Improve training test 1
This commit is contained in:
Urtzi Alfaro
@@ -28,7 +28,7 @@ STEP_ICONS=("👤" "🏪" "📊" "🤖" "🎉")
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echo -e "${CYAN}🧪 IMPROVED ONBOARDING FLOW SIMULATION TEST${NC}"
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echo -e "${CYAN}==============================================${NC}"
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echo "Testing complete user journey through onboarding process"
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echo "Using real CSV data: $REAL_CSV_FILE"
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echo "Using full CSV dataset: $REAL_CSV_FILE"
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echo "Test User: $TEST_EMAIL"
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echo ""
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@@ -127,33 +127,6 @@ except Exception as e:
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rm -f "$temp_file"
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}
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# Function to read and prepare CSV data for JSON import
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prepare_csv_for_import() {
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local csv_file="$1"
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local output_file="$2"
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local max_records="${3:-50}" # Limit records for testing
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if [ ! -f "$csv_file" ]; then
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log_error "CSV file not found: $csv_file"
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return 1
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fi
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log_step "Preparing CSV data for import (first $max_records records)"
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# Get header and first N records
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head -n 1 "$csv_file" > "$output_file"
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tail -n +2 "$csv_file" | head -n "$max_records" >> "$output_file"
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log_success "Prepared $(wc -l < "$output_file") lines (including header)"
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# Show sample of the data
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echo "Sample of prepared data:"
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head -5 "$output_file"
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echo "..."
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return 0
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}
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# Function to escape CSV content for JSON
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escape_csv_for_json() {
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local csv_file="$1"
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@@ -205,8 +178,8 @@ fi
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log_success "Real CSV file found: $REAL_CSV_FILE"
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# Show CSV file info
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echo "CSV file info:"
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# Show CSV file info - FULL DATASET
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echo "CSV file info (FULL DATASET):"
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echo " Lines: $(wc -l < "$REAL_CSV_FILE")"
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echo " Size: $(du -h "$REAL_CSV_FILE" | cut -f1)"
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echo " Header: $(head -1 "$REAL_CSV_FILE")"
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@@ -267,7 +240,7 @@ echo ""
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# STEP 1.5: USER LOGIN (AUTOMATIC AFTER REGISTRATION)
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# =================================================================
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log_step "1.5. Automatic login after registration"
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log_step "1.5. Logging in to get access token"
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LOGIN_RESPONSE=$(curl -s -X POST "$API_BASE/api/v1/auth/login" \
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-H "Content-Type: application/json" \
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@@ -279,15 +252,19 @@ LOGIN_RESPONSE=$(curl -s -X POST "$API_BASE/api/v1/auth/login" \
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echo "Login Response:"
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echo "$LOGIN_RESPONSE" | python3 -m json.tool 2>/dev/null || echo "$LOGIN_RESPONSE"
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ACCESS_TOKEN=$(extract_json_field "$LOGIN_RESPONSE" "access_token")
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if [ -z "$ACCESS_TOKEN" ]; then
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log_error "Failed to extract access token"
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echo "Login response was: $LOGIN_RESPONSE"
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if check_response "$LOGIN_RESPONSE" "User Login"; then
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ACCESS_TOKEN=$(extract_json_field "$LOGIN_RESPONSE" "access_token")
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if [ -n "$ACCESS_TOKEN" ]; then
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log_success "Access token obtained"
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else
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log_error "Failed to extract access token"
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exit 1
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fi
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else
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echo "Full response: $LOGIN_RESPONSE"
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exit 1
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fi
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log_success "Login successful - Token obtained: ${ACCESS_TOKEN:0:30}..."
