import streamlit as st
import yfinance as yf
import plotly.graph_objects as go
from datetime import datetime, timedelta
import warnings
warnings.filterwarnings('ignore')

# Configure page
st.set_page_config(
    page_title="AI Stock Trading Signals",
    page_icon="📈",
    layout="wide"
)

def get_stock_data(symbol, period="3mo"):
    """Get stock data using yfinance"""
    try:
        ticker = yf.Ticker(symbol)
        data = ticker.history(period=period)
        return data
    except Exception as e:
        st.error(f"Error fetching data: {str(e)}")
        return None

def get_live_price(stock_symbol):
    """Get live stock price"""
    try:
        # Try nsepython first
        try:
            import nsepython as nse
            stock_name = stock_symbol.replace('.NS', '')
            live_data = nse.equity_quote(stock_name)
            if live_data and 'lastPrice' in live_data:
                return float(live_data['lastPrice'])
        except:
            pass
        
        # Fallback to yfinance
        ticker = yf.Ticker(stock_symbol)
        data = ticker.history(period="1d", interval="1m")
        if not data.empty:
            return float(data['Close'].iloc[-1])
        
        return None
    except Exception as e:
        st.warning(f"Could not fetch live price: {str(e)}")
        return None

def create_simple_chart(stock_symbol):
    """Create simple price chart"""
    try:
        data = get_stock_data(stock_symbol, period="1mo")
        if data is None or data.empty:
            return None
        
        # Get last 30 days
        data = data.tail(30)
        
        fig = go.Figure()
        
        # Add candlestick chart
        fig.add_trace(go.Candlestick(
            x=data.index,
            open=data['Open'],
            high=data['High'],
            low=data['Low'],
            close=data['Close'],
            name='Price'
        ))
        
        # Add simple moving averages
        sma_20 = data['Close'].rolling(window=20).mean()
        sma_50 = data['Close'].rolling(window=50).mean()
        
        fig.add_trace(go.Scatter(
            x=data.index, 
            y=sma_20, 
            name='SMA 20',
            line=dict(color='orange', width=2)
        ))
        
        fig.add_trace(go.Scatter(
            x=data.index, 
            y=sma_50, 
            name='SMA 50',
            line=dict(color='blue', width=2)
        ))
        
        fig.update_layout(
            title=f"{stock_symbol} - Price Chart",
            xaxis_rangeslider_visible=False,
            height=600,
            yaxis_title="Price (₹)"
        )
        
        return fig
        
    except Exception as e:
        st.error(f"Error creating chart: {str(e)}")
        return None

def simple_trading_signal(stock_symbol):
    """Generate simple trading signal based on moving averages"""
    try:
        data = get_stock_data(stock_symbol, period="3mo")
        if data is None or data.empty:
            return None, "No data available"
        
        # Calculate simple moving averages
        current_price = data['Close'].iloc[-1]
        sma_20 = data['Close'].rolling(window=20).mean().iloc[-1]
        sma_50 = data['Close'].rolling(window=50).mean().iloc[-1]
        
        # Simple signal logic
        if current_price > sma_20 and sma_20 > sma_50:
            signal = "BUY"
            confidence = 0.75
        elif current_price < sma_20 and sma_20 < sma_50:
            signal = "SELL"
            confidence = 0.75
        else:
            signal = "HOLD"
            confidence = 0.60
        
        return {
            'signal': signal,
            'confidence': confidence,
            'current_price': current_price,
            'sma_20': sma_20,
            'sma_50': sma_50
        }, None
        
    except Exception as e:
        return None, f"Error generating signal: {str(e)}"

def main():
    st.title("📈 Stock Trading Signals App")
    st.markdown("### NSE Stock Analysis (Simplified Version)")
    
    # Sidebar for stock selection
    st.sidebar.header("Stock Selection")
    
    # Stock options
    stock_options = {
        "Reliance Industries": "RELIANCE.NS",
        "Tata Consultancy Services": "TCS.NS",
        "Infosys": "INFY.NS"
    }
    
    selected_stock_name = st.sidebar.selectbox(
        "Choose a stock:",
        list(stock_options.keys())
    )
    
    selected_stock = stock_options[selected_stock_name]
    
    # Main content
    st.header("📊 Live Market Data")
    
    col1, col2 = st.columns(2)
    
    with col1:
        if st.button("🔄 Get Live Price", type="primary"):
            live_price = get_live_price(selected_stock)
            if live_price:
                st.metric("Live Price (LTP)", f"₹{live_price:.2f}")
            else:
                st.warning("Could not fetch live price")
    
    # Trading signal section
    st.header("🎯 Trading Signal")
    
    if st.button("📈 Get Signal", type="primary"):
        signal_result, error = simple_trading_signal(selected_stock)
        
        if signal_result:
            signal = signal_result['signal']
            confidence = signal_result['confidence']
            
            # Display signal with color coding
            if signal == "BUY":
                st.success(f"🟢 **{signal}** Signal")
            elif signal == "SELL":
                st.error(f"🔴 **{signal}** Signal")
            else:
                st.info(f"🟡 **{signal}** Signal")
            
            # Display metrics
            col1, col2, col3 = st.columns(3)
            with col1:
                st.metric("Confidence", f"{confidence:.1%}")
            with col2:
                st.metric("Current Price", f"₹{signal_result['current_price']:.2f}")
            with col3:
                st.metric("SMA 20", f"₹{signal_result['sma_20']:.2f}")
            
        else:
            st.error(f"Signal generation failed: {error}")
    
    # Chart section
    st.header("📈 Price Chart")
    
    if st.button("📊 Show Chart"):
        chart = create_simple_chart(selected_stock)
        if chart:
            st.plotly_chart(chart, use_container_width=True)
    
    # Information section
    st.header("ℹ️ About This App")
    
    col1, col2 = st.columns(2)
    with col1:
        st.info("**Signal Logic:**\n- BUY: Price > SMA20 > SMA50\n- SELL: Price < SMA20 < SMA50\n- HOLD: Mixed signals")
    
    with col2:
        st.info("**Data Source:**\n- Yahoo Finance (yfinance)\n- NSE Python for live prices\n- 3 months historical data")

if __name__ == "__main__":
    main()