backend/press_release_nl/processor/tasks.py

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from time import sleep
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import requests
import textract
from celery import shared_task
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from press_release_nl.processor.models import Entry, Text
from press_release_nl.processor.services import create_highlighted_document
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from press_release_nl.utils.celery import get_scheduled_tasks_name
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ML_HOST = "http://192.168.107.95:8000/"
# ML_HOST = "https://dev2.akarpov.ru/"
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ML_SUM_HOST = "https://dev.akarpov.ru/"
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@shared_task
def load_text(pk: int):
text = Text.objects.get(pk=pk)
if not text.text:
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text.text = textract.process(
text.file.path, encoding="unicode_escape", language="rus"
).decode()
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text.save()
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if not text.text:
text.delete()
return
@shared_task
def run_ml(pk: int, f=True):
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if get_scheduled_tasks_name().count("press_release_nl.processor.tasks.run_ml") >= 2:
run_ml.apply_async(kwargs={"pk": pk}, countdown=10)
return
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try:
entry = Entry.objects.get(pk=pk)
except Entry.DoesNotExist:
return
if entry.texts.filter(text__isnull=True).exists():
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run_ml.apply_async(kwargs={"pk": pk}, countdown=10)
return
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for text in entry.texts.all():
re_bert = requests.post(ML_HOST + "bert/process", json={"data": text.text})
re_tf = requests.post(ML_HOST + "tfidf/process", json={"data": text.text})
if re_bert.status_code != 200:
print(re_bert.status_code, "bert")
continue
if re_tf.status_code != 200:
print(re_tf.status_code, "tf-idf")
continue
text.refresh_from_db()
text.score = {
"bert": re_bert.json(),
"f": re_tf.json(),
}
text.save(update_fields=["score"])
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return pk
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@shared_task
def load_text_sum(pk: int):
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try:
text = Text.objects.get(pk=pk)
except Text.DoesNotExist:
return
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if not text.text:
sleep(3)
text.refresh_from_db()
re = requests.post(ML_SUM_HOST, json={"body": text.text})
if re.status_code != 200:
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raise ValueError(re.status_code)
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data = re.json()
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text.refresh_from_db()
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text.summery = str(data)
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text.save(update_fields=["summery"])
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return pk
@shared_task
def run_create_highlighted_document(pk: int, var: str):
text = Text.objects.get(pk=pk)
file_path = create_highlighted_document(pk, var)
text.description[var]["file"] = file_path
text.save()
return pk