mirror of
https://github.com/langgenius/dify.git
synced 2025-11-04 12:53:38 +00:00
89 lines
3.4 KiB
Python
89 lines
3.4 KiB
Python
import datetime
|
|
import logging
|
|
import time
|
|
|
|
import click
|
|
from celery import shared_task
|
|
|
|
from core.indexing_runner import IndexingRunner
|
|
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
|
|
from extensions.ext_database import db
|
|
from extensions.ext_redis import redis_client
|
|
from models.dataset import Dataset, Document, DocumentSegment
|
|
from services.feature_service import FeatureService
|
|
|
|
|
|
@shared_task(queue="dataset")
|
|
def sync_website_document_indexing_task(dataset_id: str, document_id: str):
|
|
"""
|
|
Async process document
|
|
:param dataset_id:
|
|
:param document_id:
|
|
|
|
Usage: sync_website_document_indexing_task.delay(dataset_id, document_id)
|
|
"""
|
|
start_at = time.perf_counter()
|
|
|
|
dataset = db.session.query(Dataset).filter(Dataset.id == dataset_id).first()
|
|
|
|
sync_indexing_cache_key = "document_{}_is_sync".format(document_id)
|
|
# check document limit
|
|
features = FeatureService.get_features(dataset.tenant_id)
|
|
try:
|
|
if features.billing.enabled:
|
|
vector_space = features.vector_space
|
|
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:
|
|
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.utcnow()
|
|
db.session.add(document)
|
|
db.session.commit()
|
|
redis_client.delete(sync_indexing_cache_key)
|
|
return
|
|
|
|
logging.info(click.style("Start sync website document: {}".format(document_id), fg="green"))
|
|
document = db.session.query(Document).filter(Document.id == document_id, Document.dataset_id == dataset_id).first()
|
|
try:
|
|
if document:
|
|
# clean old data
|
|
index_processor = IndexProcessorFactory(document.doc_form).init_index_processor()
|
|
|
|
segments = db.session.query(DocumentSegment).filter(DocumentSegment.document_id == document_id).all()
|
|
if segments:
|
|
index_node_ids = [segment.index_node_id for segment in segments]
|
|
# delete from vector index
|
|
index_processor.clean(dataset, index_node_ids)
|
|
|
|
for segment in segments:
|
|
db.session.delete(segment)
|
|
db.session.commit()
|
|
|
|
document.indexing_status = "parsing"
|
|
document.processing_started_at = datetime.datetime.utcnow()
|
|
db.session.add(document)
|
|
db.session.commit()
|
|
|
|
indexing_runner = IndexingRunner()
|
|
indexing_runner.run([document])
|
|
redis_client.delete(sync_indexing_cache_key)
|
|
except Exception as ex:
|
|
document.indexing_status = "error"
|
|
document.error = str(ex)
|
|
document.stopped_at = datetime.datetime.utcnow()
|
|
db.session.add(document)
|
|
db.session.commit()
|
|
logging.info(click.style(str(ex), fg="yellow"))
|
|
redis_client.delete(sync_indexing_cache_key)
|
|
pass
|
|
end_at = time.perf_counter()
|
|
logging.info(click.style("Sync document: {} latency: {}".format(document_id, end_at - start_at), fg="green"))
|