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89 lines
3.4 KiB
Python
89 lines
3.4 KiB
Python
import datetime
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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 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 extensions.ext_redis import redis_client
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from models.dataset import Dataset, Document, DocumentSegment
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from services.feature_service import FeatureService
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@shared_task(queue="dataset")
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def sync_website_document_indexing_task(dataset_id: str, document_id: str):
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"""
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Async process document
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:param dataset_id:
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:param document_id:
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Usage: sunc_website_document_indexing_task.delay(dataset_id, document_id)
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"""
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start_at = time.perf_counter()
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dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first()
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sync_indexing_cache_key = "document_{}_is_sync".format(document_id)
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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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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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document = (
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db.session.query(Document).filter(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 = datetime.datetime.utcnow()
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db.session.add(document)
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db.session.commit()
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redis_client.delete(sync_indexing_cache_key)
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return
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logging.info(click.style("Start sync website document: {}".format(document_id), fg="green"))
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document = db.session.query(Document).filter(Document.id == document_id, Document.dataset_id == dataset_id).first()
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try:
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if document:
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# clean old data
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index_processor = IndexProcessorFactory(document.doc_form).init_index_processor()
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segments = db.session.query(DocumentSegment).filter(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)
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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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document.indexing_status = "parsing"
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document.processing_started_at = datetime.datetime.utcnow()
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db.session.add(document)
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db.session.commit()
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indexing_runner = IndexingRunner()
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indexing_runner.run([document])
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redis_client.delete(sync_indexing_cache_key)
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except Exception as ex:
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document.indexing_status = "error"
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document.error = str(ex)
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document.stopped_at = datetime.datetime.utcnow()
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db.session.add(document)
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db.session.commit()
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logging.info(click.style(str(ex), fg="yellow"))
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redis_client.delete(sync_indexing_cache_key)
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pass
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end_at = time.perf_counter()
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logging.info(click.style("Sync document: {} latency: {}".format(document_id, end_at - start_at), fg="green"))
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