Initial commit — GeoOptions Intelligence Cockpit v2.0

Stack: FastAPI + React/TypeScript + SQLite + GPT-4o
Features: Radar géopolitique, Marchés, Régime Macro, Journal de Bord MTM,
Rapport IA, Super Contexte (base de raisonnement évolutive), Boucle feedback IA.
Deploy: Docker + docker-compose + nginx pour openfin.open-squared.tech

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/models/schemas.py

@@ -0,0 +1,155 @@
+from pydantic import BaseModel
+from typing import Optional, List, Dict, Any
+from datetime import datetime
+from enum import Enum
+
+
+class AssetClass(str, Enum):
+    ENERGY = "energy"
+    METALS = "metals"
+    AGRICULTURE = "agriculture"
+    EQUITIES = "equities"
+    INDICES = "indices"
+    FOREX = "forex"
+    CRYPTO = "crypto"
+    RATES = "rates"
+
+
+class RiskLevel(str, Enum):
+    LOW = "low"
+    MEDIUM = "medium"
+    HIGH = "high"
+    EXTREME = "extreme"
+
+
+class GeopoliticalCategory(str, Enum):
+    MILITARY = "military"
+    SANCTIONS = "sanctions"
+    ELECTIONS = "elections"
+    NATURAL_DISASTER = "natural_disaster"
+    HEALTH_CRISIS = "health_crisis"
+    RESOURCE_SCARCITY = "resource_scarcity"
+    TRADE_WAR = "trade_war"
+    ENERGY_CRISIS = "energy_crisis"
+    POLITICAL_SPEECH = "political_speech"
+    FINANCIAL_CRISIS = "financial_crisis"
+
+
+class GeoEvent(BaseModel):
+    id: str
+    title: str
+    summary: str
+    category: GeopoliticalCategory
+    date: datetime
+    source: str
+    impact_score: float  # -1.0 to 1.0
+    asset_impacts: Dict[AssetClass, float]  # impact per asset class
+    tags: List[str]
+    is_processed: bool = False
+
+
+class MarketQuote(BaseModel):
+    symbol: str
+    name: str
+    price: float
+    change: float
+    change_pct: float
+    volume: int
+    iv: Optional[float] = None  # implied volatility
+    asset_class: AssetClass
+    timestamp: datetime
+
+
+class OptionsContract(BaseModel):
+    symbol: str
+    underlying: str
+    expiry: str
+    strike: float
+    option_type: str  # call / put
+    bid: float
+    ask: float
+    last: float
+    volume: int
+    open_interest: int
+    iv: float
+    delta: float
+    gamma: float
+    theta: float
+    vega: float
+    rho: float
+
+
+class TradeIdea(BaseModel):
+    id: str
+    title: str
+    rationale: str
+    asset_class: AssetClass
+    underlying: str
+    strategy: str  # e.g. "Bull Call Spread", "Long Put", "Straddle"
+    legs: List[Dict[str, Any]]
+    max_loss: float
+    max_gain: Optional[float]
+    breakeven: List[float]
+    horizon_days: int
+    confidence: float  # 0-100
+    geo_trigger: Optional[str]
+    risk_level: RiskLevel
+    capital_required: float
+    created_at: datetime
+
+
+class BacktestParams(BaseModel):
+    start_date: str
+    end_date: str
+    strategy: str
+    underlying: str
+    geo_filters: Optional[List[GeopoliticalCategory]] = None
+    capital: float = 1000.0
+
+
+class BacktestResult(BaseModel):
+    params: BacktestParams
+    trades: List[Dict[str, Any]]
+    total_return: float
+    win_rate: float
+    max_drawdown: float
+    sharpe_ratio: float
+    profit_factor: float
+    equity_curve: List[Dict[str, Any]]
+
+
+class EconomicEvent(BaseModel):
+    id: str
+    title: str
+    country: str
+    date: datetime
+    importance: str  # low / medium / high
+    previous: Optional[str]
+    forecast: Optional[str]
+    actual: Optional[str]
+    asset_impact: List[AssetClass]
+
+
+class PortfolioPosition(BaseModel):
+    id: str
+    trade_idea_id: Optional[str]
+    symbol: str
+    strategy: str
+    entry_date: datetime
+    expiry: str
+    legs: List[Dict[str, Any]]
+    capital_invested: float
+    current_value: float
+    pnl: float
+    pnl_pct: float
+    status: str  # open / closed / expired
+
+
+class GeoPatternMatch(BaseModel):
+    pattern_id: str
+    description: str
+    historical_date: datetime
+    current_similarity: float
+    historical_outcome: str
+    suggested_trades: List[str]
+    asset_class: AssetClass