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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
@shared_task(queue="dataset")
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
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