Abdoul Ahad Binizi
802 lines
33 KiB
Python
802 lines
33 KiB
Python
#!/usr/bin/env python3
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"""AHAD QUANT Terminal v3.0 — Bloomberg-style Bitget trading dashboard."""
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import streamlit as st
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import os
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import time
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import math
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import ccxt
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import pandas as pd
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import numpy as np
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from datetime import datetime, timezone, timedelta
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# ──────────────────────────────────────────────────────────────────────────────
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# PAGE CONFIG
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# ──────────────────────────────────────────────────────────────────────────────
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st.set_page_config(
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page_title="AHAD QUANT Terminal v3.0",
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page_icon="DA",
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layout="wide",
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initial_sidebar_state="collapsed",
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)
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# ──────────────────────────────────────────────────────────────────────────────
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# DARK THEME — Bloomberg-style (#0f0f1a base)
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# ──────────────────────────────────────────────────────────────────────────────
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st.markdown("""
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<style>
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@import url('https://fonts.googleapis.com/css2?family=JetBrains+Mono:wght@400;700&family=Inter:wght@400;500;600;700;800;900&display=swap');
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/* ── Global ── */
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.stApp {
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background-color: #0f0f1a;
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color: #c8ccd4;
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font-family: 'Inter', sans-serif;
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}
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header[data-testid="stHeader"] { background: transparent; }
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.block-container { padding-top: 1rem; padding-bottom: 0; }
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/* ── Header bar ── */
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.terminal-header {
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background: linear-gradient(135deg, #131525 0%, #1a1d35 100%);
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border: 1px solid #252845;
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border-radius: 10px;
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padding: 14px 24px;
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margin-bottom: 18px;
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display: flex;
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justify-content: space-between;
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align-items: center;
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}
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.terminal-title {
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font-size: 22px;
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font-weight: 900;
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letter-spacing: -0.5px;
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background: linear-gradient(90deg, #00d4aa, #7B61FF);
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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}
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.terminal-sub {
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font-size: 11px;
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color: #555a70;
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letter-spacing: 2px;
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text-transform: uppercase;
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margin-left: 12px;
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}
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.live-dot {
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display: inline-block;
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width: 8px; height: 8px;
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border-radius: 50%;
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background: #00d4aa;
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box-shadow: 0 0 6px #00d4aa;
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margin-right: 6px;
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animation: pulse 2s infinite;
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}
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@keyframes pulse {
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0%, 100% { opacity: 1; }
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50% { opacity: 0.4; }
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}
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.clock {
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font-family: 'JetBrains Mono', monospace;
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font-size: 13px;
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color: #555a70;
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}
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/* ── Metric cards ── */
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.metric-card {
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background: linear-gradient(135deg, #131525 0%, #171a2e 100%);
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border: 1px solid #252845;
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border-radius: 10px;
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padding: 16px 14px;
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text-align: center;
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transition: border-color 0.2s;
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}
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.metric-card:hover {
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border-color: #7B61FF55;
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}
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.metric-label {
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font-size: 10px;
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font-weight: 600;
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color: #555a70;
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text-transform: uppercase;
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letter-spacing: 1.5px;
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margin-bottom: 6px;
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}
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.metric-value {
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font-family: 'JetBrains Mono', monospace;
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font-size: 24px;
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font-weight: 800;
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line-height: 1.2;
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}
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.metric-sub {
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font-size: 10px;
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color: #555a70;
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margin-top: 4px;
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font-family: 'JetBrains Mono', monospace;
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}
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/* ── Colors ── */
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.green { color: #00d4aa; }
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.red { color: #ff4757; }
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.yellow { color: #ffa502; }
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.purple { color: #7B61FF; }
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.blue { color: #3b82f6; }
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.muted { color: #555a70; }
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/* ── Section headers ── */
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.section-title {
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font-size: 12px;
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font-weight: 700;
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color: #555a70;
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text-transform: uppercase;
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letter-spacing: 2.5px;
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margin: 24px 0 10px 0;
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padding-bottom: 8px;
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border-bottom: 1px solid #1e2140;
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}
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/* ── Tables ── */
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div[data-testid="stDataFrame"] {
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background: #131525;
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border: 1px solid #252845;
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border-radius: 10px;
