| from pydantic import BaseModel, Field
|
| from typing import List, Optional
|
|
|
| class ESGFirmBase(BaseModel):
|
| """The core data structure for an ESG record."""
|
| Firm_ID: str = Field(..., example="FIRM_001")
|
| Year: int = Field(..., example=2024)
|
| Industry_Type: str = Field(..., example="Manufacturing")
|
| E_Score: float = Field(..., ge=0, le=100)
|
| S_Score: float = Field(..., ge=0, le=100)
|
| G_Score: float = Field(..., ge=0, le=100)
|
| Board_Independence: float = Field(..., ge=0, le=1.0)
|
|
|
| class ESGRiskResponse(ESGFirmBase):
|
| """Data returned when checking risk levels."""
|
| final_esg_risk_score: Optional[float] = None
|
| alert_level: Optional[str] = Field(None, example="Critical")
|
| Overall_Compliance: Optional[str] = "Compliant"
|
|
|
| class RiskSummary(BaseModel):
|
| """Structure for the dashboard 'Risk Summary' widget."""
|
| Critical: int = 0
|
| Warning: int = 0
|
| Low: int = 0
|
|
|
| class PredictionRequest(BaseModel):
|
| """Input for the Machine Learning prediction agent."""
|
| risk_score: float
|
| |
