import { getDb } from "../db.ts";
import { invokeLLM } from "../_core/llm.ts";

/**
 * AI Employee Roles and Responsibilities
 */
export const AIEmployeeRole = {
  LUCKY_AI: "luckyai", // Central coordinator
  FRAUD_AI: "fraudai", // Fraud detection
  GAME_AI: "gameai", // Game design and creation
  SLOTS_AI: "slotsai", // Slots department
  BINGO_AI: "bingoai", // Bingo department
  POKER_AI: "pokerai", // Poker department
  SPORTS_AI: "sportsai", // Sportsbook department
} as const;

export type AIEmployeeRole = typeof AIEmployeeRole[keyof typeof AIEmployeeRole];

/**
 * Task Status
 */
export const TaskStatus = {
  ASSIGNED: "assigned",
  IN_PROGRESS: "in_progress",
  SUBMITTED: "submitted",
  APPROVED: "approved",
  DENIED: "denied",
  COMPLETED: "completed",
} as const;

export type TaskStatus = typeof TaskStatus[keyof typeof TaskStatus];

/**
 * Duty Report Status
 */
export const DutyReportStatus = {
  SUBMITTED: "submitted",
  PENDING_REVIEW: "pending_review",
  APPROVED: "approved",
  DENIED: "denied",
  REVISED: "revised",
} as const;

export type DutyReportStatus = typeof DutyReportStatus[keyof typeof DutyReportStatus];

/**
 * AI Employee Task
 */
export interface AITask {
  id: number;
  employeeRole: AIEmployeeRole;
  title: string;
  description: string;
  status: TaskStatus;
  dueDate: string;
  priority: "low" | "medium" | "high";
  assignedBy: number; // admin user id
  metadata: Record<string, any>;
  createdAt: string;
  updatedAt: string;
}

/**
 * AI Duty Report
 */
export interface AIDutyReport {
  id: number;
  employeeRole: AIEmployeeRole;
  reportDate: string;
  submittedAt: string;
  status: DutyReportStatus;
  tasksCompleted: number;
  recommendations: string[];
  summary: string;
  metadata: Record<string, any>;
}

/**
 * Create a new task for an AI employee
 */
export async function createAITask(
  employeeRole: AIEmployeeRole,
  title: string,
  description: string,
  priority: "low" | "medium" | "high" = "medium",
  dueDate: string = new Date(Date.now() + 24 * 60 * 60 * 1000).toISOString(),
  assignedBy: number = 1,
  metadata: Record<string, any> = {}
): Promise<AITask> {
  // In a real implementation, this would insert into database
  // For now, return a mock task
  return {
    id: Math.floor(Math.random() * 10000),
    employeeRole,
    title,
    description,
    status: TaskStatus.ASSIGNED,
    dueDate,
    priority,
    assignedBy,
    metadata,
    createdAt: new Date().toISOString(),
    updatedAt: new Date().toISOString(),
  };
}

/**
 * Get all tasks for an AI employee
 */
export async function getAIEmployeeTasks(employeeRole: AIEmployeeRole): Promise<AITask[]> {
  // Mock implementation
  return [];
}

/**
 * Update task status
 */
export async function updateTaskStatus(
  taskId: number,
  status: TaskStatus,
  metadata: Record<string, any> = {}
): Promise<AITask | null> {
  // Mock implementation
  return null;
}

/**
 * Generate LuckyAI daily coordination report
 */
export async function generateLuckyAIReport(): Promise<string> {
  const prompt = `You are LuckyAI, the central coordinator for CoinKrazy casino AI operations. 
Generate a brief daily operations summary covering:
1. Status of all AI departments (FraudAI, GameAI, SlotsAI, BingoAI, PokerAI, SportsAI)
2. Key metrics and KPIs
3. Any critical issues or alerts
4. Recommendations for the admin team

Keep it concise and actionable.`;

  const response = await invokeLLM({
    messages: [{ role: "user", content: prompt }],
  });

  return response.choices[0]?.message?.content || "Unable to generate report";
}

/**
 * Generate FraudAI daily report
 */
export async function generateFraudAIReport(): Promise<string> {
  const prompt = `You are FraudAI, responsible for detecting fraud and cheating at CoinKrazy casino.
Generate a daily fraud detection report including:
1. Suspicious accounts detected
2. Unusual betting patterns flagged
3. Multi-account fraud clusters identified
4. Recommended actions (suspend, investigate, monitor)
5. False positive rate and accuracy metrics

Format as actionable recommendations for admin review.`;

  const response = await invokeLLM({
    messages: [{ role: "user", content: prompt }],
  });

  return response.choices[0]?.message?.content || "Unable to generate fraud report";
}

/**
 * Generate GameAI daily report with new game designs
 */
export async function generateGameAIReport(): Promise<{
  report: string;
  games: Array<{
    name: string;
    theme: string;
    reels: number;
    symbols: string[];
    bonusFeatures: string[];
    description: string;
  }>;
}> {
  const prompt = `You are GameAI, responsible for designing and creating new branded PlayCoinKrazy.com games daily.
Design 15 new slot games for today including:
- Game name (branded as "PlayCoinKrazy - [Name]")
- Theme and visual style
- Number of reels (3, 5, or 6)
- Symbol names and types
- Bonus features (free spins, multipliers, scatters, etc.)
- Brief description

Format as JSON array with each game having: name, theme, reels, symbols[], bonusFeatures[], description`;

  const response = await invokeLLM({
    messages: [{ role: "user", content: prompt }],
    response_format: {
      type: "json_schema",
      json_schema: {
        name: "game_designs",
        strict: true,
        schema: {
          type: "object",
          properties: {
            games: {
              type: "array",
              items: {
                type: "object",
                properties: {
                  name: { type: "string" },
                  theme: { type: "string" },
                  reels: { type: "number" },
                  symbols: { type: "array", items: { type: "string" } },
                  bonusFeatures: { type: "array", items: { type: "string" } },
                  description: { type: "string" },
                },
                required: ["name", "theme", "reels", "symbols", "bonusFeatures", "description"],
              },
            },
          },
          required: ["games"],
        },
      },
    },
  });

  let games = [];
  try {
    const content = response.choices[0]?.message?.content;
    if (content) {
      const parsed = JSON.parse(content);
      games = parsed.games || [];
    }
  } catch (error) {
    console.error("Failed to parse GameAI response:", error);
  }

  return {
    report: `Generated ${games.length} new games for approval`,
    games,
  };
}

/**
 * Generate SlotsAI department report
 */
export async function generateSlotsAIReport(): Promise<string> {
  const prompt = `You are SlotsAI, responsible for the Slots department at CoinKrazy.
Generate a daily report including:
1. Top performing slot games
2. Underperforming games needing adjustment
3. Player engagement metrics
4. Recommended RTP adjustments
5. New feature recommendations for slot games

Keep recommendations specific and actionable.`;

  const response = await invokeLLM({
    messages: [{ role: "user", content: prompt }],
  });

  return response.choices[0]?.message?.content || "Unable to generate slots report";
}

/**
 * Generate BingoAI department report
 */
export async function generateBingoAIReport(): Promise<string> {
  const prompt = `You are BingoAI, responsible for the Bingo department at CoinKrazy.
Generate a daily report including:
1. Bingo room performance and player count
2. Card sales and revenue metrics
3. Player retention and engagement
4. Recommended room configurations or prize adjustments
5. New bingo game variations to introduce

Provide specific, actionable recommendations.`;

  const response = await invokeLLM({
    messages: [{ role: "user", content: prompt }],
  });

  return response.choices[0]?.message?.content || "Unable to generate bingo report";
}

/**
 * Generate PokerAI department report
 */
export async function generatePokerAIReport(): Promise<string> {
  const prompt = `You are PokerAI, responsible for the Poker department at CoinKrazy.
Generate a daily report including:
1. Active poker tables and tournament status
2. Player skill distribution and rake metrics
3. Tournament performance and prize pool utilization
4. Recommended stake levels and table configurations
5. New tournament format suggestions

Provide specific, actionable recommendations.`;

  const response = await invokeLLM({
    messages: [{ role: "user", content: prompt }],
  });

  return response.choices[0]?.message?.content || "Unable to generate poker report";
}

/**
 * Generate SportsAI department report
 */
export async function generateSportsAIReport(): Promise<string> {
  const prompt = `You are SportsAI, responsible for the Sportsbook department at CoinKrazy.
Generate a daily report including:
1. Sports event coverage and betting volume
2. Parlay and bet slip performance
3. Odds accuracy and sharp action detection
4. Player win rate and house edge metrics
5. Recommended sports additions or market expansions

Provide specific, actionable recommendations.`;

  const response = await invokeLLM({
    messages: [{ role: "user", content: prompt }],
  });

  return response.choices[0]?.message?.content || "Unable to generate sports report";
}

/**
 * Submit daily duty report for AI employee
 */
export async function submitAIDutyReport(
  employeeRole: AIEmployeeRole,
  tasksCompleted: number,
  recommendations: string[],
  summary: string,
  metadata: Record<string, any> = {}
): Promise<AIDutyReport> {
  const today = new Date().toISOString().split("T")[0];

  return {
    id: Math.floor(Math.random() * 10000),
    employeeRole,
    reportDate: today,
    submittedAt: new Date().toISOString(),
    status: DutyReportStatus.SUBMITTED,
    tasksCompleted,
    recommendations,
    summary,
    metadata,
  };
}

/**
 * Get all duty reports for a specific date
 */
export async function getDutyReportsForDate(date: string): Promise<AIDutyReport[]> {
  // Mock implementation
  return [];
}

/**
 * Approve or deny duty report
 */
export async function approveDutyReport(
  reportId: number,
  approved: boolean,
  adminNotes: string = ""
): Promise<AIDutyReport | null> {
  // Mock implementation
  return null;
}