/**
 * Real AgentDB Integration
 *
 * Full-featured AgentDB integration with:
 * - Vector similarity search for expert retrieval
 * - Causal reasoning for decision tracking
 * - Reflexion memory for self-improvement
 * - Skill library for learned capabilities
 * - Episodic memory for experience tracking
 *
 * @module agentdb-integration
 * @version 1.0.0
 */

import { AgentDBSingleton } from './agentdb-singleton'

/**
 * Expert embedding for semantic search
 */
export interface ExpertEmbedding {
  expertId: string
  name: string
  signature: string
  embedding: number[]
  performance: number
  metadata: Record<string, any>
}

/**
 * Causal decision record for tracking reasoning chains
 */
export interface CausalDecision {
  id: string
  timestamp: Date
  expertId: string
  input: Record<string, any>
  output: any
  reasoning: string[]
  causality: {
    causes: string[]
    effects: string[]
    confidence: number
  }
  outcome?: {
    success: boolean
    metrics: Record<string, number>
  }
}

/**
 * Reflexion entry for self-improvement
 */
export interface ReflexionEntry {
  id: string
  timestamp: Date
  experience: string
  reflection: string
  insights: string[]
  actionItems: string[]
  relatedDecisions: string[]
}

/**
 * Learned skill in the skill library
 */
export interface LearnedSkill {
  id: string
  name: string
  description: string
  implementation: string
  prerequisites: string[]
  performance: {
    successRate: number
    avgLatency: number
    usageCount: number
  }
  examples: Array<{
    input: any
    output: any
    context?: string
  }>
}

/**
 * Configuration for AgentDB integration
 */
export interface AgentDBConfig {
  dbPath?: string
  enableCausalReasoning?: boolean
  enableReflexion?: boolean
  enableSkillLibrary?: boolean
  vectorDimension?: number
  similarityThreshold?: number
}

/**
 * AgentDB Manager for learning and memory
 */
export class AgentDBManager {
  private db: any | null = null
  private config: Required<AgentDBConfig>

  constructor(config: AgentDBConfig = {}) {
    this.config = {
      dbPath: config.dbPath || ':memory:',
      enableCausalReasoning: config.enableCausalReasoning ?? true,
      enableReflexion: config.enableReflexion ?? true,
      enableSkillLibrary: config.enableSkillLibrary ?? true,
      vectorDimension: config.vectorDimension ?? 1536, // OpenAI ada-002 dimension
      similarityThreshold: config.similarityThreshold ?? 0.75
    }

    // Initialize database asynchronously (methods have null guards)
    this.initializeAgentDb()
  }

  /**
   * Initialize AgentDB using singleton pattern
   */
  private initializeAgentDb(): Promise<void> {
    return (async () => {
      try {
        this.db = await AgentDBSingleton.getInstance(this.config.dbPath)
        this.initializeTables()
      } catch (error) {
        console.warn('⚠ AgentDBManager: Database initialization failed (sql.js compatibility issue):', error)
        this.db = null
      }
    })()
  }

  /**
   * Initialize database tables for learning features
   */
  private initializeTables(): void {
    if (!this.db) return

    try {
      // Expert embeddings table with vector search
      this.db.exec(`
        CREATE TABLE IF NOT EXISTS expert_embeddings (
          expert_id TEXT PRIMARY KEY,
          name TEXT NOT NULL,
          signature TEXT NOT NULL,
          embedding BLOB NOT NULL,
          performance REAL DEFAULT 0.0,
          metadata TEXT,
          created_at INTEGER DEFAULT (strftime('%s', 'now'))
        )
      `)

      // Causal decisions table
      if (this.config.enableCausalReasoning) {
        this.db.exec(`
          CREATE TABLE IF NOT EXISTS causal_decisions (
            id TEXT PRIMARY KEY,
            timestamp INTEGER NOT NULL,
            expert_id TEXT NOT NULL,
            input TEXT NOT NULL,
            output TEXT NOT NULL,
            reasoning TEXT NOT NULL,
            causality TEXT NOT NULL,
            outcome TEXT,
            FOREIGN KEY (expert_id) REFERENCES expert_embeddings(expert_id)
          )
        `)
      }

