chore(deps): update dependency fastapi to v0.137.0

bot/data/news.py

@@ -51,11 +51,7 @@ _DATE_RE = re.compile(
     r"|\bQ[1-4]\b",
     flags=re.IGNORECASE,
 )
-# Hyphens/dashes are GNews query operators (a leading '-' means "exclude the
-# next term"), so a token like "El-Sayed" makes the API return HTTP 400.  Strip
-# them to spaces along with the rest of the punctuation so the query stays a
-# plain keyword list.  – = en dash, — = em dash.
-_PUNCT_RE = re.compile(r"[?!\"'.,;:()\[\]{}\-–—]")
+_PUNCT_RE = re.compile(r"[?!\"'.,;:()\[\]{}]")
 
 
 class NewsClient:
@@ -83,18 +79,6 @@ class NewsClient:
     # Public API
     # ------------------------------------------------------------------
 
-    @property
-    def enabled(self) -> bool:
-        """True only when a GNews API key is configured.
-
-        When False, get_sentiment() is a no-op that returns 0.0 without any
-        network call, so callers must skip GNews entirely — including the
-        per-cycle query budget accounting — instead of "spending" a query that
-        never reaches the API (which inflated gnews_queries_used to a phantom
-        5/5 while the key was missing).
-        """
-        return bool(self._api_key)
-
     async def get_sentiment(self, question: str) -> float:
         """
         Return a sentiment score ∈ [-1.0, +1.0] for the market question.

bot/main.py

@@ -27,12 +27,6 @@ logging.basicConfig(
     level=logging.INFO,
     format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
 )
-# httpx logs every request URL at INFO, and the GNews URL carries the API key as
-# a `?token=` query param — that would leak GNEWS_API_KEY in plaintext into the
-# pod logs.  Raise httpx/httpcore to WARNING so request URLs never reach INFO.
-# The bot's own GNews log lines only print the sanitised query, not the token.
-logging.getLogger("httpx").setLevel(logging.WARNING)
-logging.getLogger("httpcore").setLevel(logging.WARNING)
 log = logging.getLogger("bot.main")
 
 PAPER_MODE = os.getenv("PAPER_MODE", "true").lower() == "true"
@@ -277,20 +271,6 @@ async def run_trading_loop(
                 manifold_summary,
             )
 
-            # NEWS SUMMARY — one compact line, only on cycles where at least
-            # one market had a material GNews contribution (never an empty
-            # section on news-less cycles).
-            if stats["news_with_material"] > 0:
-                log.info(
-                    "NEWS SUMMARY | with_news=%d | avg_shift=%+.2f | "
-                    "max_shift=%+.2f | guardrail_applied=%d | changed_decisions=%d",
-                    stats["news_with_material"],
-                    stats["news_avg_shift"],
-                    stats["news_max_shift"],
-                    stats["news_guardrail_applied"],
-                    stats["news_changed_decisions"],
-                )
-
             # 9. Update daily metrics
             await metrics.update_daily_summary()
 

bot/strategy/bayesian.py

@@ -84,27 +84,6 @@ def _env_bool(name: str, default: bool) -> bool:
 MANIFOLD_SIGNAL_ENABLED = _env_bool("MANIFOLD_SIGNAL_ENABLED", False)
 MANIFOLD_AUDIT_ENABLED  = _env_bool("MANIFOLD_AUDIT_ENABLED", True)
 
