chemavxandClaude Fable 5
7f84bc3ec7
Post-mortem NVIDIA 631181: one uncorroborated high-weight signal (legacy Manifold 0.13 at weight 0.6) flipped a 0.845 market to 0.431 and lost. With Manifold observational-only and macro signals gated behind is_non_price, GNews (weight 1.5) is the only live signal able to move politics markets 20-30 pp against the order-book consensus. This adds a catastrophic fuse, not a fine calibration: - apply_news_guardrail(): when |news_lo| >= NEWS_MATERIAL_LOGODDS_THRESHOLD (0.10) and every other signal (fg, mom, btc_dom, mfld) is below it, clamp the posterior to prior ± MAX_NEWS_ONLY_PROB_SHIFT (0.25). Any corroborating material signal disables the clamp. Config via env (NEWS_GUARDRAIL_ENABLED=true by default). - edge_gross/edge_net computed from the clamped posterior; raw_final_prob preserved in reasoning (persisted via trades.reasoning — no schema migration) and in the NEWS_MATERIAL log line. - guardrail_changed_trade_decision: raw edge crossed the regime gate but the clamped edge no longer does (fuse prevented a trade). Note: with the default 0.25 band the clamped edge_net is 0.21, above every regime minimum, so the flag only fires with a tighter configured band. - Observability gated on materiality: NEWS_MATERIAL per-market line and a compact NEWS SUMMARY cycle line, only when with_news > 0 — no flood from the ~145 news-less markets per cycle. - 9 deterministic tests (extreme clamp, in-band passthrough, corroboration, inclusive threshold, disabled, changed_decision). No changes to NEWS_LOGODDS_WEIGHT, Manifold flags, edge thresholds, sizing, payout, resolution, or historical trades. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
495 lines
20 KiB
Python
495 lines
20 KiB
Python
"""
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Polymarket Trading Bot — Main Entry Point
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# ci-test: 2026-04-16
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"""
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import asyncio
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import logging
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import os
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from datetime import datetime, timezone
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from bot.data.polymarket import PolymarketClient, Market, market_family_key
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from bot.data.external import ExternalDataClient
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from bot.data.news import NewsClient
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from bot.data.manifold import ManifoldClient
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from bot.strategy.bayesian import (
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BayesianStrategy,
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gnews_priority,
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MAX_NEWS_QUERIES_PER_CYCLE,
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MANIFOLD_SIGNAL_ENABLED,
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)
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from bot.risk.manager import RiskManager
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from bot.executor.paper import PaperExecutor
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from bot.metrics.tracker import MetricsTracker
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from bot.data.db import Database
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from bot.notify.checkpoints import CheckpointMonitor
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
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)
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# httpx logs every request URL at INFO, and the GNews URL carries the API key as
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# a `?token=` query param — that would leak GNEWS_API_KEY in plaintext into the
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# pod logs. Raise httpx/httpcore to WARNING so request URLs never reach INFO.
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# The bot's own GNews log lines only print the sanitised query, not the token.
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logging.getLogger("httpx").setLevel(logging.WARNING)
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logging.getLogger("httpcore").setLevel(logging.WARNING)
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log = logging.getLogger("bot.main")
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PAPER_MODE = os.getenv("PAPER_MODE", "true").lower() == "true"
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PAPER_BANKROLL = float(os.getenv("PAPER_BANKROLL", "10000"))
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# Check open positions for market resolution every N trading cycles (~N minutes
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# at the 60s cycle cadence). Keeps Gamma API load at ~1 request per open
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# position per 10 minutes.
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RESOLUTION_CHECK_INTERVAL = 10
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async def check_resolutions(
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poly: PolymarketClient,
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executor: PaperExecutor,
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db: Database,
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) -> None:
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"""Detect resolved markets and settle their open paper positions.
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For each open position, asks the Gamma API whether the market resolved.
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On a definitive resolution, PaperExecutor.close_position() settles the
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payout, persists close_reason='resolved' + resolution + close_pnl, and
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sends the Telegram notification.
