REFACTOR ALL APIs
This commit is contained in:
Urtzi Alfaro
367
services/inventory/app/api/inventory_operations.py
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367
services/inventory/app/api/inventory_operations.py
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# services/inventory/app/api/inventory_operations.py
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"""
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Inventory Operations API - Business operations for inventory management
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"""
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from typing import List, Optional, Dict, Any
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from uuid import UUID, uuid4
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from fastapi import APIRouter, Depends, HTTPException, Query, Path, status
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from sqlalchemy.ext.asyncio import AsyncSession
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from pydantic import BaseModel, Field
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import structlog
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from app.core.database import get_db
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from app.services.inventory_service import InventoryService
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from app.services.product_classifier import ProductClassifierService, get_product_classifier
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from shared.auth.decorators import get_current_user_dep
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from shared.auth.access_control import require_user_role
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from shared.routing import RouteBuilder
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logger = structlog.get_logger()
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route_builder = RouteBuilder('inventory')
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router = APIRouter(tags=["inventory-operations"])
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def get_current_user_id(current_user: dict = Depends(get_current_user_dep)) -> UUID:
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"""Extract user ID from current user context"""
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user_id = current_user.get('user_id')
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if not user_id:
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if current_user.get('type') == 'service':
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return None
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raise HTTPException(
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status_code=status.HTTP_401_UNAUTHORIZED,
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detail="User ID not found in context"
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)
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try:
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return UUID(user_id)
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except (ValueError, TypeError):
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return None
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# ===== Stock Operations =====
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@router.post(
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route_builder.build_operations_route("consume-stock"),
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response_model=dict
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)
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@require_user_role(['admin', 'owner', 'member'])
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async def consume_stock(
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tenant_id: UUID = Path(..., description="Tenant ID"),
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ingredient_id: UUID = Query(..., description="Ingredient ID to consume"),
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quantity: float = Query(..., gt=0, description="Quantity to consume"),
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reference_number: Optional[str] = Query(None, description="Reference number"),
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notes: Optional[str] = Query(None, description="Additional notes"),
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fifo: bool = Query(True, description="Use FIFO method"),
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current_user: dict = Depends(get_current_user_dep),
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db: AsyncSession = Depends(get_db)
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):
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"""Consume stock for production"""
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try:
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user_id = get_current_user_id(current_user)
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service = InventoryService()
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consumed_items = await service.consume_stock(
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ingredient_id, quantity, tenant_id, user_id, reference_number, notes, fifo
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)
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return {
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"ingredient_id": str(ingredient_id),
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"total_quantity_consumed": quantity,
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"consumed_items": consumed_items,
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"method": "FIFO" if fifo else "LIFO"
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}
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except ValueError as e:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=str(e)
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)
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except Exception as e:
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail="Failed to consume stock"
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)
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@router.get(
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route_builder.build_operations_route("stock/expiring"),
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response_model=List[dict]
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)
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async def get_expiring_stock(
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tenant_id: UUID = Path(..., description="Tenant ID"),
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days_ahead: int = Query(7, ge=1, le=365, description="Days ahead to check"),
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current_user: dict = Depends(get_current_user_dep),
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db: AsyncSession = Depends(get_db)
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):
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"""Get stock items expiring within specified days"""
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try:
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service = InventoryService()
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expiring_items = await service.check_expiration_alerts(tenant_id, days_ahead)
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return expiring_items
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except Exception as e:
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail="Failed to get expiring stock"
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)
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@router.get(
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route_builder.build_operations_route("stock/low-stock"),
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response_model=List[dict]
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)
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async def get_low_stock(
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tenant_id: UUID = Path(..., description="Tenant ID"),
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current_user: dict = Depends(get_current_user_dep),
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db: AsyncSession = Depends(get_db)
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):
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"""Get ingredients with low stock levels"""
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try:
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service = InventoryService()
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low_stock_items = await service.check_low_stock_alerts(tenant_id)
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return low_stock_items
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except Exception as e:
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail="Failed to get low stock items"
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)
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@router.get(
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route_builder.build_operations_route("stock/summary"),
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response_model=dict
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)
