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			449 lines
		
	
	
		
			19 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			449 lines
		
	
	
		
			19 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import base64
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| import json
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| import secrets
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| 
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| import click
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| from flask import current_app
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| from werkzeug.exceptions import NotFound
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| 
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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 libs.helper import email as email_validate
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| from libs.password import hash_password, password_pattern, valid_password
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| from libs.rsa import generate_key_pair
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| from models.account import Tenant
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| from models.dataset import Dataset, DatasetCollectionBinding, DocumentSegment
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| from models.dataset import Document as DatasetDocument
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| from models.model import Account, App, AppAnnotationSetting, AppMode, Conversation, MessageAnnotation
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| from models.provider import Provider, ProviderModel
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| 
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| 
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| @click.command('reset-password', help='Reset the account password.')
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| @click.option('--email', prompt=True, help='The email address of the account whose password you need to reset')
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| @click.option('--new-password', prompt=True, help='the new password.')
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| @click.option('--password-confirm', prompt=True, help='the new password confirm.')
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| def reset_password(email, new_password, password_confirm):
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|     """
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|     Reset password of owner account
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|     Only available in SELF_HOSTED mode
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|     """
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|     if str(new_password).strip() != str(password_confirm).strip():
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|         click.echo(click.style('sorry. The two passwords do not match.', fg='red'))
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|         return
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| 
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|     account = db.session.query(Account). \
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|         filter(Account.email == email). \
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|         one_or_none()
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| 
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|     if not account:
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|         click.echo(click.style('sorry. the account: [{}] not exist .'.format(email), fg='red'))
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|         return
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| 
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|     try:
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|         valid_password(new_password)
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|     except:
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|         click.echo(
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|             click.style('sorry. The passwords must match {} '.format(password_pattern), fg='red'))
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|         return
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| 
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|     # generate password salt
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|     salt = secrets.token_bytes(16)
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|     base64_salt = base64.b64encode(salt).decode()
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| 
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|     # encrypt password with salt
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|     password_hashed = hash_password(new_password, salt)
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|     base64_password_hashed = base64.b64encode(password_hashed).decode()
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|     account.password = base64_password_hashed
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|     account.password_salt = base64_salt
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|     db.session.commit()
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|     click.echo(click.style('Congratulations!, password has been reset.', fg='green'))
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| 
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| 
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| @click.command('reset-email', help='Reset the account email.')
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| @click.option('--email', prompt=True, help='The old email address of the account whose email you need to reset')
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| @click.option('--new-email', prompt=True, help='the new email.')
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| @click.option('--email-confirm', prompt=True, help='the new email confirm.')
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| def reset_email(email, new_email, email_confirm):
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|     """
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|     Replace account email
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|     :return:
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|     """
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|     if str(new_email).strip() != str(email_confirm).strip():
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|         click.echo(click.style('Sorry, new email and confirm email do not match.', fg='red'))
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|         return
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| 
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|     account = db.session.query(Account). \
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|         filter(Account.email == email). \
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|         one_or_none()
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| 
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|     if not account:
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|         click.echo(click.style('sorry. the account: [{}] not exist .'.format(email), fg='red'))
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|         return
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| 
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|     try:
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|         email_validate(new_email)
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|     except:
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|         click.echo(
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|             click.style('sorry. {} is not a valid email. '.format(email), fg='red'))
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|         return
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| 
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|     account.email = new_email
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|     db.session.commit()
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|     click.echo(click.style('Congratulations!, email has been reset.', fg='green'))
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| 
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| 
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| @click.command('reset-encrypt-key-pair', help='Reset the asymmetric key pair of workspace for encrypt LLM credentials. '
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|                                               'After the reset, all LLM credentials will become invalid, '
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|                                               'requiring re-entry.'
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|                                               'Only support SELF_HOSTED mode.')
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| @click.confirmation_option(prompt=click.style('Are you sure you want to reset encrypt key pair?'
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|                                               ' this operation cannot be rolled back!', fg='red'))
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| def reset_encrypt_key_pair():
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|     """
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|     Reset the encrypted key pair of workspace for encrypt LLM credentials.
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|     After the reset, all LLM credentials will become invalid, requiring re-entry.
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|     Only support SELF_HOSTED mode.