-# ── GNews guardrail (catastrophic fuse) ────────────────────────────────────────
-# Post-mortem NVIDIA 631181: a single strong signal (legacy Manifold 0.13 at
-# weight 0.6) flipped a 0.845 market to 0.431 and lost.  With Manifold now
-# observational-only and macro signals gated behind is_non_price, GNews
-# (weight 1.5) is the only live signal that can move politics markets 20-30 pp
-# against the order-book consensus.  This is NOT a fine calibration — it is a
-# fuse against the extreme case: one uncorroborated signal violently inverting
-# the market.
-#
-# NEWS_GUARDRAIL_ENABLED: master switch for the fuse.
-# MAX_NEWS_ONLY_PROB_SHIFT: when GNews is the ONLY material signal, the final
-#   probability is clamped to prior ± this value.  0.25 still allows a 25 pp
-#   move (edge_net 0.21 after costs) — trades still happen, sizing is bounded.
-# NEWS_MATERIAL_LOGODDS_THRESHOLD: a signal counts as *material* iff its
-#   |log-odds contribution| >= this value.  Below it, a signal is noise and
-#   does NOT count as corroboration.  If ANY other signal (fg, momentum,
-#   btc_dom, manifold) is material, the fuse does not apply.
-NEWS_GUARDRAIL_ENABLED = _env_bool("NEWS_GUARDRAIL_ENABLED", True)
-MAX_NEWS_ONLY_PROB_SHIFT = float(os.getenv("MAX_NEWS_ONLY_PROB_SHIFT", "0.25"))
-NEWS_MATERIAL_LOGODDS_THRESHOLD = float(os.getenv("NEWS_MATERIAL_LOGODDS_THRESHOLD", "0.10"))
-
 # GNews free tier: 100 req/day.  We limit to 5 queries per trading cycle
 # (politics markets only) and rely on 6 h cache to stay within budget.
 MAX_NEWS_QUERIES_PER_CYCLE = 5
@@ -200,42 +179,6 @@ def has_token(text: str, token: str) -> bool:
 # Phase 3 — GNews priority scoring
 # ─────────────────────────────────────────────────────────────────────────────
 
-def apply_news_guardrail(
-    prior: float,
-    raw_final_prob: float,
-    feat_news_lo: float,
-    other_feats_lo: tuple[float, ...],
-) -> tuple[float, bool]:
-    """
-    GNews guardrail (catastrophic fuse).
-
-    Clamp raw_final_prob to prior ± MAX_NEWS_ONLY_PROB_SHIFT when ALL hold:
-      1. NEWS_GUARDRAIL_ENABLED
-      2. |feat_news_lo| >= NEWS_MATERIAL_LOGODDS_THRESHOLD (news is material)
-      3. every other signal's |log-odds contribution| is below the threshold
-         (GNews is the ONLY material signal — no corroboration)
-
-    Returns (final_prob, guardrail_applied).  guardrail_applied is True only
-    when the clamp actually changed the value; a raw_final_prob already inside
-    the band passes through untouched with applied=False.
-
-    Module globals are read at call time so tests can monkeypatch them.
-    """
-    if not NEWS_GUARDRAIL_ENABLED:
-        return raw_final_prob, False
-    if abs(feat_news_lo) < NEWS_MATERIAL_LOGODDS_THRESHOLD:
-        return raw_final_prob, False
-    if any(abs(v) >= NEWS_MATERIAL_LOGODDS_THRESHOLD for v in other_feats_lo):
-        return raw_final_prob, False  # corroborated — fuse does not apply
-    clamped = min(
-        max(raw_final_prob, prior - MAX_NEWS_ONLY_PROB_SHIFT),
-        prior + MAX_NEWS_ONLY_PROB_SHIFT,
-    )
-    if clamped == raw_final_prob:
-        return raw_final_prob, False
-    return clamped, True
-
-
 def gnews_priority(market: Market, news: "NewsClient") -> float:
     """
     Score a market for GNews query priority (higher = more valuable to query).
@@ -357,10 +300,6 @@ class BayesianStrategy:
         # (edge_gross, edge_net, regime_min) for every market that reached the
         # edge computation stage (passed prior-extreme, family, unsupported filters)
         self._evaluated_edges: list[tuple[float, float, float]] = []
-        # GNews guardrail observability — only markets with material news
-        self._news_shifts: list[float] = []       # final_prob - prior, signed
-        self._news_guardrail_applied: int = 0
-        self._news_changed_decisions: int = 0
 
