accounted/lib/transactions/category-suggestions.ts

import { suggestCategory } from '@/lib/tax/expense-warnings'
import { getExpenseAccountForCategory } from '@/lib/bookkeeping/category-mapping'
import { findMatchingTemplates, getTemplateById, type TemplateMatch } from '@/lib/bookkeeping/booking-templates'
import { extensionRegistry } from '@/lib/extensions/registry'
import type { Transaction, TransactionCategory, EntityType, MappingRule } from '@/types'

export interface SuggestedCategory {
  category: TransactionCategory
  label: string
  account: string | null
  confidence: number
  source: 'mapping_rule' | 'pattern' | 'history' | 'ai'
  match_reason?: string
}

const CATEGORY_LABELS: Record<string, string> = {
  income_services: 'Tjänster',
  income_products: 'Produkter',
  income_other: 'Övriga intäkter',
  expense_equipment: 'Utrustning',
  expense_software: 'Programvara',
  expense_travel: 'Resor',
  expense_office: 'Kontor',
  expense_marketing: 'Marknadsföring',
  expense_professional_services: 'Konsulter',
  expense_education: 'Utbildning',
  expense_representation: 'Representation',
  expense_consumables: 'Material',
  expense_vehicle: 'Bil & drivmedel',
  expense_telecom: 'Telefon & internet',
  expense_bank_fees: 'Bankavgift',
  expense_card_fees: 'Kortavgift',
  expense_currency_exchange: 'Valutaväxling',
  expense_other: 'Övrigt',
}

/**
 * Get suggested categories for a transaction
 * Combines mapping rules, pattern matching, and user history
 */
export function getSuggestedCategories(
  transaction: Transaction,
  mappingRules: MappingRule[],
  categoryHistory: Record<string, number>
): SuggestedCategory[] {
  const suggestions: SuggestedCategory[] = []
  const seen = new Set<string>()

  // 1. Check mapping rules (highest confidence)
  for (const rule of mappingRules) {
    if (!rule.is_active) continue

    let matches = false

    if (rule.merchant_pattern && transaction.merchant_name) {
      const pattern = new RegExp(rule.merchant_pattern, 'i')
      if (pattern.test(transaction.merchant_name)) {
        matches = true
      }
    }

    if (rule.description_pattern) {
      const pattern = new RegExp(rule.description_pattern, 'i')
      if (pattern.test(transaction.description)) {
        matches = true
      }
    }

    if (rule.mcc_codes && transaction.mcc_code) {
      if (rule.mcc_codes.includes(transaction.mcc_code)) {
        matches = true
      }
    }

    if (matches && rule.debit_account && !rule.default_private) {
      // Reverse-lookup: find category from debit account
      const category = accountToCategory(rule.debit_account, transaction.amount)
      if (category && !seen.has(category)) {
        seen.add(category)
        const suggestion: SuggestedCategory = {
          category: category as TransactionCategory,
          label: CATEGORY_LABELS[category] || category,
          account: rule.debit_account,
          confidence: rule.confidence_score || 0.8,
          source: 'mapping_rule',
        }
        if (rule.source === 'user_description' && rule.user_description) {
          suggestion.match_reason = `Matchad på din beskrivning: ${rule.user_description}`
        }
        suggestions.push(suggestion)
      }
    }
  }

  // 2. Pattern matching from expense-warnings
  const patternMatch = suggestCategory(transaction.description)
  if (patternMatch && !seen.has(patternMatch)) {
    seen.add(patternMatch)
    suggestions.push({
      category: patternMatch as TransactionCategory,
      label: CATEGORY_LABELS[patternMatch] || patternMatch,
      account: getExpenseAccountForCategory(patternMatch as TransactionCategory),
      confidence: 0.6,
      source: 'pattern',
    })
  }