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|     """
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|     if current_app.config['EDITION'] != 'SELF_HOSTED':
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|         click.echo(click.style('Sorry, only support SELF_HOSTED mode.', fg='red'))
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|         return
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| 
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|     tenants = db.session.query(Tenant).all()
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|     for tenant in tenants:
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|         if not tenant:
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|             click.echo(click.style('Sorry, no workspace found. Please enter /install to initialize.', fg='red'))
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|             return
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| 
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|         tenant.encrypt_public_key = generate_key_pair(tenant.id)
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| 
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|         db.session.query(Provider).filter(Provider.provider_type == 'custom', Provider.tenant_id == tenant.id).delete()
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|         db.session.query(ProviderModel).filter(ProviderModel.tenant_id == tenant.id).delete()
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|         db.session.commit()
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| 
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|         click.echo(click.style('Congratulations! '
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|                                'the asymmetric key pair of workspace {} has been reset.'.format(tenant.id), fg='green'))
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| 
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| 
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| @click.command('vdb-migrate', help='migrate vector db.')
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| @click.option('--scope', default='all', prompt=False, help='The scope of vector database to migrate, Default is All.')
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| def vdb_migrate(scope: str):
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|     if scope in ['knowledge', 'all']:
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|         migrate_knowledge_vector_database()
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|     if scope in ['annotation', 'all']:
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|         migrate_annotation_vector_database()
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| 
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| 
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| def migrate_annotation_vector_database():
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|     """
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|     Migrate annotation datas to target vector database .
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|     """
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|     click.echo(click.style('Start migrate annotation data.', fg='green'))
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|     create_count = 0
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|     skipped_count = 0
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|     total_count = 0
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|     page = 1
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|     while True:
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|         try:
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|             # get apps info
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|             apps = db.session.query(App).filter(
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|                 App.status == 'normal'
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|             ).order_by(App.created_at.desc()).paginate(page=page, per_page=50)
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|         except NotFound:
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|             break
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| 
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|         page += 1
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|         for app in apps:
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|             total_count = total_count + 1
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|             click.echo(f'Processing the {total_count} app {app.id}. '
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|                        + f'{create_count} created, {skipped_count} skipped.')
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|             try:
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|                 click.echo('Create app annotation index: {}'.format(app.id))
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|                 app_annotation_setting = db.session.query(AppAnnotationSetting).filter(
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|                     AppAnnotationSetting.app_id == app.id
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|                 ).first()
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| 
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|                 if not app_annotation_setting:
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|                     skipped_count = skipped_count + 1
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|                     click.echo('App annotation setting is disabled: {}'.format(app.id))
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|                     continue
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|                 # get dataset_collection_binding info
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|                 dataset_collection_binding = db.session.query(DatasetCollectionBinding).filter(
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|                     DatasetCollectionBinding.id == app_annotation_setting.collection_binding_id
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|                 ).first()
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|                 if not dataset_collection_binding:
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|                     click.echo('App annotation collection binding is not exist: {}'.format(app.id))
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|                     continue
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|                 annotations = db.session.query(MessageAnnotation).filter(MessageAnnotation.app_id == app.id).all()
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|                 dataset = Dataset(
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|                     id=app.id,
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|                     tenant_id=app.tenant_id,
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|                     indexing_technique='high_quality',
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|                     embedding_model_provider=dataset_collection_binding.provider_name,
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|                     embedding_model=dataset_collection_binding.model_name,
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|                     collection_binding_id=dataset_collection_binding.id
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|                 )
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|                 documents = []
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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={
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|                                 "annotation_id": annotation.id,
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|                                 "app_id": app.id,
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|                                 "doc_id": annotation.id
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|                             }
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|                         )
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|                         documents.append(document)
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| 
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|                 vector = Vector(dataset, attributes=['doc_id', 'annotation_id', 'app_id'])
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|                 click.echo(f"Start to migrate annotation, app_id: {app.id}.")
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| 
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|                 try:
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|                     vector.delete()
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|                     click.echo(
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|                         click.style(f'Successfully delete vector index for app: {app.id}.',
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|                                     fg='green'))
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|                 except Exception as e:
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|                     click.echo(
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|                         click.style(f'Failed to delete vector index for app {app.id}.',
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|                                     fg='red'))
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|                     raise e
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|                 if documents:
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|                     try:
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|                         click.echo(click.style(
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|                             f'Start to created vector index with {len(documents)} annotations for app {app.id}.',
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|                             fg='green'))
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|                         vector.create(documents)
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|                         click.echo(
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|                             click.style(f'Successfully created vector index for app {app.id}.', fg='green'))
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|                     except Exception as e:
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|                         click.echo(click.style(f'Failed to created vector index for app {app.id}.', fg='red'))
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|                         raise e
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|                 click.echo(f'Successfully migrated app annotation {app.id}.')
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|                 create_count += 1
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|             except Exception as e:
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|                 click.echo(
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|                     click.style('Create app annotation index error: {} {}'.format(e.__class__.__name__, str(e)),
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|                                 fg='red'))
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|                 continue
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| 
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|     click.echo(
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|         click.style(f'Congratulations! Create {create_count} app annotation indexes, and skipped {skipped_count} apps.',
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|                     fg='green'))
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| 
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| 
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| def migrate_knowledge_vector_database():
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|     """
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|     Migrate vector database datas to target vector database .