     def reset_cycle(self) -> None:
         """Call once at the start of each trading cycle to reset per-cycle counters."""
@@ -372,9 +311,6 @@ class BayesianStrategy:
         self._manifold_fetched = 0
         self._manifold_on_trade = 0
         self._evaluated_edges = []
-        self._news_shifts = []
-        self._news_guardrail_applied = 0
-        self._news_changed_decisions = 0
 
     def get_cycle_stats(self) -> dict:
         """Return per-cycle counters for the [CYCLE SUMMARY] log block."""
@@ -394,14 +330,6 @@ class BayesianStrategy:
             "gross_gt_004": sum(1 for g in all_gross if g > 0.04),
             "manifold_matches_accepted": self._manifold_on_trade,
             "manifold_matches_rejected": self._manifold_fetched - self._manifold_on_trade,
-            # GNews guardrail — markets with |news_lo| >= NEWS_MATERIAL_LOGODDS_THRESHOLD
-            "news_with_material":     len(self._news_shifts),
-            "news_avg_shift":         (sum(self._news_shifts) / len(self._news_shifts))
-                                      if self._news_shifts else 0.0,
-            "news_max_shift":         max(self._news_shifts, key=abs)
-                                      if self._news_shifts else 0.0,
-            "news_guardrail_applied": self._news_guardrail_applied,
-            "news_changed_decisions": self._news_changed_decisions,
         }
 
     async def evaluate(
@@ -575,16 +503,11 @@ class BayesianStrategy:
         # Phase 3: caller has pre-sorted markets by gnews_priority() so the
         # highest-value markets reach this block first.
         news_log_adj = 0.0
-        news_sentiment = 0.0
-        # self._news.enabled gates the whole block: with no GNews API key the
-        # client is a no-op, so we must not consume (or report) query budget for
-        # it — see NewsClient.enabled.
-        if is_politics and self._news is not None and self._news.enabled:
+        if is_politics and self._news is not None:
             if self._news_queries_this_cycle < MAX_NEWS_QUERIES_PER_CYCLE:
                 self._news_queries_this_cycle += 1
                 sentiment = await self._news.get_sentiment(market.question)
                 if abs(sentiment) > 0.05:
-                    news_sentiment = sentiment
                     news_log_adj = sentiment * NEWS_LOGODDS_WEIGHT
                     sources.append(f"GNews: {sentiment:+.2f}")
             else:
@@ -726,31 +649,8 @@ class BayesianStrategy:
         # Posterior via log-odds updating
         log_odds_prior = math.log(prior / (1 - prior))
         total_adj = sum(adjustments)
-        # raw_final_prob: posterior BEFORE the news guardrail.
-        raw_final_prob = _sigmoid(log_odds_prior + total_adj * 2 + news_log_adj + manifold_log_adj)
-        raw_final_prob = max(0.05, min(0.95, raw_final_prob))
-
-        # Per-feature log-odds contributions (Phase 6) — computed here (not
-        # after the edge gate) because the guardrail below needs them to decide
-        # signal materiality.
-        # fg / mom / btc_dom: probability-delta × 2 → log-odds.
-        # news / mfld: already log-odds (LOGODDS_WEIGHT already applied).
-        feat_fg_lo      = _fg_contribution * 2
-        feat_mom_lo     = _momentum_contribution * 2
-        feat_news_lo    = news_log_adj
-        feat_mfld_lo    = manifold_log_adj
-        feat_btc_dom_lo = _btc_dom_contribution * 2
-
-        # ── GNews guardrail (catastrophic fuse) ──────────────────────────────
-        # When GNews is the ONLY material signal, clamp the posterior to
-        # prior ± MAX_NEWS_ONLY_PROB_SHIFT.  estimated_prob (post-guardrail) is
-        # what edge/trading uses; raw_final_prob is kept for observability.
-        estimated_prob, news_guardrail_applied = apply_news_guardrail(
-            prior,
-            raw_final_prob,
-            feat_news_lo,
-            (feat_fg_lo, feat_mom_lo, feat_btc_dom_lo, feat_mfld_lo),
-        )
+        estimated_prob = _sigmoid(log_odds_prior + total_adj * 2 + news_log_adj + manifold_log_adj)
+        estimated_prob = max(0.05, min(0.95, estimated_prob))
 