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"""
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positions = await db.get_open_position_details()
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checked = 0
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resolved = 0
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for pos in positions:
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market_id = str(pos["market_id"])
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try:
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res = await poly.get_market_resolution(market_id)
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except Exception as exc:
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log.warning("Resolution check failed for market %s: %s", market_id, exc)
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continue
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checked += 1
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if res is None or not res.resolved or res.resolution is None:
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continue
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try:
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pnl = await executor.close_position(
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market_id, res.resolution, question=pos.get("question") or "",
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)
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except Exception as exc:
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log.error("Failed to close resolved market %s: %s", market_id, exc)
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continue
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resolved += 1
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log.info(
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"MARKET_RESOLVED market_id=%s resolution=%.1f pnl=%s | %s",
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market_id,
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res.resolution,
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f"{pnl:+.2f}" if pnl is not None else "n/a",
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(pos.get("question") or "")[:60],
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)
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log.info("Resolution check: %d positions checked, %d resolved", checked, resolved)
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async def run_trading_loop(
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poly: PolymarketClient,
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external: ExternalDataClient,
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strategy: BayesianStrategy,
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risk: RiskManager,
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executor: PaperExecutor,
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metrics: MetricsTracker,
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db: Database,
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) -> None:
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"""Main trading loop — runs every 60 seconds."""
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log.info("Trading loop started. PAPER_MODE=%s", PAPER_MODE)
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checkpoint_monitor = CheckpointMonitor()
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cycle_count = 0
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while True:
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try:
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cycle_count += 1
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# 0. Resolution detector — every RESOLUTION_CHECK_INTERVAL cycles,
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# settle paper positions whose market resolved on Polymarket.
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# Runs before evaluation so freed cash/families are usable this cycle.
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if (
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PAPER_MODE
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and isinstance(executor, PaperExecutor)
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and cycle_count % RESOLUTION_CHECK_INTERVAL == 0
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):
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await check_resolutions(poly, executor, db)
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# 1. Fetch active markets (90-day window)
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markets = await poly.get_active_markets()
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log.info("Found %d active markets", len(markets))
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# 2. Get external signals
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ext_data = await external.get_all_signals()
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# 3. Build occupied_families from the current open portfolio positions.
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# This prevents re-entering a family where we already hold a position.
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# We also pull from DB to survive pod restarts.
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portfolio = executor.get_portfolio()
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occupied_families: set[str] = set()
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for market_id in portfolio.positions:
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mkt = next((m for m in markets if m.id == market_id), None)
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if mkt:
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occupied_families.add(market_family_key(mkt))
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# Also seed from DB in case a family was traded in a prior cycle
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# that isn't reflected in the current markets list
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db_families = await db.get_open_families()
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occupied_families |= db_families
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if occupied_families:
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log.info("Occupied families (from portfolio): %s", sorted(occupied_families))
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# 4. Sort markets.
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# Politics: sort by gnews_priority DESC (highest-value markets get
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# GNews budget first — Phase 3).
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# Others: sort by end_date ASC (soonest-resolving first).
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def _sort_key(m):
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try:
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dt = datetime.fromisoformat(m.end_date.replace("Z", "+00:00"))
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except Exception:
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dt = datetime(9999, 12, 31, tzinfo=timezone.utc)
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if m.category == "politics":
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priority = gnews_priority(m, strategy._news) if strategy._news else 0.0
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# Bucket 0 = politics, sort by priority DESC (negate for asc sort)
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return (0, -priority, dt)
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return (1, 0.0, dt)
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markets = sorted(markets, key=_sort_key)
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for _m in markets:
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log.info(
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" [market] %-55s | cat=%-12s | family=%-28s | ends=%s | yes=%.3f",
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_m.question[:55], _m.category, market_family_key(_m),
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_m.end_date[:10] if _m.end_date else "?", _m.yes_price,
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)
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# Reset per-cycle GNews counter
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strategy.reset_cycle()
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# 5. Evaluate each market
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# Fetch markets recently closed for inversion bug — block re-entry for 24h
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inverted_guard: set[str] = await db.get_recently_closed_inverted(hours=24)
