src/streamlit_app.py

import streamlit as st
import pandas as pd
import numpy as np
import yfinance as yf
import ta
import time
from sklearn.ensemble import GradientBoostingClassifier

st.set_page_config(page_title="Trading Father Empire", page_icon="👑", layout="wide")
st.markdown("<h1 style='text-align: center; color: #FFD700;'>👑 TRADING FATHER: ALGORITHM BREAKER</h1>", unsafe_html=True)
st.markdown("<h3 style='text-align: center; color: #FFFFFF;'>Global Market Maker Matrix & Live Signal Feed</h3>", unsafe_html=True)

WATCH_LIST = {
    "Bitcoin (Crypto)": "BTC-USD",
    "Ethereum (Crypto)": "ETH-USD",
    "Gold (Commodity)": "GC=F",
    "NVIDIA (Stock)": "NVDA",
    "EUR/USD (Forex)": "EURUSD=X"
}

st.sidebar.header("👑 Trading Father Control Panel")
selected_market = st.sidebar.selectbox("Select Market to Inspect", list(WATCH_LIST.keys()))
ticker = WATCH_LIST[selected_market]

st.subheader(f"📊 Live Market State: {selected_market} ({ticker})")

try:
    df = yf.download(tickers=ticker, period="1d", interval="1m", progress=False)
    if not df.empty:
        current_price = df['Close'].iloc[-1]
        high_price = df['High'].max()
        low_price = df['Low'].min()
        
        col1, col2, col3 = st.columns(3)
        col1.metric(label="Current Live Price", value=f"${current_price:,.4f}")
        col2.metric(label="Today's Highest Point", value=f"${high_price:,.4f}")
        col3.metric(label="Today's Lowest Point", value=f"${low_price:,.4f}")
        
        st.line_chart(df['Close'].tail(30))
        
        df['BB_Width'] = (ta.volatility.BollingerBands(df['Close']).bollinger_hband() - ta.volatility.BollingerBands(df['Close']).bollinger_lband()) / df['Close']
        df['CMF'] = ta.volume.chaikin_money_flow(df['High'], df['Low'], df['Close'], df['Volume'])
        df['ROC'] = ta.momentum.roc(df['Close'], window=5)
        df['Target'] = np.where(df['Close'].shift(-1) > df['Close'], 1, 0)
        df.dropna(inplace=True)
        
        X = df[['BB_Width', 'CMF', 'ROC']]
        y = df['Target']
        
        ai_brain = GradientBoostingClassifier(n_estimators=300, learning_rate=0.05, max_depth=6, random_state=42)
        ai_brain.fit(X[:-1], y[:-1])
        
        prediction = ai_brain.predict(X.tail(1))
        probability = ai_brain.predict_proba(X.tail(1))[prediction] * 100
        
        st.write("---")
        st.subheader("🕵️‍♂️ Trading Father Intelligence Feed (Updated Every 60s)")
        
        if probability >= 95.00:
            if prediction == 1:
                st.success(f"🟢 UP SIGNAL (BUY) DETECTED! Institutional Confidence: {probability:.2f}%")
            else:
                st.error(f"🔴 DOWN SIGNAL (SELL) DETECTED! Institutional Confidence: {probability:.2f}%")
        else:
            st.info(f"⏳ HOLDING - Market Maker Algorithm is in Squeeze Range (AI Confidence: {probability:.2f}%). Waiting for Sniper entry.")
except Exception as e:
    st.error(f"Connecting to market data stream... {e}")

time.sleep(60)
st.rerun()