"""求职助手 Agent 对话 + 岗位简历优化 Service

主要功能：查询简历数据，调用 AI 模块完成对话；针对岗位并发优化简历。
依赖：resume_loader（简历统一查询）、customize_resume_store（定制简历存取+构建）、job_agent.chat AI 模块、job_agent.resume_optimizer（岗位简历优化）
使用表：bg_user_resume + 5张子表（通过 resume_loader 查询）、bg_job（查岗位）
"""

import asyncio
import json

from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession

from app.ai.job_agent.chat import agent_chat
from app.ai.job_agent.resume_optimizer import optimize_summary, optimize_experience
from app.core.logger import log
from app.models.job import Job
from app.schemas.customize_resume import CustomizeResume, Education, Work, Internship, Project, Competition
from app.services.resume_loader import ResumeDetail, load_resume_detail
from app.services import customize_resume_store


class JobAgentChatService:

    def __init__(self, session: AsyncSession):
        self.session = session

    async def chat(self, user_id: int, resume_id: int, message: str,
                   history: list[dict], job_categories: list[str],
                   regions: list[str], industries: list[str]) -> dict:
        """求职助手对话：查简历 → 序列化 → 调 AI 模块"""
        detail = await load_resume_detail(self.session, resume_id, user_id)
        resume_text = self._build_resume_text(detail)
        return await agent_chat(resume_text, message, history, job_categories, regions, industries)

    @staticmethod
    def _build_resume_text(detail: ResumeDetail) -> str:
        """将简历数据序列化为文本供 AI 使用"""
        resume = detail.resume
        parts = []
        if resume.name:
            parts.append(f"姓名：{resume.name}")
        if resume.target_position:
            parts.append(f"目标岗位：{resume.target_position}")
        if resume.skills:
            parts.append(f"技能：{'、'.join(resume.skills)}")
        if resume.certificates:
            parts.append(f"证书：{'、'.join(resume.certificates)}")
        if resume.summary:
            parts.append(f"个人概述：{resume.summary}")
        if detail.education:
            parts.append("教育经历：")
            for r in detail.education:
                parts.append(f"  - {r.school or ''} {r.major or ''} {r.degree or ''}")
        if detail.work:
            parts.append("工作经历：")
            for r in detail.work:
                parts.append(f"  - {r.company_name or ''} {r.position or ''}")
        if detail.internship:
            parts.append("实习经历：")
            for r in detail.internship:
                parts.append(f"  - {r.company_name or ''} {r.position or ''}")
        if detail.project:
            parts.append("项目经历：")
            for r in detail.project:
                parts.append(f"  - {r.project_name or ''} {r.role or ''}")
        if detail.competition:
            parts.append("竞赛经历：")
            for r in detail.competition:
                parts.append(f"  - {r.competition_name or ''} {r.award or ''}")
        return "\n".join(parts) if parts else "暂无简历信息"

    async def optimize_resume(self, user_id: int, resume_id: int, job_id: int) -> dict:
        """针对岗位优化简历：查简历+岗位 → 构建定制简历 → 并发AI优化 → 存Redis → 返回"""
        # 1. 查简历 + 岗位
        detail = await load_resume_detail(self.session, resume_id, user_id)
        job = await self._get_job(job_id)
        # 2. 构建定制简历
        cr = customize_resume_store.build_from_detail(detail)
        # 3. 并发 AI 优化（summary + 5张子表经历）
        tasks = []
        job_desc = f"{job.description or ''}\n{job.requirement or ''}"
        if cr.resume.summary:
            tasks.append(("summary", optimize_summary(job.title or "", job_desc, cr.resume.summary)))
        for name, items in [("education", cr.education), ("work", cr.work), ("internship", cr.internship),
                            ("project", cr.project), ("competition", cr.competition)]:
            if items:
                rows_json = json.dumps([item.model_dump(by_alias=True) for item in items], ensure_ascii=False)
                tasks.append((name, optimize_experience(job.title or "", job_desc, rows_json)))
        # 执行并发
        if tasks:
            keys = [t[0] for t in tasks]
            results = await asyncio.gather(*[t[1] for t in tasks], return_exceptions=True)
            for key, result in zip(keys, results):
                if isinstance(result, Exception):
                    log.warning(f"岗位简历优化[{key}]失败: {result}")
                    continue
                self._apply_optimize_result(cr, key, result)
        # 4. 存 Redis
        await customize_resume_store.save(user_id, cr)
        # 5. 返回
        return cr.model_dump(by_alias=True)

    async def _get_job(self, job_id: int) -> Job:
        """查岗位"""
        result = await self.session.execute(select(Job).where(Job.id == job_id))
        job = result.scalar_one_or_none()
        if not job:
            raise ValueError("岗位不存在")
        return job

    @staticmethod
    def _apply_optimize_result(cr: CustomizeResume, key: str, result) -> None:
        """将 AI 优化结果应用到定制简历"""
        if key == "summary" and isinstance(result, str):
            cr.resume.summary = result
        elif key == "education" and isinstance(result, list):
            cr.education = [Education.model_validate(item) for item in result]
        elif key == "work" and isinstance(result, list):
            cr.work = [Work.model_validate(item) for item in result]
        elif key == "internship" and isinstance(result, list):
            cr.internship = [Internship.model_validate(item) for item in result]
        elif key == "project" and isinstance(result, list):
            cr.project = [Project.model_validate(item) for item in result]
        elif key == "competition" and isinstance(result, list):
            cr.competition = [Competition.model_validate(item) for item in result]