         # ── Phase 1: edge_gross and edge_net ─────────────────────────────────
         raw_edge = estimated_prob - market.yes_price
@@ -772,6 +672,15 @@ class BayesianStrategy:
         if manifold_log_adj != 0.0:
             confidence = min(confidence_cap, confidence + 0.08)
 
+        # Per-feature log-odds contributions (Phase 6).
+        # fg / mom / btc_dom: probability-delta × 2 → log-odds.
+        # news / mfld: already log-odds (LOGODDS_WEIGHT already applied).
+        feat_fg_lo      = _fg_contribution * 2
+        feat_mom_lo     = _momentum_contribution * 2
+        feat_news_lo    = news_log_adj
+        feat_mfld_lo    = manifold_log_adj
+        feat_btc_dom_lo = _btc_dom_contribution * 2
+
         feat_str = (
             f"fg_lo={feat_fg_lo:+.4f} mom_lo={feat_mom_lo:+.4f} "
             f"news_lo={feat_news_lo:+.4f} mfld_lo={feat_mfld_lo:+.4f} "
@@ -783,48 +692,6 @@ class BayesianStrategy:
         passed_net = edge_net >= regime_min
         can_trade = passed_net and confidence >= MIN_CONFIDENCE
 
-        # ── Guardrail decision impact ────────────────────────────────────────
-        # True when the un-clamped posterior's edge crossed the regime gate but
-        # the clamped one no longer does — i.e. the fuse PREVENTED a trade.
-        # Confidence is invariant under the clamp (it depends only on signal
-        # agreement), so the edge gate is the only component that can flip.
-        guardrail_changed_trade_decision = False
-        if news_guardrail_applied:
-            raw_edge_net = abs(raw_final_prob - market.yes_price) - TOTAL_COST_RATE
-            guardrail_changed_trade_decision = (
-                raw_edge_net >= regime_min and edge_net < regime_min
-            )
-
-        # ── Guardrail observability — ONLY markets with material news ───────
-        # Gated on materiality so the ~145 markets/cycle without news don't
-        # flood the logs.  posterior_before_news = everything except GNews.
-        news_is_material = abs(feat_news_lo) >= NEWS_MATERIAL_LOGODDS_THRESHOLD
-        if news_is_material:
-            posterior_before_news = max(0.05, min(0.95, _sigmoid(
-                log_odds_prior + total_adj * 2 + manifold_log_adj
-            )))
-            self._news_shifts.append(estimated_prob - prior)
-            if news_guardrail_applied:
-                self._news_guardrail_applied += 1
-            if guardrail_changed_trade_decision:
-                self._news_changed_decisions += 1
-            log.info(
-                "NEWS_MATERIAL      %-50s | cat=%-12s | family=%-28s | "
-                "prior=%.3f | before_news=%.3f | raw=%.3f | final=%.3f | "
-                "sent=%+.2f | news_lo=%+.4f | "
-                "edge_before_news=%.3f | edge_after_raw=%.3f | edge_after_guardrail=%.3f | "
-                "guardrail=%s | changed_decision=%s | max_shift=%.2f",
-                market.question[:50], category, family,
-                prior, posterior_before_news, raw_final_prob, estimated_prob,
-                news_sentiment, feat_news_lo,
-                abs(posterior_before_news - market.yes_price),
-                abs(raw_final_prob - market.yes_price),
-                edge_gross,
-                "applied" if news_guardrail_applied else "none",
-                str(guardrail_changed_trade_decision).lower(),
-                MAX_NEWS_ONLY_PROB_SHIFT,
-            )
-
         if not can_trade:
             # Increment the appropriate edge-net counter
             if edge_net <= 0:
@@ -853,21 +720,8 @@ class BayesianStrategy:
             )
             return None
 