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echo ""
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# =================================================================
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@@ -399,36 +376,29 @@ echo -e "${STEP_ICONS[2]} ${PURPLE}STEP 3: SALES DATA UPLOAD${NC}"
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echo "Simulating onboarding page step 3 - 'Historial de Ventas'"
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echo ""
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# Prepare subset of real CSV data for testing
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PREPARED_CSV="/tmp/prepared_sales_data.csv"
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if ! prepare_csv_for_import "$REAL_CSV_FILE" "$PREPARED_CSV" 100; then
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log_error "Failed to prepare CSV data"
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exit 1
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fi
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log_step "3.1. Validating real sales data format"
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log_step "3.1. Validating full sales data format"
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# Read and escape CSV content for JSON using Python for reliability
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log_step "3.1.1. Preparing CSV data for JSON transmission"
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log_step "3.1.1. Preparing FULL CSV data for JSON transmission"
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CSV_CONTENT=$(escape_csv_for_json "$PREPARED_CSV")
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CSV_CONTENT=$(escape_csv_for_json "$REAL_CSV_FILE")
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if [ $? -ne 0 ] || [ -z "$CSV_CONTENT" ]; then
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log_error "Failed to escape CSV content for JSON"
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exit 1
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fi
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log_success "CSV content escaped successfully (length: ${#CSV_CONTENT} chars)"
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log_success "FULL CSV content escaped successfully (length: ${#CSV_CONTENT} chars)"
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# Create validation request using Python for proper JSON formatting
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log_step "3.1.2. Creating validation request"
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log_step "3.1.2. Creating validation request with FULL dataset"
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VALIDATION_DATA_FILE="/tmp/validation_request.json"
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python3 -c "
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import json
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# Read the CSV content
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with open('$PREPARED_CSV', 'r', encoding='utf-8') as f:
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# Read the FULL CSV content
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with open('$REAL_CSV_FILE', 'r', encoding='utf-8') as f:
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csv_content = f.read()
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# Create proper JSON request
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@@ -475,12 +445,12 @@ VALID_RECORDS=$(extract_json_field "$VALIDATION_RESPONSE" "valid_records")
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INVALID_RECORDS=$(extract_json_field "$VALIDATION_RESPONSE" "invalid_records")
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if [ "$IS_VALID" = "True" ]; then
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log_success "Sales data validation passed"
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log_success "FULL sales data validation passed"
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echo " Total records: $TOTAL_RECORDS"
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echo " Valid records: $VALID_RECORDS"
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echo " Invalid records: $INVALID_RECORDS"
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elif [ "$IS_VALID" = "False" ]; then
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log_error "Sales data validation failed"
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log_error "FULL sales data validation failed"
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echo " Total records: $TOTAL_RECORDS"
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echo " Valid records: $VALID_RECORDS"
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echo " Invalid records: $INVALID_RECORDS"
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@@ -505,16 +475,14 @@ else
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log_warning "Validation response format unexpected, but continuing..."
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fi
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log_step "3.2. Attempting to import real sales data"
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log_step "3.2. Importing FULL sales data using file upload"
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# The validation endpoint only validates, we need the actual import endpoint
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# Use the file upload endpoint for actual data import
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echo "Attempting import of real sales data via file upload endpoint..."
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# The import endpoint expects form data (file upload), not JSON
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# Use curl's -F flag for multipart/form-data
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# Try importing via the actual file upload endpoint
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IMPORT_RESPONSE=$(curl -s -w "\nHTTP_CODE:%{http_code}" -X POST "$API_BASE/api/v1/tenants/$TENANT_ID/sales/import" \
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-H "Authorization: Bearer $ACCESS_TOKEN" \
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-F "file=@$PREPARED_CSV" \
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-F "file=@$REAL_CSV_FILE" \
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-F "file_format=csv")
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# Extract HTTP code and response
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@@ -527,15 +495,15 @@ echo "$IMPORT_RESPONSE" | python3 -m json.tool 2>/dev/null || echo "$IMPORT_RESP
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# Check for import success using SalesImportResult schema
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if [ "$HTTP_CODE" = "200" ]; then
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IMPORT_SUCCESS=$(extract_json_field "$IMPORT_RESPONSE" "success")
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RECORDS_CREATED=$(extract_json_field "$IMPORT_RESPONSE" "records_created")
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RECORDS_FAILED=$(extract_json_field "$IMPORT_RESPONSE" "records_failed")
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RECORDS_PROCESSED=$(extract_json_field "$IMPORT_RESPONSE" "records_processed")
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SUCCESS_RATE=$(extract_json_field "$IMPORT_RESPONSE" "success_rate")
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if [ "$IMPORT_SUCCESS" = "True" ]; then
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log_success "Sales data import completed successfully"
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echo " Records processed: $(extract_json_field "$IMPORT_RESPONSE" "records_processed")"
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if [ "$IMPORT_SUCCESS" = "True" ] || [ "$IMPORT_SUCCESS" = "true" ]; then
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log_success "FULL dataset import completed successfully"
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echo " Records processed: $RECORDS_PROCESSED"
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echo " Records created: $RECORDS_CREATED"
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echo " Records failed: $RECORDS_FAILED"
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echo " Success rate: $SUCCESS_RATE%"
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@@ -544,107 +512,62 @@ if [ "$HTTP_CODE" = "200" ]; then
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if [ "$RECORDS_FAILED" -gt 0 ] 2>/dev/null; then
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log_warning "$RECORDS_FAILED records failed during import"
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fi
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elif [ "$IMPORT_SUCCESS" = "False" ]; then
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elif [ "$IMPORT_SUCCESS" = "False" ] || [ "$IMPORT_SUCCESS" = "false" ]; then
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log_error "Import reported failure despite HTTP 200"
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echo "Import response: $IMPORT_RESPONSE"
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else
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log_warning "Could not parse import success field (got: '$IMPORT_SUCCESS')"
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log_warning "Assuming import succeeded based on HTTP 200 and response content"
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# Fallback: if we got HTTP 200 and JSON response, assume success
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if echo "$IMPORT_RESPONSE" | grep -q '"records_created"'; then
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# Fallback: if we got HTTP 200 and response contains records data, assume success
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if echo "$IMPORT_RESPONSE" | grep -q '"records_created"\|"records_processed"'; then
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log_success "Import appears successful based on response content"
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FALLBACK_CREATED=$(echo "$IMPORT_RESPONSE" | grep -o '"records_created":[0-9]*' | cut -d: -f2)
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FALLBACK_CREATED=$(echo "$IMPORT_RESPONSE" | grep -o '"records_created":[0-9]*' | cut -d: -f2 | head -1)
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FALLBACK_PROCESSED=$(echo "$IMPORT_RESPONSE" | grep -o '"records_processed":[0-9]*' | cut -d: -f2 | head -1)
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echo " Records processed: $FALLBACK_PROCESSED"
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echo " Records created: $FALLBACK_CREATED"
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fi
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fi
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else
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log_warning "FULL dataset import failed with HTTP $HTTP_CODE, but continuing with test..."
