import { Injectable, Logger } from '@nestjs/common'
import { InjectModel } from '@nestjs/mongoose'
import { Model } from 'mongoose'
import { AiService } from '../ai/ai.service'
import { HotPosition } from '../positions/positions.schema'

export interface CareerProfile {
  major: string
  grade?: string
  interests?: string
  gpa?: string
  goal?: string
}

export interface CareerPath {
  name: string
  reason: string
  matchScore: number
  salary?: string
}

export interface ChatMessage {
  role: 'user' | 'assistant'
  content: string
}

@Injectable()
export class CareerAdviceService {
  private readonly logger = new Logger(CareerAdviceService.name)

  constructor(
    @InjectModel(HotPosition.name) private positionModel: Model<HotPosition>,
    private aiService: AiService,
  ) {}

  /**
   * Analyze user profile and return career advice with position recommendations.
   */
  async analyze(profile: CareerProfile) {
    const positions = await this.positionModel.find({ active: true })
      .sort({ sort: 1 })
      .lean()
      .exec()

    const positionsContext = positions.map(p =>
      `- ${p.name}${p.salary ? ` (薪资: ${p.salary})` : ''}${p.company ? ` - ${p.company}` : ''}`
    ).join('\n')

    const systemPrompt = `你是一位资深的中国大学生职业规划顾问。你的任务是根据学生的专业背景和个人情况,给出个性化的择业建议。

你的建议需要涵盖:
1. 该专业的典型职业方向和发展路径
2. "考研vs就业vs考公"的决策分析(基于学生具体情况)
3. 当前就业市场的真实形势(如AI对各行业的影响)
4. 具体可行动的建议(实习、技能提升等)

你需要从以下可用岗位中,推荐最匹配该学生的3-5个方向:

${positionsContext}

注意:
- 你的回答要诚恳务实,不要画大饼
- 指出每个选择的利弊和风险
- 结合AI时代对各行业的影响给出建议
- 最后以JSON格式输出推荐岗位列表

回复格式:
先输出一段详细的个性化分析建议(中文,300-500字)。
然后在最后单独一行输出JSON数组(不要任何其他内容):
---JSON---
[{"name":"岗位名","reason":"推荐理由简要说明","matchScore":85,"salary":"薪资范围"},...]
---JSON---`

    const userMessage = this.buildProfileMessage(profile)
    const rawReply = await this.aiService.call({
      systemPrompt,
      userMessage,
      temperature: 0.7,
      maxTokens: 2048,
    })

    return this.parseResponse(rawReply, positions)
  }

  /**
   * Continue a chat conversation about career choices.
   */
  async chat(message: string, history: ChatMessage[]) {
    const positions = await this.positionModel.find({ active: true })
      .sort({ sort: 1 })
      .lean()
      .exec()

    const positionsContext = positions.map(p =>
      `- ${p.name}${p.salary ? ` (薪资: ${p.salary})` : ''}`
    ).join('\n')

    const systemPrompt = `你是一位资深的中国大学生职业规划顾问。继续与学生的对话,回答他们的择业相关问题。

可推荐的岗位列表:
${positionsContext}

注意:
- 回答诚恳务实,结合AI时代背景
- 给出具体可操作的建议
- 如果学生提到具体岗位,可以从推荐列表中选择匹配的
- 保持对话亲切自然,用中文回复`

    const historyMessages = history.map(h =>
      `${h.role === 'user' ? '学生' : '顾问'}: ${h.content}`
    ).join('\n')

    const userMessage = `对话历史:\n${historyMessages}\n\n学生最新提问: ${message}`

    const reply = await this.aiService.call({
      systemPrompt,
      userMessage,
      temperature: 0.7,
      maxTokens: 1024,
    })

    return { reply }
  }

  private buildProfileMessage(profile: CareerProfile): string {
    const parts: string[] = [`学生专业: ${profile.major}`]
    if (profile.grade) parts.push(`年级: ${profile.grade}`)
    if (profile.interests) parts.push(`兴趣方向: ${profile.interests}`)
    if (profile.gpa) parts.push(`GPA/成绩: ${profile.gpa}`)
    if (profile.goal) parts.push(`目标/困惑: ${profile.goal}`)
    return parts.join('\n')
  }

  private parseResponse(rawReply: string, allPositions: any[]): {
    reply: string
    careerPaths: CareerPath[]
  } {
    // Extract JSON array from ---JSON--- markers
    const jsonMatch = rawReply.match(/---JSON---\s*(\[[\s\S]*?\])\s*---JSON---/)
    let careerPaths: CareerPath[] = []

    if (jsonMatch) {
      try {
        careerPaths = JSON.parse(jsonMatch[1])
      } catch {
        this.logger.warn('Failed to parse career paths JSON')
      }
    }

    // Clean reply (remove --JSON-- markers)
    const reply = rawReply.replace(/---JSON---[\s\S]*?---JSON---/g, '').trim()

    return { reply, careerPaths }
  }

  /** Get hot positions (delegated from positions module) */
  async getHotPositions() {
    return this.positionModel.find({ active: true })
      .sort({ sort: 1 })
      .lean()
      .exec()
  }
}