-        # When GNews participated, expose raw vs final and the guardrail verdict
-        # (Task 4 of the guardrail spec); otherwise keep the legacy format.
-        if news_log_adj != 0.0:
-            prob_part = (
-                f"Prior=poly({prior:.3f}) → raw={raw_final_prob:.3f} "
-                f"→ final={estimated_prob:.3f} | "
-                f"GNews sent={news_sentiment:+.2f} | "
-                f"guardrail={'applied' if news_guardrail_applied else 'none'} | "
-                f"changed_decision={str(guardrail_changed_trade_decision).lower()} | "
-                f"max_shift={MAX_NEWS_ONLY_PROB_SHIFT:.2f} | "
-            )
-        else:
-            prob_part = f"Prior=poly({prior:.3f}) → estimate={estimated_prob:.3f} | "
         reasoning = (
-            prob_part +
+            f"Prior=poly({prior:.3f}) → estimate={estimated_prob:.3f} | "
             f"Poly price={market.yes_price:.3f} | "
             f"edge_gross={edge_gross:+.3f} | edge_net={edge_net:+.3f} | "
             f"regime_min={regime_min:.2f} | days={days} | "

requirements.txt

@@ -1,7 +1,7 @@
 # Core
 asyncpg==0.29.0
 httpx==0.27.0
-fastapi==0.111.0
+fastapi==0.137.0
 uvicorn[standard]==0.29.0
 pydantic==2.7.0
 

