import yfinance as yf
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import pandas as pd
import gradio as gr
import os

def fetch_data(ticker, period):
    data = yf.download(ticker, period=period)
    return data

def compute_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 compute_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()
    histogram = macd - signal_line
    return macd, signal_line, histogram

def buy_sell_signals(data, rsi, macd, signal_line):
    buy_signals_rsi, sell_signals_rsi = [], []
    buy_signals_macd, sell_signals_macd = [], []
    for i in range(2, len(data)):
        # RSI Buy Signal (RSI < 30)
        if rsi.iloc[i-1] < 30 and rsi.iloc[i] >= 30:
            buy_signals_rsi.append((data.index[i], data['Close'].iloc[i]))
        # RSI Sell Signal (RSI > 70)
        elif rsi.iloc[i-1] > 70 and rsi.iloc[i] <= 70:
            sell_signals_rsi.append((data.index[i], data['Close'].iloc[i]))
        # MACD Buy Signal (MACD crosses above Signal)
        if macd.iloc[i-1] < signal_line.iloc[i-1] and macd.iloc[i] >= signal_line.iloc[i]:
            buy_signals_macd.append((data.index[i], data['Close'].iloc[i]))
        # MACD Sell Signal (MACD crosses below Signal)
        elif macd.iloc[i-1] > signal_line.iloc[i-1] and macd.iloc[i] <= signal_line.iloc[i]:
            sell_signals_macd.append((data.index[i], data['Close'].iloc[i]))
    return buy_signals_rsi, sell_signals_rsi, buy_signals_macd, sell_signals_macd

def plot_data(data, buy_signals_rsi, sell_signals_rsi, buy_signals_macd, sell_signals_macd):
    fig = make_subplots(rows=2, cols=1, shared_xaxes=True)
    
    # Add the candlestick chart
    fig.add_trace(go.Candlestick(x=data.index, open=data['Open'], high=data['High'], low=data['Low'], close=data['Close'], name='Market Data'), row=1, col=1)
    
    # Combine all buy signals into one list and create a custom hover text list
    buy_dates = [date for date, _ in buy_signals_rsi + buy_signals_macd]
    buy_prices = [price for _, price in buy_signals_rsi + buy_signals_macd]
    buy_text = ["RSI Buy" for _ in buy_signals_rsi] + ["MACD Buy" for _ in buy_signals_macd]
    
    fig.add_trace(go.Scatter(x=buy_dates, y=buy_prices, mode='markers', marker_symbol='triangle-up', marker_color='green', name='Buy Signals', text=buy_text, hoverinfo='text'))
    
    # Combine all sell signals into one list and create a custom hover text list
    sell_dates = [date for date, _ in sell_signals_rsi + sell_signals_macd]
    sell_prices = [price for _, price in sell_signals_rsi + sell_signals_macd]
    sell_text = ["RSI Sell" for _ in sell_signals_rsi] + ["MACD Sell" for _ in sell_signals_macd]
    
    fig.add_trace(go.Scatter(x=sell_dates, y=sell_prices, mode='markers', marker_symbol='triangle-down', marker_color='red', name='Sell Signals', text=sell_text, hoverinfo='text'))
    
    fig.update_layout(title='Stock Analysis with RSI and MACD Signals', xaxis_title='Date', yaxis_title='Price')
    
    return fig


def main_interface(ticker, period):
    data = fetch_data(ticker, period)
    rsi = compute_rsi(data)
    macd, signal_line, _ = compute_macd(data)
    buy_signals_rsi, sell_signals_rsi, buy_signals_macd, sell_signals_macd = buy_sell_signals(data, rsi, macd, signal_line)
    plot = plot_data(data, buy_signals_rsi, sell_signals_rsi, buy_signals_macd, sell_signals_macd)
    return plot  # Return the plot directly

# Step 7: Set Up Gradio Interface with corrected type parameter
iface = gr.Interface(fn=main_interface,
                     inputs=[gr.Textbox(label="Asset Ticker"), gr.Textbox(label="Period: (e.g., 1mo, 2mo, 3mo, 1y, 2y, 5y)")],
                     outputs=gr.Plot(),
                     title="Stock Analysis Tool",
                     description="Enter a stock ticker and period to analyze buy/sell signals based on RSI and MACD.")


iface.launch()