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|     """
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|     click.echo(click.style('Start migrate vector db.', fg='green'))
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|     create_count = 0
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|     skipped_count = 0
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|     total_count = 0
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|     config = current_app.config
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|     vector_type = config.get('VECTOR_STORE')
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|     page = 1
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|     while True:
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|         try:
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|             datasets = db.session.query(Dataset).filter(Dataset.indexing_technique == 'high_quality') \
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|                 .order_by(Dataset.created_at.desc()).paginate(page=page, per_page=50)
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|         except NotFound:
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|             break
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| 
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|         page += 1
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|         for dataset in datasets:
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|             total_count = total_count + 1
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|             click.echo(f'Processing the {total_count} dataset {dataset.id}. '
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|                        + f'{create_count} created, {skipped_count} skipped.')
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|             try:
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|                 click.echo('Create dataset vdb index: {}'.format(dataset.id))
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|                 if dataset.index_struct_dict:
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|                     if dataset.index_struct_dict['type'] == vector_type:
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|                         skipped_count = skipped_count + 1
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|                         continue
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|                 collection_name = ''
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|                 if vector_type == "weaviate":
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|                     dataset_id = dataset.id
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|                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
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|                     index_struct_dict = {
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|                         "type": 'weaviate',
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|                         "vector_store": {"class_prefix": collection_name}
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|                     }
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|                     dataset.index_struct = json.dumps(index_struct_dict)
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|                 elif vector_type == "qdrant":
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|                     if dataset.collection_binding_id:
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|                         dataset_collection_binding = db.session.query(DatasetCollectionBinding). \
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|                             filter(DatasetCollectionBinding.id == dataset.collection_binding_id). \
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|                             one_or_none()
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|                         if dataset_collection_binding:
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|                             collection_name = dataset_collection_binding.collection_name
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|                         else:
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|                             raise ValueError('Dataset Collection Bindings is not exist!')
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|                     else:
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|                         dataset_id = dataset.id
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|                         collection_name = Dataset.gen_collection_name_by_id(dataset_id)
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|                     index_struct_dict = {
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|                         "type": 'qdrant',
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|                         "vector_store": {"class_prefix": collection_name}
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|                     }
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|                     dataset.index_struct = json.dumps(index_struct_dict)
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| 
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|                 elif vector_type == "milvus":
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|                     dataset_id = dataset.id
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|                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
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|                     index_struct_dict = {
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|                         "type": 'milvus',
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|                         "vector_store": {"class_prefix": collection_name}
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|                     }
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|                     dataset.index_struct = json.dumps(index_struct_dict)
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|                 elif vector_type == "relyt":
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|                     dataset_id = dataset.id
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|                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
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|                     index_struct_dict = {
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|                         "type": 'relyt',
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|                         "vector_store": {"class_prefix": collection_name}
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|                     }
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|                     dataset.index_struct = json.dumps(index_struct_dict)
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|                 else:
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|                     raise ValueError(f"Vector store {config.get('VECTOR_STORE')} is not supported.")
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| 
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|                 vector = Vector(dataset)
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|                 click.echo(f"Start to migrate dataset {dataset.id}.")
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| 
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|                 try:
 | |
|                     vector.delete()
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|                     click.echo(
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|                         click.style(f'Successfully delete vector index {collection_name} for dataset {dataset.id}.',
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|                                     fg='green'))
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|                 except Exception as e:
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|                     click.echo(
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|                         click.style(f'Failed to delete vector index {collection_name} for dataset {dataset.id}.',
 | |
|                                     fg='red'))
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|                     raise e
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| 
 | |
|                 dataset_documents = db.session.query(DatasetDocument).filter(
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|                     DatasetDocument.dataset_id == dataset.id,
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|                     DatasetDocument.indexing_status == 'completed',
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|                     DatasetDocument.enabled == True,
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|                     DatasetDocument.archived == False,
 | |
|                 ).all()
 | |
| 
 | |
|                 documents = []
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|                 segments_count = 0
 | |
|                 for dataset_document in dataset_documents:
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|                     segments = db.session.query(DocumentSegment).filter(
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|                         DocumentSegment.document_id == dataset_document.id,
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|                         DocumentSegment.status == 'completed',
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|                         DocumentSegment.enabled == True
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|                     ).all()
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| 
 | |
|                     for segment in segments:
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|                         document = Document(
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|                             page_content=segment.content,
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|                             metadata={
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|                                 "doc_id": segment.index_node_id,
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|                                 "doc_hash": segment.index_node_hash,
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|                                 "document_id": segment.document_id,
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|                                 "dataset_id": segment.dataset_id,
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|                             }
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|                         )
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| 
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|                         documents.append(document)
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|                         segments_count = segments_count + 1
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| 
 | |
|                 if documents:
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|                     try:
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|                         click.echo(click.style(
 | |
|                             f'Start to created vector index with {len(documents)} documents of {segments_count} segments for dataset {dataset.id}.',
 | |
|                             fg='green'))
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|                         vector.create(documents)
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|                         click.echo(
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|                             click.style(f'Successfully created vector index for dataset {dataset.id}.', fg='green'))
 | |
|                     except Exception as e:
 | |
|                         click.echo(click.style(f'Failed to created vector index for dataset {dataset.id}.', fg='red'))
 | |
|                         raise e
 | |
|                 db.session.add(dataset)
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|                 db.session.commit()
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|                 click.echo(f'Successfully migrated dataset {dataset.id}.')
