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