# -*- coding: utf-8 -*-
"""
企业微信 AI 智能体消息回调控制器
接收企业微信用户发送给 AI 应用的消息，异步处理后主动推送回复
"""

import logging
import threading

from odoo import http, api, SUPERUSER_ID
from odoo.http import request, Response

from ..utils.wx_biz_msg_crypt import WXBizMsgCrypt, WXBizMsgCryptError, parse_wecom_message

_logger = logging.getLogger(__name__)


class WecomAiCallback(http.Controller):
    """企业微信 AI 消息回调"""

    def _get_ai_app_config(self):
        """获取 AI 智能体对应的企业微信应用配置"""
        config = request.env['wecom.apps.config'].sudo().search([
            ('wecom_apps_type', '=', 'ai_callback'),
            ('wecom_apps_category', '=', 'agent'),
        ], limit=1)
        if not config or not config.wecom_apps_id:
            return None
        return config.wecom_apps_id

    def _get_crypt_instance(self, wecom_app):
        """创建加解密实例"""
        token = wecom_app.callback_token
        aes_key = wecom_app.encoding_aes_key
        corpid = wecom_app.corpid
        if not all([token, aes_key, corpid]):
            _logger.error("企业微信 AI 回调配置不完整: token=%s, aes_key=%s, corpid=%s",
                          bool(token), bool(aes_key), bool(corpid))
            return None
        return WXBizMsgCrypt(token, aes_key, corpid)

    @http.route('/wecom/ai/callback', type='http', auth='none',
                methods=['GET', 'POST'], csrf=False)
    def ai_callback(self, msg_signature=None, timestamp=None, nonce=None,
                    echostr=None, **kw):
        """
        企业微信 AI 应用消息回调入口

        GET: URL验证（配置接收消息服务器时企业微信发起的验证请求）
        POST: 接收用户消息
        """
        # 获取 AI 应用配置
        wecom_app = self._get_ai_app_config()
        if not wecom_app:
            _logger.error("未找到 AI 回调应用配置（wecom_apps_type=ai_callback, category=agent）")
            return Response("config error", content_type='text/plain')

        crypt = self._get_crypt_instance(wecom_app)
        if not crypt:
            return Response("config error", content_type='text/plain')

        # === GET: URL验证 ===
        if request.httprequest.method == 'GET':
            return self._handle_verify(crypt, msg_signature, timestamp, nonce, echostr)

        # === POST: 接收消息 ===
        return self._handle_message(crypt, msg_signature, timestamp, nonce)

    def _handle_verify(self, crypt, msg_signature, timestamp, nonce, echostr):
        """处理URL验证请求"""
        if not all([msg_signature, timestamp, nonce, echostr]):
            _logger.warning("AI回调URL验证缺少参数: sig=%s, ts=%s, nonce=%s, echo=%s",
                           msg_signature, timestamp, nonce, bool(echostr))
            return Response("param error", content_type='text/plain')
        try:
            echo_plain = crypt.verify_url(msg_signature, timestamp, nonce, echostr)
            _logger.info("企业微信 AI 回调URL验证成功")
            return Response(echo_plain, content_type='text/plain')
        except WXBizMsgCryptError as e:
            _logger.error("AI回调URL验证失败: %s", e)
            return Response("verify error", content_type='text/plain')

    def _handle_message(self, crypt, msg_signature, timestamp, nonce):
        """处理接收消息请求"""
        if not all([msg_signature, timestamp, nonce]):
            _logger.warning("AI回调消息缺少签名参数")
            return Response("", content_type='text/plain')

        post_data = request.httprequest.get_data(as_text=True)
        if not post_data:
            _logger.warning("AI回调消息体为空")
            return Response("", content_type='text/plain')

        # 解密消息
        try:
            xml_plain = crypt.decrypt_msg(msg_signature, timestamp, nonce, post_data)
        except WXBizMsgCryptError as e:
            _logger.error("AI回调消息解密失败: %s", e)
            return ""

        # 解析消息
        msg = parse_wecom_message(xml_plain)
        if not msg:
            _logger.error("AI回调消息XML解析失败")
            return ""

        _logger.info("收到企业微信AI消息: from=%s, type=%s, content=%s",
                     msg.get('from_user'), msg.get('msg_type'),
                     msg.get('content', '')[:50])

        # 只处理文本消息
        if msg.get('msg_type') != 'text':
            _logger.info("AI回调收到非文本消息类型: %s，暂不处理", msg.get('msg_type'))
            return Response("", content_type='text/plain')

        wecom_userid = msg.get('from_user')
        content = msg.get('content', '').strip()
        if not wecom_userid or not content:
            return Response("", content_type='text/plain')

        # 异步处理: 立即返回空响应，后台线程处理AI对话并推送回复
        db_name = request.env.cr.dbname
        threading.Thread(
            target=self._async_process_ai_message,
            args=(db_name, wecom_userid, content),
            daemon=True,
        ).start()

        # 立即返回空字符串，表示成功接收
        return Response("", content_type='text/plain')

    def _async_process_ai_message(self, db_name, wecom_userid, content):
        """
        后台线程: 处理 AI 对话并推送回复
        使用独立的数据库游标和环境
        """
        try:
            registry = api.Registry(db_name)
            with registry.cursor() as cr:
                env = api.Environment(cr, SUPERUSER_ID, {})
                env['wecom.ai.chat'].process_ai_message(wecom_userid, content)
                cr.commit()
        except Exception as e:
            _logger.exception("AI消息异步处理失败 [user=%s]: %s", wecom_userid, e)