update config

app.py

@@ -97,13 +97,31 @@ def calculate_stockout_forecast(method, api_token):
         # Get current inventory (demo data if API unavailable)
         wb_client = initialize_wb_client(api_token)
         
-        if wb_client:
-            inventory_data = wb_client.get_stocks()
+        # Determine if we're in demo mode
+        use_demo_mode = not api_token or api_token.strip() == ""
+        
+        if wb_client and not use_demo_mode:
+            try:
+                inventory_data = wb_client.get_stocks()
+                # If API returns empty data, fall back to demo
+                if inventory_data.empty:
+                    inventory_data = utils.load_demo_inventory_data()
+                    use_demo_mode = True
+            except Exception:
+                inventory_data = utils.load_demo_inventory_data()
+                use_demo_mode = True
         else:
             inventory_data = utils.load_demo_inventory_data()
+            use_demo_mode = True
         
-        # Get sales data for forecasting
-        sales_data = get_sales_data("month", api_token)
+        # Get sales data for forecasting - ensure consistency with inventory data source
+        if use_demo_mode:
+            sales_data = utils.load_demo_sales_data("month")
+        else:
+            sales_data = get_sales_data("month", api_token)
+            # If API sales data is empty, fall back to demo
+            if sales_data.empty:
+                sales_data = utils.load_demo_sales_data("month")
         
         # Initialize forecaster
         forecaster = InventoryForecaster()
@@ -113,52 +131,66 @@ def calculate_stockout_forecast(method, api_token):
         for _, item in inventory_data.iterrows():
             product_sales = sales_data[sales_data['product_id'] == item['product_id']]
             
-            if not product_sales.empty:
-                if method == "simple":
-                    days_left = forecaster.simple_division_method(
-                        item['current_stock'], 
-                        product_sales['quantity'].mean()
-                    )
-                elif method == "safety_stock":
-                    days_left = forecaster.safety_stock_method(
-                        item['current_stock'],
-                        product_sales['quantity'].mean(),
-                        product_sales['quantity'].max(),
-                        avg_lead_time=7,
-                        max_lead_time=14
-                    )
-                elif method == "weighted":
+            # If no sales data for this product, use average daily sales of 1
+            if product_sales.empty:
+                avg_daily_sales = 1
+                max_daily_sales = 1
+            else:
+                avg_daily_sales = product_sales['quantity'].mean()
+                max_daily_sales = product_sales['quantity'].max()
+            
+            if method == "simple":
+                days_left = forecaster.simple_division_method(
+                    item['current_stock'], 
+                    avg_daily_sales
+                )
+            elif method == "safety_stock":
+                days_left = forecaster.safety_stock_method(
+                    item['current_stock'],
+                    avg_daily_sales,
+                    max_daily_sales,
+                    avg_lead_time=7,
+                    max_lead_time=14
+                )
+            elif method == "weighted":
+                if not product_sales.empty:
                     days_left = forecaster.weighted_average_method(
                         item['current_stock'],
                         product_sales
                     )
                 else:
-                    days_left = forecaster.seasonal_adjustment_method(
+                    days_left = forecaster.simple_division_method(
                         item['current_stock'],
-                        product_sales['quantity'].mean(),
-                        seasonal_factor=1.0
+                        avg_daily_sales
                     )
-                
-                # Risk categorization
-                if days_left < 7:
-                    risk_level = "🔴 Critical"
-                elif days_left < 14:
-                    risk_level = "🟡 Warning"
-                else:
-                    risk_level = "🟢 Safe"
-                
-                forecasts.append({
-                    'Product': item['product_name'],
-                    'Current Stock': item['current_stock'],
-                    'Days Until Stockout': round(days_left, 1),
-                    'Risk Level': risk_level
-                })
+            else:
+                days_left = forecaster.seasonal_adjustment_method(
+                    item['current_stock'],
+                    avg_daily_sales,
+                    seasonal_factor=1.0
+                )
+            
+            # Risk categorization
+            if days_left < 7:
+                risk_level = "🔴 Critical"
+            elif days_left < 14:
+                risk_level = "🟡 Warning"
+            else:
+                risk_level = "🟢 Safe"
+            
+            forecasts.append({
+                'Product': item['product_name'],
+                'Current Stock': item['current_stock'],
+                'Days Until Stockout': round(days_left, 1),
+                'Risk Level': risk_level
+            })
         
         # Create results DataFrame
         results_df = pd.DataFrame(forecasts)
         
         if results_df.empty:
-            return "No inventory data available.", None
+            # Return all 3 required values for Gradio
+            return "No inventory data available.", pd.DataFrame(), None
         
         # Sort by days until stockout
         results_df = results_df.sort_values('Days Until Stockout')
@@ -167,8 +199,9 @@ def calculate_stockout_forecast(method, api_token):
         critical_items = len(results_df[results_df['Days Until Stockout'] < 7])
         warning_items = len(results_df[results_df['Days Until Stockout'].between(7, 14)])
         
+        mode_indicator = "Demo Mode" if use_demo_mode else "Live Data"
         summary = f"""
-        ## Inventory Forecast - {method.replace('_', ' ').title()} Method
+        ## Inventory Forecast - {method.replace('_', ' ').title()} Method ({mode_indicator})
         
         - **Critical Items** (< 7 days): {critical_items}
         - **Warning Items** (7-14 days): {warning_items}
@@ -183,7 +216,8 @@ def calculate_stockout_forecast(method, api_token):
     except Exception as e:
         error_msg = f"Error calculating forecast: {str(e)}"
         gr.Error(error_msg)
-        return error_msg, None, None
+        # Return all 3 required values for Gradio
+        return error_msg, pd.DataFrame(), None
 
 def update_status(api_token):
     """Update API status based on token"""

config.py

@@ -17,12 +17,12 @@ class Config:
         self.wildberries_api_token = os.getenv("WILDBERRIES_API_TOKEN")
         self.wildberries_base_url = "https://statistics-api.wildberries.ru"
         self.wildberries_content_url = "https://content-api.wildberries.ru"
-        self.wildberries_analytics_url = "https://analytics-api.wildberries.ru"
+        self.wildberries_analytics_url = "https://seller-analytics-api.wildberries.ru"
+        self.wildberries_common_url = "https://common-api.wildberries.ru"
         
-        # Rate limiting settings (based on Wildberries API documentation)
+        # Rate limiting settings (matches official documentation)
         self.rate_limit_requests = 300  # requests per minute
         self.rate_limit_window = 60     # seconds
-        self.rate_limit_burst = 10      # burst allowance
         
         # Request timeout settings
         self.request_timeout = 30       # seconds
@@ -75,7 +75,13 @@ class Config:
             "incomes": f"{self.wildberries_base_url}/api/v1/supplier/incomes",
             "reportDetailByPeriod": f"{self.wildberries_base_url}/api/v1/supplier/reportDetailByPeriod",
             "analytics": f"{self.wildberries_analytics_url}/api/v2/nm-report/detail",
-            "content": f"{self.wildberries_content_url}/content/v1/cards/cursor/list"
+            "content": f"{self.wildberries_content_url}/content/v1/cards/cursor/list",
+            "ping_statistics": f"{self.wildberries_base_url}/ping",
+            "ping_content": f"{self.wildberries_content_url}/ping",
+            "ping_analytics": f"{self.wildberries_analytics_url}/ping",
+            "ping_common": f"{self.wildberries_common_url}/ping",
+            "news": f"{self.wildberries_common_url}/api/communications/v2/news",
+            "seller_info": f"{self.wildberries_common_url}/api/v1/seller-info"
         }
     
     def validate_token(self, token: str) -> bool: