import datetime import logging import time import click from celery import shared_task from langchain.schema import Document from werkzeug.exceptions import NotFound from core.rag.datasource.vdb.vector_factory import Vector 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.utcnow() 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.add_texts(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)