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refactor: use session factory instead of call db.session directly (#31198)
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
This commit is contained in:
wangxiaolei
GitHub
@ -6,11 +6,11 @@ import click
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from celery import shared_task
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from configs import dify_config
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from core.db.session_factory import session_factory
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from core.entities.document_task import DocumentTask
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from core.indexing_runner import DocumentIsPausedError, IndexingRunner
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from core.rag.pipeline.queue import TenantIsolatedTaskQueue
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from enums.cloud_plan import CloudPlan
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from extensions.ext_database import db
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from libs.datetime_utils import naive_utc_now
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from models.dataset import Dataset, Document
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from services.feature_service import FeatureService
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@ -46,66 +46,63 @@ def _document_indexing(dataset_id: str, document_ids: Sequence[str]):
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documents = []
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start_at = time.perf_counter()
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dataset = db.session.query(Dataset).where(Dataset.id == dataset_id).first()
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if not dataset:
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logger.info(click.style(f"Dataset is not found: {dataset_id}", fg="yellow"))
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db.session.close()
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return
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# check document limit
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features = FeatureService.get_features(dataset.tenant_id)
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try:
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if features.billing.enabled:
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vector_space = features.vector_space
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count = len(document_ids)
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batch_upload_limit = int(dify_config.BATCH_UPLOAD_LIMIT)
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if features.billing.subscription.plan == CloudPlan.SANDBOX and count > 1:
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raise ValueError("Your current plan does not support batch upload, please upgrade your plan.")
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if count > batch_upload_limit:
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raise ValueError(f"You have reached the batch upload limit of {batch_upload_limit}.")
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if 0 < vector_space.limit <= vector_space.size:
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raise ValueError(
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"Your total number of documents plus the number of uploads have over the limit of "
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"your subscription."
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with session_factory.create_session() as session:
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dataset = session.query(Dataset).where(Dataset.id == dataset_id).first()
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if not dataset:
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logger.info(click.style(f"Dataset is not found: {dataset_id}", fg="yellow"))
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return
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# check document limit
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features = FeatureService.get_features(dataset.tenant_id)
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try:
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if features.billing.enabled:
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vector_space = features.vector_space
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count = len(document_ids)
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batch_upload_limit = int(dify_config.BATCH_UPLOAD_LIMIT)
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if features.billing.subscription.plan == CloudPlan.SANDBOX and count > 1:
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raise ValueError("Your current plan does not support batch upload, please upgrade your plan.")
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if count > batch_upload_limit:
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raise ValueError(f"You have reached the batch upload limit of {batch_upload_limit}.")
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if 0 < vector_space.limit <= vector_space.size:
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raise ValueError(
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"Your total number of documents plus the number of uploads have over the limit of "
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"your subscription."
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)
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except Exception as e:
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for document_id in document_ids:
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document = (
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session.query(Document).where(Document.id == document_id, Document.dataset_id == dataset_id).first()
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)
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except Exception as e:
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if document:
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document.indexing_status = "error"
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document.error = str(e)
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document.stopped_at = naive_utc_now()
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session.add(document)
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session.commit()
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return
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for document_id in document_ids:
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logger.info(click.style(f"Start process document: {document_id}", fg="green"))
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document = (
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db.session.query(Document).where(Document.id == document_id, Document.dataset_id == dataset_id).first()
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session.query(Document).where(Document.id == document_id, Document.dataset_id == dataset_id).first()
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)
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if document:
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document.indexing_status = "error"
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document.error = str(e)
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document.stopped_at = naive_utc_now()
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db.session.add(document)
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db.session.commit()
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db.session.close()
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return
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document.indexing_status = "parsing"
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document.processing_started_at = naive_utc_now()
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documents.append(document)
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session.add(document)
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session.commit()
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for document_id in document_ids:
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logger.info(click.style(f"Start process document: {document_id}", fg="green"))
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document = (
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db.session.query(Document).where(Document.id == document_id, Document.dataset_id == dataset_id).first()
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)
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if document:
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document.indexing_status = "parsing"
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document.processing_started_at = naive_utc_now()
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documents.append(document)
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db.session.add(document)
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db.session.commit()
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try:
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indexing_runner = IndexingRunner()
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indexing_runner.run(documents)
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end_at = time.perf_counter()
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logger.info(click.style(f"Processed dataset: {dataset_id} latency: {end_at - start_at}", fg="green"))
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except DocumentIsPausedError as ex:
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logger.info(click.style(str(ex), fg="yellow"))
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except Exception:
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logger.exception("Document indexing task failed, dataset_id: %s", dataset_id)
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finally:
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db.session.close()
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try:
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indexing_runner = IndexingRunner()
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indexing_runner.run(documents)
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end_at = time.perf_counter()
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logger.info(click.style(f"Processed dataset: {dataset_id} latency: {end_at - start_at}", fg="green"))
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except DocumentIsPausedError as ex:
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logger.info(click.style(str(ex), fg="yellow"))
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except Exception:
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logger.exception("Document indexing task failed, dataset_id: %s", dataset_id)
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def _document_indexing_with_tenant_queue(
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