File size: 3,230 Bytes
0a1d03f 57331b8 847392c 212462e 847392c 18afae5 847392c 9e1b2d4 94062ea 0a1d03f 94062ea 0a1d03f 94062ea 0a1d03f 9e1b2d4 ecfd501 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 |
from pydantic import BaseModel, Field, validator
from typing import Optional, List
from datetime import datetime
from enum import Enum
class ExpenseType(str, Enum):
INCOME = "income"
EXPENSE = "expense"
class Expense(BaseModel):
user_id: str
amount: float = Field(..., gt=0, description="Expense amount")
category: str = Field(..., description="Expense category (e.g., Groceries, Transport)")
description: Optional[str] = None
date: datetime
type: ExpenseType = ExpenseType.EXPENSE
class Budget(BaseModel):
user_id: str
category: str
amount: float = Field(..., gt=0, description="Budget amount")
period: str = Field(..., description="Budget period: daily, weekly, monthly, yearly")
start_date: datetime
end_date: Optional[datetime] = None
class BudgetRecommendation(BaseModel):
category: str = Field(..., description="Category name (e.g., Groceries, Transport)")
category_id: Optional[str] = Field(None, description="Category ID from database")
average_expense: float
recommended_budget: float
reason: str
confidence: float = Field(..., ge=0, le=1, description="Confidence score (0-1)")
action: Optional[str] = Field(
None,
description="AI suggestion: increase, decrease, or keep"
)
class CategoryExpense(BaseModel):
category: str
average_monthly_expense: float
total_expenses: int
months_analyzed: int
class RecommendationRequest(BaseModel):
user_id: str = Field(..., description="User identifier")
category_id: str = Field(..., description="Category ID to check for previous data")
budget_amount: Optional[float] = Field(None, gt=0, description="Current budget amount for this category (optional)")
@validator('budget_amount')
def validate_budget_amount(cls, v):
if v is not None:
if v <= 0:
raise ValueError('budget_amount must be greater than 0')
# Auto-cap unreasonably large numbers instead of rejecting
# This handles corrupted data gracefully - cap at 1 trillion
if v > 1e12: # More than 1 trillion is likely corrupted data
print(f"⚠️ Auto-capping corrupted budget_amount: {v:,.2e} -> 1,000,000,000,000")
return 1e12 # Cap at 1 trillion instead of rejecting
return v
class RecommendationResponse(BaseModel):
has_previous_data: bool
message: Optional[str] = None
recommendations: Optional[List[BudgetRecommendation]] = None
class RecommendationByNameRequest(BaseModel):
user_id: str = Field(..., description="User identifier")
category_name: str = Field(..., description="Head Category name (e.g., 'Food & Drinks', 'Shopping', 'Housing')")
budget_amount: Optional[float] = Field(None, gt=0, description="Current budget amount for this category (optional)")
@validator('budget_amount')
def validate_budget_amount(cls, v):
if v is not None:
if v <= 0:
raise ValueError('budget_amount must be greater than 0')
if v > 1e12:
print(f"⚠️ Auto-capping corrupted budget_amount: {v:,.2e} -> 1,000,000,000,000")
return 1e12
return v
|