176 lines
7.6 KiB
Python
176 lines
7.6 KiB
Python
import asyncio
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import io
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import os
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import traceback
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from typing import Literal
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from asgiref.sync import sync_to_async
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from langchain.agents import create_agent
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from langchain_openai import ChatOpenAI
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from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver
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from pydantic import BaseModel
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from pypdf import PdfReader
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from telegram import (
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InlineKeyboardButton,
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InlineKeyboardMarkup,
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KeyboardButton,
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ReplyKeyboardMarkup,
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Update,
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)
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from telegram.ext import (
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ApplicationBuilder,
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CommandHandler,
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ContextTypes,
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MessageHandler,
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filters,
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)
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from vacancies.conf.settings import DB_URI
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from vacancies.main import prompts
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from vacancies.main.models import Customer, CustomerCV, JobTitle
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from vacancies.main.recommendations import get_next_vacancy
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from django.conf import settings
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from qdrant_client import AsyncQdrantClient
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from openai import AsyncOpenAI
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qdrant_client = AsyncQdrantClient(url=settings.QDRANT_URL)
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openai_client = AsyncOpenAI(base_url="https://openrouter.ai/api/v1")
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async def get_relevant_messages(query: str):
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"""Получает релевантные сообщения по запросу пользователя."""
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embedding = await openai_client.embeddings.create(
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model="qwen/qwen3-embedding-8b",
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input=query,
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encoding_format="float",
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)
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response = await qdrant_client.query_points(
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collection_name="messages",
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query=embedding.data[0].embedding,
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limit=20,
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)
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messages = [hit.payload["message"] for hit in response.points]
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return "\n\n".join(messages)
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async def get_user_resume(user_id: int):
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"""Получает резюме пользователя для подбора вакансий."""
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customer_cv = await CustomerCV.objects.filter(customer__telegram_id=user_id).afirst()
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return customer_cv.content if customer_cv else ""
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async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
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await Customer.objects.aget_or_create(
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telegram_id=update.effective_user.id,
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defaults=dict(
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username=update.effective_user.username,
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chat_id=update.effective_chat.id,
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),
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)
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keyboard = [[KeyboardButton("Получить следующую вакансию")]]
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reply_markup = ReplyKeyboardMarkup(keyboard, resize_keyboard=True, one_time_keyboard=False)
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text = "Привет! Я карьерный копилот: помогу с работой, интервью и расскажу новости по рынку, специально для тебя. С чего начнем?"
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await context.bot.send_message(chat_id=update.effective_chat.id, text=text, reply_markup=reply_markup)
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async def next_vacancy(update: Update, context: ContextTypes.DEFAULT_TYPE):
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await context.bot.send_message(update.effective_chat.id, "⏳ Обрабатываю твой запрос. Пожалуйста, подождите...")
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customer_cv = await CustomerCV.objects.filter(customer__telegram_id=update.effective_user.id).afirst()
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if not customer_cv:
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message = "Пришлите мне свое резюме, чтобы я мог подобрать вам вакансии!"
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await context.bot.send_message(chat_id=update.effective_chat.id, text=message)
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return
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vacancy = await asyncio.to_thread(get_next_vacancy, customer_cv)
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if not vacancy:
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message = "Вакансии закончились, возвращайтесь позже!"
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await context.bot.send_message(chat_id=update.effective_chat.id, text=message)
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return
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await context.bot.send_message(
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chat_id=update.effective_chat.id,
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parse_mode="Markdown",
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text=vacancy.get_formatted_response(),
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reply_markup=InlineKeyboardMarkup([[
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InlineKeyboardButton("Откликнуться", url=vacancy.link),
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]]),
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)
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async def prompt(update: Update, context: ContextTypes.DEFAULT_TYPE):
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async with AsyncPostgresSaver.from_conn_string(DB_URI) as checkpointer:
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chat_model = ChatOpenAI(
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model_name="openai/gpt-5-mini:online",
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openai_api_base="https://openrouter.ai/api/v1",
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)
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agent = create_agent(
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model=chat_model,
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tools=[get_user_resume, get_relevant_messages],
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system_prompt=prompts.BOT_SYSTEM_PROMPT,
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checkpointer=checkpointer,
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)
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message = await context.bot.send_message(update.effective_chat.id, "⏳ Обрабатываю твой запрос. Пожалуйста, подождите...")
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response = await agent.ainvoke(
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input={"messages": [{"role": "user", "content": f'user_id = {update.effective_user.id}\n{update.message.text}'}]},
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config={"configurable": {"thread_id": update.effective_user.id}},
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)
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await context.bot.editMessageText(response['messages'][-1].content, update.effective_chat.id, message.id)
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async def error_handler(update: object, context: ContextTypes.DEFAULT_TYPE) -> None:
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traceback.print_exception(context.error)
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await context.bot.send_message(chat_id=update.effective_chat.id, text="Произошла ошибка. Повтоите попытку позже.")
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async def handle_document(update: Update, context: ContextTypes.DEFAULT_TYPE):
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message = await context.bot.send_message(update.effective_chat.id, "⏳ Обрабатываю твой запрос. Пожалуйста, подождите...")
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if not update.message.document:
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await context.bot.send_message(chat_id=update.effective_chat.id, text="Не удалось прочитать информацию из файла! Попробуйте другой формат.")
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return
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buffer = io.BytesIO()
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file = await update.message.document.get_file()
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await file.download_to_memory(buffer)
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reader = PdfReader(buffer)
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resume = "\n".join(page.extract_text() for page in reader.pages)
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db_job_titles = await sync_to_async(list)(JobTitle.objects.values_list('title', flat=True))
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job_title_map = await sync_to_async(dict)(JobTitle.objects.values_list('title', 'id'))
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class Structure(BaseModel):
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job_titles: list[Literal[tuple(db_job_titles)]]
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min_salary_rub: int | None
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max_salary_rub: int | None
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openai_client = ChatOpenAI(model_name="gpt-5-mini", temperature=0, seed=42, top_p=1)
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structured_llm = openai_client.with_structured_output(Structure)
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prompt = f'{prompts.STRUCTURED_OUTPUT_PROMPT} {resume}'
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response = await structured_llm.ainvoke(prompt)
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customer = await Customer.objects.aget(telegram_id=update.effective_user.id)
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customer_cv, _ = await CustomerCV.objects.aupdate_or_create(customer=customer, defaults=dict(
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content=resume,
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min_salary_rub=response.min_salary_rub,
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max_salary_rub=response.max_salary_rub,
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))
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await customer_cv.job_titles.aset([job_title_map[job_title] for job_title in response.job_titles])
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await context.bot.editMessageText("Отлично! Запомнил Ваше резюме.", update.effective_chat.id, message.id)
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application = ApplicationBuilder().token(os.environ["BOT_TOKEN"]).concurrent_updates(True).build()
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application.add_handler(CommandHandler('start', start, block=False))
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application.add_handler(MessageHandler(filters.Text("Получить следующую вакансию"), next_vacancy, block=False))
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application.add_handler(MessageHandler(filters.TEXT & (~filters.COMMAND), prompt, block=False))
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application.add_handler(MessageHandler((filters.Document.ALL | filters.PHOTO) & (~filters.COMMAND), handle_document, block=False))
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application.add_error_handler(error_handler)
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