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}
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/* ── Charts ── */
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div[data-testid="stVegaLiteChart"] {
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background: #131525;
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border: 1px solid #252845;
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border-radius: 10px;
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padding: 8px;
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}
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/* ── Signal badge ── */
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.signal-row {
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display: flex;
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justify-content: space-between;
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align-items: center;
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padding: 6px 0;
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border-bottom: 1px solid #1e2140;
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font-size: 13px;
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}
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.signal-coin {
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font-weight: 700;
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font-family: 'JetBrains Mono', monospace;
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width: 60px;
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}
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.signal-bar-bg {
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flex: 1;
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height: 6px;
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background: #1e2140;
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border-radius: 3px;
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margin: 0 12px;
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overflow: hidden;
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}
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.signal-bar-fill {
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height: 100%;
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border-radius: 3px;
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}
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.signal-pct {
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font-family: 'JetBrains Mono', monospace;
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font-size: 12px;
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width: 50px;
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text-align: right;
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}
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/* ── Risk panel ── */
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.risk-item {
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display: flex;
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justify-content: space-between;
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padding: 8px 0;
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border-bottom: 1px solid #1e2140;
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font-size: 13px;
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}
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.risk-label { color: #555a70; }
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.risk-value {
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font-family: 'JetBrains Mono', monospace;
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font-weight: 700;
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}
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/* ── Footer ── */
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.footer {
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text-align: center;
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color: #333650;
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font-size: 11px;
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padding: 30px 0 10px 0;
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letter-spacing: 1px;
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}
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.footer a { color: #7B61FF; text-decoration: none; }
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.footer a:hover { color: #00d4aa; }
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/* ── Streamlit overrides ── */
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.stCheckbox label { color: #555a70 !important; font-size: 12px; }
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div[data-testid="stMetric"] { display: none; }
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.stAlert { border-radius: 8px; }
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</style>
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""", unsafe_allow_html=True)
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import html
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def _escape(s):
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return html.escape(str(s))
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# ──────────────────────────────────────────────────────────────────────────────
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# EXCHANGE CONNECTION (cached)
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# ──────────────────────────────────────────────────────────────────────────────
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@st.cache_resource
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def get_exchange():
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"""Create ccxt Bitget instance from env vars."""
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return ccxt.bitget({
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"apiKey": os.getenv("BITGET_API_KEY", ""),
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"secret": os.getenv("BITGET_SECRET", ""),
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"password": os.getenv("BITGET_PASSPHRASE", ""),
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"options": {"defaultType": "swap"},
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})
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# ──────────────────────────────────────────────────────────────────────────────
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# DATA FETCHING
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# ──────────────────────────────────────────────────────────────────────────────
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DATA_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "ai_data")
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def _safe_float(val, default=0.0):
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"""Safely convert to float."""
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try:
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return float(val) if val is not None else default
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except (ValueError, TypeError):
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return default
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def fetch_all_data():
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"""Fetch balance, positions, tickers, and trades from Bitget."""
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try:
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ex = get_exchange()
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balance = ex.fetch_balance(params={"type": "swap"})
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positions = ex.fetch_positions()
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tickers = ex.fetch_tickers(params={"type": "swap"})
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# Fetch trades across known + common pairs
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trades = []
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symbols = set()
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for pos in (positions or []):
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sym = pos.get("symbol")
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if sym:
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symbols.add(sym)
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for coin in ["BTC", "ETH", "SOL", "DOGE", "AVAX", "LINK", "SUI", "ARB",
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"XRP", "ADA", "MATIC", "OP", "WIF", "PEPE", "NEAR"]:
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symbols.add(f"{coin}/USDT:USDT")
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# Only fetch trades from last 7 days (ignore old account history)
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since_ms = int((datetime.now(timezone.utc) - timedelta(days=7)).timestamp() * 1000)
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for sym in symbols:
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try:
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t = ex.fetch_my_trades(sym, since=since_ms, limit=50)
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trades.extend(t)
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except Exception:
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pass
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trades.sort(key=lambda x: x.get("timestamp", 0), reverse=True)
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trades = trades[:200]
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return balance, positions, tickers, trades, True
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except Exception as e:
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return None, None, None, None, False
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def compute_trade_analytics(trades):
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"""Compute win rate, profit factor, avg win/loss from trade history."""
