Start integrating the onboarding flow with backend 2

services/sales/app/services/data_import_service.py

@@ -26,7 +26,7 @@ logger = structlog.get_logger()
 
 
 # Import result schemas (dataclass definitions)
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from typing import List, Dict, Any
 
 @dataclass
@@ -38,6 +38,8 @@ class SalesValidationResult:
     errors: List[Dict[str, Any]]
     warnings: List[Dict[str, Any]]
     summary: Dict[str, Any]
+    unique_products: int = 0
+    product_list: List[str] = field(default_factory=list)
 
 @dataclass
 class SalesImportResult:
@@ -99,7 +101,9 @@ class DataImportService:
                 invalid_records=0,
                 errors=[],
                 warnings=[],
-                summary={}
+                summary={},
+                unique_products=0,
+                product_list=[]
             )
             
             errors = []
@@ -216,6 +220,22 @@ class DataImportService:
                                 "code": "MISSING_PRODUCT_COLUMN"
                             })
                         
+                        # Extract unique products for AI suggestions
+                        if column_mapping.get('product') and not errors:
+                            product_column = column_mapping['product']
+                            unique_products_set = set()
+                            
+                            for row in rows:
+                                product_name = row.get(product_column, '').strip()
+                                if product_name and len(product_name) > 0:
+                                    unique_products_set.add(product_name)
+                            
+                            validation_result.product_list = list(unique_products_set)
+                            validation_result.unique_products = len(unique_products_set)
+                            
+                            logger.info(f"Extracted {validation_result.unique_products} unique products from CSV", 
+                                      tenant_id=data.get("tenant_id"))
+                        
                         if not column_mapping.get('quantity'):
                             warnings.append({
                                 "type": "missing_column",