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document_indexing_task.py 3.1KB

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  1. import datetime
  2. import logging
  3. import time
  4. import click
  5. from celery import shared_task # type: ignore
  6. from configs import dify_config
  7. from core.indexing_runner import DocumentIsPausedError, IndexingRunner
  8. from extensions.ext_database import db
  9. from models.dataset import Dataset, Document
  10. from services.feature_service import FeatureService
  11. @shared_task(queue="dataset")
  12. def document_indexing_task(dataset_id: str, document_ids: list):
  13. """
  14. Async process document
  15. :param dataset_id:
  16. :param document_ids:
  17. Usage: document_indexing_task.delay(dataset_id, document_ids)
  18. """
  19. documents = []
  20. start_at = time.perf_counter()
  21. dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first()
  22. if not dataset:
  23. logging.info(click.style("Dataset is not found: {}".format(dataset_id), fg="yellow"))
  24. return
  25. # check document limit
  26. features = FeatureService.get_features(dataset.tenant_id)
  27. try:
  28. if features.billing.enabled:
  29. vector_space = features.vector_space
  30. count = len(document_ids)
  31. batch_upload_limit = int(dify_config.BATCH_UPLOAD_LIMIT)
  32. if features.billing.subscription.plan == "sandbox" and count > 1:
  33. raise ValueError("Your current plan does not support batch upload, please upgrade your plan.")
  34. if count > batch_upload_limit:
  35. raise ValueError(f"You have reached the batch upload limit of {batch_upload_limit}.")
  36. if 0 < vector_space.limit <= vector_space.size:
  37. raise ValueError(
  38. "Your total number of documents plus the number of uploads have over the limit of "
  39. "your subscription."
  40. )
  41. except Exception as e:
  42. for document_id in document_ids:
  43. document = (
  44. db.session.query(Document).filter(Document.id == document_id, Document.dataset_id == dataset_id).first()
  45. )
  46. if document:
  47. document.indexing_status = "error"
  48. document.error = str(e)
  49. document.stopped_at = datetime.datetime.now(datetime.UTC).replace(tzinfo=None)
  50. db.session.add(document)
  51. db.session.commit()
  52. return
  53. for document_id in document_ids:
  54. logging.info(click.style("Start process document: {}".format(document_id), fg="green"))
  55. document = (
  56. db.session.query(Document).filter(Document.id == document_id, Document.dataset_id == dataset_id).first()
  57. )
  58. if document:
  59. document.indexing_status = "parsing"
  60. document.processing_started_at = datetime.datetime.now(datetime.UTC).replace(tzinfo=None)
  61. documents.append(document)
  62. db.session.add(document)
  63. db.session.commit()
  64. try:
  65. indexing_runner = IndexingRunner()
  66. indexing_runner.run(documents)
  67. end_at = time.perf_counter()
  68. logging.info(click.style("Processed dataset: {} latency: {}".format(dataset_id, end_at - start_at), fg="green"))
  69. except DocumentIsPausedError as ex:
  70. logging.info(click.style(str(ex), fg="yellow"))
  71. except Exception:
  72. pass