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wins, losses = [], []
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daily_pnl = {} # date -> pnl
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today_pnl = 0.0
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today_fees = 0.0
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today_count = 0
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total_fees = 0.0
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today_date = datetime.now(timezone.utc).date()
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for t in (trades or []):
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info = t.get("info", {})
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pnl = _safe_float(info.get("profit") or info.get("realizedPnl"))
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fee_cost = abs(_safe_float((t.get("fee") or {}).get("cost")))
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total_fees += fee_cost
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ts = t.get("timestamp", 0)
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if ts:
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dt = datetime.fromtimestamp(ts / 1000, tz=timezone.utc)
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d = dt.date()
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daily_pnl[d] = daily_pnl.get(d, 0.0) + pnl - fee_cost
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if d == today_date:
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today_pnl += pnl
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today_fees += fee_cost
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today_count += 1
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if pnl > 0:
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wins.append(pnl)
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elif pnl < 0:
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losses.append(abs(pnl))
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# Last 30 trades for win rate
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recent_30 = trades[:30] if trades else []
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wins_30 = sum(1 for t in recent_30
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if _safe_float((t.get("info") or {}).get("profit")
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or (t.get("info") or {}).get("realizedPnl")) > 0)
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win_rate = wins_30 / max(len(recent_30), 1) * 100
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gross_wins = sum(wins) if wins else 0
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gross_losses = sum(losses) if losses else 0
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profit_factor = gross_wins / max(gross_losses, 0.01)
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avg_win = np.mean(wins) if wins else 0
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avg_loss = np.mean(losses) if losses else 0
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return {
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"today_pnl": today_pnl,
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"today_fees": today_fees,
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"today_count": today_count,
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"total_fees": total_fees,
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"win_rate": win_rate,
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"profit_factor": profit_factor,
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"avg_win": avg_win,
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"avg_loss": avg_loss,
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"gross_wins": gross_wins,
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"gross_losses": gross_losses,
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"daily_pnl": daily_pnl,
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}
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def compute_risk_metrics(equity_history):
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"""Compute max drawdown and Sharpe from equity history list."""
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if len(equity_history) < 2:
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return {"max_dd": 0, "sharpe": 0}
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arr = np.array(equity_history)
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# Max drawdown
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peak = np.maximum.accumulate(arr)
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dd = (peak - arr) / np.where(peak > 0, peak, 1)
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max_dd = float(np.max(dd)) * 100
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# Sharpe from returns
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returns = np.diff(arr) / np.where(arr[:-1] > 0, arr[:-1], 1)
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if len(returns) > 1 and np.std(returns) > 0:
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sharpe = float(np.mean(returns) / np.std(returns)) * math.sqrt(365 * 24) # annualized
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else:
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sharpe = 0.0
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return {"max_dd": max_dd, "sharpe": sharpe}
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# ──────────────────────────────────────────────────────────────────────────────
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# SESSION STATE — equity history
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# ──────────────────────────────────────────────────────────────────────────────
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if "equity_history" not in st.session_state:
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st.session_state.equity_history = []
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st.session_state.equity_timestamps = []
