37 lines
1.5 KiB
Python
37 lines
1.5 KiB
Python
from django.core.management import BaseCommand
|
|
from vacancies.main.vector_store import search_similarities
|
|
from vacancies.main.models import CustomerCV, RecommendedVacancy
|
|
from vacancies.main.bot import application
|
|
from vacancies.main.features_extractor import extract_vacancy_features
|
|
from telegram import InlineKeyboardButton, InlineKeyboardMarkup
|
|
from qdrant_client.models import Filter, HasIdCondition
|
|
|
|
|
|
class Command(BaseCommand):
|
|
help = "Generates new recommended vacancies"
|
|
|
|
def handle(self, *args, **options):
|
|
customer_cvs = CustomerCV.objects.all()
|
|
|
|
for customer_cv in customer_cvs:
|
|
features = extract_vacancy_features(customer_cv.content)
|
|
recommended_vacancy_ids = RecommendedVacancy.objects.filter(
|
|
customer=customer_cv.customer,
|
|
).values_list('vacancy_id', flat=True)
|
|
|
|
query_filter = Filter(must_not=[HasIdCondition(has_id=recommended_vacancy_ids)])
|
|
search_result_id = search_similarities(features.model_dump(), query_filter)
|
|
|
|
recommendation = RecommendedVacancy.objects.create(
|
|
customer=customer_cv.customer,
|
|
vacancy_id=search_result_id,
|
|
)
|
|
|
|
application.bot.send_message(
|
|
chat_id=recommendation.customer.chat_id,
|
|
text=recommendation.vacancy.content,
|
|
reply_markup=InlineKeyboardMarkup([[
|
|
InlineKeyboardButton("Откликнуться", url=recommendation.vacancy.link),
|
|
]]),
|
|
)
|