30d)", interactive=False) | |
| predicted_low = gr.Number(label="Predicted Low (30d)", interactive=False) | |
| predicted_change = gr.Number(label="Expected Change (%)", interactive=False) | |
| prediction_summary = gr.Textbox( | |
| label="📊 Prediction Analysis", | |
| lines=5, | |
| interactive=False | |
| ) | |
| # Event handlers | |
| def update_analysis(symbol, pred_days): | |
| fundamental_info, indicators, signals, fig_price, fig_technical, fig_prediction = analyze_stock(symbol, pred_days) # Receives renamed local variables | |
| if fundamental_info is None: | |
| return { | |
| company_name: "Error loading data", | |
| current_price: 0, | |
| market_cap: "N/A", | |
| pe_ratio: 0, | |
| dividend_yield: 0, | |
| volume: 0, | |
| fundamentals_text: "Unable to fetch stock data. Please try another symbol.", | |
| rsi_value: 0, | |
| macd_signal: "N/A", | |
| bb_position: "N/A", | |
| overall_signal: "N/A", | |
| signal_strength: 0, | |
| signals_text: "No signals available", | |
| support_level: 0, | |
| resistance_level: 0, | |
| stop_loss: 0, | |
| predicted_high: 0, | |
| predicted_low: 0, | |
| predicted_change: 0, | |
| prediction_summary: "No predictions available", | |
| price_chart: None, | |
| technical_chart: None, | |
| prediction_chart: None | |
| } | |
| # Format outputs | |
| # CRITICAL FIX: Use the Gradio component objects (left) as keys | |
| # and the Plotly Figure objects (right) as values. | |
| return { | |
| company_name: fundamental_info.get('name', 'N/A'), | |
| current_price: fundamental_info.get('current_price', 0), | |
| market_cap: format_large_number(fundamental_info.get('market_cap', 0)), | |
| pe_ratio: fundamental_info.get('pe_ratio', 0), | |
| dividend_yield: fundamental_info.get('dividend_yield', 0), | |
| volume: fundamental_info.get('volume', 0), | |
| fundamentals_text: fundamental_info.get('info', ''), | |
| rsi_value: indicators.get('rsi', {}).get('current', 0), | |
| macd_signal: indicators.get('macd', {}).get('signal', 'N/A'), | |
| bb_position: indicators.get('bollinger', {}).get('position', 'N/A'), | |
| overall_signal: signals.get('overall', 'HOLD'), | |
| signal_strength: signals.get('strength', 50), | |
| signals_text: signals.get('details', ''), | |
| support_level: signals.get('support', 0), | |
| resistance_level: signals.get('resistance', 0), | |
| stop_loss: signals.get('stop_loss', 0), | |
| predicted_high: indicators.get('predictions', {}).get('high_30d', 0), | |
| predicted_low: indicators.get('predictions', {}).get('low_30d', 0), | |
| predicted_change: indicators.get('predictions', {}).get('change_pct', 0), | |
| prediction_summary: indicators.get('predictions', {}).get('summary', ''), | |
| price_chart: fig_price, | |
| technical_chart: fig_technical, | |
| prediction_chart: fig_prediction | |
| } | |
| analyze_btn.click( | |
| fn=update_analysis, | |
| inputs=[stock_selector, prediction_days], | |
| outputs=[ | |
| company_name, current_price, market_cap, pe_ratio, dividend_yield, volume, fundamentals_text, | |
| rsi_value, macd_signal, bb_position, overall_signal, signal_strength, signals_text, | |
| support_level, resistance_level, stop_loss, predicted_high, predicted_low, predicted_change, | |
| prediction_summary, price_chart, technical_chart, prediction_chart | |
| ] | |
| ) | |
| # Load initial analysis | |
| demo.load( | |
| fn=update_analysis, | |
| inputs=[stock_selector, prediction_days], | |
| outputs=[ | |
| company_name, current_price, market_cap, pe_ratio, dividend_yield, volume, fundamentals_text, | |
| rsi_value, macd_signal, bb_position, overall_signal, signal_strength, signals_text, | |
| support_level, resistance_level, stop_loss, predicted_high, predicted_low, predicted_change, | |
| prediction_summary, price_chart, technical_chart, prediction_chart | |
| ] | |
| ) | |
| return demo | |
| if __name__ == "__main__": | |
| demo = create_ui() | |
| demo.launch() |