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if inverted_guard:
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log.info(
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"Reentry guard active for %d market(s) (inversion, 24h): %s",
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len(inverted_guard), sorted(inverted_guard),
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)
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reentry_guard_count = 0
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cycle_trades = 0
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for market in markets:
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if market.id in inverted_guard:
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log.info(
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"reentry_guard_triggered market=%s | skipping — closed for inversion within 24h | %s",
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market.id, market.question[:60],
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)
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reentry_guard_count += 1
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continue
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# evaluate() returns None for all skips — reasons are logged internally
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signal = await strategy.evaluate(market, ext_data, occupied_families)
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if signal is None:
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continue
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log.info(
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"Signal generated: market=%-50s | edge_gross=%+.3f | edge_net=%+.3f | "
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"regime_min=%.2f | family=%s | conf=%.2f",
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market.question[:50],
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signal.edge_gross,
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signal.edge_net,
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signal.regime_min_edge,
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signal.family_key,
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signal.confidence,
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)
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# 6. Risk check + position sizing
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order = risk.size_order(signal, portfolio)
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if order is None:
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log.debug("Risk manager rejected order for %s", market.id)
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continue
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# 7. Execute (paper)
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trade = await executor.execute(order)
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if trade:
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log.info("Trade executed: %s", trade)
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# Block this family for the rest of the cycle (Phase 2)
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occupied_families.add(signal.family_key)
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cycle_trades += 1
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# Mark manifold audit record as used in this trade
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if signal.mfld_audit_id:
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try:
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await db.mark_manifold_audit_used(signal.mfld_audit_id)
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except Exception as exc:
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log.warning("Failed to mark manifold audit used: %s", exc)
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# 8. [CYCLE SUMMARY] — one block per cycle, stable format for grep/compare
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stats = strategy.get_cycle_stats()
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legacy_incomplete_count = await db.get_legacy_incomplete_count()
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n_total = len(markets)
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n_uncertainty = sum(1 for m in markets if 0.35 <= m.yes_price <= 0.65)
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n_eval = stats["evaluated_count"]
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def _pct(n: int, denom: int) -> str:
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if denom == 0:
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return "0% (0/0)"
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return f"{n * 100 // denom}% ({n}/{denom})"
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# The accepted/rejected counters only increment on the active-signal
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# path, so with the signal disabled they always print 0/0 — say
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# "disabled" instead of pretending the matcher found nothing.
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if MANIFOLD_SIGNAL_ENABLED:
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manifold_summary = (
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f" manifold_matches_accepted: {stats['manifold_matches_accepted']}\n"
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f" manifold_matches_rejected: {stats['manifold_matches_rejected']}"
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)
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else:
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manifold_summary = " manifold_signal: disabled"
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log.info(
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"[CYCLE SUMMARY]\n"
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" markets_total: %d\n"
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" markets_uncertainty_zone: %d (prior 0.35-0.65)\n"
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" max_edge_gross: %+.3f\n"
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" max_edge_net: %+.3f\n"
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" pct_edge_gross_gt_002: %s\n"
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" pct_edge_gross_gt_004: %s\n"
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" blocked_by_family: %d\n"
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" blocked_by_prior_extreme: %d\n"
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" blocked_by_edge_net_nonpositive:%d\n"
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" blocked_by_edge_net_below_regime:%d\n"
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" trades_executed: %d\n"
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" gnews_queries_used: %d/%d\n"
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" reentry_guard_blocked: %d\n"
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" legacy_incomplete_seen: %d\n"
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"%s",
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n_total,
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n_uncertainty,
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stats["max_edge_gross"],
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stats["max_edge_net"],
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_pct(stats["gross_gt_002"], n_total),
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_pct(stats["gross_gt_004"], n_total),
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stats["skip_family"],
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stats["skip_prior_extreme"],
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stats["skip_edge_net_nonpositive"],
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stats["skip_edge_net_below_regime"],
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cycle_trades,
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stats["gnews_queries_used"], MAX_NEWS_QUERIES_PER_CYCLE,
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reentry_guard_count,
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legacy_incomplete_count,
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manifold_summary,
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)
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# NEWS SUMMARY — one compact line, only on cycles where at least
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# one market had a material GNews contribution (never an empty
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# section on news-less cycles).