tests/test_news_guardrail.py

@@ -1,247 +0,0 @@
-"""
-Tests for the GNews guardrail (catastrophic fuse).
-
-Post-mortem NVIDIA 631181: one uncorroborated signal at high weight flipped a
-0.845 market to 0.431.  With Manifold observational-only and macro signals
-gated behind is_non_price, GNews is the only live signal able to move politics
-markets 20-30 pp against the order-book consensus.  The fuse clamps the
-posterior to prior ± MAX_NEWS_ONLY_PROB_SHIFT when GNews is the ONLY material
-signal (|log-odds| >= NEWS_MATERIAL_LOGODDS_THRESHOLD); any other material
-signal counts as corroboration and disables the clamp.
-
-Politics markets have no macro adjustments, so full-path tests exercise the
-"GNews only" branch naturally; the corroboration branch is tested through the
-pure helper apply_news_guardrail().
-
-evaluate() emits a NEWS_MATERIAL log line for every market whose news
-contribution is material (trade or skip); tests parse it via caplog.
-"""
-import asyncio
-import logging
-import math
-import re
-
-import pytest
-
-import bot.strategy.bayesian as bayesian
-from bot.data.external import ExternalSignals
-from bot.data.polymarket import Market
-from bot.strategy.bayesian import (
-    NEWS_LOGODDS_WEIGHT,
-    BayesianStrategy,
-    apply_news_guardrail,
-)
-
-NEWS_MATERIAL_RE = re.compile(
-    r"NEWS_MATERIAL.*raw=(\d+\.\d+) \| final=(\d+\.\d+).*"
-    r"guardrail=(applied|none) \| changed_decision=(true|false)"
-)
-
-
-def _logodds(p: float) -> float:
-    return math.log(p / (1 - p))
-
-
-def _sentiment_for(prior: float, target_raw: float) -> float:
-    """Sentiment that moves `prior` to exactly `target_raw` via GNews alone."""
-    return (_logodds(target_raw) - _logodds(prior)) / NEWS_LOGODDS_WEIGHT
-
-
-class FakeNews:
-    """Deterministic NewsClient stub returning a fixed sentiment."""
-
-    enabled = True
-
-    def __init__(self, sentiment: float) -> None:
-        self._sentiment = sentiment
-
-    async def get_sentiment(self, question: str) -> float:
-        return self._sentiment
-
-    def get_freshness(self, question: str) -> float:
-        return 1.0
-
-
-def _make_market(yes_price: float) -> Market:
-    return Market(
-        id="mkt-guardrail-1",
-        condition_id="cond-guardrail-1",
-        question="Will John Smith win the election?",
-        yes_token_id="yes-tok",
-        no_token_id="no-tok",
-        yes_price=yes_price,
-        no_price=1.0 - yes_price,
-        volume_24h=50_000.0,
-        end_date="2026-07-15T00:00:00Z",  # politics <30 d → regime_min 0.08
-        active=True,
-        category="politics",
-    )
-
-
-def _make_signals() -> ExternalSignals:
-    # Neutral macro environment; irrelevant for politics (gated) but explicit.
-    return ExternalSignals(
-        btc_price=100_000.0,
-        btc_change_24h=0.0,
-        eth_price=4_000.0,
-        eth_change_24h=0.0,
-        btc_dominance=50.0,
-        fear_greed_index=50,
-        fear_greed_label="neutral",
-        total_market_cap_change=0.0,
-        valid=True,
-    )
-
-
-def _evaluate(yes_price: float, sentiment: float, caplog) -> tuple[
-    BayesianStrategy, tuple[float, float, str, str]
-]:
-    """Run evaluate() on a politics market and parse the NEWS_MATERIAL line."""
-    strategy = BayesianStrategy(news=FakeNews(sentiment), manifold=None, db=None)
-    market = _make_market(yes_price)
-    with caplog.at_level(logging.INFO, logger="bot.strategy.bayesian"):
-        asyncio.run(strategy.evaluate(market, _make_signals(), occupied_families=set()))
-    for record in caplog.records:
-        m = NEWS_MATERIAL_RE.search(record.getMessage())
-        if m:
-            return strategy, (
-                float(m.group(1)), float(m.group(2)), m.group(3), m.group(4)
-            )
-    pytest.fail(
-        "No NEWS_MATERIAL log line found; got: "
-        f"{[r.getMessage() for r in caplog.records]}"
-    )
-
-
-# ─────────────────────────────────────────────────────────────────────────────
-# Test 1 — extreme uncorroborated shift: clamp to prior - MAX_NEWS_ONLY_PROB_SHIFT
-# ─────────────────────────────────────────────────────────────────────────────
-
-def test_extreme_news_only_shift_is_clamped(caplog):
-    """prior=0.845, raw 0.431 (NVIDIA signature) → final clamped to 0.595."""
-    strategy, (raw, final, guardrail, _) = _evaluate(
-        yes_price=0.845, sentiment=_sentiment_for(0.845, 0.431), caplog=caplog
-    )
-    assert raw == pytest.approx(0.431, abs=1e-3)
-    assert guardrail == "applied"
-    assert final >= 0.595
-    assert final == pytest.approx(0.845 - bayesian.MAX_NEWS_ONLY_PROB_SHIFT, abs=1e-3)
-    assert strategy.get_cycle_stats()["news_guardrail_applied"] == 1