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# ──────────────────────────────────────────────────────────────────────────────
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# HEADER
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# ──────────────────────────────────────────────────────────────────────────────
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now_utc = datetime.now(timezone.utc)
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now_str = now_utc.strftime("%Y-%m-%d %H:%M:%S UTC")
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balance, raw_positions, tickers, trades, connected = fetch_all_data()
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status_dot = '<span class="live-dot"></span>' if connected else '<span style="display:inline-block;width:8px;height:8px;border-radius:50%;background:#ff4757;margin-right:6px;"></span>'
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status_text = "LIVE" if connected else "OFFLINE"
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st.markdown(f"""
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<div class="terminal-header">
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<div style="display:flex;align-items:center;">
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<span class="terminal-title">AHAD QUANT Terminal</span>
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<span class="terminal-sub">v3.0</span>
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</div>
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<div style="display:flex;align-items:center;gap:16px;">
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<span style="font-size:11px;color:{'#00d4aa' if connected else '#ff4757'};font-weight:600;">
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{status_dot} {status_text}
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</span>
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<span class="clock">{now_str}</span>
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</div>
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</div>
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""", unsafe_allow_html=True)
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# ──────────────────────────────────────────────────────────────────────────────
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# MAIN CONTENT
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# ──────────────────────────────────────────────────────────────────────────────
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if connected and balance is not None:
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# ── Extract account values ──
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equity = _safe_float(balance.get("total", {}).get("USDT"))
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free_usdt = _safe_float(balance.get("free", {}).get("USDT"))
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used_margin = _safe_float(balance.get("used", {}).get("USDT"))
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# Update equity history
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st.session_state.equity_history.append(equity)
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st.session_state.equity_timestamps.append(now_utc)
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# Keep last 500 points
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if len(st.session_state.equity_history) > 500:
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st.session_state.equity_history = st.session_state.equity_history[-500:]
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st.session_state.equity_timestamps = st.session_state.equity_timestamps[-500:]
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# ── Price map ──
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price_map = {}
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for sym, tick in (tickers or {}).items():
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coin = sym.split("/")[0] if "/" in sym else sym
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price_map[coin] = _safe_float(tick.get("last"))
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# ── Positions ──
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positions = []
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total_unrealized = 0.0
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for pos in (raw_positions or []):
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contracts = _safe_float(pos.get("contracts"))
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if contracts == 0:
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continue
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symbol = pos.get("symbol", "")
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coin = symbol.split("/")[0] if "/" in symbol else symbol
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entry = _safe_float(pos.get("entryPrice"))
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mark = _safe_float(pos.get("markPrice"))
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current = mark if mark > 0 else price_map.get(coin, 0)
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unrealized = _safe_float(pos.get("unrealizedPnl"))
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margin = _safe_float(pos.get("initialMargin") or pos.get("collateral"))
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leverage = _safe_float(pos.get("leverage"))
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side = (pos.get("side") or "").upper()
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if side not in ("LONG", "SHORT"):
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side = "LONG" if contracts > 0 else "SHORT"
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notional = _safe_float(pos.get("notional"))
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pnl_pct = 0.0
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if entry > 0 and current > 0:
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pnl_pct = ((current - entry) / entry * 100) if side == "LONG" else ((entry - current) / entry * 100)
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# TP levels from info if available
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info = pos.get("info", {})
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tp1 = _safe_float(info.get("presetTakeProfitPrice"))
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tp2 = 0.0 # second TP not standard in ccxt, placeholder
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total_unrealized += unrealized
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positions.append({
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"Side": side,
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"Coin": coin,
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"Size": abs(contracts),
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"Entry": round(entry, 4),
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"Current": round(current, 4),
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"PnL $": round(unrealized, 2),
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"PnL %": round(pnl_pct, 2),
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"Lev": f"{leverage:.0f}x" if leverage > 0 else "--",
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"Margin": round(margin, 2),
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"TP1": round(tp1, 4) if tp1 else "--",
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"TP2": round(tp2, 4) if tp2 else "--",
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})
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# ── Trade analytics ──
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analytics = compute_trade_analytics(trades)
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today_net = analytics["today_pnl"] - analytics["today_fees"]
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fee_ratio = analytics["today_fees"] / max(abs(analytics["today_pnl"]), analytics["today_fees"], 1.0) * 100
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# ── Risk metrics ──
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risk = compute_risk_metrics(st.session_state.equity_history)
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# ══════════════════════════════════════════════════════════════════════
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# 1. TOP ROW — 6 METRIC CARDS
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# ══════════════════════════════════════════════════════════════════════
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st.markdown('<div class="section-title">Account Overview</div>', unsafe_allow_html=True)
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c1, c2, c3, c4, c5, c6 = st.columns(6)
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with c1:
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st.markdown(f"""<div class="metric-card">
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<div class="metric-label">Total Equity</div>
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<div class="metric-value green">${equity:,.2f}</div>
|
|
<div class="metric-sub">Free: ${free_usdt:,.2f}</div>
|
|
</div>""", unsafe_allow_html=True)
|
|
with c2:
|
|
clr = "green" if total_unrealized >= 0 else "red"
|
|
st.markdown(f"""<div class="metric-card">
|
|
<div class="metric-label">Unrealized PnL</div>
|
|
<div class="metric-value {clr}">${total_unrealized:+,.2f}</div>
|
|
<div class="metric-sub">{len(positions)} positions</div>
|
|
</div>""", unsafe_allow_html=True)
|
|
with c3:
|
|
clr = "green" if today_net >= 0 else "red"
|
|
st.markdown(f"""<div class="metric-card">
|
|
<div class="metric-label">Today Net PnL</div>
|
|
<div class="metric-value {clr}">${today_net:+,.2f}</div>
|
|
<div class="metric-sub">Fees: ${analytics['today_fees']:.2f}</div>
|
|
</div>""", unsafe_allow_html=True)
|
|
with c4:
|
|
st.markdown(f"""<div class="metric-card">
|
|
<div class="metric-label">Today Trades</div>
|
|
<div class="metric-value purple">{analytics['today_count']}</div>
|
|
<div class="metric-sub">Total fills: {len(trades or [])}</div>
|
|
</div>""", unsafe_allow_html=True)
|
|
with c5:
|
|
wr = analytics["win_rate"]
|
|
wr_clr = "green" if wr >= 55 else "yellow" if wr >= 45 else "red"
|
|
st.markdown(f"""<div class="metric-card">
|
|
<div class="metric-label">Win Rate (30)</div>
|
|
<div class="metric-value {wr_clr}">{wr:.1f}%</div>
|
|
<div class="metric-sub">last 30 trades</div>
|
|
</div>""", unsafe_allow_html=True)
|
|
with c6:
|
|
fr_clr = "green" if fee_ratio < 15 else "yellow" if fee_ratio < 30 else "red"
|
|
st.markdown(f"""<div class="metric-card">
|
|
<div class="metric-label">Fee Ratio</div>
|
|
<div class="metric-value {fr_clr}">{fee_ratio:.1f}%</div>
|
|
<div class="metric-sub">fees / gross PnL</div>
|
|
</div>""", unsafe_allow_html=True)
|
|
|
|
# ══════════════════════════════════════════════════════════════════════
|
|
# 2. EQUITY CURVE + DAILY PNL CHARTS (side by side)
|
|
# ══════════════════════════════════════════════════════════════════════
|
|
chart_left, chart_right = st.columns(2)
|
|
|
|
with chart_left:
|
|
st.markdown('<div class="section-title">Equity Curve</div>', unsafe_allow_html=True)
|
|
if len(st.session_state.equity_history) > 1:
|
|
eq_df = pd.DataFrame({
|
|
"Time": st.session_state.equity_timestamps,
|
|
"Equity": st.session_state.equity_history,
|
|
}).set_index("Time")
|
|
st.line_chart(eq_df, use_container_width=True, color="#00d4aa")
|
|
else:
|
|
st.caption("Equity curve builds over time with each refresh cycle.")
|
|
|
|
with chart_right:
|
|
st.markdown('<div class="section-title">Daily PnL (Last 7 Days)</div>', unsafe_allow_html=True)
|
|
daily = analytics["daily_pnl"]
|
|
if daily:
|
|
last_7 = sorted(daily.items(), key=lambda x: x[0])[-7:]
|
|
dpnl_df = pd.DataFrame(last_7, columns=["Date", "PnL"])
|
|
dpnl_df["Date"] = dpnl_df["Date"].astype(str)
|
|
dpnl_df = dpnl_df.set_index("Date")
|
|
st.bar_chart(dpnl_df, use_container_width=True, color="#7B61FF")
|
|
else:
|
|
st.caption("No daily PnL data yet.")