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if stats["news_with_material"] > 0:
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log.info(
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"NEWS SUMMARY | with_news=%d | avg_shift=%+.2f | "
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"max_shift=%+.2f | guardrail_applied=%d | changed_decisions=%d",
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stats["news_with_material"],
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stats["news_avg_shift"],
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stats["news_max_shift"],
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stats["news_guardrail_applied"],
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stats["news_changed_decisions"],
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)
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# 9. Update daily metrics
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await metrics.update_daily_summary()
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# 10. Checkpoint alerts — one-shot / rate-limited Telegram notifications
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current_portfolio = executor.get_portfolio()
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try:
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await checkpoint_monitor.check_all(
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db,
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exposure_pct=current_portfolio.exposure_pct,
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exposure_cap_pct=risk.max_exposure_pct,
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)
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except Exception as exc:
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log.warning("checkpoint_monitor.check_all failed: %s", exc)
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except Exception as e:
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log.error("Error in trading loop: %s", e, exc_info=True)
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await asyncio.sleep(60)
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async def run_legacy_scan(
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db: Database,
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markets: list,
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executor: PaperExecutor,
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paper_mode: bool,
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) -> None:
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"""
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One-time startup scan: re-key all open DB positions with the current
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market_family_key() logic, detect family conflicts, and report
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KEEP / REVIEW / CLOSE_RECOMMENDED per position.
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Manifold is intentionally not consulted here: with
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MANIFOLD_SIGNAL_ENABLED=false it is observational-only and must not
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drive position closures.
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In paper_mode: auto-closes all CLOSE_RECOMMENDED positions after logging.
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"""
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positions = await db.get_open_position_details()
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if not positions:
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log.info("Legacy scan: no open positions — skipping.")
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return
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market_by_id: dict = {str(m.id): m for m in markets}
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# Step 1: enrich each position with the re-computed family key
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enriched: list[dict] = []
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for pos in positions:
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mid = str(pos["market_id"])
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live_mkt = market_by_id.get(mid)
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old_fk = pos.get("family_key") or ""
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if live_mkt:
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new_fk = market_family_key(live_mkt)
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else:
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# Market not in active list — compute from stored question alone
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_dummy = Market(
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id=mid, condition_id="", question=pos["question"],
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yes_token_id="", no_token_id="",
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yes_price=0.5, no_price=0.5,
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volume_24h=0, end_date="", active=False, category="",
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)
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computed = market_family_key(_dummy)
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# Reject degenerate fallbacks that start with "-" (missing category + end_date)
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new_fk = computed if not computed.startswith("-") else (old_fk or "unknown")
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is_legacy_incomplete = (pos.get("edge_net") is None) and (not live_mkt)
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enriched.append({
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**dict(pos),
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"market_id": mid,
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"live_market": live_mkt,
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"family_key_old": old_fk,
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"family_key_new": new_fk,
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"fk_changed": new_fk != old_fk,
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"recommendation": "legacy_incomplete" if is_legacy_incomplete else "OK",
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"rec_reason": "edge_net and live market unavailable" if is_legacy_incomplete else "no family conflict",
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})
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# Step 2: group by new family key — identify conflicting siblings
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family_groups: dict[str, list[dict]] = {}
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for p in enriched:
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family_groups.setdefault(p["family_key_new"], []).append(p)
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for p in enriched:
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group = family_groups[p["family_key_new"]]
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if len(group) > 1:
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best = max(group, key=lambda x: (x.get("edge_net") or 0.0))
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if p["market_id"] == best["market_id"]:
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p["recommendation"] = "KEEP"
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p["rec_reason"] = (
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f"highest edge_net={p.get('edge_net') or 0.0:.3f} in family"
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)
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else:
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p["recommendation"] = "CLOSE_RECOMMENDED"
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p["rec_reason"] = (
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f"family conflict: sibling {best['market_id']} "
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f"has edge_net={best.get('edge_net') or 0.0:.3f}"
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)
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elif p["fk_changed"]:
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p["recommendation"] = "REVIEW"
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p["rec_reason"] = "family key changed but no sibling conflict"
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# Step 2.5: persist corrected family keys in DB for changed positions
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for p in enriched:
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if p["fk_changed"] and p["family_key_new"] not in ("unknown", ""):
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await db.update_family_key(p["market_id"], p["family_key_new"])
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log.info(
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"family_key updated in DB: market=%s | %s → %s",
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p["market_id"], p["family_key_old"] or "none", p["family_key_new"],
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)
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# Step 3: log the full scan report (before any closures)
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n_close = sum(1 for p in enriched if p["recommendation"] == "CLOSE_RECOMMENDED")
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n_keep = sum(1 for p in enriched if p["recommendation"] == "KEEP")
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n_ok = sum(1 for p in enriched if p["recommendation"] == "OK")
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n_review = sum(1 for p in enriched if p["recommendation"] == "REVIEW")
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n_legacy = sum(1 for p in enriched if p["recommendation"] == "legacy_incomplete")
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log.warning(
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"━" * 70 + "\nLEGACY SCAN — %d position(s): OK=%d KEEP=%d REVIEW=%d CLOSE_RECOMMENDED=%d LEGACY_INCOMPLETE=%d",
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len(enriched), n_ok, n_keep, n_review, n_close, n_legacy,
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)
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for p in enriched:
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log.warning(
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" [%-18s] market=%-8s | dir=%-8s | edge_net=%+.3f\n"
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" stored_family: %s\n"
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" new_family: %s%s\n"
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" reason: %s",
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p["recommendation"],
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p["market_id"], p["direction"],
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p.get("edge_net") or 0.0,
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p["family_key_old"] or "none",
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p["family_key_new"],
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" [CHANGED]" if p["fk_changed"] else "",
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p["rec_reason"],
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)
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log.warning("━" * 70)
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# Step 4: auto-close in paper mode
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if paper_mode and n_close > 0 and isinstance(executor, PaperExecutor):
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log.warning("PAPER MODE: auto-closing %d CLOSE_RECOMMENDED position(s)...", n_close)
|
|
for p in enriched:
|
|
if p["recommendation"] == "CLOSE_RECOMMENDED":
|
|
recovered = await executor.close_legacy_position(p["market_id"], p["rec_reason"], question=p["question"])
|
|
log.warning(
|
|
" AUTO_CLOSED market=%s | $%.2f returned to cash | %s",
|
|
p["market_id"], recovered, p["question"][:60],
|
|
)
|
|
log.warning("Legacy scan closures complete.")
|
|
elif n_close > 0:
|
|
log.warning("REAL MODE: %d position(s) marked CLOSE_RECOMMENDED — close manually.", n_close)
|
|
|
|
|
|
async def main() -> None:
|
|
if PAPER_MODE:
|
|
log.info("=" * 60)
|
|
log.info(" PAPER TRADING MODE — No real money at risk")
|
|
log.info(" Bankroll: $%.2f simulated", PAPER_BANKROLL)
|
|
log.info("=" * 60)
|
|
else:
|
|
log.warning("REAL TRADING MODE ACTIVE — Real money at risk!")
|
|
|
|
db = Database()
|
|
await db.connect()
|
|
await db.run_migrations()
|
|
await db.backfill_feature_columns()
|
|
|
|
poly = PolymarketClient()
|
|
external = ExternalDataClient()
|
|
news = NewsClient()
|
|
manifold = ManifoldClient()
|
|
strategy = BayesianStrategy(news=news, manifold=manifold, db=db)
|
|
risk = RiskManager(max_position_pct=0.05, max_exposure_pct=0.30)
|
|
executor = PaperExecutor(db=db, bankroll=PAPER_BANKROLL) if PAPER_MODE else None
|
|
metrics = MetricsTracker(db=db)
|
|
|
|
if executor is None:
|
|
from bot.executor.real import RealExecutor # noqa
|
|
executor = RealExecutor(db=db)
|
|
|
|
if PAPER_MODE:
|
|
await executor.initialize()
|
|
|
|
# Legacy scan: re-key all open positions, detect contradictions, auto-close
|
|
# CLOSE_RECOMMENDED in paper mode. Runs once at startup using a fresh
|
|
# market snapshot; the trading loop will re-fetch on its own first cycle.
|
|
try:
|
|
scan_markets = await poly.get_active_markets()
|
|
except Exception as e:
|
|
log.warning("Could not fetch markets for legacy scan: %s — scan skipped", e)
|
|
scan_markets = []
|
|
await run_legacy_scan(db, scan_markets, executor, PAPER_MODE)
|
|
|
|
try:
|
|
await run_trading_loop(poly, external, strategy, risk, executor, metrics, db)
|
|
finally:
|
|
await db.disconnect()
|
|
await news.close()
|
|
await manifold.close()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|