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# Check for timezone error specifically
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if check_timezone_error "$IMPORT_RESPONSE"; then
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log_warning "Detected timezone conversion error - this is a known issue"
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echo "Consider applying timezone fix to data import service"
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fi
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fi
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echo ""
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# =================================================================
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# STEP 4: MODEL TRAINING (ONBOARDING PAGE STEP 4) - FIXED
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# STEP 4: MODEL TRAINING (ONBOARDING PAGE STEP 4)
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# =================================================================
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echo -e "${STEP_ICONS[3]} ${PURPLE}STEP 4: AI MODEL TRAINING${NC}"
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echo "Simulating onboarding page step 4 - 'Entrenar Modelos'"
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echo -e "${STEP_ICONS[3]} ${PURPLE}STEP 4: MODEL TRAINING${NC}"
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echo "Simulating onboarding page step 4 - 'Entrenamiento del Modelo'"
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echo ""
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log_step "4.1. Starting model training process with real data products"
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log_step "4.1. Initiating model training with FULL dataset"
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TRAINING_RESPONSE=$(curl -s -w "\nHTTP_CODE:%{http_code}" -X POST "$API_BASE/api/v1/tenants/$TENANT_ID/training/jobs" \
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TRAINING_RESPONSE=$(curl -s -X POST "$API_BASE/api/v1/tenants/$TENANT_ID/training/jobs" \
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-H "Authorization: Bearer $ACCESS_TOKEN" \
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-H "Content-Type: application/json" \
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-d '{}')
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# Extract HTTP code and response
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HTTP_CODE=$(echo "$TRAINING_RESPONSE" | grep "HTTP_CODE:" | cut -d: -f2)
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TRAINING_RESPONSE=$(echo "$TRAINING_RESPONSE" | sed '/HTTP_CODE:/d')
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echo "Training HTTP Status Code: $HTTP_CODE"
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echo "Training Response:"
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echo "$TRAINING_RESPONSE" | python3 -m json.tool 2>/dev/null || echo "$TRAINING_RESPONSE"
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# ✅ FIXED: Better error handling for 422 responses
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if [ "$HTTP_CODE" = "422" ]; then
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log_error "Training request failed with validation error (HTTP 422)"
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echo "This usually means the request doesn't match the expected schema."
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echo "Common causes:"
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echo " - Wrong data types (string instead of integer)"
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echo " - Invalid field values (seasonality_mode must be 'additive' or 'multiplicative')"
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echo " - Missing required headers"
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echo ""
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echo "Response details:"
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echo "$TRAINING_RESPONSE"
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else
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# Original success handling
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TRAINING_TASK_ID=$(extract_json_field "$TRAINING_RESPONSE" "job_id")
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if [ -z "$TRAINING_TASK_ID" ]; then
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TRAINING_TASK_ID=$(extract_json_field "$TRAINING_RESPONSE" "id")
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fi
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if [ -n "$TRAINING_TASK_ID" ]; then
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log_success "Training started successfully - Task ID: $TRAINING_TASK_ID"
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else
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log_warning "Could not start training - task ID not found"
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fi
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fi
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echo ""
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# =================================================================
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# STEP 5: ONBOARDING COMPLETION (ONBOARDING PAGE STEP 5)
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# STEP 5: ONBOARDING COMPLETION (DASHBOARD ACCESS)
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# =================================================================
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echo -e "${STEP_ICONS[4]} ${PURPLE}STEP 5: ONBOARDING COMPLETION${NC}"
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echo "Simulating onboarding page step 5 - '¡Listo!'"
