import gradio as gr
import pandas as pd
import numpy as np
from data_processor import DataProcessor
from sentiment_analyzer import SentimentAnalyzer
from model_handler import ModelHandler
from trading_logic import TradingLogic
from plotter import create_mplfinance_chart
import plotly.graph_objects as go 

# Global instances
data_processor = DataProcessor()
sentiment_analyzer = SentimentAnalyzer()
model_handler = ModelHandler()
trading_logic = TradingLogic()

def create_chart_analysis(ticker, interval):
    """Create chart with technical indicators and predictions"""
    try:
        df = data_processor.get_market_data(ticker, interval)
        if df.empty:
            return "No data available", None
        
        # Hitung indikator
        df = data_processor.calculate_indicators(df)
        
        # Prepare data for Chronos
        prepared_data = data_processor.prepare_for_chronos(df)

        # Generate predictions (Chronos-2 atau Fallback)
        predictions = model_handler.predict(prepared_data, horizon=10)

        current_price = df['Close'].iloc[-1]
        
        # Buat chart menggunakan MPLFINANCE (dikembalikan sebagai HTML)
        chart_html = create_mplfinance_chart(
            df, 
            ticker=f'{ticker} ({interval})', 
            predictions=predictions
        )

        # Hasilkan sinyal trading
        signal, confidence = trading_logic.generate_signal(
            predictions, current_price, df
        )
        
        # Hitung TP/SL
        tp, sl = trading_logic.calculate_tp_sl(
            current_price, df['ATR'].iloc[-1], signal
        )
        
        # Create metrics display
        metrics = {
            "Ticker": ticker,
            "Current Price": f"${current_price:.2f}",
            "Signal": signal.upper(),
            "Confidence": f"{confidence:.1%}",
            "Take Profit": f"${tp:.2f}" if tp else "N/A",
            "Stop Loss": f"${sl:.2f}" if sl else "N/A",
            "RSI": f"{df['RSI'].iloc[-1]:.1f}",
            "MACD": f"{df['MACD'].iloc[-1]:.4f}",
            "Volume": f"{df['Volume'].iloc[-1]:,.0f}"
        }
        
        return chart_html, metrics
        
    except Exception as e:
        return f"Error creating chart: {str(e)}", None

def analyze_sentiment(ticker):
    """Analyze gold/crypto market sentiment"""
    
    # KOREKSI: Panggil fungsi yang diperbarui dan kirim ticker
    sentiment_score, news_summary = sentiment_analyzer.analyze_market_sentiment(ticker)
    
    # Gunakan template terang untuk Plotly
    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)"},
                {'range': [-0.5, 0.5], 'color': "rgba(100,100,100,0.3)"},
                {'range': [0.5, 1], 'color': "rgba(0,255,0,0.5)"}
            ],
            'threshold': {
                'line': {'color': "black", 'width': 4},
                'thickness': 0.75,
                'value': 0
            }
        }
    ))
    
    fig.update_layout(
        template='plotly_white',
        height=300,
        paper_bgcolor='#f0f4f9', 
        plot_bgcolor='#f0f4f9',
        font=dict(color='black')
    )
    
    return fig, news_summary

def get_fundamentals(ticker):
    """Get fundamental analysis data"""
    try:
        fundamentals = data_processor.get_fundamental_data(ticker)
        
        # Buat fundamentals table
        table_data = []
        for key, value in fundamentals.items():
            table_data.append([key, value])
        
        df = pd.DataFrame(table_data, columns=['Metric', 'Value'])
        
        # Ambil nilai kunci untuk gauge
        if ticker == "BTC-USD":
            gauge_title = "Crypto Volatility Index"
            gauge_value = fundamentals.get(gauge_title, 100)
            gauge_range = [0, 200]
        else:
            gauge_title = "Gold Strength Index"
            gauge_value = fundamentals.get(gauge_title, 50)
            gauge_range = [0, 100]
            
        # Create fundamentals gauge chart
        fig = go.Figure(go.Indicator(
            mode="gauge+number",
            value=gauge_value,
            title={'text': gauge_title},
            gauge={
                'axis': {'range': gauge_range},
                'bar': {'color': "#FFD700"},
                'steps': [
                    {'range': [gauge_range[0], gauge_range[1] * 0.3], 'color': "rgba(255,0,0,0.5)"},
                    {'range': [gauge_range[1] * 0.3, gauge_range[1] * 0.7], 'color': "rgba(100,100,100,0.3)"},
                    {'range': [gauge_range[1] * 0.7, gauge_range[1]], 'color': "rgba(0,255,0,0.5)"}
                ]
            }
        ))
        
        fig.update_layout(
            template='plotly_white',
            height=300,
            paper_bgcolor='#f0f4f9', 
            plot_bgcolor='#f0f4f9',
            font=dict(color='black')
        )
        
        return fig, df
        
    except Exception as e:
        return str(e), None

# Create Gradio interface
with gr.Blocks(
    theme=gr.themes.Default(primary_hue="yellow", secondary_hue="yellow"),
    title="Ultimate Market Analysis & Prediction",
    css="""
        .gradio-container {background-color: #f0f4f9; color: black}
        .gr-button-primary {background-color: #FFD700 !important; color: #000000 !important}
        .gr-button-secondary {border-color: #FFD700 !important; color: #000000 !important}
        .gr-tab button {color: black !important}
        .gr-tab button.selected {background-color: #FFD700 !important; color: #000000 !important}
        .gr-highlighted {background-color: #CCCCCC !important}
        .anycoder-link {color: #FFD700 !important; text-decoration: none; font-weight: bold}
        .mpl-chart-container {
            border: 1px solid #CCCCCC; 
            border-radius: 5px; 
            overflow: hidden; 
            background: white; 
            width: 100%;
        }
        .chart-title {color: black !important;}
        .metric-label {color: black !important;}
    """
) as demo:
    
    gr.HTML("""
        <div style="text-align: center; padding: 20px;">
            <h1 style="color: black;">Ultimate Market Analysis & Prediction (Chronos-2)</h1>
            <p style="color: black;">AI-powered analysis for Gold Futures (GC=F) and Bitcoin (BTC-USD)</p>
            <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" class="anycoder-link">Built with anycoder</a>
        </div>
    """)
    
    with gr.Row():
        ticker_dropdown = gr.Dropdown(
            choices=["GC=F", "BTC-USD"],
            value="GC=F",
            label="Market Ticker",
            info="Select asset for analysis"
        )
        # KOREKSI: Mengembalikan semua opsi interval waktu
        interval_dropdown = 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("売 Refresh Data & Predict", variant="primary")
    
    with gr.Tabs():
        with gr.TabItem("投 Chart Analysis"):
            # Chart MPLFinance lebar penuh
            chart_html = gr.HTML(label="Price Chart & Indicators", elem_classes=["mpl-chart-container"])
            
            with gr.Row():
                metrics_output = gr.JSON(label="Trading Metrics")
        
        with gr.TabItem("堂 Sentiment Analysis"):
            with gr.Row():
                sentiment_gauge = gr.Plot(label="Sentiment Score")
                news_display = gr.HTML(label="Market News")
        
        with gr.TabItem("嶋 Fundamentals"):
            with gr.Row():
                fundamentals_gauge = gr.Plot(label="Strength Index Gauge")
                fundamentals_table = gr.Dataframe(
                    headers=["Metric", "Value"],
                    label="Key Fundamentals",
                    interactive=False
                )
    
    # Event handlers
    def update_all(ticker, interval):
        # FIX: create_chart_analysis sekarang hanya mengembalikan 2 output
        chart, metrics = create_chart_analysis(ticker, interval)
        # FIX: Panggil fungsi yang sudah diperbarui dan kirim ticker
        sentiment_gauge, news_display = analyze_sentiment(ticker) 
        fund_gauge, fund_table = get_fundamentals(ticker)
        
        # Total 5 outputs Gradio components
        return chart, metrics, sentiment_gauge, news_display, fund_gauge, fund_table
    
    refresh_btn.click(
        fn=update_all,
        inputs=[ticker_dropdown, interval_dropdown],
        outputs=[
            chart_html, metrics_output,
            sentiment_gauge, news_display,
            fundamentals_gauge, fundamentals_table
        ]
    )
    
    demo.load(
        fn=update_all,
        inputs=[ticker_dropdown, interval_dropdown],
        outputs=[
            chart_html, metrics_output,
            sentiment_gauge, news_display,
            fundamentals_gauge, fundamentals_table
        ]
    )

if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False,
        show_api=True
    )