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- import datetime
- import logging
- import time
- import click
- from celery import shared_task
- from werkzeug.exceptions import NotFound
- from core.rag.datasource.vdb.vector_factory import Vector
- from core.rag.models.document import Document
- from extensions.ext_database import db
- from extensions.ext_redis import redis_client
- from models.dataset import Dataset
- from models.model import App, AppAnnotationSetting, MessageAnnotation
- from services.dataset_service import DatasetCollectionBindingService
- @shared_task(queue='dataset')
- def enable_annotation_reply_task(job_id: str, app_id: str, user_id: str, tenant_id: str, score_threshold: float,
- embedding_provider_name: str, embedding_model_name: str):
- """
- Async enable annotation reply task
- """
- logging.info(click.style('Start add app annotation to index: {}'.format(app_id), fg='green'))
- start_at = time.perf_counter()
- # get app info
- app = db.session.query(App).filter(
- App.id == app_id,
- App.tenant_id == tenant_id,
- App.status == 'normal'
- ).first()
- if not app:
- raise NotFound("App not found")
- annotations = db.session.query(MessageAnnotation).filter(MessageAnnotation.app_id == app_id).all()
- enable_app_annotation_key = 'enable_app_annotation_{}'.format(str(app_id))
- enable_app_annotation_job_key = 'enable_app_annotation_job_{}'.format(str(job_id))
- try:
- documents = []
- dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding(
- embedding_provider_name,
- embedding_model_name,
- 'annotation'
- )
- annotation_setting = db.session.query(AppAnnotationSetting).filter(
- AppAnnotationSetting.app_id == app_id).first()
- if annotation_setting:
- annotation_setting.score_threshold = score_threshold
- annotation_setting.collection_binding_id = dataset_collection_binding.id
- annotation_setting.updated_user_id = user_id
- annotation_setting.updated_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None)
- db.session.add(annotation_setting)
- else:
- new_app_annotation_setting = AppAnnotationSetting(
- app_id=app_id,
- score_threshold=score_threshold,
- collection_binding_id=dataset_collection_binding.id,
- created_user_id=user_id,
- updated_user_id=user_id
- )
- db.session.add(new_app_annotation_setting)
- dataset = Dataset(
- id=app_id,
- tenant_id=tenant_id,
- indexing_technique='high_quality',
- embedding_model_provider=embedding_provider_name,
- embedding_model=embedding_model_name,
- collection_binding_id=dataset_collection_binding.id
- )
- if annotations:
- for annotation in annotations:
- document = Document(
- page_content=annotation.question,
- metadata={
- "annotation_id": annotation.id,
- "app_id": app_id,
- "doc_id": annotation.id
- }
- )
- documents.append(document)
- vector = Vector(dataset, attributes=['doc_id', 'annotation_id', 'app_id'])
- try:
- vector.delete_by_metadata_field('app_id', app_id)
- except Exception as e:
- logging.info(
- click.style('Delete annotation index error: {}'.format(str(e)),
- fg='red'))
- vector.create(documents)
- db.session.commit()
- redis_client.setex(enable_app_annotation_job_key, 600, 'completed')
- end_at = time.perf_counter()
- logging.info(
- click.style('App annotations added to index: {} latency: {}'.format(app_id, end_at - start_at),
- fg='green'))
- except Exception as e:
- logging.exception("Annotation batch created index failed:{}".format(str(e)))
- redis_client.setex(enable_app_annotation_job_key, 600, 'error')
- enable_app_annotation_error_key = 'enable_app_annotation_error_{}'.format(str(job_id))
- redis_client.setex(enable_app_annotation_error_key, 600, str(e))
- db.session.rollback()
- finally:
- redis_client.delete(enable_app_annotation_key)
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