angel
72b6879f4b
- Refactored max_bot from nested packages to flat module structure - Q2: Extended BotUser model (patronymic, email, org, address, vcf_raw, contact_hash, phone_verified, email_verified, last_interaction, total_conversations, total_tickets) - Q2: VCF parser (FN, N, TEL, EMAIL, ORG, ADR), upsert on re-contact, NLP history context (_get_user_history_context -> YandexGPT) - Q1: Broadcast preview modal with 10s confirmation timer - Q3: CSS var(--white)->var(--bg-card), var(--text)->var(--text-primary) - Q4: bot_settings showNotification(), editable max_bot_id - Q5: Webhook secret passthrough via X-Max-Bot-Api-Secret - Masking sensitive keys, dialog_cleared handler, migrate via _add_column_if_not_exists() - Rate limit (asyncio.sleep 0.5 per 10), dead code removed, conv.intent context in contact.py - Portal pages: bot_consent, bot_kb (edit), bot_settings, bot_test, bot_tickets, portal_settings - Tests: 21/21 passing, added test_yandex_gpt.py, test_email_sender.py - Deploy: deploy_full.sh, schema.sql, seed_knowledge_base.sql
271 lines
9.2 KiB
Python
271 lines
9.2 KiB
Python
import logging
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import datetime
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from typing import Optional
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from sqlalchemy import select
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from app.database import async_session
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from app.models import BotUser, BotConversation, BotMessage, BotKnowledgeBase, BotCategory
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from app.max_api import max_api
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from app.yandex_gpt import yandex_gpt
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from app.config_reader import config_reader
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from app.settings_cache import settings_cache
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from app.keyboards import consent_keyboard, return_to_consent_keyboard
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logger = logging.getLogger(__name__)
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async def handle_greeting(
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user_id: int,
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text: Optional[str] = None,
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first_name: str = "",
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last_name: str = "",
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username: str = "",
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) -> None:
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assistant_name = await settings_cache.get("assistant_name", "София")
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greeting_text = (
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f"Здравствуйте! Я {assistant_name}, помощник AegisOne Engineering. "
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f"Чем я могу быть вам полезна?"
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)
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await max_api.send_message(user_id, greeting_text)
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async with async_session() as db:
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existing = await db.execute(
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select(BotUser).where(BotUser.id == user_id)
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)
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user = existing.scalar_one_or_none()
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now = datetime.datetime.utcnow()
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if not user:
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user = BotUser(
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id=user_id,
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first_name=first_name,
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last_name=last_name,
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username=username,
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last_interaction=now,
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total_conversations=1,
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created_at=now,
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)
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db.add(user)
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else:
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if first_name:
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user.first_name = first_name
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if last_name:
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user.last_name = last_name
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if username:
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user.username = username
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user.last_interaction = now
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user.total_conversations = (user.total_conversations or 0) + 1
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await db.commit()
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await db.refresh(user)
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conv = BotConversation(
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user_id=user_id,
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state="analyzing",
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created_at=now,
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)
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db.add(conv)
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await db.commit()
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await db.refresh(conv)
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if text:
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await analyze_and_respond(user_id, conv.id, text)
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else:
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async with async_session() as db:
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conv.state = "awaiting_input"
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await db.commit()
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async def handle_message(user_id: int, text: str) -> None:
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async with async_session() as db:
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result = await db.execute(
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select(BotConversation)
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.where(BotConversation.user_id == user_id)
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.order_by(BotConversation.id.desc())
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.limit(1)
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)
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conv = result.scalar_one_or_none()
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if not conv:
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await handle_greeting(user_id, text)
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return
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msg = BotMessage(
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conversation_id=conv.id,
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direction="incoming",
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text=text,
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created_at=datetime.datetime.utcnow(),
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)
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db.add(msg)
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await db.commit()
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state = conv.state if conv else "greeting"
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if state in ("greeting", "analyzing", "awaiting_input"):
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await analyze_and_respond(user_id, conv.id, text)
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elif state == "awaiting_consent":
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from app.handlers.consent import handle_consent_response
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await handle_consent_response(user_id, conv.id, text)
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elif state == "consent_refused":
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from app.handlers.consent import handle_refused_again
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await handle_refused_again(user_id, conv.id, text)
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elif state == "awaiting_contact":
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from app.handlers.contact import handle_manual_contact
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await handle_manual_contact(user_id, conv.id, text)
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elif state == "awaiting_inquiry":
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from app.handlers.inquiry import handle_inquiry
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await handle_inquiry(user_id, conv.id, text)
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elif state in ("completed", "escalated"):
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await max_api.send_message(
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user_id,
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"Ваше обращение уже передано специалисту. "
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"Если у вас новый вопрос, напишите его, и я помогу.",
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)
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async def _get_user_history_context(user_id: int) -> str:
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from app.models import BotTicket
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async with async_session() as db:
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recent_msgs = await db.execute(
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select(BotMessage)
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.join(BotConversation)
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.where(BotConversation.user_id == user_id)
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.order_by(BotMessage.id.desc())
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.limit(10)
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)
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messages = list(reversed(recent_msgs.scalars().all()))
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open_tickets = await db.execute(
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select(BotTicket)
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.where(BotTicket.user_id == user_id)
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.where(BotTicket.status != "Закрыта")
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.order_by(BotTicket.id.desc())
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)
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tickets = open_tickets.scalars().all()
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parts = []
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if messages:
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msg_lines = []
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for m in messages:
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who = "Клиент" if m.direction == "incoming" else "Бот"
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msg_lines.append(f"{who}: {m.text or ''}")
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parts.append("Последние сообщения из прошлых диалогов:\n" + "\n".join(msg_lines))
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if tickets:
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ticket_lines = []
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for t in tickets:
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ticket_lines.append(f" - Заявка #{t.id}: {t.title} (статус: {t.status})")
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parts.append("Открытые заявки пользователя:\n" + "\n".join(ticket_lines))
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return "\n\n".join(parts)
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async def analyze_and_respond(user_id: int, conv_id: int, text: str) -> None:
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gpt_available = await yandex_gpt.is_available()
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if not gpt_available:
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await _limited_mode(user_id, conv_id)
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return
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history_context = await _get_user_history_context(user_id)
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intent = await yandex_gpt.analyze_intent(text, history_context)
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async with async_session() as db:
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result = await db.execute(
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select(BotConversation).where(BotConversation.id == conv_id)
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)
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conv = result.scalar_one_or_none()
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if not conv:
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return
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conv.intent = intent
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if intent == "question":
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kb_context = await _get_knowledge_base_context(text)
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answer = await yandex_gpt.generate_answer(text, kb_context, history_context)
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if answer:
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await max_api.send_message(user_id, answer)
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else:
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await _send_contacts(user_id)
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conv.state = "completed"
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elif intent == "ticket":
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conv.state = "awaiting_consent"
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consent_text = (
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"Для обработки Вашего запроса нам нужны ваши контактные данные "
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"для обратной связи. Даёте согласие на обработку "
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"персональных данных?"
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)
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await max_api.send_message(
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user_id, consent_text, attachments=consent_keyboard()
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)
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else:
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clarification = await yandex_gpt.clarify_intent(text, history_context)
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await max_api.send_message(user_id, clarification)
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conv.state = "awaiting_consent"
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after_text = (
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"\n\nДля обработки Вашего запроса нам нужны ваши контактные данные "
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"для обратной связи. Даёте согласие на обработку "
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"персональных данных?"
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)
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await max_api.send_message(
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user_id, after_text, attachments=consent_keyboard()
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)
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await db.commit()
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async def _limited_mode(user_id: int, conv_id: int) -> None:
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async with async_session() as db:
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result = await db.execute(
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select(BotConversation).where(BotConversation.id == conv_id)
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)
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conv = result.scalar_one_or_none()
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if conv:
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conv.state = "completed"
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await db.commit()
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await _send_contacts(user_id)
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async def _send_contacts(user_id: int) -> None:
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phones = config_reader.get_phones()
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email = config_reader.get_site_mail()
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phone_text = "\n".join(
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f"📞 {phone} — [позвонить](tel:{link})"
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for phone, link in phones
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)
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message = (
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"Вы можете связаться с нами:\n\n"
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f"{phone_text}\n"
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f"📧 [Написать на почту](mailto:{email})\n\n"
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f"Или написать на почту: {email}"
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)
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await max_api.send_message(user_id, message, format="markdown")
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async def _get_knowledge_base_context(query: str) -> str:
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async with async_session() as db:
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result = await db.execute(
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select(BotKnowledgeBase)
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.where(BotKnowledgeBase.is_active == True)
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.order_by(BotKnowledgeBase.sort_order)
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)
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cards = result.scalars().all()
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if not cards:
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return ""
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parts = []
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for card in cards:
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keywords = " ".join(card.keywords) if card.keywords else ""
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answer = card.answer or "Нет ответа"
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cat_name = card.category.name if card.category else "Общее"
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parts.append(f"[{cat_name}] {card.question}: {answer} (ключевые слова: {keywords})")
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return "\n\n".join(parts[:20])
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