      // Reflexion entries table
      if (this.config.enableReflexion) {
        this.db.exec(`
          CREATE TABLE IF NOT EXISTS reflexion_entries (
            id TEXT PRIMARY KEY,
            timestamp INTEGER NOT NULL,
            experience TEXT NOT NULL,
            reflection TEXT NOT NULL,
            insights TEXT NOT NULL,
            action_items TEXT NOT NULL,
            related_decisions TEXT NOT NULL
          )
        `)
      }

      // Skill library table
      if (this.config.enableSkillLibrary) {
        this.db.exec(`
          CREATE TABLE IF NOT EXISTS skill_library (
            id TEXT PRIMARY KEY,
            name TEXT NOT NULL UNIQUE,
            description TEXT NOT NULL,
            implementation TEXT NOT NULL,
            prerequisites TEXT NOT NULL,
            performance TEXT NOT NULL,
            examples TEXT NOT NULL,
            created_at INTEGER DEFAULT (strftime('%s', 'now')),
            updated_at INTEGER DEFAULT (strftime('%s', 'now'))
          )
        `)
      }
    } catch (error) {
      console.warn('⚠ AgentDBManager: Table initialization failed (sql.js compatibility issue):', error)
      this.db = null
    }
  }

  // ============================================================================
  // Expert Embeddings & Vector Search
  // ============================================================================

  /**
   * Store expert embedding for semantic search
   */
  async storeExpertEmbedding(expert: ExpertEmbedding): Promise<void> {
    if (!this.db) return

    const stmt = this.db.prepare(`
      INSERT OR REPLACE INTO expert_embeddings
      (expert_id, name, signature, embedding, performance, metadata)
      VALUES (?, ?, ?, ?, ?, ?)
    `)

    const embeddingBuffer = Buffer.from(new Float32Array(expert.embedding).buffer)

    stmt.run(
      expert.expertId,
      expert.name,
      expert.signature,
      embeddingBuffer,
      expert.performance,
      JSON.stringify(expert.metadata)
    )
  }

  /**
   * Find similar experts using vector similarity search
   */
  async findSimilarExperts(
    queryEmbedding: number[],
    topK: number = 5
  ): Promise<ExpertEmbedding[]> {
    if (!this.db) return []

    const results = this.db.vectorSearch({
      table: 'expert_embeddings',
      column: 'embedding',
      queryVector: queryEmbedding,
      limit: topK,
      threshold: this.config.similarityThreshold
    })

    return results.map((row: any) => ({
      expertId: row.expert_id,
      name: row.name,
      signature: row.signature,
      embedding: Array.from(new Float32Array(row.embedding.buffer)),
      performance: row.performance,
      metadata: JSON.parse(row.metadata || '{}')
    }))
  }

  /**
   * Get expert by ID
   */
  async getExpert(expertId: string): Promise<ExpertEmbedding | null> {
    if (!this.db) return null

    const stmt = this.db.prepare(`
      SELECT * FROM expert_embeddings WHERE expert_id = ?
    `)

    const row = stmt.get(expertId) as any

    if (!row) return null

    return {
      expertId: row.expert_id,
      name: row.name,
      signature: row.signature,
      embedding: Array.from(new Float32Array(row.embedding.buffer)),
      performance: row.performance,
      metadata: JSON.parse(row.metadata || '{}')
    }
  }

  // ============================================================================
  // Causal Reasoning
  // ============================================================================

