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			79 lines
		
	
	
		
			2.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			79 lines
		
	
	
		
			2.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import datetime
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| 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
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| 
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| from configs import dify_config
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| from core.indexing_runner import DocumentIsPausedException, IndexingRunner
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| from extensions.ext_database import db
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| from models.dataset import Dataset, Document
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| from services.feature_service import FeatureService
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| 
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| 
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| @shared_task(queue='dataset')
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| def document_indexing_task(dataset_id: str, document_ids: list):
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|     """
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|     Async process document
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|     :param dataset_id:
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|     :param document_ids:
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| 
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|     Usage: document_indexing_task.delay(dataset_id, document_id)
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|     """
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|     documents = []
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|     start_at = time.perf_counter()
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| 
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|     dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first()
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| 
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|     # check document limit
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|     features = FeatureService.get_features(dataset.tenant_id)
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|     try:
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|         if features.billing.enabled:
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|             vector_space = features.vector_space
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|             count = len(document_ids)
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|             batch_upload_limit = int(dify_config.BATCH_UPLOAD_LIMIT)
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|             if count > batch_upload_limit:
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|                 raise ValueError(f"You have reached the batch upload limit of {batch_upload_limit}.")
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|             if 0 < vector_space.limit <= vector_space.size:
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|                 raise ValueError("Your total number of documents plus the number of uploads have over the limit of "
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|                                  "your subscription.")
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|     except Exception as e:
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|         for document_id in document_ids:
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|             document = db.session.query(Document).filter(
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|                 Document.id == document_id,
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|                 Document.dataset_id == dataset_id
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|             ).first()
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|             if document:
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|                 document.indexing_status = 'error'
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|                 document.error = str(e)
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|                 document.stopped_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None)
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|                 db.session.add(document)
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|         db.session.commit()
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|         return
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| 
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|     for document_id in document_ids:
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|         logging.info(click.style('Start process document: {}'.format(document_id), fg='green'))
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| 
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|         document = db.session.query(Document).filter(
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|             Document.id == document_id,
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|             Document.dataset_id == dataset_id
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|         ).first()
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| 
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|         if document:
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|             document.indexing_status = 'parsing'
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|             document.processing_started_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None)
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|             documents.append(document)
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|             db.session.add(document)
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|     db.session.commit()
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| 
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|     try:
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|         indexing_runner = IndexingRunner()
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|         indexing_runner.run(documents)
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|         end_at = time.perf_counter()
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|         logging.info(click.style('Processed dataset: {} latency: {}'.format(dataset_id, end_at - start_at), fg='green'))
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|     except DocumentIsPausedException as ex:
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|         logging.info(click.style(str(ex), fg='yellow'))
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|     except Exception:
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|         pass
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