394 lines
16 KiB
Python
394 lines
16 KiB
Python
# -*- coding: utf-8 -*-
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import json
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import logging
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from odoo import http
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from odoo.http import request
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_logger = logging.getLogger(__name__)
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from odoo.tools import format_datetime
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class AiChatController(http.Controller):
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"""AI 聊天 API"""
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def _check_ai_access(self):
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"""检查用户是否有 AI Agent 使用权限"""
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if not request.env.user.has_group('yuthon_ai_agent.group_ai_agent_user'):
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return {'error': '您没有使用 AI 助手的权限，请联系管理员开通。'}
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return None
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@http.route('/ai/chat/send', type='json', auth='user', methods=['POST'], csrf=False)
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def chat_send(self, conversation_id, message, attachment_ids=None):
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"""发送消息（支持附件 OCR）"""
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err = self._check_ai_access()
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if err:
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return err
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conv = request.env['ai.conversation'].browse(conversation_id)
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if not conv.exists():
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return {'error': '对话不存在'}
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reply = conv.send_message(message, attachment_ids=attachment_ids)
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if isinstance(reply, dict) and 'error' in reply:
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return reply
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# 提取 assistant 回复内容（支持 dict 和纯文本两种返回格式）
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content = reply.get('content') if isinstance(reply, dict) else reply
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action = reply.get('action') if isinstance(reply, dict) else None
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# 获取刚创建的用户消息（附件信息）
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user_msg = conv.message_ids.filtered(lambda m: m.role == 'user')[-1:]
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user_attachments = []
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if user_msg:
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for att in user_msg.attachment_ids:
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user_attachments.append({
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'id': att.id,
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'name': att.name,
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'mimetype': att.mimetype,
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})
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last_msg = conv.message_ids.filtered(lambda m: m.role == 'assistant')[-1:]
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result = {
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'content': content,
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'message_id': last_msg.id if last_msg else False,
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'attachments': user_attachments,
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}
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if action:
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result['action'] = action
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return result
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@http.route('/ai/chat/history', type='json', auth='user')
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def chat_history(self, conversation_id):
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"""获取对话历史"""
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conv = request.env['ai.conversation'].browse(conversation_id)
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if not conv.exists():
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return {'error': '对话不存在'}
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user_tz = request.env.user.tz or 'Asia/Shanghai'
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from pytz import timezone, utc
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local_tz = timezone(user_tz)
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messages = []
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for msg in conv.message_ids:
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if msg.create_date:
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utc_dt = msg.create_date.replace(tzinfo=utc)
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local_dt = utc_dt.astimezone(local_tz)
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time_str = local_dt.strftime('%H:%M')
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else:
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time_str = ''
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# 附件信息
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msg_attachments = []
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for att in msg.attachment_ids:
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msg_attachments.append({
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'id': att.id,
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'name': att.name,
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'mimetype': att.mimetype,
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})
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messages.append({
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'id': msg.id,
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'role': msg.role,
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'content': msg.content,
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'date': time_str,
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'attachments': msg_attachments,
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'action': msg.action if msg.action else None,
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})
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return {'messages': messages}
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@http.route('/ai/chat/clear', type='json', auth='user', methods=['POST'], csrf=False)
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def chat_clear(self, conversation_id):
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"""清空对话"""
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conv = request.env['ai.conversation'].browse(conversation_id)
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if not conv.exists():
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return {'error': '对话不存在'}
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conv.message_ids.unlink()
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return {'success': True}
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@http.route('/ai/conversation/create', type='json', auth='user', methods=['POST'], csrf=False)
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def conversation_create(self):
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"""创建新对话并返回ID"""
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provider = request.env['ai.provider'].search([('active', '=', True)], limit=1)
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if not provider:
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return {'error': '请先在服务商配置中设置 AI 服务'}
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conv = request.env['ai.conversation'].create({
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'name': '新对话',
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'provider_id': provider.id,
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})
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return {'id': conv.id}
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@http.route('/ai/conversation/get_or_create_personal', type='json', auth='user')
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def get_or_create_personal(self):
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"""获取或创建当前用户的个人对话（浮动聊天用）"""
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err = self._check_ai_access()
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if err:
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return err
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conv = request.env['ai.conversation'].search([
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('create_uid', '=', request.env.uid),
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], limit=1, order='create_date desc')
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if not conv:
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provider = request.env['ai.provider'].search([('active', '=', True)], limit=1)
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if not provider:
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return {'error': '请先在服务商配置中设置 AI 服务'}
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conv = request.env['ai.conversation'].create({
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'name': '个人对话',
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'provider_id': provider.id,
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})
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return {'id': conv.id, 'name': conv.name}