  /**
   * Record a causal decision
   */
  async recordCausalDecision(decision: CausalDecision): Promise<void> {
    if (!this.db) return
    if (!this.config.enableCausalReasoning) return

    const stmt = this.db.prepare(`
      INSERT INTO causal_decisions
      (id, timestamp, expert_id, input, output, reasoning, causality, outcome)
      VALUES (?, ?, ?, ?, ?, ?, ?, ?)
    `)

    stmt.run(
      decision.id,
      decision.timestamp.getTime(),
      decision.expertId,
      JSON.stringify(decision.input),
      JSON.stringify(decision.output),
      JSON.stringify(decision.reasoning),
      JSON.stringify(decision.causality),
      decision.outcome ? JSON.stringify(decision.outcome) : null
    )
  }

  /**
   * Get causal chain for a decision
   */
  async getCausalChain(decisionId: string, depth: number = 3): Promise<CausalDecision[]> {
    if (!this.db) return []

    const chain: CausalDecision[] = []
    const visited = new Set<string>()

    const getDecision = (id: string): CausalDecision | null => {
      const stmt = this.db.prepare(`
        SELECT * FROM causal_decisions WHERE id = ?
      `)
      const row = stmt.get(id) as any

      if (!row) return null

      return {
        id: row.id,
        timestamp: new Date(row.timestamp),
        expertId: row.expert_id,
        input: JSON.parse(row.input),
        output: JSON.parse(row.output),
        reasoning: JSON.parse(row.reasoning),
        causality: JSON.parse(row.causality),
        outcome: row.outcome ? JSON.parse(row.outcome) : undefined
      }
    }

    const traverse = (id: string, currentDepth: number) => {
      if (currentDepth >= depth || visited.has(id)) return

      visited.add(id)
      const decision = getDecision(id)

      if (!decision) return

      chain.push(decision)

      // Traverse causes
      for (const causeId of decision.causality.causes) {
        traverse(causeId, currentDepth + 1)
      }
    }

    traverse(decisionId, 0)
    return chain
  }

  // ============================================================================
  // Reflexion Memory
  // ============================================================================

  /**
   * Add reflexion entry for self-improvement
   */
  async addReflexion(entry: ReflexionEntry): Promise<void> {
    if (!this.db) return
    if (!this.config.enableReflexion) return

    const stmt = this.db.prepare(`
      INSERT INTO reflexion_entries
      (id, timestamp, experience, reflection, insights, action_items, related_decisions)
      VALUES (?, ?, ?, ?, ?, ?, ?)
    `)

    stmt.run(
      entry.id,
      entry.timestamp.getTime(),
      entry.experience,
      entry.reflection,
      JSON.stringify(entry.insights),
      JSON.stringify(entry.actionItems),
      JSON.stringify(entry.relatedDecisions)
    )
  }

  /**
   * Get recent reflexions
   */
  async getRecentReflexions(limit: number = 10): Promise<ReflexionEntry[]> {
    if (!this.db) return []

    const stmt = this.db.prepare(`
      SELECT * FROM reflexion_entries
      ORDER BY timestamp DESC
      LIMIT ?
    `)

    const rows = stmt.all(limit) as any[]

    return rows.map(row => ({
      id: row.id,
      timestamp: new Date(row.timestamp),
      experience: row.experience,
      reflection: row.reflection,
      insights: JSON.parse(row.insights),
      actionItems: JSON.parse(row.action_items),
      relatedDecisions: JSON.parse(row.related_decisions)
    }))
  }

  // ============================================================================
  // Skill Library
  // ============================================================================

  /**
   * Add skill to library
   */
  async addSkill(skill: LearnedSkill): Promise<void> {
    if (!this.db) return
    if (!this.config.enableSkillLibrary) return

    const stmt = this.db.prepare(`
      INSERT OR REPLACE INTO skill_library
      (id, name, description, implementation, prerequisites, performance, examples, updated_at)
      VALUES (?, ?, ?, ?, ?, ?, ?, strftime('%s', 'now'))
    `)

    stmt.run(
      skill.id,
      skill.name,
      skill.description,
      skill.implementation,
      JSON.stringify(skill.prerequisites),
      JSON.stringify(skill.performance),
      JSON.stringify(skill.examples)
    )
  }

