5fb1d52026
Big-picture changes since b941223:
KOL pipeline (new) — Substack/podcast/blog RSS → AI ticker extraction →
on-chain wallet diff → talks-vs-trades divergence detection. Daily polls,
19 feeds, divergence emits Post + Telegram fan-out.
Telegram push (new) — walletless free tier + wallet-linked Pro upgrade,
in-bot preference commands (/trump /btc /funding /kol /conf /quiet),
signed-envelope API for dashboard. Disconnect-wallet keeps free
subscription.
BTC funding-rate reversal scanner (new) — hourly cron, 30d cumulative
funding threshold + mean-revert + 7d price confirm, emits via
/api/signals/ingest. BTC bottom-reversal scanner promoted to System 2.
WS broadcast rewrite — per-client send timeout + parallel fan-out
(asyncio.gather). Fixes "Binance WS no close frame" reconnect storms +
APScheduler 11-min job misses, both caused by one slow client stalling
the kline loop.
Error visibility — three silent-error sites (trumpstruth/truth_social
fetchers, funding_reversal scanner) now include exception type name so
httpx ConnectError-style empty-message errors stop logging blank lines.
Telegram bot loop now classifies ReadTimeout vs network vs unknown +
logger.exception for the unknown bucket.
Security hygiene — trumpsignal.db untracked from git (held subscriber
wallets + encrypted HL keys + 22 bot trades); .gitignore now blocks
*.db/.next/backups. CORS only allows FRONTEND_URL in production.
New ops scripts —
- scripts/preflight.py: env/DB/Telegram/AI auth verification gate
- scripts/backup_db.sh: cron-friendly daily DB backup (SQLite + Postgres)
- scripts/seed_kol_wallets.py: idempotent KOL on-chain wallet seeder
15 new Alembic migrations (007-021) covering convex strategy fields,
phase-1 safety, two-system frozen exits, invalidation prices, dynamic
SYS2 leverage, staged de-risk + pyramiding, peak gain tracking, risk
mode, auto-trade + grow flags, KOL module, KOL on-chain, KOL divergence,
Telegram bindings + walletless.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
87 lines
2.6 KiB
Python
87 lines
2.6 KiB
Python
import logging
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from datetime import datetime, timedelta, timezone
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from fastapi import APIRouter, Depends, Query
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from sqlalchemy import select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.database import get_db
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from app.models import BotTrade
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from app.schemas import BotPerformance
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from app.services.signed_request import verify_signed_request
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router = APIRouter()
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logger = logging.getLogger(__name__)
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PERIOD_DAYS = 30
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ACTION_VIEW_PERFORMANCE = "view_performance"
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@router.get("/performance", response_model=BotPerformance)
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async def get_performance(
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wallet: str = Query(..., description="Wallet address (lower-cased internally)"),
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ts: int = Query(..., description="Signed timestamp (ms)"),
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sig: str = Query(..., description="EIP-191 signature"),
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db: AsyncSession = Depends(get_db),
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):
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wallet = wallet.lower().strip()
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verify_signed_request(
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action=ACTION_VIEW_PERFORMANCE,
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wallet=wallet,
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timestamp_ms=ts,
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signature=sig,
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body=None,
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allow_replay=True,
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)
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since = datetime.now(timezone.utc).replace(tzinfo=None) - timedelta(days=PERIOD_DAYS)
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result = await db.execute(
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select(BotTrade)
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.where(BotTrade.wallet_address == wallet)
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.where(BotTrade.closed_at.is_not(None))
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.where(BotTrade.opened_at >= since)
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.order_by(BotTrade.opened_at.asc())
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)
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trades = result.scalars().all()
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total_trades = len(trades)
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if total_trades == 0:
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return BotPerformance(
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period_days=PERIOD_DAYS,
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total_trades=0,
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win_rate=0.0,
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net_pnl_usd=0.0,
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avg_hold_seconds=0.0,
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max_drawdown_pct=0.0,
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)
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winning = sum(1 for t in trades if (t.pnl_usd or 0) > 0)
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win_rate = winning / total_trades
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pnl_values = [(t.pnl_usd or 0.0) for t in trades]
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net_pnl = sum(pnl_values)
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hold_values = [(t.hold_seconds or 0) for t in trades]
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avg_hold = sum(hold_values) / len(hold_values)
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# Max drawdown: running peak → trough of cumulative PnL
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cumulative = 0.0
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peak = 0.0
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max_drawdown = 0.0
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for pnl in pnl_values:
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cumulative += pnl
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if cumulative > peak:
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peak = cumulative
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drawdown = (peak - cumulative) / peak * 100 if peak > 0 else 0.0
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if drawdown > max_drawdown:
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max_drawdown = drawdown
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return BotPerformance(
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period_days=PERIOD_DAYS,
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total_trades=total_trades,
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win_rate=round(win_rate, 4),
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net_pnl_usd=round(net_pnl, 2),
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avg_hold_seconds=round(avg_hold, 1),
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max_drawdown_pct=round(max_drawdown, 4),
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)
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