Imporve the predicciones page

frontend/src/api/services/forecasting.ts

@@ -15,10 +15,11 @@ import {
   DeleteForecastResponse,
   GetForecastsParams,
   ForecastingHealthResponse,
+  MultiDayForecastResponse,
 } from '../types/forecasting';
 
 export class ForecastingService {
-  private readonly baseUrl = '/forecasts';
+  private readonly baseUrl = '/tenants';
 
   /**
    * Generate a single product forecast
@@ -29,7 +30,7 @@ export class ForecastingService {
     request: ForecastRequest
   ): Promise<ForecastResponse> {
     return apiClient.post<ForecastResponse, ForecastRequest>(
-      `/tenants/${tenantId}${this.baseUrl}/single`,
+      `${this.baseUrl}/${tenantId}/forecasts/single`,
       request
     );
   }
@@ -43,7 +44,7 @@ export class ForecastingService {
     request: BatchForecastRequest
   ): Promise<BatchForecastResponse> {
     return apiClient.post<BatchForecastResponse, BatchForecastRequest>(
-      `/tenants/${tenantId}${this.baseUrl}/batch`,
+      `${this.baseUrl}/${tenantId}/forecasts/batch`,
       request
     );
   }
@@ -75,7 +76,7 @@ export class ForecastingService {
     }
 
     const queryString = searchParams.toString();
-    const url = `/tenants/${tenantId}${this.baseUrl}${queryString ? `?${queryString}` : ''}`;
+    const url = `${this.baseUrl}/${tenantId}/forecasts${queryString ? `?${queryString}` : ''}`;
 
     return apiClient.get<ForecastListResponse>(url);
   }
@@ -89,7 +90,7 @@ export class ForecastingService {
     forecastId: string
   ): Promise<ForecastByIdResponse> {
     return apiClient.get<ForecastByIdResponse>(
-      `/tenants/${tenantId}${this.baseUrl}/${forecastId}`
+      `${this.baseUrl}/${tenantId}/forecasts/${forecastId}`
     );
   }
 
@@ -102,7 +103,7 @@ export class ForecastingService {
     forecastId: string
   ): Promise<DeleteForecastResponse> {
     return apiClient.delete<DeleteForecastResponse>(
-      `/tenants/${tenantId}${this.baseUrl}/${forecastId}`
+      `${this.baseUrl}/${tenantId}/forecasts/${forecastId}`
     );
   }
 
@@ -114,7 +115,21 @@ export class ForecastingService {
     tenantId: string
   ): Promise<ForecastStatistics> {
     return apiClient.get<ForecastStatistics>(
-      `/tenants/${tenantId}${this.baseUrl}/statistics`
+      `${this.baseUrl}/${tenantId}/forecasts/statistics`
+    );
+  }
+
+  /**
+   * Generate multi-day forecasts for a single product
+   * POST /tenants/{tenant_id}/forecasts/multi-day
+   */
+  async createMultiDayForecast(
+    tenantId: string,
+    request: ForecastRequest
+  ): Promise<MultiDayForecastResponse> {
+    return apiClient.post<MultiDayForecastResponse, ForecastRequest>(
+      `${this.baseUrl}/${tenantId}/forecasts/multi-day`,
+      request
     );
   }
 

frontend/src/api/services/training.ts

@@ -83,7 +83,7 @@ class TrainingService {
 
     const queryString = params.toString() ? `?${params.toString()}` : '';
     return apiClient.get<PaginatedResponse<TrainedModelResponse>>(
-      `${this.baseUrl}/${tenantId}/models${queryString}`
+      `${this.baseUrl}/${tenantId}/models/${queryString}`
     );
   }
 

frontend/src/api/types/forecasting.ts

@@ -158,3 +158,14 @@ export interface ForecastingHealthResponse {
   features: string[];
   timestamp: string;
 }
+
+export interface MultiDayForecastResponse {
+  tenant_id: string;
+  inventory_product_id: string;
+  forecast_start_date: string; // ISO date string
+  forecast_days: number;
+  forecasts: ForecastResponse[];
+  total_predicted_demand: number;
+  average_confidence_level: number;
+  processing_time_ms: number;
+}

frontend/src/components/domain/forecasting/DemandChart.tsx

@@ -88,9 +88,15 @@ const DemandChart: React.FC<DemandChartProps> = ({
 
   // Process forecast data for chart
   const chartData = useMemo(() => {
+    console.log('🔍 Processing forecast data for chart:', data);
+
     const processedData: ChartDataPoint[] = data.map(forecast => {
+      // Convert forecast_date to a proper date format for the chart
+      const forecastDate = new Date(forecast.forecast_date);
+      const dateString = forecastDate.toISOString().split('T')[0];
+
       return {
-        date: forecast.forecast_date,
+        date: dateString,
         actualDemand: undefined, // Not available in current forecast response
         predictedDemand: forecast.predicted_demand,
         confidenceLower: forecast.confidence_lower,
@@ -99,23 +105,32 @@ const DemandChart: React.FC<DemandChartProps> = ({
       };
     });
 
+    console.log('📊 Processed chart data:', processedData);
     return processedData.sort((a, b) => new Date(a.date).getTime() - new Date(b.date).getTime());
   }, [data]);
 
   // Filter data based on selected period
   const filteredData = useMemo(() => {
+    console.log('🔍 Filtering data - selected period:', selectedPeriod);
+    console.log('🔍 Chart data before filtering:', chartData);
+
     if (!selectedPeriod.start || !selectedPeriod.end) {
+      console.log('📊 No period filter, returning all chart data');
       return chartData;
     }
 
-    return chartData.filter(point => {
+    const filtered = chartData.filter(point => {
       const pointDate = new Date(point.date);
       return pointDate >= selectedPeriod.start! && pointDate <= selectedPeriod.end!;
     });
+
+    console.log('📊 Filtered data:', filtered);
+    return filtered;
   }, [chartData, selectedPeriod]);
 
   // Update zoomed data when filtered data changes
   useEffect(() => {
+    console.log('🔍 Setting zoomed data from filtered data:', filteredData);
     setZoomedData(filteredData);
   }, [filteredData]);
 
@@ -221,8 +236,11 @@ const DemandChart: React.FC<DemandChartProps> = ({
     );
   }
 
-  // Empty state
+  // Use filteredData if zoomedData is empty but we have data
-  if (zoomedData.length === 0) {
+  const displayData = zoomedData.length > 0 ? zoomedData : filteredData;
+
+  // Empty state - only show if we truly have no data
+  if (displayData.length === 0 && chartData.length === 0) {
     return (
       <Card className={className}>
         <CardHeader>
@@ -286,7 +304,7 @@ const DemandChart: React.FC<DemandChartProps> = ({
             )}
 
             {/* Reset zoom */}
-            {zoomedData.length !== filteredData.length && (
+            {displayData.length !== filteredData.length && (
               <Button variant="ghost" size="sm" onClick={handleResetZoom}>
                 Restablecer Zoom
               </Button>
@@ -298,28 +316,57 @@ const DemandChart: React.FC<DemandChartProps> = ({
       <CardBody padding="lg">
         <div style={{ width: '100%', height }}>
           <ResponsiveContainer>
-            <ComposedChart data={zoomedData} margin={{ top: 20, right: 30, left: 20, bottom: 5 }}>
+            <ComposedChart data={displayData} margin={{ top: 20, right: 30, left: 20, bottom: 60 }}>
-              <CartesianGrid strokeDasharray="3 3" stroke="#e5e7eb" />
+              <defs>
+                <linearGradient id="demandGradient" x1="0" y1="0" x2="0" y2="1">
+                  <stop offset="5%" stopColor="#10b981" stopOpacity={0.3}/>
+                  <stop offset="95%" stopColor="#10b981" stopOpacity={0.05}/>
+                </linearGradient>
+                <linearGradient id="confidenceGradient" x1="0" y1="0" x2="0" y2="1">
+                  <stop offset="5%" stopColor="#10b981" stopOpacity={0.1}/>
+                  <stop offset="95%" stopColor="#10b981" stopOpacity={0.02}/>
+                </linearGradient>
+              </defs>
+              <CartesianGrid
+                strokeDasharray="2 2"
+                stroke="#e5e7eb"
+                strokeOpacity={0.5}
+                horizontal={true}
+                vertical={false}
+              />
               <XAxis
                 dataKey="date"
                 stroke="#6b7280"
-                fontSize={12}
+                fontSize={11}
+                tickMargin={8}
+                angle={-45}
+                textAnchor="end"
+                height={80}
+                interval={0}
                 tickFormatter={(value) => {
                   const date = new Date(value);
-                  return timeframe === 'weekly' 
+                  return date.toLocaleDateString('es-ES', {
-                    ? date.toLocaleDateString('es-ES', { month: 'short', day: 'numeric' })
+                    month: 'short',
-                    : timeframe === 'monthly'
+                    day: 'numeric',
-                    ? date.toLocaleDateString('es-ES', { month: 'short', year: '2-digit' })
+                    weekday: displayData.length <= 7 ? 'short' : undefined
-                    : date.getFullYear().toString();
+                  });
                 }}
               />
               <YAxis
                 stroke="#6b7280"
-                fontSize={12}
+                fontSize={11}
-                tickFormatter={(value) => `${value}`}
+                width={60}
+                tickFormatter={(value) => value.toFixed(0)}
+                domain={['dataMin - 5', 'dataMax + 5']}
+              />
+              <Tooltip
+                content={<CustomTooltip />}
+                cursor={{ stroke: '#10b981', strokeWidth: 1, strokeOpacity: 0.5 }}
+              />
+              <Legend
+                wrapperStyle={{ paddingTop: '20px' }}
+                iconType="line"
               />
-              <Tooltip content={<CustomTooltip />} />
-              <Legend />
 
               {/* Confidence interval area */}
               {showConfidenceInterval && (
@@ -328,9 +375,9 @@ const DemandChart: React.FC<DemandChartProps> = ({
                   dataKey="confidenceUpper"
                   stackId={1}
                   stroke="none"
-                  fill="#10b98120"
+                  fill="url(#confidenceGradient)"
-                  fillOpacity={0.3}
+                  fillOpacity={0.4}
-                  name="Intervalo de Confianza Superior"
+                  name="Límite Superior"
                 />
               )}
               {showConfidenceInterval && (
@@ -340,20 +387,40 @@ const DemandChart: React.FC<DemandChartProps> = ({
                   stackId={1}
                   stroke="none"
                   fill="#ffffff"
-                  name="Intervalo de Confianza Inferior"
+                  name="Límite Inferior"
                 />
               )}
 
+              {/* Background area for main prediction */}
+              <Area
+                type="monotone"
+                dataKey="predictedDemand"
+                stroke="none"
+                fill="url(#demandGradient)"
+                fillOpacity={0.2}
+                name="Área de Demanda"
+              />
+
               {/* Predicted demand line */}
               <Line
                 type="monotone"
                 dataKey="predictedDemand"
                 stroke="#10b981"
                 strokeWidth={3}
-                dot={true}
+                dot={{
-                dotSize={6}
+                  fill: '#10b981',
-                activeDot={{ r: 8, stroke: '#10b981', strokeWidth: 2 }}
+                  strokeWidth: 2,
+                  stroke: '#ffffff',
+                  r: 4
+                }}
+                activeDot={{
+                  r: 6,
+                  stroke: '#10b981',
+                  strokeWidth: 3,
+                  fill: '#ffffff'
+                }}
                 name="Demanda Predicha"
+                connectNulls={false}
               />
             </ComposedChart>
           </ResponsiveContainer>
@@ -386,18 +453,46 @@ const DemandChart: React.FC<DemandChartProps> = ({
           </div>
         )}
 
-        {/* Chart legend */}
+        {/* Enhanced Chart legend and insights */}
-        <div className="flex items-center justify-center gap-6 mt-4 text-sm">
+        <div className="mt-6 space-y-4">
-          <div className="flex items-center gap-2">
+          <div className="flex items-center justify-center gap-6 text-sm">
-            <div className="w-4 h-0.5 bg-green-500"></div>
-            <span className="text-text-secondary">Demanda Predicha</span>
-          </div>
-          {showConfidenceInterval && (
             <div className="flex items-center gap-2">
-              <div className="w-4 h-2 bg-green-500 bg-opacity-20"></div>
+              <div className="w-4 h-0.5 bg-green-500 rounded"></div>
-              <span className="text-text-secondary">Intervalo de Confianza</span>
+              <span className="text-text-secondary">Demanda Predicha</span>
             </div>
-          )}
+            {showConfidenceInterval && (
+              <div className="flex items-center gap-2">
+                <div className="w-4 h-2 bg-green-500 bg-opacity-20 rounded"></div>
+                <span className="text-text-secondary">Intervalo de Confianza</span>
+              </div>
+            )}
+            <div className="flex items-center gap-2">
+              <div className="w-3 h-3 bg-green-500 rounded-full"></div>
+              <span className="text-text-secondary">Puntos de Datos</span>
+            </div>
+          </div>
+
+          {/* Quick stats */}
+          <div className="grid grid-cols-3 gap-4 p-4 bg-gray-50 rounded-lg">
+            <div className="text-center">
+              <div className="text-lg font-bold text-green-600">
+                {Math.min(...displayData.map(d => d.predictedDemand || 0)).toFixed(1)}
+              </div>
+              <div className="text-xs text-gray-500">Mínimo</div>
+            </div>
+            <div className="text-center">
+              <div className="text-lg font-bold text-blue-600">
+                {(displayData.reduce((sum, d) => sum + (d.predictedDemand || 0), 0) / displayData.length).toFixed(1)}
+              </div>
+              <div className="text-xs text-gray-500">Promedio</div>
+            </div>
+            <div className="text-center">
+              <div className="text-lg font-bold text-orange-600">
+                {Math.max(...displayData.map(d => d.predictedDemand || 0)).toFixed(1)}
+              </div>
+              <div className="text-xs text-gray-500">Máximo</div>
+            </div>
+          </div>
         </div>
       </CardBody>
     </Card>

frontend/src/pages/app/database/models/ModelsConfigPage.tsx

@@ -0,0 +1,680 @@
+import React, { useState, useMemo } from 'react';
+import { Brain, TrendingUp, AlertCircle, Play, RotateCcw, Eye, Loader, CheckCircle } from 'lucide-react';
+import { Button, Card, Badge, Modal, Table, Select, Input } from '../../../../components/ui';
+import { PageHeader } from '../../../../components/layout';
+import { useToast } from '../../../../hooks/ui/useToast';
+import { useCurrentTenant } from '../../../../stores/tenant.store';
+import { useIngredients } from '../../../../api/hooks/inventory';
+import {
+  useModels,
+  useActiveModel,
+  useTrainSingleProduct,
+  useModelMetrics,
+  useModelPerformance,
+  useTenantTrainingStatistics
+} from '../../../../api/hooks/training';
+import type { IngredientResponse } from '../../../../api/types/inventory';
+import type { TrainedModelResponse, SingleProductTrainingRequest } from '../../../../api/types/training';
+
+// Actual API response structure (different from expected paginated response)
+interface ModelsApiResponse {
+  tenant_id: string;
+  models: TrainedModelResponse[];
+  total_returned: number;
+  active_only: boolean;
+  pagination: any;
+  enhanced_features: boolean;
+  repository_integration: boolean;
+}
+
+interface ModelStatus {
+  ingredient: IngredientResponse;
+  hasModel: boolean;
+  model?: TrainedModelResponse;
+  isTraining: boolean;
+  trainingJobId?: string;
+  lastTrainingDate?: string;
+  accuracy?: number;
+  status: 'no_model' | 'active' | 'training' | 'error';
+}
+
+const ModelsConfigPage: React.FC = () => {
+  const { addToast } = useToast();
+  const currentTenant = useCurrentTenant();
+  const tenantId = currentTenant?.id || '';
+
+  const [selectedIngredient, setSelectedIngredient] = useState<IngredientResponse | null>(null);
+  const [showTrainingModal, setShowTrainingModal] = useState(false);
+  const [showModelDetailsModal, setShowModelDetailsModal] = useState(false);
+  const [trainingSettings, setTrainingSettings] = useState<Partial<SingleProductTrainingRequest>>({
+    seasonality_mode: 'additive',
+    daily_seasonality: true,
+    weekly_seasonality: true,
+    yearly_seasonality: false,
+  });
+
+  // API hooks
+  const { data: ingredients = [], isLoading: ingredientsLoading } = useIngredients(tenantId);
+  const { data: modelsData, isLoading: modelsLoading, error: modelsError } = useModels(tenantId);
+  const { data: statistics, error: statsError } = useTenantTrainingStatistics(tenantId);
+  const trainMutation = useTrainSingleProduct();
+
+  // Debug: Log the models data structure
+  React.useEffect(() => {
+    console.log('Models data structure:', {
+      modelsData,
+      modelsLoading,
+      modelsError,
+      ingredients: ingredients.length
+    });
+  }, [modelsData, modelsLoading, modelsError, ingredients]);
+
+  // Build model status for each ingredient
+  const modelStatuses = useMemo<ModelStatus[]>(() => {
+    // Handle different possible data structures from the API response
+    let models: TrainedModelResponse[] = [];
+
+    // The API actually returns { models: [...], tenant_id: ..., total_returned: ... }
+    const apiResponse = modelsData as any as ModelsApiResponse;
+    if (apiResponse?.models && Array.isArray(apiResponse.models)) {
+      models = apiResponse.models;
+    } else if (modelsData?.data && Array.isArray(modelsData.data)) {
+      models = modelsData.data;
+    } else if (modelsData && Array.isArray(modelsData)) {
+      models = modelsData as any;
+    }
+
+    console.log('Processing models:', {
+      modelsData,
+      extractedModels: models,
+      modelsCount: models.length,
+      ingredientsCount: ingredients.length
+    });
+
+    return ingredients.map((ingredient: IngredientResponse) => {
+      const model = models.find((m: any) => {
+        // Focus only on ID-based matching
+        return m.inventory_product_id === ingredient.id ||
+               String(m.inventory_product_id) === String(ingredient.id);
+      });
+
+      const isTraining = false; // We'll track this separately for active training jobs
+
+      console.log(`Ingredient ${ingredient.name} (${ingredient.id}):`, {
+        hasModel: !!model,
+        model: model ? {
+          id: model.model_id,
+          created: model.created_at,
+          inventory_product_id: model.inventory_product_id
+        } : null
+      });
+
+      return {
+        ingredient,
+        hasModel: !!model,
+        model,
+        isTraining,
+        lastTrainingDate: model?.created_at,
+        accuracy: model?.training_metrics?.mape ? (100 - model.training_metrics.mape) : undefined,
+        status: model
+          ? (isTraining ? 'training' : 'active')
+          : 'no_model'
+      };
+    });
+  }, [ingredients, modelsData]);
+
+  // Calculate orphaned models (models for ingredients that no longer exist)
+  const orphanedModels = useMemo(() => {
+    const apiResponse = modelsData as any as ModelsApiResponse;
+    const models = apiResponse?.models || [];
+    const ingredientIds = new Set(ingredients.map(ing => ing.id));
+
+    return models.filter((model: any) => !ingredientIds.has(model.inventory_product_id));
+  }, [modelsData, ingredients]);
+
+  // Filter and search
+  const [searchTerm, setSearchTerm] = useState('');
+  const [statusFilter, setStatusFilter] = useState<string>('all');
+
+  const filteredStatuses = useMemo(() => {
+    return modelStatuses.filter(status => {
+      const matchesSearch = status.ingredient.name.toLowerCase().includes(searchTerm.toLowerCase());
+      const matchesStatus = statusFilter === 'all' || status.status === statusFilter;
+      return matchesSearch && matchesStatus;
+    });
+  }, [modelStatuses, searchTerm, statusFilter]);
+
+  const handleTrainModel = async () => {
+    if (!selectedIngredient) return;
+
+    try {
+      await trainMutation.mutateAsync({
+        tenantId,
+        inventoryProductId: selectedIngredient.id,
+        request: trainingSettings
+      });
+
+      addToast(`Entrenamiento iniciado para ${selectedIngredient.name}`, { type: 'success' });
+      setShowTrainingModal(false);
+    } catch (error) {
+      addToast('Error al iniciar el entrenamiento', { type: 'error' });
+    }
+  };
+
+  const handleViewModelDetails = (ingredient: IngredientResponse) => {
+    setSelectedIngredient(ingredient);
+    setShowModelDetailsModal(true);
+  };
+
+  const handleStartTraining = (ingredient: IngredientResponse) => {
+    setSelectedIngredient(ingredient);
+    setShowTrainingModal(true);
+  };
+
+  const getStatusBadge = (status: ModelStatus['status']) => {
+    switch (status) {
+      case 'no_model':
+        return <Badge variant="secondary">Sin modelo</Badge>;
+      case 'active':
+        return <Badge variant="success">Activo</Badge>;
+      case 'training':
+        return <Badge variant="warning">Entrenando</Badge>;
+      case 'error':
+        return <Badge variant="error">Error</Badge>;
+      default:
+        return <Badge variant="secondary">Desconocido</Badge>;
+    }
+  };
+
+  const getAccuracyBadge = (accuracy?: number) => {
+    if (!accuracy) return null;
+
+    const variant = accuracy >= 90 ? 'success' : accuracy >= 75 ? 'warning' : 'error';
+    return <Badge variant={variant} size="sm">{accuracy.toFixed(1)}%</Badge>;
+  };
+
+  // Table columns configuration
+  const tableColumns = [
+    {
+      key: 'ingredient',
+      title: 'Ingrediente',
+      render: (_: any, status: ModelStatus) => (
+        <div className="flex items-center gap-3">
+          <div className="w-10 h-10 bg-gradient-to-br from-[var(--color-primary)] to-[var(--color-primary-dark)] rounded-lg flex items-center justify-center text-white font-bold">
+            {status.ingredient.name.charAt(0).toUpperCase()}
+          </div>
+          <div>
+            <div className="font-medium text-[var(--text-primary)]">{status.ingredient.name}</div>
+            <div className="text-sm text-[var(--text-secondary)]">{status.ingredient.category}</div>
+          </div>
+        </div>
+      ),
+    },
+    {
+      key: 'status',
+      title: 'Estado del Modelo',
+      render: (_: any, status: ModelStatus) => (
+        <div className="flex items-center gap-2">
+          {getStatusBadge(status.status)}
+          {status.accuracy && getAccuracyBadge(status.accuracy)}
+        </div>
+      ),
+    },
+    {
+      key: 'lastTrained',
+      title: 'Último Entrenamiento',
+      render: (_: any, status: ModelStatus) => (
+        <div className="text-sm text-[var(--text-secondary)]">
+          {status.lastTrainingDate
+            ? new Date(status.lastTrainingDate).toLocaleDateString('es-ES')
+            : 'Nunca'
+          }
+        </div>
+      ),
+    },
+    {
+      key: 'actions',
+      title: 'Acciones',
+      render: (_: any, status: ModelStatus) => (
+        <div className="flex items-center gap-2">
+          {status.hasModel && (
+            <Button
+              variant="ghost"
+              size="sm"
+              onClick={() => handleViewModelDetails(status.ingredient)}
+              leftIcon={<Eye className="w-4 h-4" />}
+            >
+              Ver detalles
+            </Button>
+          )}
+          <Button
+            variant={status.hasModel ? "outline" : "primary"}
+            size="sm"
+            onClick={() => handleStartTraining(status.ingredient)}
+            leftIcon={status.hasModel ? <RotateCcw className="w-4 h-4" /> : <Play className="w-4 h-4" />}
+            disabled={status.isTraining}
+          >
+            {status.hasModel ? 'Reentrenar' : 'Entrenar'}
+          </Button>
+        </div>
+      ),
+    },
+  ];
+
+  if (ingredientsLoading || modelsLoading) {
+    return (
+      <div className="p-6 space-y-6">
+        <PageHeader
+          title="Configuración de Modelos IA"
+          description="Gestiona el entrenamiento y configuración de modelos de predicción para cada ingrediente"
+        />
+        <div className="flex items-center justify-center h-64">
+          <Loader className="w-8 h-8 animate-spin" />
+          <span className="ml-2">
+            {ingredientsLoading ? 'Cargando ingredientes...' : 'Cargando modelos...'}
+          </span>
+        </div>
+      </div>
+    );
+  }
+
+  if (modelsError) {
+    console.error('Error loading models:', modelsError);
+  }
+
+  return (
+    <div className="p-6 space-y-6">
+      <PageHeader
+        title="Configuración de Modelos IA"
+        description="Gestiona el entrenamiento y configuración de modelos de predicción para cada ingrediente"
+      />
+
+
+      {/* Statistics Cards */}
+      <div className="grid grid-cols-1 md:grid-cols-4 gap-6">
+        <Card className="p-6">
+          <div className="flex items-center justify-between">
+            <div>
+              <div className="text-2xl font-bold text-[var(--text-primary)]">
+                {modelStatuses.filter(s => s.hasModel).length}
+              </div>
+              <div className="text-sm text-[var(--text-secondary)]">Ingredientes con Modelo</div>
+            </div>
+            <Brain className="w-8 h-8 text-[var(--color-primary)]" />
+          </div>
+        </Card>
+
+        <Card className="p-6">
+          <div className="flex items-center justify-between">
+            <div>
+              <div className="text-2xl font-bold text-[var(--text-primary)]">
+                {modelStatuses.filter(s => s.status === 'no_model').length}
+              </div>
+              <div className="text-sm text-[var(--text-secondary)]">Sin Modelo</div>
+            </div>
+            <AlertCircle className="w-8 h-8 text-[var(--color-warning)]" />
+          </div>
+        </Card>
+
+        <Card className="p-6">
+          <div className="flex items-center justify-between">
+            <div>
+              <div className="text-2xl font-bold text-[var(--text-primary)]">
+                {orphanedModels.length}
+              </div>
+              <div className="text-sm text-[var(--text-secondary)]">Modelos Huérfanos</div>
+            </div>
+            <AlertCircle className="w-8 h-8 text-[var(--color-secondary)]" />
+          </div>
+        </Card>
+
+        <Card className="p-6">
+          <div className="flex items-center justify-between">
+            <div>
+              <div className="text-2xl font-bold text-[var(--text-primary)]">
+                {statsError ? 'N/A' : (statistics?.average_accuracy ? `${(100 - statistics.average_accuracy).toFixed(1)}%` : 'N/A')}
+              </div>
+              <div className="text-sm text-[var(--text-secondary)]">Precisión Promedio</div>
+            </div>
+            <TrendingUp className="w-8 h-8 text-[var(--color-primary)]" />
+          </div>
+        </Card>
+      </div>
+
+      {/* Orphaned Models Warning */}
+      {orphanedModels.length > 0 && (
+        <Card className="p-4 bg-orange-50 border-orange-200">
+          <div className="flex items-start gap-3">
+            <AlertCircle className="w-5 h-5 text-orange-600 mt-0.5" />
+            <div>
+              <h4 className="font-medium text-orange-900 mb-1">
+                Modelos Huérfanos Detectados
+              </h4>
+              <p className="text-sm text-orange-700">
+                Se encontraron {orphanedModels.length} modelos entrenados para ingredientes que ya no existen en el inventario.
+                Estos modelos pueden ser eliminados para optimizar el espacio de almacenamiento.
+              </p>
+            </div>
+          </div>
+        </Card>
+      )}
+
+      {/* Filters */}
+      <Card className="p-6">
+        <div className="flex flex-col sm:flex-row gap-4">
+          <div className="flex-1">
+            <Input
+              placeholder="Buscar ingrediente..."
+              value={searchTerm}
+              onChange={(e) => setSearchTerm(e.target.value)}
+            />
+          </div>
+          <div className="w-full sm:w-48">
+            <Select
+              value={statusFilter}
+              onChange={(value) => setStatusFilter(value as string)}
+              options={[
+                { value: 'all', label: 'Todos los estados' },
+                { value: 'no_model', label: 'Sin modelo' },
+                { value: 'active', label: 'Activo' },
+                { value: 'training', label: 'Entrenando' },
+                { value: 'error', label: 'Error' },
+              ]}
+            />
+          </div>
+        </div>
+      </Card>
+
+      {/* Models Table */}
+      <Card>
+        {filteredStatuses.length === 0 ? (
+          <div className="flex flex-col items-center justify-center py-12">
+            <Brain className="w-12 h-12 text-[var(--color-secondary)] mb-4" />
+            <h3 className="text-lg font-medium text-[var(--text-primary)] mb-2">
+              No se encontraron ingredientes
+            </h3>
+            <p className="text-[var(--text-secondary)] text-center">
+              No hay ingredientes que coincidan con los filtros aplicados.
+            </p>
+          </div>
+        ) : (
+          <Table
+            data={filteredStatuses}
+            columns={tableColumns}
+          />
+        )}
+      </Card>
+
+      {/* Training Modal */}
+      <Modal
+        isOpen={showTrainingModal}
+        onClose={() => setShowTrainingModal(false)}
+        title={`Entrenar Modelo - ${selectedIngredient?.name}`}
+        size="lg"
+      >
+        <div className="space-y-6">
+          <div className="p-4 bg-blue-50 rounded-lg">
+            <h4 className="font-medium text-blue-900 mb-2">Configuración de Entrenamiento</h4>
+            <p className="text-sm text-blue-700">
+              Configure los parámetros para el entrenamiento del modelo de predicción de demanda.
+            </p>
+          </div>
+
+          <div className="grid grid-cols-1 md:grid-cols-2 gap-6">
+            <div>
+              <label className="block text-sm font-medium mb-2">Modo de Estacionalidad</label>
+              <Select
+                value={trainingSettings.seasonality_mode || 'additive'}
+                onChange={(value) => setTrainingSettings(prev => ({ ...prev, seasonality_mode: value as any }))}
+                options={[
+                  { value: 'additive', label: 'Aditivo' },
+                  { value: 'multiplicative', label: 'Multiplicativo' }
+                ]}
+              />
+            </div>
+
+            <div className="space-y-4">
+              <h4 className="font-medium text-sm">Patrones Estacionales</h4>
+
+              <label className="flex items-center space-x-2">
+                <input
+                  type="checkbox"
+                  checked={trainingSettings.daily_seasonality || false}
+                  onChange={(e) => setTrainingSettings(prev => ({ ...prev, daily_seasonality: e.target.checked }))}
+                  className="rounded border-[var(--border-primary)]"
+                />
+                <span className="text-sm">Estacionalidad diaria</span>
+              </label>
+
+              <label className="flex items-center space-x-2">
+                <input
+                  type="checkbox"
+                  checked={trainingSettings.weekly_seasonality || false}
+                  onChange={(e) => setTrainingSettings(prev => ({ ...prev, weekly_seasonality: e.target.checked }))}
+                  className="rounded border-[var(--border-primary)]"
+                />
+                <span className="text-sm">Estacionalidad semanal</span>
+              </label>
+
+              <label className="flex items-center space-x-2">
+                <input
+                  type="checkbox"
+                  checked={trainingSettings.yearly_seasonality || false}
+                  onChange={(e) => setTrainingSettings(prev => ({ ...prev, yearly_seasonality: e.target.checked }))}
+                  className="rounded border-[var(--border-primary)]"
+                />
+                <span className="text-sm">Estacionalidad anual</span>
+              </label>
+            </div>
+          </div>
+
+          <div className="flex justify-end space-x-3 pt-4 border-t">
+            <Button variant="outline" onClick={() => setShowTrainingModal(false)}>
+              Cancelar
+            </Button>
+            <Button
+              onClick={handleTrainModel}
+              isLoading={trainMutation.isPending}
+              leftIcon={<Play className="w-4 h-4" />}
+            >
+              Iniciar Entrenamiento
+            </Button>
+          </div>
+        </div>
+      </Modal>
+
+      {/* Model Details Modal */}
+      <Modal
+        isOpen={showModelDetailsModal}
+        onClose={() => setShowModelDetailsModal(false)}
+        title={`Detalles del Modelo - ${selectedIngredient?.name}`}
+        size="lg"
+      >
+        <div className="space-y-6">
+          {selectedIngredient && (
+            <ModelDetailsContent
+              tenantId={tenantId}
+              ingredientId={selectedIngredient.id}
+            />
+          )}
+        </div>
+      </Modal>
+    </div>
+  );
+};
+
+// Component for model details content
+const ModelDetailsContent: React.FC<{
+  tenantId: string;
+  ingredientId: string;
+}> = ({ tenantId, ingredientId }) => {
+  const { data: activeModel } = useActiveModel(tenantId, ingredientId);
+
+  if (!activeModel) {
+    return (
+      <div className="text-center py-12">
+        <AlertCircle className="w-16 h-16 text-[var(--color-warning)] mx-auto mb-4" />
+        <h3 className="text-xl font-semibold mb-2 text-[var(--text-primary)]">No hay modelo disponible</h3>
+        <p className="text-[var(--text-secondary)] max-w-md mx-auto">
+          Este ingrediente no tiene un modelo entrenado disponible. Puedes entrenar uno nuevo usando el botón "Entrenar".
+        </p>
+      </div>
+    );
+  }
+
+  const precision = activeModel.training_metrics?.mape
+    ? (100 - activeModel.training_metrics.mape).toFixed(1)
+    : 'N/A';
+
+  return (
+    <div className="space-y-6">
+      {/* Model Overview */}
+      <div className="grid grid-cols-1 md:grid-cols-3 gap-4">
+        <div className="bg-gradient-to-br from-green-50 to-green-100 p-6 rounded-xl border border-green-200">
+          <div className="text-center">
+            <div className="text-3xl font-bold text-green-700 mb-1">
+              {precision}%
+            </div>
+            <div className="text-sm font-medium text-green-600">Precisión</div>
+          </div>
+        </div>
+
+        <div className="bg-gradient-to-br from-blue-50 to-blue-100 p-6 rounded-xl border border-blue-200">
+          <div className="text-center">
+            <div className="text-3xl font-bold text-blue-700 mb-1">
+              {activeModel.training_metrics?.mae?.toFixed(2) || 'N/A'}
+            </div>
+            <div className="text-sm font-medium text-blue-600">MAE</div>
+          </div>
+        </div>
+
+        <div className="bg-gradient-to-br from-purple-50 to-purple-100 p-6 rounded-xl border border-purple-200">
+          <div className="text-center">
+            <div className="text-3xl font-bold text-purple-700 mb-1">
+              {activeModel.training_metrics?.rmse?.toFixed(2) || 'N/A'}
+            </div>
+            <div className="text-sm font-medium text-purple-600">RMSE</div>
+          </div>
+        </div>
+      </div>
+
+      {/* Model Information */}
+      <Card className="p-6 bg-[var(--bg-primary)]">
+        <h4 className="text-lg font-semibold mb-6 text-[var(--text-primary)] flex items-center">
+          <Brain className="w-5 h-5 mr-2 text-[var(--color-primary)]" />
+          Información del Modelo
+        </h4>
+        <div className="grid grid-cols-1 md:grid-cols-2 gap-6">
+          <div className="space-y-4">
+            <div className="flex flex-col">
+              <span className="text-xs font-semibold text-[var(--text-tertiary)] uppercase tracking-wide mb-1">
+                Creado
+              </span>
+              <span className="text-sm text-[var(--text-primary)]">
+                {new Date(activeModel.created_at).toLocaleString('es-ES', {
+                  year: 'numeric',
+                  month: 'long',
+                  day: 'numeric',
+                  hour: '2-digit',
+                  minute: '2-digit'
+                })}
+              </span>
+            </div>
+
+            <div className="flex flex-col">
+              <span className="text-xs font-semibold text-[var(--text-tertiary)] uppercase tracking-wide mb-1">
+                Características usadas
+              </span>
+              <span className="text-sm text-[var(--text-primary)]">
+                {activeModel.features_used?.length || 0} variables
+              </span>
+            </div>
+          </div>
+
+          <div className="space-y-4">
+            <div className="flex flex-col">
+              <span className="text-xs font-semibold text-[var(--text-tertiary)] uppercase tracking-wide mb-1">
+                Período de entrenamiento
+              </span>
+              <span className="text-sm text-[var(--text-primary)]">
+                {activeModel.training_period?.start_date && activeModel.training_period?.end_date
+                  ? `${new Date(activeModel.training_period.start_date).toLocaleDateString('es-ES')} - ${new Date(activeModel.training_period.end_date).toLocaleDateString('es-ES')}`
+                  : 'No disponible'
+                }
+              </span>
+            </div>
+
+            <div className="flex flex-col">
+              <span className="text-xs font-semibold text-[var(--text-tertiary)] uppercase tracking-wide mb-1">
+                Hiperparámetros
+              </span>
+              <span className="text-sm text-[var(--text-primary)]">
+                {Object.keys(activeModel.hyperparameters || {}).length} configurados
+              </span>
+            </div>
+          </div>
+        </div>
+      </Card>
+
+      {/* Features Used */}
+      {activeModel.features_used && activeModel.features_used.length > 0 && (
+        <Card className="p-6 bg-[var(--bg-primary)]">
+          <h4 className="text-lg font-semibold mb-4 text-[var(--text-primary)] flex items-center">
+            <TrendingUp className="w-5 h-5 mr-2 text-[var(--color-primary)]" />
+            Características del Modelo
+          </h4>
+          <div className="grid grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-3">
+            {activeModel.features_used.map((feature: string, index: number) => (
+              <div
+                key={index}
+                className="bg-[var(--bg-secondary)] border border-[var(--border-primary)] rounded-lg px-3 py-2 text-center"
+              >
+                <span className="text-sm font-medium text-[var(--text-primary)]">
+                  {feature.replace(/_/g, ' ').replace(/\b\w/g, l => l.toUpperCase())}
+                </span>
+              </div>
+            ))}
+          </div>
+        </Card>
+      )}
+
+      {/* Training Performance */}
+      {activeModel.training_metrics && (
+        <Card className="p-6 bg-[var(--bg-primary)]">
+          <h4 className="text-lg font-semibold mb-4 text-[var(--text-primary)] flex items-center">
+            <CheckCircle className="w-5 h-5 mr-2 text-[var(--color-success)]" />
+            Métricas de Rendimiento
+          </h4>
+          <div className="grid grid-cols-2 md:grid-cols-4 gap-4">
+            <div className="text-center p-4 bg-[var(--bg-secondary)] rounded-lg border border-[var(--border-primary)]">
+              <div className="text-2xl font-bold text-[var(--color-success)] mb-1">
+                {precision}%
+              </div>
+              <div className="text-xs text-[var(--text-tertiary)] uppercase tracking-wide">Precisión</div>
+            </div>
+            <div className="text-center p-4 bg-[var(--bg-secondary)] rounded-lg border border-[var(--border-primary)]">
+              <div className="text-2xl font-bold text-[var(--text-primary)] mb-1">
+                {activeModel.training_metrics.mae?.toFixed(2) || 'N/A'}
+              </div>
+              <div className="text-xs text-[var(--text-tertiary)] uppercase tracking-wide">MAE</div>
+            </div>
+            <div className="text-center p-4 bg-[var(--bg-secondary)] rounded-lg border border-[var(--border-primary)]">
+              <div className="text-2xl font-bold text-[var(--text-primary)] mb-1">
+                {activeModel.training_metrics.rmse?.toFixed(2) || 'N/A'}
+              </div>
+              <div className="text-xs text-[var(--text-tertiary)] uppercase tracking-wide">RMSE</div>
+            </div>
+            <div className="text-center p-4 bg-[var(--bg-secondary)] rounded-lg border border-[var(--border-primary)]">
+              <div className="text-2xl font-bold text-[var(--text-primary)] mb-1">
+                {activeModel.training_metrics.r2_score?.toFixed(3) || 'N/A'}
+              </div>
+              <div className="text-xs text-[var(--text-tertiary)] uppercase tracking-wide">R²</div>
+            </div>
+          </div>
+        </Card>
+      )}
+    </div>
+  );
+};
+
+export default ModelsConfigPage;

frontend/src/pages/app/database/models/index.ts

@@ -0,0 +1 @@
+export { default as ModelsConfigPage } from './ModelsConfigPage';

frontend/src/pages/app/operations/procurement/ProcurementPage.tsx

@@ -8,6 +8,7 @@ import {
   useProcurementPlans,
   useCurrentProcurementPlan,
   useCriticalRequirements,
+  usePlanRequirements,
   useGenerateProcurementPlan,
   useUpdateProcurementPlanStatus,
   useTriggerDailyScheduler
@@ -22,6 +23,8 @@ const ProcurementPage: React.FC = () => {
   const [selectedPlan, setSelectedPlan] = useState<any>(null);
   const [editingPlan, setEditingPlan] = useState<any>(null);
   const [editFormData, setEditFormData] = useState<any>({});
+  const [selectedPlanForRequirements, setSelectedPlanForRequirements] = useState<string | null>(null);
+  const [showCriticalRequirements, setShowCriticalRequirements] = useState(false);
 
   const { currentTenant } = useTenantStore();
   const tenantId = currentTenant?.id || '';
@@ -36,6 +39,15 @@ const ProcurementPage: React.FC = () => {
   const { data: currentPlan, isLoading: isCurrentPlanLoading } = useCurrentProcurementPlan(tenantId);
   const { data: criticalRequirements, isLoading: isCriticalLoading } = useCriticalRequirements(tenantId);
 
+  // Get plan requirements for selected plan
+  const { data: planRequirements, isLoading: isPlanRequirementsLoading } = usePlanRequirements({
+    tenant_id: tenantId,
+    plan_id: selectedPlanForRequirements || '',
+    status: 'critical' // Only get critical requirements
+  }, {
+    enabled: !!selectedPlanForRequirements && !!tenantId
+  });
+  
   const generatePlanMutation = useGenerateProcurementPlan();
   const updatePlanStatusMutation = useUpdateProcurementPlanStatus();
   const triggerSchedulerMutation = useTriggerDailyScheduler();
@@ -107,6 +119,16 @@ const ProcurementPage: React.FC = () => {
     setEditFormData({});
   };
 
+  const handleShowCriticalRequirements = (planId: string) => {
+    setSelectedPlanForRequirements(planId);
+    setShowCriticalRequirements(true);
+  };
+
+  const handleCloseCriticalRequirements = () => {
+    setShowCriticalRequirements(false);
+    setSelectedPlanForRequirements(null);
+  };
+
   if (!tenantId) {
     return (
       <div className="flex justify-center items-center h-64">
@@ -391,6 +413,15 @@ const ProcurementPage: React.FC = () => {
                   }
                 });
 
+                // Show Critical Requirements button
+                actions.push({
+                  label: 'Req. Críticos',
+                  icon: AlertCircle,
+                  variant: 'outline' as const,
+                  priority: 'secondary' as const,
+                  onClick: () => handleShowCriticalRequirements(plan.id)
+                });
+
                 // Tertiary action: Cancel (least prominent, destructive)
                 if (!['completed', 'cancelled'].includes(plan.status)) {
                   actions.push({

frontend/src/router/AppRouter.tsx

@@ -33,6 +33,7 @@ const TeamPage = React.lazy(() => import('../pages/app/settings/team/TeamPage'))
 
 // Database pages
 const DatabasePage = React.lazy(() => import('../pages/app/database/DatabasePage'));
+const ModelsConfigPage = React.lazy(() => import('../pages/app/database/models/ModelsConfigPage'));
 
 // Data pages
 const WeatherPage = React.lazy(() => import('../pages/app/data/weather/WeatherPage'));
@@ -176,6 +177,16 @@ export const AppRouter: React.FC = () => {
             </ProtectedRoute>
           }
         />
+        <Route
+          path="/app/database/models"
+          element={
+            <ProtectedRoute>
+              <AppShell>
+                <ModelsConfigPage />
+              </AppShell>
+            </ProtectedRoute>
+          }
+        />
 
         {/* Analytics Routes */}
         <Route 

frontend/src/router/routes.config.ts

@@ -330,6 +330,16 @@ export const routesConfig: RouteConfig[] = [
         showInNavigation: true,
         showInBreadcrumbs: true,
       },
+      {
+        path: '/app/database/models',
+        name: 'ModelsConfig',
+        component: 'ModelsConfigPage',
+        title: 'Modelos IA',
+        icon: 'training',
+        requiresAuth: true,
+        showInNavigation: true,
+        showInBreadcrumbs: true,
+      },
     ],
   },
 

gateway/app/routes/tenant.py

@@ -113,6 +113,12 @@ async def proxy_tenant_models(request: Request, tenant_id: str = Path(...), path
     target_path = f"/api/v1/tenants/{tenant_id}/models/{path}".rstrip("/")
     return await _proxy_to_training_service(request, target_path, tenant_id=tenant_id)
 
+@router.api_route("/{tenant_id}/statistics", methods=["GET", "OPTIONS"])
+async def proxy_tenant_statistics(request: Request, tenant_id: str = Path(...)):
+    """Proxy tenant statistics requests to training service"""
+    target_path = f"/api/v1/tenants/{tenant_id}/statistics"
+    return await _proxy_to_training_service(request, target_path, tenant_id=tenant_id)
+
 # ================================================================
 # TENANT-SCOPED FORECASTING SERVICE ENDPOINTS
 # ================================================================

services/forecasting/app/api/forecasts.py

@@ -12,7 +12,7 @@ import uuid
 from app.services.forecasting_service import EnhancedForecastingService
 from app.schemas.forecasts import (
     ForecastRequest, ForecastResponse, BatchForecastRequest,
-    BatchForecastResponse
+    BatchForecastResponse, MultiDayForecastResponse
 )
 from shared.auth.decorators import (
     get_current_user_dep,
@@ -89,6 +89,70 @@ async def create_enhanced_single_forecast(
         )
 
 
+@router.post("/tenants/{tenant_id}/forecasts/multi-day", response_model=MultiDayForecastResponse)
+@track_execution_time("enhanced_multi_day_forecast_duration_seconds", "forecasting-service")
+async def create_enhanced_multi_day_forecast(
+    request: ForecastRequest,
+    tenant_id: str = Path(..., description="Tenant ID"),
+    request_obj: Request = None,
+    enhanced_forecasting_service: EnhancedForecastingService = Depends(get_enhanced_forecasting_service)
+):
+    """Generate multiple daily forecasts for the specified period using enhanced repository pattern"""
+    metrics = get_metrics_collector(request_obj)
+
+    try:
+        logger.info("Generating enhanced multi-day forecast",
+                   tenant_id=tenant_id,
+                   inventory_product_id=request.inventory_product_id,
+                   forecast_days=request.forecast_days,
+                   forecast_date=request.forecast_date.isoformat())
+
+        # Record metrics
+        if metrics:
+            metrics.increment_counter("enhanced_multi_day_forecasts_total")
+
+        # Validate forecast_days parameter
+        if request.forecast_days <= 0 or request.forecast_days > 30:
+            raise ValueError("forecast_days must be between 1 and 30")
+
+        # Generate multi-day forecast using enhanced service
+        forecast_result = await enhanced_forecasting_service.generate_multi_day_forecast(
+            tenant_id=tenant_id,
+            request=request
+        )
+
+        if metrics:
+            metrics.increment_counter("enhanced_multi_day_forecasts_success_total")
+
+        logger.info("Enhanced multi-day forecast generated successfully",
+                   tenant_id=tenant_id,
+                   inventory_product_id=request.inventory_product_id,
+                   forecast_days=len(forecast_result.get("forecasts", [])))
+
+        return MultiDayForecastResponse(**forecast_result)
+
+    except ValueError as e:
+        if metrics:
+            metrics.increment_counter("enhanced_multi_day_forecast_validation_errors_total")
+        logger.error("Enhanced multi-day forecast validation error",
+                    error=str(e),
+                    tenant_id=tenant_id)
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=str(e)
+        )
+    except Exception as e:
+        if metrics:
+            metrics.increment_counter("enhanced_multi_day_forecasts_errors_total")
+        logger.error("Enhanced multi-day forecast generation failed",
+                    error=str(e),
+                    tenant_id=tenant_id)
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="Enhanced multi-day forecast generation failed"
+        )
+
+
 @router.post("/tenants/{tenant_id}/forecasts/batch", response_model=BatchForecastResponse)
 @track_execution_time("enhanced_batch_forecast_duration_seconds", "forecasting-service")
 async def create_enhanced_batch_forecast(

services/forecasting/app/schemas/forecasts.py

@@ -95,4 +95,15 @@ class BatchForecastResponse(BaseModel):
     forecasts: Optional[List[ForecastResponse]]
     error_message: Optional[str]
 
+class MultiDayForecastResponse(BaseModel):
+    """Response schema for multi-day forecast results"""
+    tenant_id: str = Field(..., description="Tenant ID")
+    inventory_product_id: str = Field(..., description="Inventory product ID")
+    forecast_start_date: date = Field(..., description="Start date of forecast period")
+    forecast_days: int = Field(..., description="Number of forecasted days")
+    forecasts: List[ForecastResponse] = Field(..., description="Daily forecasts")
+    total_predicted_demand: float = Field(..., description="Total demand across all days")
+    average_confidence_level: float = Field(..., description="Average confidence across all days")
+    processing_time_ms: int = Field(..., description="Total processing time")
+
 

services/forecasting/app/services/forecasting_service.py

@@ -346,6 +346,100 @@ class EnhancedForecastingService:
                         processing_time=processing_time)
             raise
 
+    async def generate_multi_day_forecast(
+        self,
+        tenant_id: str,
+        request: ForecastRequest
+    ) -> Dict[str, Any]:
+        """
+        Generate multiple daily forecasts for the specified period.
+        """
+        start_time = datetime.utcnow()
+        forecasts = []
+
+        try:
+            logger.info("Generating multi-day forecast",
+                       tenant_id=tenant_id,
+                       inventory_product_id=request.inventory_product_id,
+                       forecast_days=request.forecast_days,
+                       start_date=request.forecast_date.isoformat())
+
+            # Generate a forecast for each day
+            for day_offset in range(request.forecast_days):
+                # Calculate the forecast date for this day
+                current_date = request.forecast_date
+                if isinstance(current_date, str):
+                    from dateutil.parser import parse
+                    current_date = parse(current_date).date()
+
+                if day_offset > 0:
+                    from datetime import timedelta
+                    current_date = current_date + timedelta(days=day_offset)
+
+                # Create a new request for this specific day
+                daily_request = ForecastRequest(
+                    inventory_product_id=request.inventory_product_id,
+                    forecast_date=current_date,
+                    forecast_days=1,  # Single day for each iteration
+                    location=request.location,
+                    confidence_level=request.confidence_level
+                )
+
+                # Generate forecast for this day
+                daily_forecast = await self.generate_forecast(tenant_id, daily_request)
+                forecasts.append(daily_forecast)
+
+            # Calculate summary statistics
+            total_demand = sum(f.predicted_demand for f in forecasts)
+            avg_confidence = sum(f.confidence_level for f in forecasts) / len(forecasts)
+            processing_time = int((datetime.utcnow() - start_time).total_seconds() * 1000)
+
+            # Convert forecasts to dictionary format for the response
+            forecast_dicts = []
+            for forecast in forecasts:
+                forecast_dicts.append({
+                    "id": forecast.id,
+                    "tenant_id": forecast.tenant_id,
+                    "inventory_product_id": forecast.inventory_product_id,
+                    "location": forecast.location,
+                    "forecast_date": forecast.forecast_date.isoformat() if hasattr(forecast.forecast_date, 'isoformat') else str(forecast.forecast_date),
+                    "predicted_demand": forecast.predicted_demand,
+                    "confidence_lower": forecast.confidence_lower,
+                    "confidence_upper": forecast.confidence_upper,
+                    "confidence_level": forecast.confidence_level,
+                    "model_id": forecast.model_id,
+                    "model_version": forecast.model_version,
+                    "algorithm": forecast.algorithm,
+                    "business_type": forecast.business_type,
+                    "is_holiday": forecast.is_holiday,
+                    "is_weekend": forecast.is_weekend,
+                    "day_of_week": forecast.day_of_week,
+                    "weather_temperature": forecast.weather_temperature,
+                    "weather_precipitation": forecast.weather_precipitation,
+                    "weather_description": forecast.weather_description,
+                    "traffic_volume": forecast.traffic_volume,
+                    "created_at": forecast.created_at.isoformat() if hasattr(forecast.created_at, 'isoformat') else str(forecast.created_at),
+                    "processing_time_ms": forecast.processing_time_ms,
+                    "features_used": forecast.features_used
+                })
+
+            return {
+                "tenant_id": tenant_id,
+                "inventory_product_id": request.inventory_product_id,
+                "forecast_start_date": request.forecast_date.isoformat() if hasattr(request.forecast_date, 'isoformat') else str(request.forecast_date),
+                "forecast_days": request.forecast_days,
+                "forecasts": forecast_dicts,
+                "total_predicted_demand": total_demand,
+                "average_confidence_level": avg_confidence,
+                "processing_time_ms": processing_time
+            }
+
+        except Exception as e:
+            logger.error("Multi-day forecast generation failed",
+                        tenant_id=tenant_id,
+                        error=str(e))
+            raise
+
     async def get_forecast_history(
         self,
         tenant_id: str,