import gradio as gr
import yfinance as yf
import pandas as pd
import numpy as np
import plotly.graph_objects as go
from transformers import pipeline
from datetime import datetime
import requests
from bs4 import BeautifulSoup
import feedparser

# ------------------- Initialize Models -------------------
sentiment_analyzer = pipeline("text-classification", model="ProsusAI/finbert")
news_summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ur-en")

# ------------------- Technical Analysis Functions -------------------
def calculate_rsi(data, window=14):
    delta = data['Close'].diff()
    gain = (delta.where(delta > 0, 0)).rolling(window=window).mean()
    loss = (-delta.where(delta < 0, 0)).rolling(window=window).mean()
    rs = gain / loss
    return 100 - (100 / (1 + rs))

def calculate_macd(data, slow=26, fast=12, signal=9):
    exp1 = data['Close'].ewm(span=fast, adjust=False).mean()
    exp2 = data['Close'].ewm(span=slow, adjust=False).mean()
    macd = exp1 - exp2
    signal_line = macd.ewm(span=signal, adjust=False).mean()
    return macd, signal_line

# ------------------- Data Fetching & Processing -------------------
def get_psx_data(ticker):
    try:
        stock = yf.Ticker(f"{ticker}.KA")
        data = stock.history(period="1y")
        if data.empty:
            return None, "Invalid ticker or no data available"
            
        # Calculate indicators
        data['RSI'] = calculate_rsi(data)
        data['MACD'], data['Signal'] = calculate_macd(data)
        data['MA50'] = data['Close'].rolling(window=50).mean()
        data['MA200'] = data['Close'].rolling(window=200).mean()
        
        return data, None
    except Exception as e:
        return None, str(e)

# ------------------- News & Sentiment Analysis -------------------
def analyze_psx_news():
    news_items = []
    try:
        feed = feedparser.parse("https://www.dawn.com/feeds/pakistan")
        for entry in feed.entries[:5]:  # Limit to 5 articles
            try:
                # Translate Urdu content to English
                if any(char in entry.title for char in ['\u0600', '\u0800']):  # Detect Urdu characters
                    translated = translator(entry.title)[0]['translation_text']
                    title = f"[URDU] {translated}"
                else:
                    title = entry.title
                
                # Analyze sentiment
                sentiment = sentiment_analyzer(title)[0]
                news_items.append({
                    'title': title,
                    'sentiment': sentiment['label'],
                    'score': sentiment['score'],
                    'link': entry.link
                })
            except:
                continue
    except:
        pass
    return news_items

# ------------------- Gradio Interface -------------------
def analyze_stock(ticker):
    # Get stock data
    data, error = get_psx_data(ticker)
    if error:
        return error, None, None, None

    # Create price chart
    fig = go.Figure()
    fig.add_trace(go.Candlestick(x=data.index,
                open=data['Open'],
                high=data['High'],
                low=data['Low'],
                close=data['Close'],
                name='Price'))
    fig.add_trace(go.Scatter(x=data.index, y=data['MA50'], line=dict(color='orange', width=1), name='MA50'))
    fig.add_trace(go.Scatter(x=data.index, y=data['MA200'], line=dict(color='blue', width=1), name='MA200'))
    fig.update_layout(title=f"{ticker} Technical Analysis", xaxis_rangeslider_visible=False)

    # Generate signals
    latest = data.iloc[-1]
    rsi_signal = "Oversold" if latest['RSI'] < 30 else "Overbought" if latest['RSI'] > 70 else "Neutral"
    macd_signal = "Bullish" if latest['MACD'] > latest['Signal'] else "Bearish"

    # News analysis
    news = analyze_psx_news()
    news_html = "<h3>Market News & Sentiment</h3>"
    for item in news:
        news_html += f"""
        <div style="margin-bottom: 15px; padding: 10px; border: 1px solid #eee; border-radius: 5px;">
            <b>{item['title']}</b><br>
            Sentiment: {item['sentiment']} ({item['score']:.2f})<br>
            <a href="{item['link']}" target="_blank" style="color: #007bff;">Read more</a>
        </div>
        """

    # Generate recommendation
    recommendation = f"""
    <div style="padding: 20px; background: {'#d4edda' if macd_signal == 'Bullish' else '#f8d7da'}; border-radius: 5px;">
        <h4>Recommendation for {ticker}</h4>
        <p>RSI: {latest['RSI']:.2f} ({rsi_signal})</p>
        <p>MACD: {macd_signal}</p>
        <p>50-Day MA: {latest['MA50']:.2f}</p>
        <p>200-Day MA: {latest['MA200']:.2f}</p>
        <h4 style="color: {'green' if macd_signal == 'Bullish' else 'red'};">{'Consider Buying' if macd_signal == 'Bullish' else 'Consider Selling'}</h4>
    </div>
    """

    return recommendation, fig.to_html(), news_html

# ------------------- App Configuration -------------------
iface = gr.Interface(
    fn=analyze_stock,
    inputs=gr.Textbox(label="Enter PSX Ticker (e.g., HBL, LUCK, OGDC)"),
    outputs=[
        gr.HTML(label="Recommendation"),
        gr.HTML(label="Technical Analysis"),
        gr.HTML(label="Market News")
    ],
    title="🚀 PSX Smart Trading Assistant",
    description="Real-time Pakistan Stock Exchange Analysis with AI-powered Insights",
    examples=[["HBL"], ["LUCK"], ["OGDC"]],
    allow_flagging="never",
    theme=gr.themes.Soft()
)

if __name__ == "__main__":
    iface.launch(server_name="0.0.0.0", server_port=7860)