import panel as pn
import pandas as pd
import numpy as np
import hvplot.pandas
import asyncio
from datetime import datetime, timedelta

pn.extension('tabulator', 'plotly', sizing_mode="stretch_width")

# --- Dummy Data Generator ---
def generate_dummy_data(n=100):
    start = datetime.now() - timedelta(minutes=n)
    times = [start + timedelta(minutes=i) for i in range(n)]
    prices = 100 + np.random.randn(n).cumsum()
    return pd.DataFrame({'Time': times, 'Price': prices}).set_index('Time')

def generate_ai_signal(price):
    mod = price % 10
    if mod < 3:
        return 'BUY', 'green'
    elif mod > 7:
        return 'SELL', 'red'
    return 'HOLD', 'orange'

data = generate_dummy_data()
signal, color = generate_ai_signal(data['Price'].iloc[-1])

# --- Widgets ---
symbol_input = pn.widgets.TextInput(name='Stock Symbol', value='AI_STOCK')
interval_slider = pn.widgets.IntSlider(name='Update Interval (s)', start=1, end=10, step=1, value=2)

signal_display = pn.indicators.Number(
    name='AI Signal',
    value=0,
    format=signal,
    font_size='36pt',
    colors=[(999, color)]
)

metrics_table = pn.widgets.Tabulator(pd.DataFrame({
    'Metric': ['Win Rate', 'Profit Factor', 'Sharpe Ratio'],
    'Value': ['62%', '1.85', '1.2']
}), disabled=True, selectable=False)

chart = data.hvplot.line(y='Price', title="📈 Live Stock Price", height=400, line_width=3).opts(yformatter="%.2f")
stream = hvplot.streams.Buffer(data, index=False, length=100)
chart.update(stream)

# --- Layout ---
sidebar = pn.Column(
    "## ⚙️ Controls", symbol_input, interval_slider,
    "## 🤖 AI Signal", signal_display,
    "## 📊 Metrics", metrics_table,
    width=300
)

main_area = pn.Column(chart)

template = pn.template.FastListTemplate(
    site="AI Trader",
    title="📊 AI Trading Dashboard",
    sidebar=[sidebar],
    main=[main_area]
)

# --- Async Update Logic ---
async def updater():
    while True:
        await asyncio.sleep(interval_slider.value)
        new_time = data.index[-1] + timedelta(seconds=10)
        new_price = data['Price'].iloc[-1] + np.random.randn() * 0.5
        new_df = pd.DataFrame([{'Time': new_time, 'Price': new_price}]).set_index('Time')
        stream.send(new_df)
        new_signal, new_color = generate_ai_signal(new_price)
        signal_display.format = new_signal
        signal_display.colors = [(999, new_color)]

template.servable()
pn.state.onload(updater)