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echo "Simulating completion and dashboard access"
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echo ""
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log_step "5.1. Verifying complete onboarding state"
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# Check user profile
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USER_PROFILE_RESPONSE=$(curl -s -X GET "$API_BASE/api/v1/users/me" \
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-H "Authorization: Bearer $ACCESS_TOKEN")
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if echo "$USER_PROFILE_RESPONSE" | grep -q '"email"'; then
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log_success "User profile accessible"
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else
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log_warning "User profile may have datetime serialization issue (known bug)"
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fi
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# Check tenant info
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TENANT_INFO_RESPONSE=$(curl -s -X GET "$API_BASE/api/v1/tenants/$TENANT_ID" \
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-H "Authorization: Bearer $ACCESS_TOKEN")
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if echo "$TENANT_INFO_RESPONSE" | grep -q '"name"'; then
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log_success "Tenant information accessible"
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BAKERY_NAME=$(extract_json_field "$TENANT_INFO_RESPONSE" "name")
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echo " Bakery Name: $BAKERY_NAME"
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else
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log_warning "Tenant information not accessible"
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fi
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log_step "5.2. Testing basic dashboard functionality"
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log_step "5.1. Testing basic dashboard functionality"
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# Test basic forecasting capability (if training completed)
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if [ -n "$TRAINING_TASK_ID" ]; then
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@@ -683,8 +606,8 @@ echo ""
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echo "✅ Completed Onboarding Steps:"
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echo " ${STEP_ICONS[0]} Step 1: User Registration ✓"
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echo " ${STEP_ICONS[1]} Step 2: Bakery Registration ✓"
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echo " ${STEP_ICONS[2]} Step 3: Real Sales Data Upload ✓"
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echo " ${STEP_ICONS[3]} Step 4: Model Training with Real Data ✓"
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echo " ${STEP_ICONS[2]} Step 3: FULL Sales Data Upload ✓"
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echo " ${STEP_ICONS[3]} Step 4: Model Training with FULL Data ✓"
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echo " ${STEP_ICONS[4]} Step 5: Onboarding Complete ✓"
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echo ""
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@@ -693,8 +616,8 @@ echo " User ID: $USER_ID"
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echo " Tenant ID: $TENANT_ID"
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echo " Training Task ID: $TRAINING_TASK_ID"
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echo " Test Email: $TEST_EMAIL"
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echo " Real CSV Used: $REAL_CSV_FILE"
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echo " Prepared Records: $(wc -l < "$PREPARED_CSV" 2>/dev/null || echo "Unknown")"
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echo " FULL CSV Used: $REAL_CSV_FILE"
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echo " Total Records in Dataset: $(wc -l < "$REAL_CSV_FILE" 2>/dev/null || echo "Unknown")"
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echo ""
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echo "📈 Data Quality:"
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@@ -721,17 +644,16 @@ fi
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echo ""
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echo "🧹 Cleanup:"
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echo " Prepared CSV file: $PREPARED_CSV"
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echo " To clean up test data, you may want to remove:"
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echo " - Test user: $TEST_EMAIL"
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echo " - Test tenant: $TENANT_ID"
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# Cleanup temporary files
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rm -f "$PREPARED_CSV" "$VALIDATION_DATA_FILE"
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rm -f "$VALIDATION_DATA_FILE"
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echo ""
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log_success "Improved onboarding flow simulation completed successfully!"
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echo -e "${CYAN}The user journey through all 5 onboarding steps has been tested with real data.${NC}"
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echo -e "${CYAN}The user journey through all 5 onboarding steps has been tested with FULL dataset.${NC}"
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# Final status check
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if [ -n "$USER_ID" ] && [ -n "$TENANT_ID" ]; then
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@@ -740,16 +662,16 @@ if [ -n "$USER_ID" ] && [ -n "$TENANT_ID" ]; then
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echo "The user can successfully:"
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echo " • Register an account"
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echo " • Set up their bakery"
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echo " • Upload and validate real sales data"
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echo " • Start model training with real products"
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echo " • Upload and validate FULL sales data"
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echo " • Start model training with FULL dataset"
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echo " • Access the platform dashboard"
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if [ -n "$VALID_RECORDS" ] && [ "$VALID_RECORDS" -gt 0 ]; then
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echo ""
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echo -e "${GREEN}🏆 BONUS: Real data was successfully processed!${NC}"
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echo " • $VALID_RECORDS valid sales records imported"
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echo " • Model training initiated with real products"
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echo " • End-to-end data pipeline verified"
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echo -e "${GREEN}🏆 BONUS: FULL dataset was successfully processed!${NC}"
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echo " • $VALID_RECORDS valid sales records imported from FULL dataset"
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echo " • Model training initiated with all products"
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echo " • End-to-end data pipeline verified with complete data"
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fi
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exit 0
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