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https://github.com/magnum-opus-nn-cp/backend.git
synced 2024-12-04 20:53:44 +03:00
updated score calc
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@ -313,9 +313,9 @@
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# https://docs.celeryq.dev/en/stable/userguide/configuration.html#std:setting-result_serializer
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CELERY_RESULT_SERIALIZER = "json"
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# https://docs.celeryq.dev/en/stable/userguide/configuration.html#task-time-limit
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CELERY_TASK_TIME_LIMIT = 5 * 60
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CELERY_TASK_TIME_LIMIT = 10 * 60
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# https://docs.celeryq.dev/en/stable/userguide/configuration.html#task-soft-time-limit
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CELERY_TASK_SOFT_TIME_LIMIT = 60
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CELERY_TASK_SOFT_TIME_LIMIT = 5 * 60
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# https://docs.celeryq.dev/en/stable/userguide/configuration.html#beat-scheduler
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CELERY_BEAT_SCHEDULER = "django_celery_beat.schedulers:DatabaseScheduler"
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# https://docs.celeryq.dev/en/stable/userguide/configuration.html#worker-send-task-events
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@ -2,8 +2,8 @@
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from django.db.models.signals import post_save
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from django.dispatch import receiver
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from press_release_nl.processor.models import Text
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from press_release_nl.processor.tasks import load_text, load_text_sum
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from press_release_nl.processor.models import Entry, Text
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from press_release_nl.processor.tasks import load_text, load_text_sum, run_ml
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@receiver(post_save, sender=Text)
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@ -21,5 +21,11 @@ def run_text_process(sender, instance: Text, created, **kwargs):
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Text.objects.create(entry=instance.entry, text=text)
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instance.delete()
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return
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load_text.apply_async(kwargs={"pk": instance.pk}, countdown=2)
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load_text.apply_async(kwargs={"pk": instance.pk}, countdown=1)
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load_text_sum.apply_async(kwargs={"pk": instance.pk}, countdown=4)
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@receiver(post_save, sender=Entry)
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def run_entry_ml(sender, instance: Entry, created, **kwargs):
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if created:
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run_ml.apply_async(kwargs={"pk": instance.pk}, countdown=4)
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@ -4,9 +4,9 @@
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import textract
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from celery import shared_task
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from press_release_nl.processor.models import Text
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from press_release_nl.processor.models import Entry, Text
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ML_HOST = "https://2b6a-176-59-106-6.ngrok-free.app/"
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ML_HOST = "http://192.168.107.95:8000/"
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ML_SUM_HOST = "https://dev.akarpov.ru/"
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@ -18,24 +18,51 @@ def load_text(pk: int):
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text.file.path, encoding="unicode_escape", language="rus"
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).decode()
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text.save()
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re = requests.post(ML_HOST + "predict", json={"data": text.text})
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if re.status_code != 200:
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raise ValueError(re.text)
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text.score = re.json()
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text.save()
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if not text.text:
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text.delete()
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return
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@shared_task
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def run_ml(pk: int, f=True):
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try:
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entry = Entry.objects.get(pk=pk)
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except Entry.DoesNotExist:
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return
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if entry.texts.filter(text__isnull=True).exists():
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sleep(10)
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for text in entry.texts.all():
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re_bert = requests.post(ML_HOST + "bert/process", json={"data": text.text})
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re_tf = requests.post(ML_HOST + "tfidf/process", json={"data": text.text})
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if re_bert.status_code != 200:
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print(re_bert.status_code, "bert")
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continue
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if re_tf.status_code != 200:
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print(re_tf.status_code, "tf-idf")
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continue
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text.refresh_from_db()
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text.score = {
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"bert": re_bert.json(),
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"f": re_tf.json(),
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}
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text.save(update_fields=["score"])
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return pk
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@shared_task
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def load_text_sum(pk: int):
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try:
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text = Text.objects.get(pk=pk)
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except Text.DoesNotExist:
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return
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if not text.text:
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sleep(3)
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text.refresh_from_db()
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re = requests.post(ML_SUM_HOST, json={"body": text.text})
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if re.status_code != 200:
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raise ValueError(re.text)
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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()
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text.save(update_fields=["summery"])
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return pk
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