  // 3. User history (most commonly used categories)
  const historyEntries = Object.entries(categoryHistory)
    .sort(([, a], [, b]) => b - a)
    .filter(([cat]) => !seen.has(cat))

  for (const [cat, count] of historyEntries) {
    if (suggestions.length >= 4) break
    // Only suggest relevant direction (expense for negative, income for positive)
    if (transaction.amount < 0 && !cat.startsWith('expense_')) continue
    if (transaction.amount > 0 && !cat.startsWith('income_')) continue

    seen.add(cat)
    suggestions.push({
      category: cat as TransactionCategory,
      label: CATEGORY_LABELS[cat] || cat,
      account: getExpenseAccountForCategory(cat as TransactionCategory),
      confidence: Math.min(0.5, count / 20),
      source: 'history',
    })
  }

  // Sort by confidence, limit to top 4
  return suggestions
    .sort((a, b) => b.confidence - a.confidence)
    .slice(0, 4)
}

/**
 * Reverse-lookup: find category from BAS account number
 */
function accountToCategory(account: string, amount: number): string | null {
  if (amount > 0) {
    // Income
    const incomeMap: Record<string, string> = {
      '3001': 'income_services',
      '3900': 'income_other',
    }
    return incomeMap[account] || 'income_other'
  }

  // Expense
  const expenseMap: Record<string, string> = {
    '5410': 'expense_equipment',
    '5420': 'expense_software',
    '5460': 'expense_consumables',
    '5611': 'expense_vehicle',
    '5800': 'expense_travel',
    '5010': 'expense_office',
    '5910': 'expense_marketing',
    '6071': 'expense_representation',
    '6072': 'expense_representation',
    '6200': 'expense_telecom',
    '6530': 'expense_professional_services',
    '6570': 'expense_bank_fees',
    '6991': 'expense_other',
    '7960': 'expense_currency_exchange',
  }
  return expenseMap[account] || null
}

/**
 * Source priority for tiebreaking — used when two suggestions
 * have the same confidence score.
 */
const SOURCE_PRIORITY: Record<SuggestedCategory['source'], number> = {
  mapping_rule: 3,
  ai: 2,
  pattern: 1,
  history: 0,
}

/**
 * Merge AI-generated suggestions into existing suggestion list.
 * AI suggestions take priority over history-based ones.
 * Deduplicates by category, preserving the higher-confidence entry.
 * When transactionAmount is provided, filters out wrong-direction suggestions.
 */
export function mergeAiSuggestions(
  existing: SuggestedCategory[],
  aiSuggestions: { category: string; basAccount: string; confidence: number; reasoning: string }[],
  transactionAmount?: number
): SuggestedCategory[] {
  const merged = [...existing]

  for (const ai of aiSuggestions) {
    // Skip suggestions that don't match transaction direction
    if (transactionAmount !== undefined) {
      if (transactionAmount > 0 && ai.category.startsWith('expense_')) continue
      if (transactionAmount < 0 && ai.category.startsWith('income_')) continue
    }

    const existingIdx = merged.findIndex((s) => s.category === ai.category)
    if (existingIdx !== -1) {
      // Upgrade existing entry if the AI has higher confidence
      if (ai.confidence > merged[existingIdx].confidence) {
        merged[existingIdx] = {
          ...merged[existingIdx],
          account: ai.basAccount || merged[existingIdx].account,
          confidence: ai.confidence,
          source: 'ai',
        }
      }
      continue
    }

    merged.push({
      category: ai.category as TransactionCategory,
      label: CATEGORY_LABELS[ai.category] || ai.category,
      account: ai.basAccount || null,
      confidence: ai.confidence,
      source: 'ai',
    })
  }

  // Sort by confidence first, then by source priority as tiebreaker
  return merged
    .sort((a, b) => {
      const confidenceDiff = b.confidence - a.confidence
      if (confidenceDiff !== 0) return confidenceDiff
      return SOURCE_PRIORITY[b.source] - SOURCE_PRIORITY[a.source]
    })
    .slice(0, 5)
}

// ============================================================
// Template Suggestions
// ============================================================

export interface SuggestedTemplate {
  template_id: string
  name_sv: string
  name_en: string
  group: string
  debit_account: string
  credit_account: string
  confidence: number
  description_sv: string
  risk_level: string
  requires_review: boolean
}

