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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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| 
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| import click
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| from celery import shared_task  # type: ignore
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| 
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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 extensions.ext_database import db
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| from models.dataset import Dataset
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| from services.dataset_service import DatasetCollectionBindingService
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| 
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| 
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| @shared_task(queue="dataset")
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| def update_annotation_to_index_task(
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|     annotation_id: str, question: str, tenant_id: str, app_id: str, collection_binding_id: str
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| ):
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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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| 
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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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| 
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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, "annotation"
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|         )
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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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| 
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|         document = Document(
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|             page_content=question, metadata={"annotation_id": annotation_id, "app_id": app_id, "doc_id": annotation_id}
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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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|             )
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|         )
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|     except Exception:
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|         logging.exception("Build index for annotation failed")
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|     finally:
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|         db.session.close()
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