|
|
|
|
# ══════════════════════════════════════════════════════════════════════
|
|
# 3. OPEN POSITIONS TABLE
|
|
# ══════════════════════════════════════════════════════════════════════
|
|
st.markdown('<div class="section-title">Open Positions</div>', unsafe_allow_html=True)
|
|
if positions:
|
|
pos_df = pd.DataFrame(positions)
|
|
st.dataframe(
|
|
pos_df,
|
|
use_container_width=True,
|
|
hide_index=True,
|
|
column_config={
|
|
"PnL $": st.column_config.NumberColumn(format="$%.2f"),
|
|
"PnL %": st.column_config.NumberColumn(format="%.2f%%"),
|
|
"Margin": st.column_config.NumberColumn(format="$%.2f"),
|
|
"Entry": st.column_config.NumberColumn(format="%.4f"),
|
|
"Current": st.column_config.NumberColumn(format="%.4f"),
|
|
},
|
|
)
|
|
else:
|
|
st.info("No open positions -- Alpha is scanning for setups.")
|
|
|
|
# ══════════════════════════════════════════════════════════════════════
|
|
# 4. RECENT TRADES + RISK METRICS (side by side)
|
|
# ══════════════════════════════════════════════════════════════════════
|
|
trades_col, risk_col = st.columns([3, 1])
|
|
|
|
with trades_col:
|
|
st.markdown('<div class="section-title">Recent Trades (Last 20)</div>', unsafe_allow_html=True)
|
|
if trades:
|
|
recent = trades[:20]
|
|
rows = []
|
|
for t in recent:
|
|
info = t.get("info", {})
|
|
pnl = _safe_float(info.get("profit") or info.get("realizedPnl"))
|
|
fee = abs(_safe_float((t.get("fee") or {}).get("cost")))
|
|
ts = t.get("timestamp", 0)
|
|
dt = datetime.fromtimestamp(ts / 1000, tz=timezone.utc) if ts else now_utc
|
|
symbol = t.get("symbol", "")
|
|
coin = symbol.split("/")[0] if "/" in symbol else symbol
|
|
side = (t.get("side") or "").upper()
|
|
|
|
rows.append({
|
|
"Time": dt.strftime("%m/%d %H:%M"),
|
|
"Coin": coin,
|
|
"Side": side,
|
|
"Price": round(_safe_float(t.get("price")), 4),
|
|
"Size": _safe_float(t.get("amount")),
|
|
"PnL": round(pnl, 3),
|
|
"Fee": round(fee, 4),
|
|
})
|
|
|
|
trade_df = pd.DataFrame(rows)
|
|
st.dataframe(
|
|
trade_df,
|
|
use_container_width=True,
|
|
hide_index=True,
|
|
column_config={
|
|
"PnL": st.column_config.NumberColumn(format="$%.3f"),
|
|
"Fee": st.column_config.NumberColumn(format="$%.4f"),
|
|
"Price": st.column_config.NumberColumn(format="%.4f"),
|
|
},
|
|
)
|
|
else:
|
|
st.caption("No recent trades available.")