-    assert strategy.get_cycle_stats()["news_with_material"] == 1
-
-
-# ─────────────────────────────────────────────────────────────────────────────
-# Test 2 — moderate shift inside the band: passes through untouched
-# ─────────────────────────────────────────────────────────────────────────────
-
-def test_moderate_news_shift_inside_band_not_clamped(caplog):
-    """prior=0.50, raw 0.62 → within ±0.25 band → final=0.62, no clamp."""
-    strategy, (raw, final, guardrail, _) = _evaluate(
-        yes_price=0.50, sentiment=_sentiment_for(0.50, 0.62), caplog=caplog
-    )
-    assert raw == pytest.approx(0.62, abs=1e-3)
-    assert final == pytest.approx(0.62, abs=1e-3)
-    assert guardrail == "none"
-    assert strategy.get_cycle_stats()["news_guardrail_applied"] == 0
-    # Still counted as a material-news market for the NEWS SUMMARY.
-    assert strategy.get_cycle_stats()["news_with_material"] == 1
-
-
-# ─────────────────────────────────────────────────────────────────────────────
-# Test 3 — corroboration: any other material signal disables the fuse
-# ─────────────────────────────────────────────────────────────────────────────
-
-def test_corroborated_news_not_clamped():
-    """GNews material + another signal >= threshold → raw passes without clamp."""
-    news_lo = _logodds(0.20) - _logodds(0.50)  # ≈ -1.386, clearly material
-    final, applied = apply_news_guardrail(
-        prior=0.50,
-        raw_final_prob=0.20,
-        feat_news_lo=news_lo,
-        other_feats_lo=(0.0, 0.15, 0.0, 0.0),  # one corroborating signal
-    )
-    assert final == 0.20
-    assert applied is False
-
-
-def test_corroboration_threshold_is_inclusive():
-    """|other| == threshold exactly counts as corroboration (>=, not >)."""
-    final, applied = apply_news_guardrail(
-        prior=0.50,
-        raw_final_prob=0.20,
-        feat_news_lo=-1.386,
-        other_feats_lo=(bayesian.NEWS_MATERIAL_LOGODDS_THRESHOLD, 0.0, 0.0, 0.0),
-    )
-    assert final == 0.20
-    assert applied is False
-
-
-def test_uncorroborated_helper_clamps():
-    """Same shift with only noise elsewhere → clamped to prior - 0.25."""
-    final, applied = apply_news_guardrail(
-        prior=0.50,
-        raw_final_prob=0.20,
-        feat_news_lo=-1.386,
-        other_feats_lo=(0.05, -0.09, 0.0, 0.0),  # all below threshold → noise
-    )
-    assert final == pytest.approx(0.25)
-    assert applied is True
-
-
-def test_sub_material_news_never_clamped():
-    """|news_lo| below threshold → fuse not armed, whatever the shift."""
-    final, applied = apply_news_guardrail(
-        prior=0.50,
-        raw_final_prob=0.10,
-        feat_news_lo=0.09,
-        other_feats_lo=(0.0, 0.0, 0.0, 0.0),
-    )
-    assert final == 0.10
-    assert applied is False
-
-
-def test_guardrail_disabled_passthrough(monkeypatch):
-    monkeypatch.setattr(bayesian, "NEWS_GUARDRAIL_ENABLED", False)
-    final, applied = apply_news_guardrail(
-        prior=0.845,
-        raw_final_prob=0.431,
-        feat_news_lo=-1.974,
-        other_feats_lo=(0.0, 0.0, 0.0, 0.0),
-    )
-    assert final == 0.431
-    assert applied is False
-
-
-# ─────────────────────────────────────────────────────────────────────────────
-# Test 4 — changed_decision: the clamp moves the edge from tradeable to not
-# ─────────────────────────────────────────────────────────────────────────────
-
-def test_guardrail_changed_trade_decision(monkeypatch, caplog):
-    """
-    With max_shift=0.10 the clamped edge (0.10 gross, 0.06 net) falls below the
-    politics <30 d regime gate (0.08) while the raw edge (0.414 gross, 0.374
-    net) crossed it → the fuse prevented the trade → changed_decision=true.
-
-    (With the default 0.25 the clamped edge_net is 0.21, above every regime
-    minimum, so the flag can only fire with a tighter configured band.)
-    """
-    monkeypatch.setattr(bayesian, "MAX_NEWS_ONLY_PROB_SHIFT", 0.10)
-    strategy, (raw, final, guardrail, changed) = _evaluate(
-        yes_price=0.845, sentiment=_sentiment_for(0.845, 0.431), caplog=caplog
-    )
-    assert raw == pytest.approx(0.431, abs=1e-3)
-    assert final == pytest.approx(0.745, abs=1e-3)
-    assert guardrail == "applied"
-    assert changed == "true"
-    stats = strategy.get_cycle_stats()
-    assert stats["news_changed_decisions"] == 1
-    assert stats["news_guardrail_applied"] == 1
-
-
-def test_default_band_does_not_change_decision(caplog):
-    """Default 0.25 band: clamp binds but edge_net 0.21 still crosses the gate."""
-    _, (_, _, guardrail, changed) = _evaluate(
-        yes_price=0.845, sentiment=_sentiment_for(0.845, 0.431), caplog=caplog
-    )
-    assert guardrail == "applied"
-    assert changed == "false"

