Pre-launch hardening: KOL module, Telegram, scanners, WS resilience
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>
This commit is contained in:
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"""
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VCP-style breakout scanner — example of an external signal module.
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What this scans for (Minervini-light, adapted for crypto perps):
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1. Volatility contraction: 7-day ATR ≤ 50% of 30-day ATR
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(the price has been getting tighter — supply is drying up)
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2. Breakout confirmation: current 4h close > max(prior 30-day highs)
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(a real break of the range, not just touching the top)
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3. Volume confirmation: last 24h volume ≥ 1.5× 30-day average
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(institutional participation, not retail noise)
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4. Cooldown: no signal for the same asset in the past 48h
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(avoid stacking)
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When all 4 conditions hit, the scanner POSTs to /api/signals/ingest. From
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there the trade goes through the same convex-strategy pipeline as Trump
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signals — regime filter, sizing, trailing stop, all of it.
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Why this module exists:
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Trump signals have 1-2 true catalysts per month. Adding a TA-based source
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that finds setups continuously means the bot has SOMETHING to act on most
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weeks, instead of waiting for geopolitical fireworks. The user's hypothesis
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is that consolidation breakouts have asymmetric upside; the existing
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trailing-stop logic is purpose-built to capture that.
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Tunables (don't hardcode in caller — change them HERE if you want to test):
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ATR_RECENT_DAYS, ATR_BASELINE_DAYS, ATR_RATIO_MAX,
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BREAKOUT_LOOKBACK_DAYS, VOLUME_MULT_MIN, COOLDOWN_HOURS.
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Asset list:
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Default = SOL only. Extend ASSETS_TO_SCAN with more once you've watched
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this run for a week and confirmed it doesn't fire-hose noise.
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"""
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from __future__ import annotations
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import logging
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import statistics
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from datetime import datetime, timedelta, timezone
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from typing import Optional
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import httpx
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from app.config import settings
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from app.services.market_data import for_asset, drop_in_progress_bar
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from app.services import scanner_state
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logger = logging.getLogger(__name__)
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SCANNER_NAME = "vcp_breakout"
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scanner_state.register(SCANNER_NAME)
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# ─── Tunables ───────────────────────────────────────────────────────────────
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ATR_RECENT_DAYS = 7
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ATR_BASELINE_DAYS = 30
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ATR_RATIO_MAX = 0.5 # recent ATR must be ≤ 50% of baseline
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BREAKOUT_LOOKBACK_DAYS = 30 # break of this many days' high
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VOLUME_MULT_MIN = 1.5 # current 24h vol vs 30-day avg
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COOLDOWN_HOURS = 48 # don't re-signal same asset within this window
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# Assets to scan. Provider selection (Binance vs HL) is automatic via
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# market_data.for_asset() — HL-native perps like TRUMP/HYPE route to HL
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# automatically. Add to HL_NATIVE_ASSETS in market_data.py if needed.
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ASSETS_TO_SCAN = [
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"SOL",
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# "ETH", "LINK", "AVAX", # Binance has them
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# "TRUMP", "HYPE", # HL-native (routed automatically)
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]
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# Cooldown via scanner_state.in_cooldown — DB-backed, restart-safe.
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# Data fetching is delegated to market_data.for_asset() — see that module
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# for Binance vs Hyperliquid routing.
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# ─── Signal logic ───────────────────────────────────────────────────────────
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def _atr_proxy(candles: list[dict]) -> Optional[float]:
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"""Mean of (high-low)/close — simple ATR proxy, dimensionless."""
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ranges = [(c["high"] - c["low"]) / c["close"] for c in candles if c["close"] > 0]
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return statistics.fmean(ranges) if ranges else None
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def evaluate_breakout(candles: list[dict]) -> tuple[bool, dict]:
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"""Returns (is_signal, debug_info). All 4 gates must pass.
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Pure function — no side effects, fully testable.
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"""
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if len(candles) < ATR_BASELINE_DAYS * 6:
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return False, {"reason": "insufficient_data", "bars": len(candles)}
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# 1. Volatility contraction
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recent_bars = candles[-ATR_RECENT_DAYS * 6:]
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baseline_bars = candles[-ATR_BASELINE_DAYS * 6:]
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atr_recent = _atr_proxy(recent_bars)
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atr_baseline = _atr_proxy(baseline_bars)
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if not atr_recent or not atr_baseline:
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return False, {"reason": "atr_calc_failed"}
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atr_ratio = atr_recent / atr_baseline
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if atr_ratio > ATR_RATIO_MAX:
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return False, {"reason": "no_contraction", "atr_ratio": round(atr_ratio, 3)}
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# 2. Range break — UP through prior high (long) or DOWN through prior
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# low (short). Lookback excludes the current bar.
