c762564d40
- Fix 71 invalid-syntax files (class-body newline-broken assignments) - Add from/None chain to 307 B904 raise-without-from sites - Add B008 ignore to ruff.toml (already in pyproject.toml) - Noqa F401 on __init__.py re-exports (137 sites) - Noqa E402 on deferred imports (63 sites) - Bulk-add stdlib/FastAPI/project imports for F821 (127 sites) - Replace ×→x, –→-, …→... in docstrings (4093 chars) - Manual refactor of 5 SIM103/SIM116 patterns Tests: 791 passed (66 deselected due to pre-existing Redis issues in test_rag.py) Co-authored-by: opencode <opencode@rugmunch.io>
276 lines
9 KiB
Python
276 lines
9 KiB
Python
"""
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Intelligence Panel Router
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=========================
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Endpoints for the intelligence feed panel on rugmunch.io/intelligence
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Data sources:
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- News service (200+ crypto news sources, 15 tiers)
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- Security alerts (rug detection, whale tracking)
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- Prediction market signals (Polymarket, Kalshi, Limitless, Manifold)
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- Crypto Fear Index (aggregated risk from prediction markets)
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- Bulletin posts (community intelligence)
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"""
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from datetime import UTC, datetime
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from fastapi import APIRouter, Query
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from pydantic import BaseModel
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from app.core.logging import get_logger
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logger = get_logger(__name__)
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router = APIRouter(prefix="/api/v1/intelligence", tags=["intelligence-panel"])
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# Import prediction market intelligence (LAZY - deferred to first request)
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pm_intel = None
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_pm_intel_loaded = False
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def _get_pm_intel():
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global pm_intel, _pm_intel_loaded
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if _pm_intel_loaded:
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return pm_intel
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_pm_intel_loaded = True
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try:
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from app.services.prediction_market_intel import (
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get_prediction_market_intel,
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)
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pm_intel = get_prediction_market_intel()
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except ImportError:
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pm_intel = None
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return pm_intel
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class IntelSignalResponse(BaseModel):
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signal_type: str
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severity: str
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headline: str
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insight: str
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action: str
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confidence: float
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generated_at: str
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class FearIndexResponse(BaseModel):
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overall_risk: float
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exploit_risk: float
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regulatory_risk: float
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stablecoin_risk: float
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exchange_risk: float
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generated_at: str
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class IntelligenceItem(BaseModel):
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id: str
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title: str
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content: str | None = None
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url: str | None = None
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source: str
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published_at: str
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category: str
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kind: str
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highlight: bool | None = False
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severity: str | None = None
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class IntelligenceFeedResponse(BaseModel):
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items: list[IntelligenceItem]
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count: int
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timestamp: str
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# ── Prediction Market Intelligence ─────────────────────────
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@router.get("/prediction-signals", response_model=list[IntelSignalResponse])
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async def get_prediction_signals(limit: int = Query(10, ge=1, le=20)):
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"""Get actionable intelligence signals from prediction markets.
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Signal types:
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- HIGH_CONSENSUS_THREAT: Markets strongly expect an adverse event
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- LOW_CONSENSUS_RISK: Markets dismiss a feared risk
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- TOKEN_RISK_SIGNAL: Specific token flagged by prediction markets
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- ECOSYSTEM_RISK: Broad ecosystem-level threat indicator
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Each signal includes: severity, plain-English insight, recommended action.
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"""
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_get_pm_intel()
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if not pm_intel:
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return []
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signals = await pm_intel.generate_signals(max_signals=limit)
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return [
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IntelSignalResponse(
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signal_type=s.signal_type,
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severity=s.severity,
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headline=s.headline,
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insight=s.insight,
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action=s.action,
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confidence=round(s.confidence, 2),
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generated_at=s.generated_at,
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)
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for s in signals
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]
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@router.get("/crypto-fear-index", response_model=FearIndexResponse)
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async def get_crypto_fear_index():
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"""Get the Crypto Fear Index - risk aggregated from prediction markets.
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Components:
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- overall_risk: Weighted aggregate of all categories
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- exploit_risk: DeFi hack/exploit/vulnerability probability
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- regulatory_risk: SEC/CFTC/enforcement action probability
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- stablecoin_risk: Depeg/collapse probability
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- exchange_risk: Insolvency/breach probability
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Derived from live prediction market data across Polymarket, Kalshi, Limitless, Manifold.
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Higher = more risk priced in by traders with real money at stake.
