Feat/add annotation migrate (#2675)

Co-authored-by: jyong <jyong@dify.ai>
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Jyong 2024-03-04 17:22:06 +08:00 committed by GitHub
parent f322d9bddb
commit 3631e53ff0
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2 changed files with 111 additions and 3 deletions

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@ -15,7 +15,7 @@ from libs.rsa import generate_key_pair
from models.account import Tenant
from models.dataset import Dataset, DatasetCollectionBinding, DocumentSegment
from models.dataset import Document as DatasetDocument
from models.model import Account
from models.model import Account, App, AppAnnotationSetting, MessageAnnotation
from models.provider import Provider, ProviderModel
@ -125,7 +125,114 @@ def reset_encrypt_key_pair():
@click.command('vdb-migrate', help='migrate vector db.')
def vdb_migrate():
@click.option('--scope', default='all', prompt=False, help='The scope of vector database to migrate, Default is All.')
def vdb_migrate(scope: str):
if scope in ['knowledge', 'all']:
migrate_knowledge_vector_database()
if scope in ['annotation', 'all']:
migrate_annotation_vector_database()
def migrate_annotation_vector_database():
"""
Migrate annotation datas to target vector database .
"""
click.echo(click.style('Start migrate annotation data.', fg='green'))
create_count = 0
skipped_count = 0
total_count = 0
page = 1
while True:
try:
# get apps info
apps = db.session.query(App).filter(
App.status == 'normal'
).order_by(App.created_at.desc()).paginate(page=page, per_page=50)
except NotFound:
break
page += 1
for app in apps:
total_count = total_count + 1
click.echo(f'Processing the {total_count} app {app.id}. '
+ f'{create_count} created, {skipped_count} skipped.')
try:
click.echo('Create app annotation index: {}'.format(app.id))
app_annotation_setting = db.session.query(AppAnnotationSetting).filter(
AppAnnotationSetting.app_id == app.id
).first()
if not app_annotation_setting:
skipped_count = skipped_count + 1
click.echo('App annotation setting is disabled: {}'.format(app.id))
continue
# get dataset_collection_binding info
dataset_collection_binding = db.session.query(DatasetCollectionBinding).filter(
DatasetCollectionBinding.id == app_annotation_setting.collection_binding_id
).first()
if not dataset_collection_binding:
click.echo('App annotation collection binding is not exist: {}'.format(app.id))
continue
annotations = db.session.query(MessageAnnotation).filter(MessageAnnotation.app_id == app.id).all()
dataset = Dataset(
id=app.id,
tenant_id=app.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
)
documents = []
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'])
click.echo(f"Start to migrate annotation, app_id: {app.id}.")
try:
vector.delete()
click.echo(
click.style(f'Successfully delete vector index for app: {app.id}.',
fg='green'))
except Exception as e:
click.echo(
click.style(f'Failed to delete vector index for app {app.id}.',
fg='red'))
raise e
if documents:
try:
click.echo(click.style(
f'Start to created vector index with {len(documents)} annotations for app {app.id}.',
fg='green'))
vector.create(documents)
click.echo(
click.style(f'Successfully created vector index for app {app.id}.', fg='green'))
except Exception as e:
click.echo(click.style(f'Failed to created vector index for app {app.id}.', fg='red'))
raise e
click.echo(f'Successfully migrated app annotation {app.id}.')
create_count += 1
except Exception as e:
click.echo(
click.style('Create app annotation index error: {} {}'.format(e.__class__.__name__, str(e)),
fg='red'))
continue
click.echo(
click.style(f'Congratulations! Create {create_count} app annotation indexes, and skipped {skipped_count} apps.',
fg='green'))
def migrate_knowledge_vector_database():
"""
Migrate vector database datas to target vector database .
"""

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@ -140,7 +140,8 @@ class MilvusVector(BaseVector):
connections.connect(alias=alias, uri=uri, user=self._client_config.user, password=self._client_config.password)
from pymilvus import utility
utility.drop_collection(self._collection_name, None, using=alias)
if utility.has_collection(self._collection_name, using=alias):
utility.drop_collection(self._collection_name, None, using=alias)
def text_exists(self, id: str) -> bool: