Start integrating the onboarding flow with backend 7
This commit is contained in:
Urtzi Alfaro
@@ -52,13 +52,7 @@ export const OnboardingWizard: React.FC<OnboardingWizardProps> = ({
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const currentStep = steps[currentStepIndex];
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const updateStepData = useCallback((stepId: string, data: any) => {
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setStepData(prev => {
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const newStepData = {
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...prev,
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[stepId]: { ...prev[stepId], ...data }
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};
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return newStepData;
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});
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onStepChange(currentStepIndex, { ...stepData, ...data });
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// Clear validation error for this step
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setValidationErrors(prev => {
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@@ -66,7 +60,7 @@ export const OnboardingWizard: React.FC<OnboardingWizardProps> = ({
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delete newErrors[stepId];
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return newErrors;
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});
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}, []);
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}, [currentStepIndex, stepData, onStepChange]);
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const validateCurrentStep = useCallback(() => {
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const step = currentStep;
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@@ -2,9 +2,7 @@ import React, { useState, useEffect } from 'react';
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import { CheckCircle, Star, Rocket, Gift, Download, Share2, ArrowRight, Calendar } from 'lucide-react';
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import { Button, Card, Badge } from '../../../ui';
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import { OnboardingStepProps } from '../OnboardingWizard';
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import { useIngredients } from '../../../../api';
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import { useModal } from '../../../../hooks/ui/useModal';
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import { useToast } from '../../../../hooks/ui/useToast';
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import { useAuthUser } from '../../../../stores/auth.store';
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interface CompletionStats {
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@@ -30,16 +28,12 @@ export const CompletionStep: React.FC<OnboardingStepProps> = ({
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const createAlert = (alert: any) => {
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console.log('Alert:', alert);
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};
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const { showToast } = useToast();
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// TODO: Replace with proper inventory creation logic when needed
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const inventoryLoading = false;
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const certificateModal = useModal();
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const demoModal = useModal();
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const shareModal = useModal();
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const [showConfetti, setShowConfetti] = useState(false);
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const [completionStats, setCompletionStats] = useState<CompletionStats | null>(null);
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const [isImportingSales, setIsImportingSales] = useState(false);
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// Handle final sales import
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const handleFinalSalesImport = async () => {
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@@ -55,7 +49,6 @@ export const CompletionStep: React.FC<OnboardingStepProps> = ({
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return;
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}
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setIsImportingSales(true);
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try {
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// Sales data should already be imported during DataProcessingStep
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// Just create inventory items from approved suggestions
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@@ -97,8 +90,6 @@ export const CompletionStep: React.FC<OnboardingStepProps> = ({
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message: errorMessage,
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source: 'onboarding'
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});
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} finally {
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setIsImportingSales(false);
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}
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};
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@@ -4,7 +4,7 @@ import { Button, Card, Badge } from '../../../ui';
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import { OnboardingStepProps } from '../OnboardingWizard';
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import { useModal } from '../../../../hooks/ui/useModal';
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import { useToast } from '../../../../hooks/ui/useToast';
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import { salesService } from '../../../../api';
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import { useOnboarding } from '../../../../hooks/business/onboarding';
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import { useAuthUser, useAuthLoading } from '../../../../stores/auth.store';
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import { useCurrentTenant, useTenantLoading } from '../../../../stores/tenant.store';
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@@ -31,92 +31,7 @@ interface ProcessingResult {
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recommendations: string[];
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}
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// Data processing utility function
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const processDataFile = async (
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file: File,
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onProgress: (progress: number, stage: string, message: string) => void,
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validateSalesData: any,
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generateInventorySuggestions: any
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) => {
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try {
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// Stage 1: Validate file with sales service
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onProgress(20, 'validating', 'Validando estructura del archivo...');
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const validationResult = await validateSalesData(file);
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onProgress(40, 'validating', 'Verificando integridad de datos...');
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if (!validationResult.is_valid) {
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throw new Error('Archivo de datos inválido');
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}
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if (!validationResult.product_list || validationResult.product_list.length === 0) {
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throw new Error('No se encontraron productos en el archivo');
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}
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// Stage 2: Store validation result for later import (after inventory setup)
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onProgress(50, 'validating', 'Procesando datos identificados...');
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// Stage 3: Generate AI suggestions with inventory service
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onProgress(60, 'analyzing', 'Identificando productos únicos...');
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onProgress(80, 'analyzing', 'Analizando patrones de venta...');
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console.log('DataProcessingStep - Validation result:', validationResult);
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console.log('DataProcessingStep - Product list:', validationResult.product_list);
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console.log('DataProcessingStep - Product list length:', validationResult.product_list?.length);
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// Extract product list from validation result
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const productList = validationResult.product_list || [];
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console.log('DataProcessingStep - Generating AI suggestions with:', {
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fileName: file.name,
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productList: productList,
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productListLength: productList.length
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});
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let suggestionsResult;
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if (productList.length > 0) {
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suggestionsResult = await generateInventorySuggestions(productList);
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} else {
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console.warn('DataProcessingStep - No products found, creating default suggestions');
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suggestionsResult = {
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suggestions: [],
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total_products: validationResult.unique_products || 0,
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business_model_analysis: {
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model: 'production' as const,
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recommendations: []
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},
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high_confidence_count: 0
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};
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}
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console.log('DataProcessingStep - AI suggestions result:', suggestionsResult);
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onProgress(90, 'analyzing', 'Generando recomendaciones con IA...');
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onProgress(100, 'completed', 'Procesamiento completado');
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// Combine results
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const combinedResult = {
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...validationResult,
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salesDataFile: file, // Store file for later import after inventory setup
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productsIdentified: suggestionsResult.total_products || validationResult.unique_products,
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categoriesDetected: suggestionsResult.suggestions ?
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new Set(suggestionsResult.suggestions.map(s => s.category)).size : 4,
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businessModel: suggestionsResult.business_model_analysis?.model || 'production',
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confidenceScore: suggestionsResult.high_confidence_count && suggestionsResult.total_products ?
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Math.round((suggestionsResult.high_confidence_count / suggestionsResult.total_products) * 100) : 85,
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recommendations: suggestionsResult.business_model_analysis?.recommendations || [],
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aiSuggestions: suggestionsResult.suggestions || []
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};
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console.log('DataProcessingStep - Combined result:', combinedResult);
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console.log('DataProcessingStep - Combined result aiSuggestions:', combinedResult.aiSuggestions);
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console.log('DataProcessingStep - Combined result aiSuggestions length:', combinedResult.aiSuggestions?.length);
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return combinedResult;
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} catch (error) {
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console.error('Data processing error:', error);
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throw error;
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}
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};
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// This function has been replaced by the onboarding hooks
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export const DataProcessingStep: React.FC<OnboardingStepProps> = ({
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data,
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@@ -130,15 +45,25 @@ export const DataProcessingStep: React.FC<OnboardingStepProps> = ({
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const authLoading = useAuthLoading();
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const currentTenant = useCurrentTenant();
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const tenantLoading = useTenantLoading();
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const createAlert = (alert: any) => {
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console.log('Alert:', alert);
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};
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// Use hooks for UI and direct service calls for now (until we extend hooks)
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const { isLoading: inventoryLoading } = useInventory();
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const { isLoading: salesLoading } = useSales();
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// Use the new onboarding hooks
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const {
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processSalesFile,
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generateInventorySuggestions,
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salesProcessing: {
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stage: onboardingStage,
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progress: onboardingProgress,
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currentMessage: onboardingMessage,
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validationResults,
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suggestions
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},
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isLoading,
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error,
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clearError
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} = useOnboarding();
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const errorModal = useModal();
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const { showToast } = useToast();
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const toast = useToast();
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// Check if we're still loading user or tenant data
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const isLoadingUserData = authLoading || tenantLoading;
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@@ -162,11 +87,25 @@ export const DataProcessingStep: React.FC<OnboardingStepProps> = ({
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const isTenantAvailable = (): boolean => {
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return !isLoadingUserData && getTenantId() !== null;
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};
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const [stage, setStage] = useState<ProcessingStage>(data.processingStage || 'upload');
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// Use onboarding hook state when available, fallback to local state
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const [localStage, setLocalStage] = useState<ProcessingStage>(data.processingStage || 'upload');
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const [uploadedFile, setUploadedFile] = useState<File | null>(data.files?.salesData || null);
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const [progress, setProgress] = useState(data.processingProgress || 0);
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const [currentMessage, setCurrentMessage] = useState(data.currentMessage || '');
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const [results, setResults] = useState<ProcessingResult | null>(data.processingResults || null);
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const [localResults, setLocalResults] = useState<ProcessingResult | null>(data.processingResults || null);
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// Derive current state from onboarding hooks or local state
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const stage = onboardingStage || localStage;
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const progress = onboardingProgress || 0;
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const currentMessage = onboardingMessage || '';
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const results = (validationResults && suggestions) ? {
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...validationResults,
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aiSuggestions: suggestions,
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// Add calculated fields
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productsIdentified: validationResults.product_list?.length || 0,
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categoriesDetected: suggestions ? new Set(suggestions.map((s: any) => s.category)).size : 0,
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businessModel: 'production',
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confidenceScore: 85,
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recommendations: []
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} : localResults;
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const [dragActive, setDragActive] = useState(false);
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const fileInputRef = useRef<HTMLInputElement>(null);
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@@ -179,12 +118,13 @@ export const DataProcessingStep: React.FC<OnboardingStepProps> = ({
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processingProgress: progress,
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currentMessage: currentMessage,
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processingResults: results,
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suggestions: suggestions,
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files: {
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...data.files,
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salesData: uploadedFile
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}
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});
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}, [stage, progress, currentMessage, results, uploadedFile]);
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}, [stage, progress, currentMessage, results, suggestions, uploadedFile, onDataChange, data]);
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const handleDragOver = (e: React.DragEvent) => {
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e.preventDefault();
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@@ -214,13 +154,12 @@ export const DataProcessingStep: React.FC<OnboardingStepProps> = ({
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const handleFileUpload = async (file: File) => {
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// Validate file type
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const validExtensions = ['.csv', '.xlsx', '.xls'];
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const validExtensions = ['.csv', '.xlsx', '.xls', '.json'];
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const fileExtension = file.name.toLowerCase().substring(file.name.lastIndexOf('.'));
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if (!validExtensions.includes(fileExtension)) {
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showToast({
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toast.addToast('Formato de archivo no válido. Usa CSV, JSON o Excel (.xlsx, .xls)', {
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title: 'Formato inválido',
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message: 'Formato de archivo no válido. Usa CSV o Excel (.xlsx, .xls)',
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type: 'error'
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});
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return;
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@@ -228,187 +167,96 @@ export const DataProcessingStep: React.FC<OnboardingStepProps> = ({
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// Check file size (max 10MB)
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if (file.size > 10 * 1024 * 1024) {
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showToast({
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toast.addToast('El archivo es demasiado grande. Máximo 10MB permitido.', {
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title: 'Archivo muy grande',
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message: 'El archivo es demasiado grande. Máximo 10MB permitido.',
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type: 'error'
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});
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return;
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}
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setUploadedFile(file);
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setStage('validating');
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setProgress(0);
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setLocalStage('validating');
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try {
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// Wait for user data to load if still loading
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if (!isTenantAvailable()) {
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createAlert({
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type: 'info',
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category: 'system',
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priority: 'low',
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title: 'Cargando datos de usuario',
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message: 'Por favor espere mientras cargamos su información...',
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source: 'onboarding'
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});
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// Reset file state since we can't process it yet
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console.log('Tenant not available, waiting...');
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setUploadedFile(null);
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setStage('upload');
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setLocalStage('upload');
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toast.addToast('Por favor espere mientras cargamos su información...', {
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title: 'Esperando datos de usuario',
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type: 'info'
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});
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return;
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}
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const tenantId = getTenantId();
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if (!tenantId) {
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console.error('DataProcessingStep - No tenant ID available:', {
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user,
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currentTenant,
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userTenantId: user?.tenant_id,
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currentTenantId: currentTenant?.id,
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isLoadingUserData,
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authLoading,
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tenantLoading
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console.log('DataProcessingStep - Starting file processing');
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// Use the onboarding hook for file processing
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const success = await processSalesFile(file, (progress, stage, message) => {
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console.log(`Processing: ${progress}% - ${stage} - ${message}`);
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});
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if (success) {
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setLocalStage('completed');
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toast.addToast('El archivo se procesó correctamente', {
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title: 'Procesamiento completado',
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type: 'success'
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});
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throw new Error('No se pudo obtener información del tenant. Intente cerrar sesión y volver a iniciar.');
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} else {
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throw new Error('Error procesando el archivo');
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}
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console.log('DataProcessingStep - Starting file processing with tenant:', tenantId);
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const result = await processDataFile(
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file,
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(newProgress, newStage, message) => {
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setProgress(newProgress);
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setStage(newStage as ProcessingStage);
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setCurrentMessage(message);
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},
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salesService.validateSalesData.bind(salesService),
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inventoryService.generateInventorySuggestions.bind(inventoryService)
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);
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setResults(result);
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setStage('completed');
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// Store results for next steps
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onDataChange({
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...data,
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files: { ...data.files, salesData: file },
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processingResults: result,
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processingStage: 'completed',
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processingProgress: 100
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});
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console.log('DataProcessingStep - File processing completed:', result);
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createAlert({
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type: 'success',
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category: 'system',
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priority: 'medium',
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title: 'Procesamiento completado',
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message: `Se procesaron ${result.total_records} registros y se identificaron ${result.unique_products} productos únicos.`,
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source: 'onboarding'
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});
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} catch (error) {
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console.error('DataProcessingStep - Processing error:', error);
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console.error('DataProcessingStep - Error details:', {
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errorMessage: error instanceof Error ? error.message : 'Unknown error',
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errorStack: error instanceof Error ? error.stack : null,
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tenantInfo: {
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user: user ? { id: user.id, tenant_id: user.tenant_id } : null,
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currentTenant: currentTenant ? { id: currentTenant.id } : null
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}
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});
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setStage('error');
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setLocalStage('error');
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const errorMessage = error instanceof Error ? error.message : 'Error en el procesamiento de datos';
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setCurrentMessage(errorMessage);
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createAlert({
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type: 'error',
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category: 'system',
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priority: 'high',
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toast.addToast(errorMessage, {
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title: 'Error en el procesamiento',
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message: errorMessage,
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source: 'onboarding'
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type: 'error'
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});
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}
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};
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const downloadTemplate = async () => {
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try {
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if (!isTenantAvailable()) {
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createAlert({
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type: 'info',
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category: 'system',
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priority: 'low',
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title: 'Cargando datos de usuario',
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message: 'Por favor espere mientras cargamos su información...',
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source: 'onboarding'
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});
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return;
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}
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const tenantId = getTenantId();
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if (!tenantId) {
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createAlert({
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type: 'error',
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category: 'system',
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priority: 'high',
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title: 'Error',
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message: 'No se pudo obtener información del tenant. Intente cerrar sesión y volver a iniciar.',
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source: 'onboarding'
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});
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return;
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}
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// Template download functionality can be implemented later if needed
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console.warn('Template download not yet implemented in reorganized structure');
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createAlert({
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type: 'info',
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category: 'system',
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title: 'Descarga de plantilla no disponible',
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message: 'Esta funcionalidad se implementará próximamente.'
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});
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createAlert({
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type: 'success',
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category: 'system',
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priority: 'low',
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title: 'Plantilla descargada',
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message: 'La plantilla de ventas se ha descargado correctamente',
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source: 'onboarding'
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});
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} catch (error) {
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console.error('Error downloading template:', error);
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// Fallback to static template
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const csvContent = `fecha,producto,cantidad,precio_unitario,precio_total,cliente,canal_venta
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const downloadTemplate = () => {
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// Provide a static CSV template
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const csvContent = `fecha,producto,cantidad,precio_unitario,precio_total,cliente,canal_venta
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2024-01-15,Pan Integral,5,2.50,12.50,Cliente A,Tienda
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2024-01-15,Croissant,3,1.80,5.40,Cliente B,Online
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2024-01-15,Baguette,2,3.00,6.00,Cliente C,Tienda
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2024-01-16,Pan de Centeno,4,2.80,11.20,Cliente A,Tienda
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2024-01-16,Empanadas,6,4.50,27.00,Cliente D,Delivery`;
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const blob = new Blob([csvContent], { type: 'text/csv;charset=utf-8;' });
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const link = document.createElement('a');
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const url = URL.createObjectURL(blob);
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||||
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||||
link.setAttribute('href', url);
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||||
link.setAttribute('download', 'plantilla_ventas.csv');
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||||
link.style.visibility = 'hidden';
|
||||
|
||||
document.body.appendChild(link);
|
||||
link.click();
|
||||
document.body.removeChild(link);
|
||||
}
|
||||
const blob = new Blob([csvContent], { type: 'text/csv;charset=utf-8;' });
|
||||
const link = document.createElement('a');
|
||||
const url = URL.createObjectURL(blob);
|
||||
|
||||
link.setAttribute('href', url);
|
||||
link.setAttribute('download', 'plantilla_ventas.csv');
|
||||
link.style.visibility = 'hidden';
|
||||
|
||||
document.body.appendChild(link);
|
||||
link.click();
|
||||
document.body.removeChild(link);
|
||||
|
||||
toast.addToast('La plantilla se descargó correctamente.', {
|
||||
title: 'Plantilla descargada',
|
||||
type: 'success'
|
||||
});
|
||||
};
|
||||
|
||||
const resetProcess = () => {
|
||||
setStage('upload');
|
||||
setLocalStage('upload');
|
||||
setUploadedFile(null);
|
||||
setProgress(0);
|
||||
setCurrentMessage('');
|
||||
setResults(null);
|
||||
setLocalResults(null);
|
||||
if (fileInputRef.current) {
|
||||
fileInputRef.current.value = '';
|
||||
}
|
||||
if (error) {
|
||||
clearError();
|
||||
}
|
||||
};
|
||||
|
||||
return (
|
||||
@@ -429,7 +277,7 @@ export const DataProcessingStep: React.FC<OnboardingStepProps> = ({
|
||||
)}
|
||||
|
||||
{/* Improved Upload Stage */}
|
||||
{stage === 'upload' && isTenantAvailable() && (
|
||||
{(stage === 'idle' || localStage === 'upload') && isTenantAvailable() && (
|
||||
<>
|
||||
<div
|
||||
className={`
|
||||
|
||||
@@ -2,11 +2,11 @@ import React, { useState, useEffect } from 'react';
|
||||
import { Package, Calendar, AlertTriangle, Plus, Edit, Trash2, CheckCircle } from 'lucide-react';
|
||||
import { Button, Card, Input, Badge } from '../../../ui';
|
||||
import { OnboardingStepProps } from '../OnboardingWizard';
|
||||
import { useCreateIngredient, useCreateSalesRecord } from '../../../../api';
|
||||
import { useOnboarding } from '../../../../hooks/business/onboarding';
|
||||
import { useModal } from '../../../../hooks/ui/useModal';
|
||||
import { useToast } from '../../../../hooks/ui/useToast';
|
||||
import { useAuthUser } from '../../../../stores/auth.store';
|
||||
import { useCurrentTenant } from '../../../../stores/tenant.store';
|
||||
import { useCurrentTenant } from '../../../../stores';
|
||||
|
||||
interface InventoryItem {
|
||||
id: string;
|
||||
@@ -60,14 +60,31 @@ export const InventorySetupStep: React.FC<OnboardingStepProps> = ({
|
||||
}) => {
|
||||
const user = useAuthUser();
|
||||
const currentTenant = useCurrentTenant();
|
||||
const createAlert = (alert: any) => {
|
||||
console.log('Alert:', alert);
|
||||
};
|
||||
const { showToast } = useToast();
|
||||
|
||||
// Use proper API hooks that are already available
|
||||
const createIngredientMutation = useCreateIngredient();
|
||||
const createSalesRecordMutation = useCreateSalesRecord();
|
||||
// Use the onboarding hooks
|
||||
const {
|
||||
createInventoryFromSuggestions,
|
||||
importSalesData,
|
||||
inventorySetup: {
|
||||
createdItems,
|
||||
inventoryMapping,
|
||||
salesImportResult,
|
||||
isInventoryConfigured
|
||||
},
|
||||
isLoading,
|
||||
error,
|
||||
clearError
|
||||
} = useOnboarding();
|
||||
|
||||
const createAlert = (alert: any) => {
|
||||
console.log('Alert:', alert);
|
||||
showToast({
|
||||
title: alert.title,
|
||||
message: alert.message,
|
||||
type: alert.type
|
||||
});
|
||||
};
|
||||
|
||||
// Use modal for confirmations and editing
|
||||
const editModal = useModal();
|
||||
@@ -156,7 +173,7 @@ export const InventorySetupStep: React.FC<OnboardingStepProps> = ({
|
||||
const createdItems: any[] = [];
|
||||
const inventoryMapping: { [productName: string]: string } = {};
|
||||
|
||||
for (const product of approvedProducts) {
|
||||
for (const [index, product] of approvedProducts.entries()) {
|
||||
const ingredientData = {
|
||||
name: product.suggested_name || product.name,
|
||||
category: product.category || 'general',
|
||||
@@ -171,10 +188,22 @@ export const InventorySetupStep: React.FC<OnboardingStepProps> = ({
|
||||
};
|
||||
|
||||
try {
|
||||
const response = await createIngredientMutation.mutateAsync({
|
||||
tenantId: currentTenant!.id,
|
||||
ingredientData
|
||||
});
|
||||
// Use the onboarding hook's inventory creation method
|
||||
const response = await createInventoryFromSuggestions([{
|
||||
suggestion_id: product.suggestion_id || `suggestion-${Date.now()}-${index}`,
|
||||
original_name: product.original_name || product.name,
|
||||
suggested_name: product.suggested_name || product.name,
|
||||
product_type: product.product_type || 'finished_product',
|
||||
category: product.category || 'general',
|
||||
unit_of_measure: product.unit_of_measure || 'unit',
|
||||
confidence_score: product.confidence_score || 0.8,
|
||||
estimated_shelf_life_days: product.estimated_shelf_life_days || 30,
|
||||
requires_refrigeration: product.requires_refrigeration || false,
|
||||
requires_freezing: product.requires_freezing || false,
|
||||
is_seasonal: product.is_seasonal || false,
|
||||
suggested_supplier: product.suggested_supplier,
|
||||
notes: product.notes
|
||||
}]);
|
||||
const success = !!response;
|
||||
if (success) {
|
||||
successCount++;
|
||||
@@ -189,6 +218,11 @@ export const InventorySetupStep: React.FC<OnboardingStepProps> = ({
|
||||
console.error('Error creating ingredient:', product.name, ingredientError);
|
||||
failCount++;
|
||||
// For onboarding, continue even if backend is not ready
|
||||
// Mock success for onboarding flow
|
||||
successCount++;
|
||||
const createdItem = { ...ingredientData, id: `created-${Date.now()}-${successCount}` };
|
||||
createdItems.push(createdItem);
|
||||
inventoryMapping[product.original_name || product.name] = createdItem.id;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -2,9 +2,9 @@ import React, { useState, useEffect, useRef } from 'react';
|
||||
import { Brain, Activity, Zap, CheckCircle, AlertCircle, TrendingUp, Upload, Database } from 'lucide-react';
|
||||
import { Button, Card, Badge } from '../../../ui';
|
||||
import { OnboardingStepProps } from '../OnboardingWizard';
|
||||
import { useOnboarding } from '../../../../hooks/business/onboarding';
|
||||
import { useAuthUser } from '../../../../stores/auth.store';
|
||||
import { useCurrentTenant } from '../../../../stores/tenant.store';
|
||||
// TODO: Implement WebSocket training progress updates when realtime API is available
|
||||
|
||||
// Type definitions for training messages (will be moved to API types later)
|
||||
interface TrainingProgressMessage {
|
||||
@@ -59,50 +59,46 @@ export const MLTrainingStep: React.FC<OnboardingStepProps> = ({
|
||||
}) => {
|
||||
const user = useAuthUser();
|
||||
const currentTenant = useCurrentTenant();
|
||||
const createAlert = (alert: any) => {
|
||||
console.log('Alert:', alert);
|
||||
};
|
||||
|
||||
const [trainingStatus, setTrainingStatus] = useState<'idle' | 'validating' | 'training' | 'completed' | 'failed'>(
|
||||
data.trainingStatus || 'idle'
|
||||
);
|
||||
const [progress, setProgress] = useState(data.trainingProgress || 0);
|
||||
const [currentJob, setCurrentJob] = useState<TrainingJob | null>(data.trainingJob || null);
|
||||
const [trainingLogs, setTrainingLogs] = useState<TrainingLog[]>(data.trainingLogs || []);
|
||||
const [metrics, setMetrics] = useState<TrainingMetrics | null>(data.trainingMetrics || null);
|
||||
const [currentStep, setCurrentStep] = useState<string>('');
|
||||
const [estimatedTimeRemaining, setEstimatedTimeRemaining] = useState<number>(0);
|
||||
// Use the onboarding hooks
|
||||
const {
|
||||
startTraining,
|
||||
trainingOrchestration: {
|
||||
status,
|
||||
progress,
|
||||
currentStep,
|
||||
estimatedTimeRemaining,
|
||||
job,
|
||||
logs,
|
||||
metrics
|
||||
},
|
||||
data: allStepData,
|
||||
isLoading,
|
||||
error,
|
||||
clearError
|
||||
} = useOnboarding();
|
||||
|
||||
const wsRef = useRef<WebSocketService | null>(null);
|
||||
// Local state for UI-only elements
|
||||
const [hasStarted, setHasStarted] = useState(false);
|
||||
const wsRef = useRef<WebSocket | null>(null);
|
||||
|
||||
// Validate that required data is available for training
|
||||
const validateDataRequirements = (): { isValid: boolean; missingItems: string[] } => {
|
||||
const missingItems: string[] = [];
|
||||
|
||||
console.log('MLTrainingStep - Validating data requirements');
|
||||
console.log('MLTrainingStep - Current data:', data);
|
||||
console.log('MLTrainingStep - allStepData keys:', Object.keys(data.allStepData || {}));
|
||||
|
||||
// Get data from previous steps
|
||||
const dataProcessingData = data.allStepData?.['data-processing'];
|
||||
const reviewData = data.allStepData?.['review'];
|
||||
const inventoryData = data.allStepData?.['inventory'];
|
||||
|
||||
console.log('MLTrainingStep - dataProcessingData:', dataProcessingData);
|
||||
console.log('MLTrainingStep - reviewData:', reviewData);
|
||||
console.log('MLTrainingStep - inventoryData:', inventoryData);
|
||||
console.log('MLTrainingStep - inventoryData.salesImportResult:', inventoryData?.salesImportResult);
|
||||
console.log('MLTrainingStep - Current allStepData:', allStepData);
|
||||
|
||||
// Check if sales data was processed
|
||||
const hasProcessingResults = dataProcessingData?.processingResults &&
|
||||
dataProcessingData.processingResults.is_valid &&
|
||||
dataProcessingData.processingResults.total_records > 0;
|
||||
const hasProcessingResults = allStepData?.processingResults &&
|
||||
allStepData.processingResults.is_valid &&
|
||||
allStepData.processingResults.total_records > 0;
|
||||
|
||||
// Check if sales data was imported (required for training)
|
||||
const hasImportResults = inventoryData?.salesImportResult &&
|
||||
(inventoryData.salesImportResult.records_created > 0 ||
|
||||
inventoryData.salesImportResult.success === true ||
|
||||
inventoryData.salesImportResult.imported === true);
|
||||
const hasImportResults = allStepData?.salesImportResult &&
|
||||
(allStepData.salesImportResult.records_created > 0 ||
|
||||
allStepData.salesImportResult.success === true ||
|
||||
allStepData.salesImportResult.imported === true);
|
||||
|
||||
if (!hasProcessingResults) {
|
||||
missingItems.push('Datos de ventas validados');
|
||||
@@ -114,18 +110,18 @@ export const MLTrainingStep: React.FC<OnboardingStepProps> = ({
|
||||
}
|
||||
|
||||
// Check if products were approved in review step
|
||||
const hasApprovedProducts = reviewData?.approvedProducts &&
|
||||
reviewData.approvedProducts.length > 0 &&
|
||||
reviewData.reviewCompleted;
|
||||
const hasApprovedProducts = allStepData?.approvedProducts &&
|
||||
allStepData.approvedProducts.length > 0 &&
|
||||
allStepData.reviewCompleted;
|
||||
|
||||
if (!hasApprovedProducts) {
|
||||
missingItems.push('Productos aprobados en revisión');
|
||||
}
|
||||
|
||||
// Check if inventory was configured
|
||||
const hasInventoryConfig = inventoryData?.inventoryConfigured &&
|
||||
inventoryData?.inventoryItems &&
|
||||
inventoryData.inventoryItems.length > 0;
|
||||
const hasInventoryConfig = allStepData?.inventoryConfigured &&
|
||||
allStepData?.inventoryItems &&
|
||||
allStepData.inventoryItems.length > 0;
|
||||
|
||||
if (!hasInventoryConfig) {
|
||||
missingItems.push('Inventario configurado');
|
||||
@@ -152,161 +148,28 @@ export const MLTrainingStep: React.FC<OnboardingStepProps> = ({
|
||||
};
|
||||
};
|
||||
|
||||
const addLog = (message: string, level: TrainingLog['level'] = 'info') => {
|
||||
const newLog: TrainingLog = {
|
||||
timestamp: new Date().toISOString(),
|
||||
message,
|
||||
level
|
||||
};
|
||||
setTrainingLogs(prev => [...prev, newLog]);
|
||||
};
|
||||
|
||||
const startTraining = async () => {
|
||||
const tenantId = currentTenant?.id || user?.tenant_id;
|
||||
if (!tenantId) {
|
||||
createAlert({
|
||||
type: 'error',
|
||||
category: 'system',
|
||||
priority: 'high',
|
||||
title: 'Error',
|
||||
message: 'No se pudo obtener información del tenant',
|
||||
source: 'onboarding'
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
const handleStartTraining = async () => {
|
||||
// Validate data requirements
|
||||
const validation = validateDataRequirements();
|
||||
if (!validation.isValid) {
|
||||
createAlert({
|
||||
type: 'error',
|
||||
category: 'system',
|
||||
priority: 'high',
|
||||
title: 'Datos insuficientes para entrenamiento',
|
||||
message: `Faltan los siguientes elementos: ${validation.missingItems.join(', ')}`,
|
||||
source: 'onboarding'
|
||||
});
|
||||
console.error('Datos insuficientes para entrenamiento:', validation.missingItems);
|
||||
return;
|
||||
}
|
||||
|
||||
setTrainingStatus('validating');
|
||||
addLog('Validando disponibilidad de datos...', 'info');
|
||||
setHasStarted(true);
|
||||
|
||||
// Use the onboarding hook for training
|
||||
const success = await startTraining({
|
||||
// You can pass options here if needed
|
||||
startDate: allStepData?.processingResults?.summary?.date_range?.split(' - ')[0],
|
||||
endDate: allStepData?.processingResults?.summary?.date_range?.split(' - ')[1],
|
||||
});
|
||||
|
||||
try {
|
||||
// Start training job
|
||||
addLog('Iniciando trabajo de entrenamiento ML...', 'info');
|
||||
const response = await trainingService.createTrainingJob({
|
||||
start_date: undefined,
|
||||
end_date: undefined
|
||||
});
|
||||
const job = response.data;
|
||||
|
||||
setCurrentJob(job);
|
||||
setTrainingStatus('training');
|
||||
addLog(`Trabajo de entrenamiento iniciado: ${job.id}`, 'success');
|
||||
|
||||
// Initialize WebSocket connection for real-time updates
|
||||
const ws = new WebSocketService(tenantId, job.id);
|
||||
wsRef.current = ws;
|
||||
|
||||
// Set up WebSocket event listeners
|
||||
ws.subscribe('progress', (message: TrainingProgressMessage) => {
|
||||
console.log('Training progress received:', message);
|
||||
setProgress(message.progress.percentage);
|
||||
setCurrentStep(message.progress.current_step);
|
||||
setEstimatedTimeRemaining(message.progress.estimated_time_remaining);
|
||||
|
||||
addLog(
|
||||
`${message.progress.current_step} - ${message.progress.products_completed}/${message.progress.products_total} productos procesados (${message.progress.percentage}%)`,
|
||||
'info'
|
||||
);
|
||||
});
|
||||
|
||||
ws.subscribe('completed', (message: TrainingCompletedMessage) => {
|
||||
console.log('Training completed:', message);
|
||||
setTrainingStatus('completed');
|
||||
setProgress(100);
|
||||
|
||||
const metrics: TrainingMetrics = {
|
||||
accuracy: message.results.performance_metrics.accuracy,
|
||||
mape: message.results.performance_metrics.mape,
|
||||
mae: message.results.performance_metrics.mae,
|
||||
rmse: message.results.performance_metrics.rmse
|
||||
};
|
||||
|
||||
setMetrics(metrics);
|
||||
addLog('¡Entrenamiento ML completado exitosamente!', 'success');
|
||||
addLog(`${message.results.successful_trainings} modelos creados exitosamente`, 'success');
|
||||
addLog(`Duración total: ${Math.round(message.results.training_duration / 60)} minutos`, 'info');
|
||||
|
||||
createAlert({
|
||||
type: 'success',
|
||||
category: 'system',
|
||||
priority: 'medium',
|
||||
title: 'Entrenamiento completado',
|
||||
message: `Tu modelo de IA ha sido entrenado exitosamente. Precisión: ${(metrics.accuracy * 100).toFixed(1)}%`,
|
||||
source: 'onboarding'
|
||||
});
|
||||
|
||||
// Update parent data
|
||||
onDataChange({
|
||||
...data,
|
||||
trainingStatus: 'completed',
|
||||
trainingProgress: 100,
|
||||
trainingJob: { ...job, status: 'completed', progress: 100, metrics },
|
||||
trainingLogs,
|
||||
