dify / api /tasks /clean_dataset_task.py
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import logging
import time
import click
from celery import shared_task
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from extensions.ext_database import db
from models.dataset import (
AppDatasetJoin,
Dataset,
DatasetProcessRule,
DatasetQuery,
Document,
DocumentSegment,
)
# Add import statement for ValueError
@shared_task(queue='dataset')
def clean_dataset_task(dataset_id: str, tenant_id: str, indexing_technique: str,
index_struct: str, collection_binding_id: str, doc_form: str):
"""
Clean dataset when dataset deleted.
:param dataset_id: dataset id
:param tenant_id: tenant id
:param indexing_technique: indexing technique
:param index_struct: index struct dict
:param collection_binding_id: collection binding id
:param doc_form: dataset form
Usage: clean_dataset_task.delay(dataset_id, tenant_id, indexing_technique, index_struct)
"""
logging.info(click.style('Start clean dataset when dataset deleted: {}'.format(dataset_id), fg='green'))
start_at = time.perf_counter()
try:
dataset = Dataset(
id=dataset_id,
tenant_id=tenant_id,
indexing_technique=indexing_technique,
index_struct=index_struct,
collection_binding_id=collection_binding_id,
)
documents = db.session.query(Document).filter(Document.dataset_id == dataset_id).all()
segments = db.session.query(DocumentSegment).filter(DocumentSegment.dataset_id == dataset_id).all()
if documents is None or len(documents) == 0:
logging.info(click.style('No documents found for dataset: {}'.format(dataset_id), fg='green'))
else:
logging.info(click.style('Cleaning documents for dataset: {}'.format(dataset_id), fg='green'))
# Specify the index type before initializing the index processor
if doc_form is None:
raise ValueError("Index type must be specified.")
index_processor = IndexProcessorFactory(doc_form).init_index_processor()
index_processor.clean(dataset, None)
for document in documents:
db.session.delete(document)
for segment in segments:
db.session.delete(segment)
db.session.query(DatasetProcessRule).filter(DatasetProcessRule.dataset_id == dataset_id).delete()
db.session.query(DatasetQuery).filter(DatasetQuery.dataset_id == dataset_id).delete()
db.session.query(AppDatasetJoin).filter(AppDatasetJoin.dataset_id == dataset_id).delete()
db.session.commit()
end_at = time.perf_counter()
logging.info(
click.style('Cleaned dataset when dataset deleted: {} latency: {}'.format(dataset_id, end_at - start_at), fg='green'))
except Exception:
logging.exception("Cleaned dataset when dataset deleted failed")