  /**
   * Get skill by name
   */
  async getSkill(name: string): Promise<LearnedSkill | null> {
    if (!this.db) return null

    const stmt = this.db.prepare(`
      SELECT * FROM skill_library WHERE name = ?
    `)

    const row = stmt.get(name) as any

    if (!row) return null

    return {
      id: row.id,
      name: row.name,
      description: row.description,
      implementation: row.implementation,
      prerequisites: JSON.parse(row.prerequisites),
      performance: JSON.parse(row.performance),
      examples: JSON.parse(row.examples)
    }
  }

  /**
   * List all skills
   */
  async listSkills(): Promise<LearnedSkill[]> {
    if (!this.db) return []

    const stmt = this.db.prepare(`
      SELECT * FROM skill_library ORDER BY updated_at DESC
    `)

    const rows = stmt.all() as any[]

    return rows.map(row => ({
      id: row.id,
      name: row.name,
      description: row.description,
      implementation: row.implementation,
      prerequisites: JSON.parse(row.prerequisites),
      performance: JSON.parse(row.performance),
      examples: JSON.parse(row.examples)
    }))
  }

  /**
   * Update skill performance metrics
   */
  async updateSkillPerformance(
    skillName: string,
    metrics: { successRate?: number; avgLatency?: number; usageCount?: number }
  ): Promise<void> {
    if (!this.db) return

    const skill = await this.getSkill(skillName)
    if (!skill) return

    const updatedPerformance = {
      ...skill.performance,
      ...metrics
    }

    const stmt = this.db.prepare(`
      UPDATE skill_library
      SET performance = ?, updated_at = strftime('%s', 'now')
      WHERE name = ?
    `)

    stmt.run(JSON.stringify(updatedPerformance), skillName)
  }

  // ============================================================================
  // Cleanup & Utilities
  // ============================================================================

  // ============================================================================
  // Cross-Project Features
  // ============================================================================

  /**
   * Find experts across all projects by role
   */
  async findExpertsByRole(role: string, topK: number = 10): Promise<ExpertEmbedding[]> {
    if (!this.db) return []

    const stmt = this.db.prepare(`
      SELECT * FROM expert_embeddings
      WHERE name LIKE ? OR expert_id LIKE ?
      ORDER BY performance DESC
      LIMIT ?
    `)

    const rows = stmt.all(`%${role}%`, `%${role}%`, topK) as any[]

    return rows.map(row => ({
      expertId: row.expert_id,
      name: row.name,
      signature: row.signature,
      embedding: Array.from(new Float32Array(row.embedding.buffer)),
      performance: row.performance,
      metadata: JSON.parse(row.metadata || '{}')
    }))
  }

  /**
   * Compare expert performance across projects
   */
  async compareExpertsAcrossProjects(expertRole: string): Promise<{
    expertRole: string
    totalExperts: number
    avgPerformance: number
    bestExpert: { expertId: string; project: string; performance: number } | null
    projectPerformance: Array<{ project: string; avgPerformance: number; count: number }>
  }> {
    const experts = await this.findExpertsByRole(expertRole, 100)

    if (experts.length === 0) {
      return {
        expertRole,
        totalExperts: 0,
        avgPerformance: 0,
        bestExpert: null,
        projectPerformance: []
      }
    }

    // Calculate overall stats
    const avgPerformance = experts.reduce((sum, e) => sum + e.performance, 0) / experts.length

    // Find best expert
    const bestExpert = experts.reduce((best, e) =>
      e.performance > best.performance ? e : best
    )

    // Group by project
    const projectMap = new Map<string, { sum: number; count: number }>()

    for (const expert of experts) {
      const project = expert.metadata.project || 'unknown'

      if (!projectMap.has(project)) {
        projectMap.set(project, { sum: 0, count: 0 })
      }

      const stats = projectMap.get(project)!
      stats.sum += expert.performance
      stats.count++
    }

    const projectPerformance = Array.from(projectMap.entries()).map(([project, stats]) => ({
      project,
      avgPerformance: stats.sum / stats.count,
      count: stats.count
    }))

    return {
      expertRole,
      totalExperts: experts.length,
      avgPerformance,
      bestExpert: {
        expertId: bestExpert.expertId,
        project: bestExpert.metadata.project || 'unknown',
        performance: bestExpert.performance
      },
      projectPerformance: projectPerformance.sort((a, b) => b.avgPerformance - a.avgPerformance)
    }
  }