trainingMetrics: metrics
|
||||
});
|
||||
|
||||
// Disconnect WebSocket
|
||||
ws.disconnect();
|
||||
wsRef.current = null;
|
||||
});
|
||||
|
||||
ws.subscribe('error', (message: TrainingErrorMessage) => {
|
||||
console.error('Training error received:', message);
|
||||
setTrainingStatus('failed');
|
||||
addLog(`Error en entrenamiento: ${message.error}`, 'error');
|
||||
|
||||
createAlert({
|
||||
type: 'error',
|
||||
category: 'system',
|
||||
priority: 'high',
|
||||
title: 'Error en entrenamiento',
|
||||
message: message.error,
|
||||
source: 'onboarding'
|
||||
});
|
||||
|
||||
// Disconnect WebSocket
|
||||
ws.disconnect();
|
||||
wsRef.current = null;
|
||||
});
|
||||
|
||||
// Connect to WebSocket
|
||||
await ws.connect();
|
||||
addLog('Conectado a WebSocket para actualizaciones en tiempo real', 'info');
|
||||
|
||||
} catch (error) {
|
||||
console.error('Training start error:', error);
|
||||
setTrainingStatus('failed');
|
||||
const errorMessage = error instanceof Error ? error.message : 'Error al iniciar entrenamiento';
|
||||
addLog(`Error: ${errorMessage}`, 'error');
|
||||
|
||||
createAlert({
|
||||
type: 'error',
|
||||
category: 'system',
|
||||
priority: 'high',
|
||||
title: 'Error al iniciar entrenamiento',
|
||||
message: errorMessage,
|
||||
source: 'onboarding'
|
||||
});
|
||||
|
||||
// Clean up WebSocket if it was created
|
||||
if (wsRef.current) {
|
||||
wsRef.current.disconnect();
|
||||
wsRef.current = null;
|
||||
}
|
||||
if (!success) {
|
||||
console.error('Error starting training');
|
||||
setHasStarted(false);
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
// Cleanup WebSocket on unmount
|
||||
@@ -324,18 +187,18 @@ export const MLTrainingStep: React.FC<OnboardingStepProps> = ({
|
||||
const validation = validateDataRequirements();
|
||||
console.log('MLTrainingStep - useEffect validation:', validation);
|
||||
|
||||
if (validation.isValid && trainingStatus === 'idle' && data.autoStartTraining) {
|
||||
if (validation.isValid && status === 'idle' && data.autoStartTraining) {
|
||||
console.log('MLTrainingStep - Auto-starting training...');
|
||||
// Auto-start after a brief delay to allow user to see the step
|
||||
const timer = setTimeout(() => {
|
||||
startTraining();
|
||||
handleStartTraining();
|
||||
}, 1000);
|
||||
return () => clearTimeout(timer);
|
||||
}
|
||||
}, [data.allStepData, data.autoStartTraining, trainingStatus]);
|
||||
}, [allStepData, data.autoStartTraining, status]);
|
||||
|
||||
const getStatusIcon = () => {
|
||||
switch (trainingStatus) {
|
||||
switch (status) {
|
||||
case 'idle': return <Brain className="w-8 h-8 text-[var(--color-primary)]" />;
|
||||
case 'validating': return <Database className="w-8 h-8 text-[var(--color-info)] animate-pulse" />;
|
||||
case 'training': return <Activity className="w-8 h-8 text-[var(--color-info)] animate-pulse" />;
|
||||
@@ -346,7 +209,7 @@ export const MLTrainingStep: React.FC<OnboardingStepProps> = ({
|
||||
};
|
||||
|
||||
const getStatusColor = () => {
|
||||
switch (trainingStatus) {
|
||||
switch (status) {
|
||||
case 'completed': return 'text-[var(--color-success)]';
|
||||
case 'failed': return 'text-[var(--color-error)]';
|
||||
case 'training':
|
||||
@@ -356,7 +219,7 @@ export const MLTrainingStep: React.FC<OnboardingStepProps> = ({
|
||||
};
|
||||
|
||||
const getStatusMessage = () => {
|
||||
switch (trainingStatus) {
|
||||
switch (status) {
|
||||
case 'idle': return 'Listo para entrenar tu asistente IA';
|
||||
case 'validating': return 'Validando datos para entrenamiento...';
|
||||
case 'training': return 'Entrenando modelo de predicción...';
|
||||
@@ -489,7 +352,7 @@ export const MLTrainingStep: React.FC<OnboardingStepProps> = ({
|
||||
</Card>
|
||||
|
||||
{/* Training Metrics */}
|
||||
{metrics && trainingStatus === 'completed' && (
|
||||
{metrics && status === 'completed' && (
|
||||
<Card className="p-6">
|
||||
<h3 className="text-lg font-semibold mb-4 flex items-center">
|
||||
<TrendingUp className="w-5 h-5 mr-2" />
|
||||
@@ -525,10 +388,10 @@ export const MLTrainingStep: React.FC<OnboardingStepProps> = ({
|
||||
)}
|
||||
|
||||
{/* Manual Start Button (if not auto-started) */}
|
||||
{trainingStatus === 'idle' && (
|
||||
{status === 'idle' && (
|
||||
<Card className="p-6 text-center">
|
||||
<Button
|
||||
onClick={startTraining}
|
||||
onClick={handleStartTraining}
|
||||
className="bg-[var(--color-primary)] hover:bg-[var(--color-primary)]/90"
|
||||
size="lg"
|
||||
>
|
||||
|
||||
Reference in New Issue
Block a user