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