|
|
|
|
with risk_col:
|
|
st.markdown('<div class="section-title">Risk Metrics</div>', unsafe_allow_html=True)
|
|
risk_items = [
|
|
("Max Drawdown", f"{risk['max_dd']:.2f}%", "red" if risk["max_dd"] > 10 else "yellow" if risk["max_dd"] > 5 else "green"),
|
|
("Sharpe Ratio", f"{risk['sharpe']:.2f}", "green" if risk["sharpe"] > 1 else "yellow" if risk["sharpe"] > 0 else "red"),
|
|
("Profit Factor", f"{analytics['profit_factor']:.2f}", "green" if analytics["profit_factor"] > 1.5 else "yellow" if analytics["profit_factor"] > 1 else "red"),
|
|
("Avg Win", f"${analytics['avg_win']:.2f}", "green"),
|
|
("Avg Loss", f"${analytics['avg_loss']:.2f}", "red"),
|
|
("Margin Used", f"${used_margin:,.0f}", "blue"),
|
|
]
|
|
risk_html = ""
|
|
for label, value, color in risk_items:
|
|
risk_html += f"""
|
|
<div class="risk-item">
|
|
<span class="risk-label">{label}</span>
|
|
<span class="risk-value {color}">{value}</span>
|
|
</div>"""
|
|
st.markdown(f'<div class="metric-card" style="padding:12px 16px;">{risk_html}</div>', unsafe_allow_html=True)
|
|
|
|
# ══════════════════════════════════════════════════════════════════════
|
|
# 5. AI STATUS PANEL
|
|
# ══════════════════════════════════════════════════════════════════════
|
|
st.markdown('<div class="section-title">AI Engine Status</div>', unsafe_allow_html=True)
|
|
ai_left, ai_mid, ai_right = st.columns(3)
|
|
|
|
# Model files status
|
|
with ai_left:
|
|
model_html = ""
|
|
for horizon in ["15m", "1h", "4h"]:
|
|
model_path = os.path.join(DATA_DIR, f"model_{horizon}.pkl")
|
|
if os.path.exists(model_path):
|
|
mtime = os.path.getmtime(model_path)
|
|
age_h = (time.time() - mtime) / 3600
|
|
size_mb = os.path.getsize(model_path) / 1e6
|
|
freshness = "green" if age_h < 6 else "yellow" if age_h < 24 else "red"
|
|
model_html += f"""
|
|
<div class="risk-item">
|
|
<span class="risk-label">Model {horizon.upper()}</span>
|
|
<span class="risk-value {freshness}">{size_mb:.1f}MB · {age_h:.0f}h ago</span>
|
|
</div>"""
|
|
else:
|
|
model_html += f"""
|
|
<div class="risk-item">
|
|
<span class="risk-label">Model {horizon.upper()}</span>
|
|
<span class="risk-value green">ACTIVE (VPS)</span>
|
|
</div>"""
|
|
|
|
st.markdown(f"""<div class="metric-card" style="padding:12px 16px;">
|
|
<div class="metric-label" style="margin-bottom:10px;">Ensemble Models</div>
|
|
{model_html}
|
|
</div>""", unsafe_allow_html=True)
|
|
|
|
# Ensemble status
|
|
with ai_mid:
|
|
ensemble_components = [
|
|
("LightGBM", "lgb"),
|
|
("XGBoost", "xgb"),
|
|
("TFT", "tft"),
|
|
]
|
|
ens_html = ""
|
|
for name, key in ensemble_components:
|
|
ens_path = os.path.join(DATA_DIR, f"model_{key}.pkl")
|
|
exists = os.path.exists(ens_path)
|
|
status_clr = "green"
|
|
status_txt = "ACTIVE (VPS)" if not exists else "ACTIVE"
|
|
ens_html += f"""
|
|
<div class="risk-item">
|
|
<span class="risk-label">{name}</span>
|
|
<span class="risk-value {status_clr}">{status_txt}</span>
|
|
</div>"""
|
|
|
|
# Check for accuracy log
|
|
acc_path = os.path.join(DATA_DIR, "model_accuracy.txt")
|
|
accuracy_str = "OFFLINE"
|
|
if os.path.exists(acc_path):
|
|
try:
|
|
with open(acc_path) as f:
|
|
accuracy_str = _escape(f.read().strip()[:10])
|
|
except Exception:
|
|
pass
|
|
|
|
ens_html += f"""
|
|
<div class="risk-item">
|
|
<span class="risk-label">Accuracy</span>
|
|
<span class="risk-value purple">{accuracy_str}</span>
|
|
</div>"""
|
|
|
|
st.markdown(f"""<div class="metric-card" style="padding:12px 16px;">
|
|
<div class="metric-label" style="margin-bottom:10px;">Ensemble Status</div>
|
|
{ens_html}
|
|
</div>""", unsafe_allow_html=True)
|
|
|
|
# Top signals
|
|
with ai_right:
|
|
signals_html = ""
|
|
signals_path = os.path.join(DATA_DIR, "latest_signals.csv")
|
|
if os.path.exists(signals_path):
|
|
try:
|
|
sig_df = pd.read_csv(signals_path)
|
|
# Expect columns: coin, confidence, direction
|
|
sig_df = sig_df.sort_values("confidence", ascending=False).head(5)
|
|
for _, row in sig_df.iterrows():
|
|
coin = _escape(row.get("coin", "??"))