/**
 * Get recently used templates from mapping rules.
 * Extracts unique template_id values and returns them as suggestions.
 */
export function getRecentlyUsedTemplates(
  mappingRules: MappingRule[],
  entityType?: EntityType,
  direction?: 'expense' | 'income' | 'transfer'
): SuggestedTemplate[] {
  const seen = new Set<string>()
  const results: SuggestedTemplate[] = []

  // Sort by most recent (highest priority first)
  const sorted = [...mappingRules]
    .filter((r) => r.is_active && r.template_id)
    .sort((a, b) => (b.confidence_score || 0) - (a.confidence_score || 0))

  for (const rule of sorted) {
    if (!rule.template_id || seen.has(rule.template_id)) continue
    seen.add(rule.template_id)

    const template = getTemplateById(rule.template_id)
    if (!template) continue

    // Filter by entity applicability
    if (entityType && template.entity_applicability !== 'all' && template.entity_applicability !== entityType) continue

    // Filter by direction
    if (direction && template.direction !== direction && template.direction !== 'transfer') continue

    results.push({
      template_id: template.id,
      name_sv: template.name_sv,
      name_en: template.name_en,
      group: template.group,
      debit_account: template.debit_account,
      credit_account: template.credit_account,
      confidence: 0.85,
      description_sv: template.description_sv,
      risk_level: template.risk_level,
      requires_review: template.requires_review,
    })

    if (results.length >= 5) break
  }

  return results
}

/**
 * Get suggested booking templates for a transaction.
 * Keyword matching as primary, AI embedding search as optional enhancer.
 */
export async function getSuggestedTemplates(
  transaction: Transaction,
  entityType?: EntityType,
  mappingRules?: MappingRule[]
): Promise<SuggestedTemplate[]> {
  const seen = new Set<string>()
  const results: SuggestedTemplate[] = []

  // 1. Boost recently-used templates from mapping rules
  if (mappingRules) {
    const direction = transaction.amount < 0 ? 'expense' : 'income'
    const recent = getRecentlyUsedTemplates(mappingRules, entityType, direction)
    for (const r of recent) {
      if (!seen.has(r.template_id)) {
        seen.add(r.template_id)
        results.push(r)
      }
    }
  }

  // 2. Keyword + MCC matching (always available, no API keys needed)
  const keywordMatches = findMatchingTemplates(transaction, entityType)
  for (const m of keywordMatches) {
    if (!seen.has(m.template.id)) {
      seen.add(m.template.id)
      results.push({
        template_id: m.template.id,
        name_sv: m.template.name_sv,
        name_en: m.template.name_en,
        group: m.template.group,
        debit_account: m.template.debit_account,
        credit_account: m.template.credit_account,
        confidence: m.confidence,
        description_sv: m.template.description_sv,
        risk_level: m.template.risk_level,
        requires_review: m.template.requires_review,
      })
    }
  }

  // 3. If AI extension loaded, merge in embedding-based matches (higher confidence)
  try {
    const aiExt = extensionRegistry.get('ai-categorization')
    if (aiExt?.services?.findSimilarTemplates) {
      const aiMatches: TemplateMatch[] = await aiExt.services.findSimilarTemplates(transaction, entityType)
      for (const m of aiMatches) {
        const existing = results.find((r) => r.template_id === m.template.id)
        if (existing) {
          // AI match upgrades confidence if higher
          if (m.confidence > existing.confidence) {
            existing.confidence = m.confidence
          }
        } else {
          results.push({
            template_id: m.template.id,
            name_sv: m.template.name_sv,
            name_en: m.template.name_en,
            group: m.template.group,
            debit_account: m.template.debit_account,
            credit_account: m.template.credit_account,
            confidence: m.confidence,
            description_sv: m.template.description_sv,
            risk_level: m.template.risk_level,
            requires_review: m.template.requires_review,
          })
        }
      }
    }
  } catch {
    // AI enhancement is non-blocking
  }

  return results
    .sort((a, b) => b.confidence - a.confidence)
    .slice(0, 10)
}