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

# ------------------- Constants -------------------
KSE_100 = [
    "HBL", "UBL", "MCB", "BAHL", "ABL", 
    "LUCK", "EFERT", "FCCL", "DGKC", "MLCF",
    "OGDC", "PPL", "POL", "PSO", "SNGP",
    "ENGRO", "HUBC", "KAPCO", "NESTLE", "EFOODS",
    "PSX", "TRG", "SYS", "NML", "ILP",
    "ATRL", "NRL", "HASCOL", "SHEL", "BAFL"
]  # Add all KSE-100 tickers

# ------------------- Hugging Face Models -------------------
sentiment_analyzer = pipeline("text-classification", model="ProsusAI/finbert")
news_summarizer = pipeline("summarization", model="facebook/bart-large-cnn")

# ------------------- Technical Analysis -------------------
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))

# ------------------- Data Fetching -------------------
def get_stock_data(ticker):
    try:
        stock = yf.Ticker(f"{ticker}.KA")
        data = stock.history(period="1y")
        if data.empty:
            return None
        data['RSI'] = calculate_rsi(data)
        return data
    except:
        return None

# ------------------- Analysis Engine -------------------
def analyze_ticker(ticker):
    data = get_stock_data(ticker)
    if data is None:
        return None
    
    current_price = data['Close'].iloc[-1]
    rsi = data['RSI'].iloc[-1]
    
    # Simple Recommendation Logic
    if rsi < 30:
        status = "STRONG BUY"
        color = "green"
    elif rsi > 70:
        status = "STRONG SELL"
        color = "red"
    else:
        status = "HOLD"
        color = "orange"
    
    return {
        "ticker": ticker,
        "price": round(current_price, 2),
        "rsi": round(rsi, 2),
        "status": status,
        "color": color
    }

# ------------------- Generate Recommendations -------------------
def get_recommendations():
    recommendations = []
    for ticker in KSE_100:
        analysis = analyze_ticker(ticker)
        if analysis:
            recommendations.append(analysis)
    
    df = pd.DataFrame(recommendations)
    df = df.sort_values(by='rsi')
    return df

# ------------------- Interface Components -------------------
def create_stock_analysis(ticker):
    data = get_stock_data(ticker)
    if data is None:
        return "Data not available", None, None
    
    # Create Plot
    fig = go.Figure(data=[go.Candlestick(
        x=data.index,
        open=data['Open'],
        high=data['High'],
        low=data['Low'],
        close=data['Close']
    )])
    fig.update_layout(title=f"{ticker} Price Chart")
    
    # Analysis
    analysis = analyze_ticker(ticker)
    status_md = f"## {analysis['status']} \n" \
                f"**Price**: {analysis['price']} \n" \
                f"**RSI**: {analysis['rsi']}"
    
    return status_md, fig.to_html(), get_news(ticker)

def get_news(ticker):
    try:
        url = f"https://www.google.com/search?q={ticker}+stock+pakistan&tbm=nws"
        response = requests.get(url)
        soup = BeautifulSoup(response.text, 'html.parser')
        articles = soup.find_all('div', class_='BNeawe vvjwJb AP7Wnd')[:3]
        return "\n\n".join([a.text for a in articles])
    except:
        return "News unavailable"

# ------------------- Gradio Interface -------------------
with gr.Blocks(title="PSX Trading Dashboard", theme=gr.themes.Soft()) as app:
    with gr.Row():
        # Left Sidebar - KSE-100 List
        with gr.Column(scale=1, min_width=200):
            gr.Markdown("## KSE-100 Constituents")
            kse_list = gr.DataFrame(
                value=pd.DataFrame(KSE_100, columns=["Ticker"]),
                interactive=False,
                height=600
            )
        
        # Main Content
        with gr.Column(scale=3):
            gr.Markdown("# PSX Trading Dashboard")
            with gr.Row():
                ticker_input = gr.Textbox(label="Enter Ticker", placeholder="HBL")
                analyze_btn = gr.Button("Analyze")
            
            status_output = gr.Markdown()
            chart_output = gr.HTML()
            news_output = gr.Textbox(label="Latest News", interactive=False)
        
        # Right Sidebar - Recommendations
        with gr.Column(scale=1, min_width=200):
            gr.Markdown("## Live Recommendations")
            recommendations = gr.DataFrame(
                headers=["Ticker", "Price", "RSI", "Status"],
                datatype=["str", "number", "number", "str"],
                interactive=False,
                height=600
            )
    
    # Event Handlers
    analyze_btn.click(
        fn=create_stock_analysis,
        inputs=ticker_input,
        outputs=[status_output, chart_output, news_output]
    )
    
    app.load(
        fn=get_recommendations,
        outputs=recommendations,
        every=300  # Refresh every 5 minutes
    )

# ------------------- Run App -------------------
if __name__ == "__main__":
    app.launch(server_port=7860, share=True)