Step 2: Risk and Stops - Generating reports with pdf. It is missing to reorder the PDF.

src/web/api/v2/schemas/calibration_risk.py

@@ -0,0 +1,84 @@
+# src/web/api/v2/schemas/calibration_risk.py
+
+from typing import Literal, Optional, Dict, Any
+from pydantic import BaseModel, Field, model_validator
+
+
+
+class StopConfigSchema(BaseModel):
+    type: Literal["fixed", "trailing", "atr"]
+
+    stop_fraction: Optional[float] = Field(None, gt=0)
+    atr_period: Optional[int] = Field(None, gt=1)
+    atr_multiplier: Optional[float] = Field(None, gt=0)
+
+    @model_validator(mode="after")
+    def validate_by_type(self):
+        if self.type in ("fixed", "trailing"):
+            if self.stop_fraction is None:
+                raise ValueError(
+                    "stop_fraction required for fixed/trailing stop"
+                )
+
+        if self.type == "atr":
+            if self.atr_period is None:
+                raise ValueError(
+                    "atr_period required for ATR stop"
+                )
+            if self.atr_multiplier is None:
+                raise ValueError(
+                    "atr_multiplier required for ATR stop"
+                )
+
+        return self
+
+
+# class StopConfigSchema(BaseModel):
+#     type: Literal["fixed", "trailing", "atr"]
+
+#     stop_fraction: Optional[float] = Field(None, gt=0)
+
+#     atr_period: Optional[int] = Field(None, gt=1)
+#     atr_multiplier: Optional[float] = Field(None, gt=0)
+
+
+class RiskConfigSchema(BaseModel):
+    risk_fraction: float = Field(..., gt=0, lt=1)
+    max_position_fraction: float = Field(..., gt=0, lt=1)
+
+
+class GlobalRiskRulesSchema(BaseModel):
+    max_drawdown_pct: float = Field(..., gt=0, lt=1)
+
+    daily_loss_limit_pct: Optional[float] = Field(None, gt=0, lt=1)
+    max_consecutive_losses: Optional[int] = Field(None, gt=0)
+    cooldown_bars: Optional[int] = Field(None, ge=0)
+
+
+class CalibrationRiskInspectRequest(BaseModel):
+    symbol: str
+    timeframe: str
+
+    stop: StopConfigSchema
+    risk: RiskConfigSchema
+    global_rules: GlobalRiskRulesSchema
+
+    account_equity: float = Field(..., gt=0)
+
+
+class CalibrationRiskInspectResponse(BaseModel):
+    valid: bool
+    status: Literal["ok", "warning", "fail"]
+
+    checks: Dict[str, Any]
+    message: str
+
+class CalibrationRiskValidateResponse(BaseModel):
+    valid: bool
+    status: Literal["ok", "warning", "fail"]
+
+    checks: Dict[str, Any]
+    message: str
+
+    # ⬇️ NUEVO
+    series: Dict[str, Any]