dify/api/tasks/annotation/add_annotation_to_index_task.py
Jyong 91ea6fe4ee
Fix/langchain document schema (#2539)
Co-authored-by: jyong <jyong@dify.ai>
2024-02-23 14:16:44 +08:00

61 lines
2.1 KiB
Python

import logging
import time
import click
from celery import shared_task
from core.rag.datasource.vdb.vector_factory import Vector
from core.rag.models.document import Document
from models.dataset import Dataset
from services.dataset_service import DatasetCollectionBindingService
@shared_task(queue='dataset')
def add_annotation_to_index_task(annotation_id: str, question: str, tenant_id: str, app_id: str,
collection_binding_id: str):
"""
Add annotation to index.
:param annotation_id: annotation id
:param question: question
:param tenant_id: tenant id
:param app_id: app id
:param collection_binding_id: embedding binding id
Usage: clean_dataset_task.delay(dataset_id, tenant_id, indexing_technique, index_struct)
"""
logging.info(click.style('Start build index for annotation: {}'.format(annotation_id), fg='green'))
start_at = time.perf_counter()
try:
dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding_by_id_and_type(
collection_binding_id,
'annotation'
)
dataset = Dataset(
id=app_id,
tenant_id=tenant_id,
indexing_technique='high_quality',
embedding_model_provider=dataset_collection_binding.provider_name,
embedding_model=dataset_collection_binding.model_name,
collection_binding_id=dataset_collection_binding.id
)
document = Document(
page_content=question,
metadata={
"annotation_id": annotation_id,
"app_id": app_id,
"doc_id": annotation_id
}
)
vector = Vector(dataset, attributes=['doc_id', 'annotation_id', 'app_id'])
vector.create([document], duplicate_check=True)
end_at = time.perf_counter()
logging.info(
click.style(
'Build index successful for annotation: {} latency: {}'.format(annotation_id, end_at - start_at),
fg='green'))
except Exception:
logging.exception("Build index for annotation failed")