tests/test_news_query.py

@@ -1,77 +0,0 @@
-"""Tests for the GNews layer minor fixes.
-
-Two faults found during the GNews capture/prioritisation diagnostic:
-
-1. Hyphens/dashes in a market question reached the GNews query verbatim and,
-   because '-' is GNews's exclusion operator, produced HTTP 400
-   (e.g. "Abdul El-Sayed Michigan Democratic Primary").
-
-2. The per-cycle GNews budget counter incremented in evaluate() *before*
-   get_sentiment() checked the API key, so with no key configured the
-   [CYCLE SUMMARY] reported a phantom "gnews_queries_used: 5/5" even though
-   zero real requests left the process.
-"""
-import asyncio
-
-from bot.data.news import NewsClient
-from bot.data.external import ExternalSignals
-from bot.data.polymarket import Market
-from bot.strategy.bayesian import BayesianStrategy
-
-
-# ── Fix 1: query sanitisation ────────────────────────────────────────────────
-
-def test_build_query_strips_hyphen_that_breaks_gnews():
-    q = NewsClient._build_query(
-        "Will Abdul El-Sayed win the 2026 Michigan Democratic Primary?"
-    )
-    assert "-" not in q              # the exclusion operator must be gone
-    assert "El-Sayed" not in q
-    assert "Sayed" in q             # the meaningful token survives as its own word
-
-
-def test_build_query_strips_unicode_dashes():
-    q = NewsClient._build_query("Trump–Putin summit — final outcome")
-    assert "–" not in q and "—" not in q
-    assert "Trump" in q and "Putin" in q
-
-
-# ── Fix 2: enabled property + budget accounting ──────────────────────────────
-
-def test_enabled_reflects_api_key(monkeypatch):
-    monkeypatch.delenv("GNEWS_API_KEY", raising=False)
-    assert NewsClient().enabled is False
-    monkeypatch.setenv("GNEWS_API_KEY", "deadbeefdeadbeefdeadbeefdeadbeef")
-    assert NewsClient().enabled is True
-
-
-def _politics_market() -> Market:
-    return Market(
-        id="m1", condition_id="c1",
-        question="Will candidate X win the 2026 governor election?",
-        yes_token_id="y", no_token_id="n",
-        yes_price=0.50, no_price=0.50, volume_24h=10_000.0,
-        end_date="2026-07-15T00:00:00Z", active=True, category="politics",
-    )
-
-
-def _signals() -> ExternalSignals:
-    return ExternalSignals(
-        btc_price=1.0, btc_change_24h=0.0, eth_price=1.0, eth_change_24h=0.0,
-        btc_dominance=50.0, fear_greed_index=50, fear_greed_label="neutral",
-        total_market_cap_change=0.0, valid=True,
-    )
-
-
-def test_disabled_news_consumes_no_gnews_budget(monkeypatch):
-    """Regression: no API key → gnews_queries_used stays 0 (was a phantom 1+)."""
-    monkeypatch.delenv("GNEWS_API_KEY", raising=False)
-    news = NewsClient()
-    assert news.enabled is False
-
-    strategy = BayesianStrategy(news=news, manifold=None, db=None)
-    strategy.reset_cycle()
-    asyncio.run(
-        strategy.evaluate(_politics_market(), _signals(), occupied_families=set())
-    )
-    assert strategy.get_cycle_stats()["gnews_queries_used"] == 0