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										 |  |  | import logging | 
					
						
							|  |  |  | 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.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 | 
					
						
							|  |  |  | from services.dataset_service import DatasetCollectionBindingService | 
					
						
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										 |  |  | @shared_task(queue="dataset") | 
					
						
							|  |  |  | def add_annotation_to_index_task( | 
					
						
							|  |  |  |     annotation_id: str, question: str, tenant_id: str, app_id: str, collection_binding_id: str | 
					
						
							|  |  |  | ): | 
					
						
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										 |  |  |     """
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							|  |  |  |     Add annotation to index. | 
					
						
							|  |  |  |     :param annotation_id: annotation id | 
					
						
							|  |  |  |     :param question: question | 
					
						
							|  |  |  |     :param tenant_id: tenant id | 
					
						
							|  |  |  |     :param app_id: app id | 
					
						
							|  |  |  |     :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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										 |  |  |     logging.info(click.style("Start build index for annotation: {}".format(annotation_id), fg="green")) | 
					
						
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										 |  |  |     start_at = time.perf_counter() | 
					
						
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							|  |  |  |     try: | 
					
						
							|  |  |  |         dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding_by_id_and_type( | 
					
						
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										 |  |  |             collection_binding_id, "annotation" | 
					
						
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										 |  |  |         ) | 
					
						
							|  |  |  |         dataset = Dataset( | 
					
						
							|  |  |  |             id=app_id, | 
					
						
							|  |  |  |             tenant_id=tenant_id, | 
					
						
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										 |  |  |             indexing_technique="high_quality", | 
					
						
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										 |  |  |             embedding_model_provider=dataset_collection_binding.provider_name, | 
					
						
							|  |  |  |             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, 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.create([document], duplicate_check=True) | 
					
						
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										 |  |  |         end_at = time.perf_counter() | 
					
						
							|  |  |  |         logging.info( | 
					
						
							|  |  |  |             click.style( | 
					
						
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										 |  |  |                 "Build index successful for annotation: {} latency: {}".format(annotation_id, end_at - start_at), | 
					
						
							|  |  |  |                 fg="green", | 
					
						
							|  |  |  |             ) | 
					
						
							|  |  |  |         ) | 
					
						
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										 |  |  |     except Exception: | 
					
						
							|  |  |  |         logging.exception("Build index for annotation failed") |