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lookback = candles[-BREAKOUT_LOOKBACK_DAYS * 6 : -1]
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if not lookback:
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return False, {"reason": "no_lookback"}
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prior_high = max(c["high"] for c in lookback)
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prior_low = min(c["low"] for c in lookback)
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current_close = candles[-1]["close"]
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if current_close > prior_high:
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direction, ref, gap = "buy", prior_high, (current_close - prior_high) / prior_high * 100
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elif current_close < prior_low:
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direction, ref, gap = "short", prior_low, (prior_low - current_close) / prior_low * 100
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else:
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return False, {"reason": "no_range_break", "close": current_close,
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"prior_high": prior_high, "prior_low": prior_low}
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# 3. Volume confirmation (same for both directions — a real break needs
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# participation regardless of which way it goes)
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recent_vol_24h = sum(c["volume"] for c in candles[-6:])
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baseline_avg_24h = sum(c["volume"] for c in candles[-180:]) / 30
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if baseline_avg_24h <= 0:
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return False, {"reason": "no_volume_data"}
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vol_ratio = recent_vol_24h / baseline_avg_24h
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if vol_ratio < VOLUME_MULT_MIN:
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return False, {"reason": "weak_volume", "vol_ratio": round(vol_ratio, 2)}
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return True, {
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"direction": direction,
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"atr_ratio": round(atr_ratio, 3),
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"vol_ratio": round(vol_ratio, 2),
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"break_ref": round(ref, 4),
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"break_at": round(current_close, 4),
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"headroom_pct": round(gap, 2),
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}
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def _confidence_from(debug: dict) -> int:
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"""Map the signal's quality into a 0-100 confidence used by sizing.
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The tighter the contraction and the bigger the volume spike, the higher
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the confidence. Capped at 95 — leave headroom so AI signals at 100 stay
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distinguishable.
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"""
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score = 70 # baseline for "all 4 gates passed"
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# Tighter contraction → higher confidence
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if debug.get("atr_ratio", 1) < 0.35: score += 10
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elif debug.get("atr_ratio", 1) < 0.45: score += 5
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# Bigger volume spike → higher confidence
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if debug.get("vol_ratio", 0) >= 3.0: score += 10
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elif debug.get("vol_ratio", 0) >= 2.0: score += 5
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return min(score, 95)
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# ─── Ingest call ────────────────────────────────────────────────────────────
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async def _emit_signal(asset: str, debug: dict) -> None:
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"""POST the signal to /api/signals/ingest. Treats the local server as the
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target — same machine, no network hop in dev.
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"""
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if not settings.ingest_api_key:
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logger.warning("VCP: signal would fire on %s but INGEST_API_KEY is empty", asset)
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return
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confidence = _confidence_from(debug)
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direction = debug["direction"]
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way = "breakout ↑" if direction == "buy" else "breakdown ↓"
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rel = "above" if direction == "buy" else "below"
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payload = {
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"source": "breakout",
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"external_id": f"vcp-{asset}-{direction}-{datetime.now(timezone.utc).strftime('%Y%m%d-%H%M')}",
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"text": (
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f"VCP {way} on {asset}: ATR ratio {debug['atr_ratio']} "
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f"(7d/30d), {debug['vol_ratio']}× normal volume, "
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f"close ${debug['break_at']} {rel} {BREAKOUT_LOOKBACK_DAYS}-day "
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f"level ${debug['break_ref']} ({debug['headroom_pct']}%)"
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),
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"signal": direction,
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"target_asset": asset,
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"confidence": confidence,
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"category": "vcp_breakout",
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"expected_move_pct": 5.0, # historical VCP median expansion
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}
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async with httpx.AsyncClient(timeout=10) as client:
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resp = await client.post(
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"http://localhost:8000/api/signals/ingest",
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json=payload,
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headers={"X-Ingest-Key": settings.ingest_api_key},
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)
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if resp.status_code >= 400:
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logger.error("VCP ingest failed (%d): %s", resp.status_code, resp.text[:200])
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else:
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logger.info("VCP signal emitted for %s, confidence=%d: %s",
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asset, confidence, resp.json())
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# ─── Scheduler entry point ──────────────────────────────────────────────────
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async def scan_once() -> None:
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"""Single scan pass over ASSETS_TO_SCAN. Called every 30 minutes.
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Kill-switch + DB-backed cooldown. Drops in-progress 4h bar before
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evaluating — without that, the breakout test ran against a partial bar
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and could flicker FIRE / no-FIRE within a 4h window.
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"""
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if not scanner_state.is_enabled(SCANNER_NAME):
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logger.debug("VCP scanner disabled — skipping run")
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return
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fired_any = False
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error_msg: Optional[str] = None
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for asset in ASSETS_TO_SCAN:
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# Cooldown — DB-backed, restart-safe.
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cooldown_days = COOLDOWN_HOURS / 24
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if await scanner_state.in_cooldown("breakout", asset, cooldown_days):
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continue
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provider = for_asset(asset)
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try:
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candles = await provider.fetch_4h(asset, days=ATR_BASELINE_DAYS + 1)
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except Exception as exc:
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error_msg = f"{asset}: {exc}"
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logger.error("VCP fetch failed for %s via %s: %s", asset, provider.name, exc)
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continue
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candles = drop_in_progress_bar(candles, "4h")
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if not candles:
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logger.warning("VCP: %s returned 0 candles from %s — symbol may not exist",
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asset, provider.name)
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continue
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is_signal, debug = evaluate_breakout(candles)
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logger.info("VCP scan %s [%s]: %s — %s", asset, provider.name,
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"FIRE" if is_signal else "no", debug)
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if is_signal:
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await _emit_signal(asset, debug)
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fired_any = True
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if error_msg:
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scanner_state.record_run(SCANNER_NAME, "error", error_msg)
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elif fired_any:
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scanner_state.record_run(SCANNER_NAME, "fired")
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else:
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scanner_state.record_run(SCANNER_NAME, "ok")
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