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6c4e6bf1d6
Co-authored-by: jyong <jyong@dify.ai>
73 lines
2.8 KiB
Python
73 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.rag.index_processor.index_processor_factory import IndexProcessorFactory
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from core.rag.models.document import Document
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from extensions.ext_database import db
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from models.dataset import Dataset, DocumentSegment
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from models.dataset import Document as DatasetDocument
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@shared_task(queue='dataset')
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def deal_dataset_vector_index_task(dataset_id: str, action: str):
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"""
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Async deal dataset from index
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:param dataset_id: dataset_id
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:param action: action
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Usage: deal_dataset_vector_index_task.delay(dataset_id, action)
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"""
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logging.info(click.style('Start deal dataset vector index: {}'.format(dataset_id), fg='green'))
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start_at = time.perf_counter()
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try:
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dataset = Dataset.query.filter_by(
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id=dataset_id
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).first()
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if not dataset:
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raise Exception('Dataset not found')
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index_type = dataset.doc_form
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index_processor = IndexProcessorFactory(index_type).init_index_processor()
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if action == "remove":
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index_processor.clean(dataset, None, with_keywords=False)
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elif action == "add":
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dataset_documents = db.session.query(DatasetDocument).filter(
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DatasetDocument.dataset_id == dataset_id,
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DatasetDocument.indexing_status == 'completed',
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DatasetDocument.enabled == True,
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DatasetDocument.archived == False,
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).all()
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if dataset_documents:
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documents = []
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for dataset_document in dataset_documents:
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# delete from vector index
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segments = db.session.query(DocumentSegment).filter(
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DocumentSegment.document_id == dataset_document.id,
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DocumentSegment.enabled == True
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) .order_by(DocumentSegment.position.asc()).all()
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for segment in segments:
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document = Document(
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page_content=segment.content,
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metadata={
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"doc_id": segment.index_node_id,
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"doc_hash": segment.index_node_hash,
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"document_id": segment.document_id,
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"dataset_id": segment.dataset_id,
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}
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)
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documents.append(document)
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# save vector index
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index_processor.load(dataset, documents, with_keywords=False)
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end_at = time.perf_counter()
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logging.info(
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click.style('Deal dataset vector index: {} latency: {}'.format(dataset_id, end_at - start_at), fg='green'))
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except Exception:
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logging.exception("Deal dataset vector index failed")
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