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116 lines
4.4 KiB
Python
116 lines
4.4 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 # type: ignore
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from core.rag.index_processor.constant.index_type import IndexType
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from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
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from core.rag.models.document import ChildDocument, Document
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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, 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 enable_segments_to_index_task(segment_ids: list, dataset_id: str, document_id: str):
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"""
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Async enable segments to index
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:param segment_ids: list of segment ids
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:param dataset_id: dataset id
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:param document_id: document id
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Usage: enable_segments_to_index_task.delay(segment_ids, 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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if not dataset:
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logging.info(click.style("Dataset {} not found, pass.".format(dataset_id), fg="cyan"))
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return
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dataset_document = db.session.query(DatasetDocument).filter(DatasetDocument.id == document_id).first()
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if not dataset_document:
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logging.info(click.style("Document {} not found, pass.".format(document_id), fg="cyan"))
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db.session.close()
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return
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if not dataset_document.enabled or dataset_document.archived or dataset_document.indexing_status != "completed":
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logging.info(click.style("Document {} status is invalid, pass.".format(document_id), fg="cyan"))
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db.session.close()
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return
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# sync index processor
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index_processor = IndexProcessorFactory(dataset_document.doc_form).init_index_processor()
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segments = (
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db.session.query(DocumentSegment)
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.filter(
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DocumentSegment.id.in_(segment_ids),
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DocumentSegment.dataset_id == dataset_id,
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DocumentSegment.document_id == document_id,
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)
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.all()
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)
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if not segments:
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logging.info(click.style("Segments not found: {}".format(segment_ids), fg="cyan"))
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db.session.close()
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return
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try:
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documents = []
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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": document_id,
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"dataset_id": dataset_id,
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},
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)
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if dataset_document.doc_form == IndexType.PARENT_CHILD_INDEX:
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child_chunks = segment.get_child_chunks()
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if child_chunks:
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child_documents = []
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for child_chunk in child_chunks:
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child_document = ChildDocument(
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page_content=child_chunk.content,
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metadata={
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"doc_id": child_chunk.index_node_id,
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"doc_hash": child_chunk.index_node_hash,
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"document_id": document_id,
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"dataset_id": dataset_id,
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},
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)
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child_documents.append(child_document)
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document.children = child_documents
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documents.append(document)
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# save vector index
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index_processor.load(dataset, documents)
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end_at = time.perf_counter()
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logging.info(click.style("Segments enabled to index latency: {}".format(end_at - start_at), fg="green"))
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except Exception as e:
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logging.exception("enable segments to index failed")
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# update segment error msg
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db.session.query(DocumentSegment).filter(
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DocumentSegment.id.in_(segment_ids),
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DocumentSegment.dataset_id == dataset_id,
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DocumentSegment.document_id == document_id,
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).update(
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{
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"error": str(e),
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"status": "error",
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"disabled_at": datetime.datetime.now(datetime.UTC).replace(tzinfo=None),
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"enabled": False,
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}
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)
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db.session.commit()
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finally:
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for segment in segments:
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indexing_cache_key = "segment_{}_indexing".format(segment.id)
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redis_client.delete(indexing_cache_key)
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db.session.close()
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