import { analyzeBrief } from './llm.service.ts';
import { generateRecommendations, type NormalizedCandidate } from './recommendation.service.ts';

export type TaskStatus = 'pending' | 'uploading' | 'analyzing' | 'searching' | 'processing' | 'exporting' | 'completed' | 'failed';
export type StepStatus = 'pending' | 'running' | 'done' | 'error';

export interface TaskStep {
  id: string;
  label: string;
  status: StepStatus;
  progress: number;
  detail?: string;
}

export interface Task {
  id: string;
  status: TaskStatus;
  fileName: string;
  briefText: string;
  steps: TaskStep[];
  requirements: Array<{ label: string; value: string; confidence: number }>;
  searchCriteria: {
    platforms: string[];
    keywords: string[];
    fanRange: { min: number; max: number };
    budgetRange: { min: number; max: number };
    region?: string;
    gender?: string;
    contentTags?: string[];
    excludeTags?: string[];
    targetCount?: number;
  } | null;
  candidates: NormalizedCandidate[];
  totalPool: number;
  error?: string;
  createdAt: string;
  updatedAt: string;
}

const tasks = new Map<string, Task>();

function generateId(): string {
  return `task_${Date.now()}_${Math.random().toString(36).slice(2, 8)}`;
}

function defaultSteps(): TaskStep[] {
  return [
    { id: 'upload', label: '上传文件', status: 'pending', progress: 0 },
    { id: 'analyze', label: 'AI 解析 Brief 需求', status: 'pending', progress: 0 },
    { id: 'rules', label: '确定筛选规则', status: 'pending', progress: 0 },
    { id: 'search', label: '搜索达人资源', status: 'pending', progress: 0 },
    { id: 'recommend', label: '生成推荐名单', status: 'pending', progress: 0 },
    { id: 'export', label: '准备导出', status: 'pending', progress: 0 },
  ];
}

export function createTask(fileName: string, briefText: string): Task {
  const task: Task = {
    id: generateId(),
    status: 'pending',
    fileName,
    briefText,
    steps: defaultSteps(),
    requirements: [],
    searchCriteria: null,
    candidates: [],
    totalPool: 0,
    createdAt: new Date().toISOString(),
    updatedAt: new Date().toISOString(),
  };

  tasks.set(task.id, task);
  return task;
}

export function getTask(taskId: string): Task | undefined {
  return tasks.get(taskId);
}

export function getAllTasks(): Task[] {
  return Array.from(tasks.values());
}

function updateStep(task: Task, stepId: string, updates: Partial<TaskStep>): void {
  const step = task.steps.find((s) => s.id === stepId);
  if (step) {
    Object.assign(step, updates);
  }
  task.updatedAt = new Date().toISOString();
}

/**
 * 执行完整的提号流程
 * Upload Brief → AI解析 → 规则确定 → 搜索达人 → 生成推荐 → 准备导出
 */
export async function runTaskPipeline(taskId: string): Promise<void> {
  const task = tasks.get(taskId);
  if (!task) {
    throw new Error(`Task not found: ${taskId}`);
  }

  try {
    // Step 1: Upload (already done)
    task.status = 'analyzing';
    updateStep(task, 'upload', { status: 'done', progress: 100, detail: `已上传 ${task.fileName}` });

    // Step 2: AI 解析 Brief
    updateStep(task, 'analyze', { status: 'running', progress: 20, detail: '正在解析 Brief 需求...' });
    console.log(`[TaskPipeline] Brief 文本长度: ${task.briefText.length} 字符`);
    console.log(`[TaskPipeline] Brief 前200字: ${task.briefText.substring(0, 200)}...`);

    const analysisResult = await analyzeBrief(task.briefText);
    task.requirements = analysisResult.requirements;
    task.searchCriteria = analysisResult.searchCriteria;
    console.log(`[TaskPipeline] LLM 提取需求数: ${analysisResult.requirements.length}`);
    console.log(`[TaskPipeline] 搜索条件 platforms:`, analysisResult.searchCriteria.platforms);
    console.log(`[TaskPipeline] 搜索条件 keywords:`, analysisResult.searchCriteria.keywords);
    console.log(`[TaskPipeline] 搜索条件 fanRange:`, analysisResult.searchCriteria.fanRange);
    console.log(`[TaskPipeline] 搜索条件 budgetRange:`, analysisResult.searchCriteria.budgetRange);

    updateStep(task, 'analyze', {
      status: 'done',
      progress: 100,
      detail: `提取 ${analysisResult.requirements.length} 项需求，${analysisResult.searchCriteria.platforms.length} 个平台`,
    });

    // Step 3: 确定规则
    task.status = 'searching';
    updateStep(task, 'rules', { status: 'running', progress: 50, detail: '应用默认筛选规则...' });

    // 规则确定是自动的（使用默认规则）
    await delay(500);
    updateStep(task, 'rules', { status: 'done', progress: 100, detail: '已应用 5 条默认规则' });

    // Step 4 & 5: 搜索达人 + 生成推荐
    updateStep(task, 'search', { status: 'running', progress: 10, detail: '正在搜索达人资源...' });

    const candidates = await generateRecommendations(
      task.searchCriteria,
      (stage, detail) => {
        if (stage === 'search') {
          updateStep(task, 'search', { status: 'running', progress: 50, detail });
        } else if (stage === 'processing') {
          updateStep(task, 'search', { status: 'done', progress: 100, detail: '搜索完成' });
          updateStep(task, 'recommend', { status: 'running', progress: 50, detail });
        }
      }
    );

    task.candidates = candidates;
    task.totalPool = candidates.length;
    console.log(`[TaskPipeline] 推荐引擎返回 ${candidates.length} 位候选达人`);

    updateStep(task, 'search', { status: 'done', progress: 100, detail: `召回 ${candidates.length} 位候选达人` });
    updateStep(task, 'recommend', {
      status: 'done',
      progress: 100,
      detail: `强推荐 ${candidates.filter((c) => c.recommendStatus === '强推荐').length} 位，备选 ${candidates.filter((c) => c.recommendStatus === '备选').length} 位`,
    });

    // Step 6: 准备导出
    task.status = 'completed';
    updateStep(task, 'export', { status: 'done', progress: 100, detail: '推荐表已准备就绪，可导出' });
  } catch (error) {
    task.status = 'failed';
    task.error = error instanceof Error ? error.message : '未知错误';

    // Mark current running step as error
    for (const step of task.steps) {
      if (step.status === 'running') {
        step.status = 'error';
        step.detail = task.error;
      }
    }
  }
}

function delay(ms: number): Promise<void> {
  return new Promise((resolve) => setTimeout(resolve, ms));
}