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62 lines
2.2 KiB
Python
62 lines
2.2 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.datasource.vdb.vector_factory import Vector
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from core.rag.models.document import Document
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from models.dataset import Dataset
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from services.dataset_service import DatasetCollectionBindingService
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@shared_task(queue='dataset')
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def update_annotation_to_index_task(annotation_id: str, question: str, tenant_id: str, app_id: str,
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collection_binding_id: str):
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"""
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Update annotation to index.
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:param annotation_id: annotation id
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:param question: question
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:param tenant_id: tenant id
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:param app_id: app id
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:param collection_binding_id: embedding binding id
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Usage: clean_dataset_task.delay(dataset_id, tenant_id, indexing_technique, index_struct)
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"""
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logging.info(click.style('Start update index for annotation: {}'.format(annotation_id), fg='green'))
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start_at = time.perf_counter()
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try:
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dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding_by_id_and_type(
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collection_binding_id,
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'annotation'
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)
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dataset = Dataset(
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id=app_id,
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tenant_id=tenant_id,
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indexing_technique='high_quality',
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embedding_model_provider=dataset_collection_binding.provider_name,
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embedding_model=dataset_collection_binding.model_name,
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collection_binding_id=dataset_collection_binding.id
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)
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document = Document(
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page_content=question,
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metadata={
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"annotation_id": annotation_id,
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"app_id": app_id,
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"doc_id": annotation_id
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}
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)
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vector = Vector(dataset, attributes=['doc_id', 'annotation_id', 'app_id'])
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vector.delete_by_metadata_field('annotation_id', annotation_id)
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vector.add_texts([document])
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end_at = time.perf_counter()
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logging.info(
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click.style(
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'Build index successful for annotation: {} latency: {}'.format(annotation_id, end_at - start_at),
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fg='green'))
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except Exception:
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logging.exception("Build index for annotation failed")
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