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async def get_stock_summary(
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tenant_id: UUID = Path(..., description="Tenant ID"),
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current_user: dict = Depends(get_current_user_dep),
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db: AsyncSession = Depends(get_db)
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):
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"""Get stock summary for tenant"""
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try:
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service = InventoryService()
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summary = await service.get_inventory_summary(tenant_id)
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return summary.dict()
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except Exception as e:
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail="Failed to get stock summary"
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)
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# ===== Product Classification Operations =====
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class ProductClassificationRequest(BaseModel):
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"""Request for single product classification"""
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product_name: str = Field(..., description="Product name to classify")
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sales_volume: float = Field(None, description="Total sales volume for context")
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sales_data: Dict[str, Any] = Field(default_factory=dict, description="Additional sales context")
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class BatchClassificationRequest(BaseModel):
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"""Request for batch product classification"""
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products: List[ProductClassificationRequest] = Field(..., description="Products to classify")
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class ProductSuggestionResponse(BaseModel):
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"""Response with product classification suggestion"""
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suggestion_id: str
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original_name: str
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suggested_name: str
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product_type: str
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category: str
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unit_of_measure: str
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confidence_score: float
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estimated_shelf_life_days: Optional[int] = None
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requires_refrigeration: bool = False
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requires_freezing: bool = False
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is_seasonal: bool = False
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suggested_supplier: Optional[str] = None
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notes: Optional[str] = None
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class BusinessModelAnalysisResponse(BaseModel):
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"""Response with business model analysis"""
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model: str
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confidence: float
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ingredient_count: int
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finished_product_count: int
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ingredient_ratio: float
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recommendations: List[str]
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class BatchClassificationResponse(BaseModel):
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"""Response for batch classification"""
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suggestions: List[ProductSuggestionResponse]
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business_model_analysis: BusinessModelAnalysisResponse
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total_products: int
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high_confidence_count: int
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low_confidence_count: int
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@router.post(
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route_builder.build_operations_route("classify-product"),
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response_model=ProductSuggestionResponse
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)
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async def classify_single_product(
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request: ProductClassificationRequest,
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tenant_id: UUID = Path(..., description="Tenant ID"),
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current_user: Dict[str, Any] = Depends(get_current_user_dep),
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classifier: ProductClassifierService = Depends(get_product_classifier)
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):
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"""Classify a single product for inventory creation"""
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try:
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suggestion = classifier.classify_product(
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request.product_name,
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request.sales_volume
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)
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response = ProductSuggestionResponse(
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suggestion_id=str(uuid4()),
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original_name=suggestion.original_name,
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suggested_name=suggestion.suggested_name,
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product_type=suggestion.product_type.value,
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category=suggestion.category,
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unit_of_measure=suggestion.unit_of_measure.value,
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confidence_score=suggestion.confidence_score,
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estimated_shelf_life_days=suggestion.estimated_shelf_life_days,
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requires_refrigeration=suggestion.requires_refrigeration,
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requires_freezing=suggestion.requires_freezing,
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is_seasonal=suggestion.is_seasonal,
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suggested_supplier=suggestion.suggested_supplier,
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notes=suggestion.notes
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)
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logger.info("Classified single product",
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product=request.product_name,
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classification=suggestion.product_type.value,
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confidence=suggestion.confidence_score,
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tenant_id=tenant_id)
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return response
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except Exception as e:
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logger.error("Failed to classify product",
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error=str(e), product=request.product_name, tenant_id=tenant_id)
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raise HTTPException(status_code=500, detail=f"Classification failed: {str(e)}")
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@router.post(
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route_builder.build_operations_route("classify-products-batch"),
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response_model=BatchClassificationResponse
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)
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async def classify_products_batch(
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request: BatchClassificationRequest,
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tenant_id: UUID = Path(..., description="Tenant ID"),
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current_user: Dict[str, Any] = Depends(get_current_user_dep),
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classifier: ProductClassifierService = Depends(get_product_classifier)
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):
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"""Classify multiple products for onboarding automation"""
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try:
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if not request.products:
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raise HTTPException(status_code=400, detail="No products provided for classification")
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product_names = [p.product_name for p in request.products]
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sales_volumes = {p.product_name: p.sales_volume for p in request.products if p.sales_volume}
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suggestions = classifier.classify_products_batch(product_names, sales_volumes)
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suggestion_responses = []
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for suggestion in suggestions:
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suggestion_responses.append(ProductSuggestionResponse(
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suggestion_id=str(uuid4()),
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original_name=suggestion.original_name,
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suggested_name=suggestion.suggested_name,
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product_type=suggestion.product_type.value,
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category=suggestion.category,
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unit_of_measure=suggestion.unit_of_measure.value,
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confidence_score=suggestion.confidence_score,
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estimated_shelf_life_days=suggestion.estimated_shelf_life_days,
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requires_refrigeration=suggestion.requires_refrigeration,
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requires_freezing=suggestion.requires_freezing,
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is_seasonal=suggestion.is_seasonal,
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suggested_supplier=suggestion.suggested_supplier,
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notes=suggestion.notes
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))
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# Analyze business model
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ingredient_count = sum(1 for s in suggestions if s.product_type.value == 'ingredient')
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finished_count = sum(1 for s in suggestions if s.product_type.value == 'finished_product')
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semi_finished_count = sum(1 for s in suggestions if 'semi' in s.suggested_name.lower() or 'frozen' in s.suggested_name.lower() or 'pre' in s.suggested_name.lower())
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total = len(suggestions)
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ingredient_ratio = ingredient_count / total if total > 0 else 0
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semi_finished_ratio = semi_finished_count / total if total > 0 else 0
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if ingredient_ratio >= 0.7:
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model = 'individual_bakery'
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elif ingredient_ratio <= 0.2 and semi_finished_ratio >= 0.3:
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model = 'central_baker_satellite'
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elif ingredient_ratio <= 0.3:
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model = 'retail_bakery'
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else:
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model = 'hybrid_bakery'
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if model == 'individual_bakery':
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confidence = min(ingredient_ratio * 1.2, 0.95)
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elif model == 'central_baker_satellite':
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confidence = min((semi_finished_ratio + (1 - ingredient_ratio)) / 2 * 1.2, 0.95)
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else:
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confidence = max(abs(ingredient_ratio - 0.5) * 2, 0.1)
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recommendations = {
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'individual_bakery': [
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'Set up raw ingredient inventory management',
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'Configure recipe cost calculation and production planning',
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'Enable supplier relationships for flour, yeast, sugar, etc.',
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'Set up full production workflow with proofing and baking schedules',
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'Enable waste tracking for overproduction'
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],
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'central_baker_satellite': [
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'Configure central baker delivery schedules',
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'Set up semi-finished product inventory (frozen dough, par-baked items)',
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'Enable finish-baking workflow and timing optimization',
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'Track freshness and shelf-life for received products',
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'Focus on customer demand forecasting for final products'
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],
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'retail_bakery': [
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'Set up finished product supplier relationships',
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'Configure delivery schedule tracking',
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'Enable freshness monitoring and expiration management',
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'Focus on sales forecasting and customer preferences'
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],
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'hybrid_bakery': [
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'Configure both ingredient and semi-finished product management',
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'Set up flexible production workflows',
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'Enable both supplier and central baker relationships',
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'Configure multi-tier inventory categories'
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]
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}
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business_model_analysis = BusinessModelAnalysisResponse(
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model=model,
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confidence=confidence,
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ingredient_count=ingredient_count,
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finished_product_count=finished_count,
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ingredient_ratio=ingredient_ratio,
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recommendations=recommendations.get(model, [])
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)
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high_confidence_count = sum(1 for s in suggestions if s.confidence_score >= 0.7)
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low_confidence_count = sum(1 for s in suggestions if s.confidence_score < 0.6)
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response = BatchClassificationResponse(
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suggestions=suggestion_responses,
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business_model_analysis=business_model_analysis,
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total_products=len(suggestions),
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high_confidence_count=high_confidence_count,
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low_confidence_count=low_confidence_count
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)
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logger.info("Batch classification complete",
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total_products=len(suggestions),
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business_model=model,
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high_confidence=high_confidence_count,
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low_confidence=low_confidence_count,
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tenant_id=tenant_id)
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return response
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except Exception as e:
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logger.error("Failed batch classification",
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error=str(e), products_count=len(request.products), tenant_id=tenant_id)
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raise HTTPException(status_code=500, detail=f"Batch classification failed: {str(e)}")
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