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"""
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_get_pm_intel()
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if not pm_intel:
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return FearIndexResponse(
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overall_risk=0,
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exploit_risk=0,
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regulatory_risk=0,
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stablecoin_risk=0,
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exchange_risk=0,
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generated_at=datetime.now(UTC).isoformat(),
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)
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fear = await pm_intel.generate_crypto_fear_index()
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return FearIndexResponse(
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overall_risk=fear.overall_risk,
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exploit_risk=fear.exploit_risk,
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regulatory_risk=fear.regulatory_risk,
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stablecoin_risk=fear.stablecoin_risk,
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exchange_risk=fear.exchange_risk,
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generated_at=fear.generated_at,
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)
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# ── Aggregated Feed ────────────────────────────────────────
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@router.get("/feed", response_model=IntelligenceFeedResponse)
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async def get_intelligence_feed(limit: int = Query(20, ge=1, le=50)):
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"""Get aggregated intelligence feed combining all sources."""
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_get_pm_intel()
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items = []
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now_ts = datetime.now(UTC).isoformat()
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# 1. Prediction market signals (highest priority - forward-looking)
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if pm_intel:
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try:
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signals = await pm_intel.generate_signals(max_signals=5)
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for s in signals:
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severity = s.severity
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items.append(
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IntelligenceItem(
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id=f"pm-{s.signal_type}-{now_ts}",
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title=s.headline,
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content=s.insight,
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url="/intelligence",
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source=f"Prediction Markets ({s.signal_type.replace('_', ' ').title()})",
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published_at=now_ts,
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category="prediction-market",
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kind="signal",
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highlight=(severity in ("critical", "high")),
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severity=severity,
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)
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)
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except Exception as e:
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logger.info(f"Prediction market signals unavailable: {e}")
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# 2. Crypto Fear Index summary
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if pm_intel:
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try:
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fear = await pm_intel.generate_crypto_fear_index()
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risk_label = (
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"EXTREME FEAR"
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if fear.overall_risk >= 75
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else "FEAR"
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if fear.overall_risk >= 50
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else "NEUTRAL"
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if fear.overall_risk >= 25
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else "GREED"
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if fear.overall_risk >= 10
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else "EXTREME GREED"
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)
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items.append(
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IntelligenceItem(
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id=f"fear-index-{now_ts}",
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title=f"Crypto Fear Index: {fear.overall_risk:.0f}/100 - {risk_label}",
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content=(
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f"Exploit risk: {fear.exploit_risk:.0f}/100 | "
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f"Regulatory: {fear.regulatory_risk:.0f}/100 | "
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f"Stablecoin: {fear.stablecoin_risk:.0f}/100 | "
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f"Exchange: {fear.exchange_risk:.0f}/100. "
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f"Derived from live Polymarket + Kalshi + Manifold prediction markets."
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),
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url="/intelligence",
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source="Crypto Fear Index",
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published_at=now_ts,
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category="risk-index",
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kind="index",
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highlight=(fear.overall_risk >= 50),
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severity="high" if fear.overall_risk >= 50 else "medium",
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)
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)
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except Exception as e:
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logger.info(f"Crypto Fear Index unavailable: {e}")
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# 3. Prediction market data sources status
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items.append(
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IntelligenceItem(
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id=f"sources-{now_ts}",
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title="Prediction Market Intelligence Active - 4 Sources Live",
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content="RMI now monitors Polymarket, Kalshi, Limitless, and Manifold for crypto security signals. Live risk indicators, token threat detection, and ecosystem monitoring are online.",
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url="/intelligence",
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source="RMI System",
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published_at=now_ts,
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category="system",
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kind="status",
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highlight=False,
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)
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)
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return IntelligenceFeedResponse(
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items=items[:limit],
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count=min(len(items), limit),
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timestamp=now_ts,
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)
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@router.get("/latest")
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async def get_latest_intelligence():
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"""Get latest intelligence snapshot for quick updates."""
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_get_pm_intel()
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latest = {
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"timestamp": datetime.now(UTC).isoformat(),
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}
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if pm_intel:
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try:
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signals = await pm_intel.generate_signals(max_signals=3)
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if signals:
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top = signals[0]
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latest["top_signal"] = {
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"headline": top.headline,
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"severity": top.severity,
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"insight": top.insight,
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"action": top.action,
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}
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fear = await pm_intel.generate_crypto_fear_index()
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latest["fear_index"] = {
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"overall": fear.overall_risk,
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"exploit": fear.exploit_risk,
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"regulatory": fear.regulatory_risk,
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"stablecoin": fear.stablecoin_risk,
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"exchange": fear.exchange_risk,
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}
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except Exception as e:
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latest["error"] = str(e)
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return latest
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