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|                 create_count += 1
 | |
|             except Exception as e:
 | |
|                 db.session.rollback()
 | |
|                 click.echo(
 | |
|                     click.style('Create dataset index error: {} {}'.format(e.__class__.__name__, str(e)),
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|                                 fg='red'))
 | |
|                 continue
 | |
| 
 | |
|     click.echo(
 | |
|         click.style(f'Congratulations! Create {create_count} dataset indexes, and skipped {skipped_count} datasets.',
 | |
|                     fg='green'))
 | |
| 
 | |
| 
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| @click.command('convert-to-agent-apps', help='Convert Agent Assistant to Agent App.')
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| def convert_to_agent_apps():
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|     """
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|     Convert Agent Assistant to Agent App.
 | |
|     """
 | |
|     click.echo(click.style('Start convert to agent apps.', fg='green'))
 | |
| 
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|     proceeded_app_ids = []
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| 
 | |
|     while True:
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|         # fetch first 1000 apps
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|         sql_query = """SELECT a.id AS id FROM apps a
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|             INNER JOIN app_model_configs am ON a.app_model_config_id=am.id
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|             WHERE a.mode = 'chat' 
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|             AND am.agent_mode is not null 
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|             AND (
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| 				am.agent_mode like '%"strategy": "function_call"%' 
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|                 OR am.agent_mode  like '%"strategy": "react"%'
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| 			) 
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|             AND (
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| 				am.agent_mode like '{"enabled": true%' 
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|                 OR am.agent_mode like '{"max_iteration": %'
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| 			) ORDER BY a.created_at DESC LIMIT 1000
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|         """
 | |
| 
 | |
|         with db.engine.begin() as conn:
 | |
|             rs = conn.execute(db.text(sql_query))
 | |
| 
 | |
|             apps = []
 | |
|             for i in rs:
 | |
|                 app_id = str(i.id)
 | |
|                 if app_id not in proceeded_app_ids:
 | |
|                     proceeded_app_ids.append(app_id)
 | |
|                     app = db.session.query(App).filter(App.id == app_id).first()
 | |
|                     apps.append(app)
 | |
| 
 | |
|             if len(apps) == 0:
 | |
|                 break
 | |
| 
 | |
|         for app in apps:
 | |
|             click.echo('Converting app: {}'.format(app.id))
 | |
| 
 | |
|             try:
 | |
|                 app.mode = AppMode.AGENT_CHAT.value
 | |
|                 db.session.commit()
 | |
| 
 | |
|                 # update conversation mode to agent
 | |
|                 db.session.query(Conversation).filter(Conversation.app_id == app.id).update(
 | |
|                     {Conversation.mode: AppMode.AGENT_CHAT.value}
 | |
|                 )
 | |
| 
 | |
|                 db.session.commit()
 | |
|                 click.echo(click.style('Converted app: {}'.format(app.id), fg='green'))
 | |
|             except Exception as e:
 | |
|                 click.echo(
 | |
|                     click.style('Convert app error: {} {}'.format(e.__class__.__name__,
 | |
|                                                                   str(e)), fg='red'))
 | |
| 
 | |
|     click.echo(click.style('Congratulations! Converted {} agent apps.'.format(len(proceeded_app_ids)), fg='green'))
 | |
| 
 | |
| 
 | |
| def register_commands(app):
 | |
|     app.cli.add_command(reset_password)
 | |
|     app.cli.add_command(reset_email)
 | |
|     app.cli.add_command(reset_encrypt_key_pair)
 | |
|     app.cli.add_command(vdb_migrate)
 | |
|     app.cli.add_command(convert_to_agent_apps)
 | 