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@http.route('/ai/conversation/list', type='json', auth='user')
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def conversation_list(self):
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"""获取当前用户的所有对话列表"""
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err = self._check_ai_access()
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if err:
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return err
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convs = request.env['ai.conversation'].search([
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('create_uid', '=', request.env.uid),
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], order='create_date desc', limit=50)
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return {
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'conversations': [{
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'id': c.id,
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'name': c.name,
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'message_count': c.message_count,
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} for c in convs]
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}
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@http.route('/ai/chat/execute-tool', type='json', auth='user', methods=['POST'], csrf=False)
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def chat_execute_tool(self, conversation_id, tool_name, tool_params=None):
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"""执行工具（主动感知按钮点击后调用）"""
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err = self._check_ai_access()
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if err:
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return err
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conv = request.env['ai.conversation'].browse(conversation_id)
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if not conv.exists():
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return {'error': '对话不存在'}
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# 调用 AI Agent 的工具执行方法
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try:
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result = conv._execute_tool(tool_name, tool_params or {})
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return result
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except Exception as e:
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_logger.exception('Execute tool %s failed: %s', tool_name, e)
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return {'error': f'执行失败：{e}'}
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@http.route('/ai/conversation/new', type='json', auth='user', methods=['POST'], csrf=False)
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def conversation_new(self):
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"""新建对话"""
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err = self._check_ai_access()
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if err:
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return err
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provider = request.env['ai.provider'].search([('active', '=', True)], limit=1)
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if not provider:
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return {'error': '请先在服务商配置中设置 AI 服务'}
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conv = request.env['ai.conversation'].create({
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'name': '新对话',
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'provider_id': provider.id,
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})
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return {'id': conv.id, 'name': conv.name}
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@http.route('/ai/conversation/delete', type='json', auth='user', methods=['POST'], csrf=False)
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def conversation_delete(self, conversation_id):
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"""删除对话"""
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err = self._check_ai_access()
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if err:
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return err
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conv = request.env['ai.conversation'].browse(conversation_id)
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if not conv.exists():
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return {'error': '对话不存在'}
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if conv.create_uid.id != request.env.uid:
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return {'error': '只能删除自己的对话'}
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conv.unlink()
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return {'success': True}
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@http.route('/ai/profile/get', type='json', auth='user')
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def get_profile(self):
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"""获取当前用户的 AI 画像（含记忆摘要）"""
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err = self._check_ai_access()
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if err:
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return err
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profile = request.env['ai.user.profile'].get_or_create()
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return {
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'id': profile.id,
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'nickname': profile.nickname or '',
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'role': profile.role or '',
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'department': profile.department or '',
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'style_preference': profile.style_preference or 'concise',
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'memory_count': profile.memory_count,
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}
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@http.route('/ai/attachment/upload', type='http', auth='user', methods=['POST'], csrf=False)
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def attachment_upload(self, **kwargs):
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"""上传聊天附件（图片/PDF/Excel），调 OCR 或 Excel 解析器提取文字并返回结果。
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请求：multipart/form-data，字段名 'file'
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可能携带 conversation_id 用于关联对话
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返回：JSON { success, attachment_id, filename, mimetype, ocr_text, error, meta }
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"""
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err = self._check_ai_access()
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if err:
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return request.make_json_response(err)
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uploaded = request.httprequest.files.get('file')
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if not uploaded:
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return request.make_json_response({'success': False, 'error': '未收到文件'})
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# 读取文件内容
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raw_bytes = uploaded.read()
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filename = uploaded.filename or 'untitled'
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mimetype = uploaded.content_type or 'application/octet-stream'
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# 文件类型分类
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IMG_MIMES = {'image/png', 'image/jpeg', 'image/jpg', 'image/bmp', 'image/gif'}
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PDF_MIMES = {'application/pdf'}
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EXCEL_MIMES = {
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'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet', # .xlsx
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'application/vnd.ms-excel', # .xls
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'text/csv', # .csv
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'application/vnd.ms-excel.sheet.macroEnabled.12', # .xlsm
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}
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is_image = mimetype in IMG_MIMES
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is_pdf = mimetype in PDF_MIMES
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is_excel = mimetype in EXCEL_MIMES
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# 对于 Excel，也接受通过文件扩展名判断（企微/浏览器可能给错 MIME）
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if not is_excel and not is_image and not is_pdf:
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lower_name = filename.lower()
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if lower_name.endswith(('.xlsx', '.xls', '.csv', '.xlsm')):
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is_excel = True
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mimetype = 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'
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if not (is_image or is_pdf or is_excel):
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return request.make_json_response({
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'success': False,
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'error': f'不支持的文件格式（{mimetype}），支持：PNG/JPG/BMP/GIF/PDF/Excel/CSV'
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})
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# 限制文件大小
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max_size = 20 * 1024 * 1024 if is_excel else 10 * 1024 * 1024
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if len(raw_bytes) > max_size:
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size_mb = len(raw_bytes) / 1024 / 1024
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return request.make_json_response({
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'success': False,
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'error': f'文件过大（{size_mb:.1f}MB），上限 {max_size // 1024 // 1024}MB'
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})
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# 获取当前对话的 Provider 配置
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conv_id = kwargs.get('conversation_id')
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provider = None
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conversation = None
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if conv_id:
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conversation = request.env['ai.conversation'].sudo().browse(int(conv_id))
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if conversation.exists():
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provider = conversation.provider_id
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# 查找或创建 AI 聊天附件专用文件夹
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Folder = request.env['documents.folder'].sudo()
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folder = Folder.search([('name', '=', 'AI 聊天附件')], limit=1)
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if not folder:
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folder = Folder.create({'name': 'AI 聊天附件'})
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# 创建 documents.document
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document = request.env['documents.document'].sudo().create({
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'name': filename,
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'mimetype': mimetype,
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'raw': raw_bytes,
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'folder_id': folder.id,
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})
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ocr_text = ''
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ocr_error = ''
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ocr_diag = {}
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file_type_code = 'image'
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# —— Excel 解析 ——
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if is_excel:
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file_type_code = 'excel'
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ocr_diag['parser'] = 'excel_parser'
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# 创建导入记录
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import_record = request.env['ai.import.record'].sudo().create({
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'document_id': document.id,
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'filename': filename,
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'file_type': 'excel',
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'user_id': request.env.uid,
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'ocr_status': 'pending',
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})
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if conversation:
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import_record.write({'conversation_id': conversation.id})
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from ..utils.excel_parser import parse_excel_to_markdown, MAX_ROWS
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ocr_diag['max_rows'] = MAX_ROWS
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markdown_text, meta = parse_excel_to_markdown(raw_bytes, filename)
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ocr_diag['meta'] = meta
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if meta.get('error'):
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ocr_error = meta['error']
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import_record.write({'ocr_status': 'failed', 'ocr_error': ocr_error})
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else:
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ocr_text = markdown_text
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document.sudo().write({'ai_ocr_content': ocr_text})
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ocr_status = 'success' if not meta.get('truncated') else 'success'
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import_record.write({
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'ocr_status': ocr_status,
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'ocr_content': ocr_text,
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'ocr_error': ''
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})
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# 查找匹配的导入规则
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rule = request.env['ai.import.rule'].sudo().find_matching_rule(
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filename, 'excel', mimetype
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)
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if rule:
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import_record.write({'import_rule_id': rule.id})
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ocr_diag['matched_rule'] = rule.name
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_logger.info('[Excel-Upload] 匹配导入规则: %s', rule.name)
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# —— 图片/PDF OCR ——
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elif is_image or is_pdf:
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file_type_code = 'image' if is_image else 'pdf'
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if provider and provider.ocr_enabled:
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from ..models.ocr_provider import get_ocr_instance
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ocr, init_err = get_ocr_instance(provider)
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ocr_diag['provider'] = provider.name
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ocr_diag['ocr_enabled'] = True
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if ocr is None:
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ocr_error = init_err or 'OCR 实例创建失败'
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ocr_diag['init_error'] = ocr_error
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else:
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ocr_diag['init_ok'] = True
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result = ocr.recognize_general(raw_bytes, mimetype)
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ocr_diag['method'] = 'GeneralBasicOCR'
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ocr_diag['success'] = result.get('success')
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if result.get('success'):
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ocr_text = result.get('text') or ''
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ocr_diag['text_len'] = len(ocr_text)
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if ocr_text:
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document.sudo().write({'ai_ocr_content': ocr_text})
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else:
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ocr_error = '图片中未识别到文字'
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else:
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ocr_error = result.get('error', 'OCR 调用失败')
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else:
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ocr_diag['ocr_enabled'] = False
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ocr_diag['reason'] = 'OCR 未启用' if provider else '未找到 AI 服务商'
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return request.make_json_response({
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'success': True,
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'attachment_id': document.id,
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'filename': filename,
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'mimetype': mimetype,
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'ocr_text': ocr_text,
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'ocr_error': ocr_error,
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'file_type': file_type_code,
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'_ocr_diag': ocr_diag,
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})
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@http.route('/ai/rule/test_guide', type='json', auth='user', methods=['POST'])
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def test_active_guide(self, rule_id):
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"""测试主动感知规则：创建引导消息，返回 conversation_id 供前端打开聊天"""
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err = self._check_ai_access()
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if err:
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return err
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rule = request.env['ai.rule'].browse(rule_id)
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if not rule.exists():
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return {'error': '规则不存在'}
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try:
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conv_id = rule._do_test_guide()
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return {'success': True, 'conversation_id': conv_id}
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except Exception as e:
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_logger.exception('Test guide failed')
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return {'error': str(e)}
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