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81 lines
2.8 KiB
Python
81 lines
2.8 KiB
Python
import logging
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import time
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import click
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from celery import shared_task
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from core.indexing_runner import DocumentIsPausedError, IndexingRunner
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from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
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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, DocumentSegment
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logger = logging.getLogger(__name__)
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@shared_task(queue="dataset")
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def document_indexing_update_task(dataset_id: str, document_id: str):
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"""
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Async update document
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:param dataset_id:
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:param document_id:
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Usage: document_indexing_update_task.delay(dataset_id, document_id)
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"""
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logger.info(click.style(f"Start update document: {document_id}", fg="green"))
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start_at = time.perf_counter()
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document = db.session.query(Document).where(Document.id == document_id, Document.dataset_id == dataset_id).first()
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if not document:
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logger.info(click.style(f"Document not found: {document_id}", fg="red"))
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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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db.session.commit()
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# delete all document segment and index
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try:
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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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raise Exception("Dataset not found")
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index_type = document.doc_form
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index_processor = IndexProcessorFactory(index_type).init_index_processor()
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segments = db.session.query(DocumentSegment).where(DocumentSegment.document_id == document_id).all()
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if segments:
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index_node_ids = [segment.index_node_id for segment in segments]
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# delete from vector index
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index_processor.clean(dataset, index_node_ids, with_keywords=True, delete_child_chunks=True)
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for segment in segments:
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db.session.delete(segment)
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db.session.commit()
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end_at = time.perf_counter()
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logger.info(
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click.style(
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"Cleaned document when document update data source or process rule: {} latency: {}".format(
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document_id, end_at - start_at
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),
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fg="green",
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)
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)
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except Exception:
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logger.exception("Cleaned document when document update data source or process rule failed")
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try:
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indexing_runner = IndexingRunner()
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indexing_runner.run([document])
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end_at = time.perf_counter()
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logger.info(click.style(f"update document: {document.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_update_task failed, document_id: %s", document_id)
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finally:
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db.session.close()
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