  /**
   * Export expert knowledge for cross-project sharing
   */
  async exportExpertKnowledge(expertId: string): Promise<{
    expert: ExpertEmbedding
    skills: LearnedSkill[]
    reflexions: ReflexionEntry[]
    decisions: CausalDecision[]
  } | null> {
    if (!this.db) return null

    const expert = await this.getExpert(expertId)

    if (!expert) return null

    // Get all related data
    const skills = await this.listSkills()
    const reflexions = await this.getRecentReflexions(100)

    // Get recent decisions
    const decisionStmt = this.db.prepare(`
      SELECT * FROM causal_decisions
      WHERE expert_id = ?
      ORDER BY timestamp DESC
      LIMIT 50
    `)

    const decisionRows = decisionStmt.all(expertId) as any[]
    const decisions = decisionRows.map(row => ({
      id: row.id,
      timestamp: new Date(row.timestamp),
      expertId: row.expert_id,
      input: JSON.parse(row.input),
      output: JSON.parse(row.output),
      reasoning: JSON.parse(row.reasoning),
      causality: JSON.parse(row.causality),
      outcome: row.outcome ? JSON.parse(row.outcome) : undefined
    }))

    return {
      expert,
      skills,
      reflexions,
      decisions
    }
  }

  /**
   * Import expert knowledge from another project
   */
  async importExpertKnowledge(
    knowledge: {
      expert: ExpertEmbedding
      skills: LearnedSkill[]
      reflexions: ReflexionEntry[]
      decisions: CausalDecision[]
    },
    targetProject: string
  ): Promise<string> {
    // Create new expert ID for target project
    const newExpertId = `${knowledge.expert.expertId}-${targetProject}-${Date.now()}`

    // Store expert with new ID
    await this.storeExpertEmbedding({
      ...knowledge.expert,
      expertId: newExpertId,
      metadata: {
        ...knowledge.expert.metadata,
        project: targetProject,
        importedFrom: knowledge.expert.metadata.project,
        originalExpertId: knowledge.expert.expertId
      }
    })

    // Import skills
    for (const skill of knowledge.skills) {
      await this.addSkill({
        ...skill,
        id: `${skill.id}-${targetProject}`,
        name: `${skill.name}_${targetProject}`
      })
    }

    return newExpertId
  }

  /**
   * Close database connection
   */
  close(): void {
    if (this.db) {
      try {
        this.db.close()
      } catch (error) {
        console.warn('⚠ AgentDBManager: Failed to close database:', error)
      } finally {
        this.db = null
      }
    }
  }

  /**
   * Get database statistics
   */
  async getStats(): Promise<{
    expertCount: number
    decisionCount: number
    reflexionCount: number
    skillCount: number
  }> {
    if (!this.db) {
      return {
        expertCount: 0,
        decisionCount: 0,
        reflexionCount: 0,
        skillCount: 0
      }
    }

    const getCount = (table: string) => {
      const stmt = this.db.prepare(`SELECT COUNT(*) as count FROM ${table}`)
      return (stmt.get() as any).count
    }

    return {
      expertCount: getCount('expert_embeddings'),
      decisionCount: this.config.enableCausalReasoning ? getCount('causal_decisions') : 0,
      reflexionCount: this.config.enableReflexion ? getCount('reflexion_entries') : 0,
      skillCount: this.config.enableSkillLibrary ? getCount('skill_library') : 0
    }
  }
}

/**
 * Create AgentDB manager with default configuration
 */
export function createAgentDB(config?: AgentDBConfig): AgentDBManager {
  return new AgentDBManager(config)
}