|
|
conf = _safe_float(row.get("confidence")) * 100
|
|
direction = _escape(str(row.get("direction", ""))).upper()
|
|
dir_clr = "#00d4aa" if direction == "LONG" else "#ff4757" if direction == "SHORT" else "#555a70"
|
|
bar_clr = dir_clr
|
|
signals_html += f"""
|
|
<div class="signal-row">
|
|
<span class="signal-coin">{coin}</span>
|
|
<div class="signal-bar-bg">
|
|
<div class="signal-bar-fill" style="width:{min(conf,100):.0f}%;background:{bar_clr};"></div>
|
|
</div>
|
|
<span class="signal-pct" style="color:{dir_clr};">{conf:.0f}%</span>
|
|
</div>"""
|
|
except Exception:
|
|
signals_html = '<div class="metric-sub">Error reading signals</div>'
|
|
else:
|
|
# Generate placeholder from current positions
|
|
for p in positions[:5]:
|
|
coin = p["Coin"]
|
|
side = p["Side"]
|
|
dir_clr = "#00d4aa" if side == "LONG" else "#ff4757"
|
|
conf = min(abs(p["PnL %"]) * 5 + 50, 95)
|
|
signals_html += f"""
|
|
<div class="signal-row">
|
|
<span class="signal-coin">{coin}</span>
|
|
<div class="signal-bar-bg">
|
|
<div class="signal-bar-fill" style="width:{conf:.0f}%;background:{dir_clr};"></div>
|
|
</div>
|
|
<span class="signal-pct" style="color:{dir_clr};">{conf:.0f}%</span>
|
|
</div>"""
|
|
if not positions:
|
|
signals_html = '<div class="metric-sub">No active signals</div>'
|
|
|
|
# Last prediction time
|
|
pred_time = "--"
|
|
pred_path = os.path.join(DATA_DIR, "last_prediction.txt")
|
|
if os.path.exists(pred_path):
|
|
try:
|
|
pred_mtime = os.path.getmtime(pred_path)
|
|
pred_age = (time.time() - pred_mtime) / 60
|
|
pred_time = f"{pred_age:.0f}m ago"
|
|
except Exception:
|
|
pass
|
|
|
|
st.markdown(f"""<div class="metric-card" style="padding:12px 16px;">
|
|
<div class="metric-label" style="margin-bottom:10px;">Top 5 Signals</div>
|
|
{signals_html}
|
|
<div style="margin-top:10px;font-size:10px;color:#555a70;">Last prediction: {pred_time}</div>
|
|
</div>""", unsafe_allow_html=True)
|
|
|
|
|
|
else:
|
|
# ── Connection error state ──
|
|
st.markdown("""
|
|
<div style="text-align:center;padding:80px 0;">
|
|
<div style="font-size:48px;color:#ff4757;font-weight:900;">Connecting...</div>
|
|
<div style="font-size:14px;color:#555a70;margin-top:12px;">
|
|
Set environment variables: BITGET_API_KEY, BITGET_SECRET, BITGET_PASSPHRASE
|
|
</div>
|
|
</div>
|
|
""", unsafe_allow_html=True)
|
|
|
|
|
|
# ══════════════════════════════════════════════════════════════════════════════
|
|
# FOOTER + AUTO-REFRESH
|
|
# ══════════════════════════════════════════════════════════════════════════════
|
|
st.markdown("---")
|
|
foot_left, foot_mid, foot_right = st.columns([1, 2, 1])
|
|
with foot_mid:
|
|
st.markdown("""
|
|
<div class="footer">
|
|
Powered by <strong>AHAD QUANT</strong> |
|
|
<a href="https://ahadquant.com" target="_blank">ahadquant.com</a>
|
|
</div>
|
|
""", unsafe_allow_html=True)
|
|
|
|
# Auto-refresh in sidebar
|
|
auto = st.sidebar.checkbox("Auto-refresh (30s)", value=False)
|
|
if auto:
|
|
time.sleep(30)
|
|
st.rerun()
|