dify/api/controllers/service_api/dataset/segment.py

212 lines
8.9 KiB
Python

from controllers.service_api import api
from controllers.service_api.app.error import ProviderNotInitializeError
from controllers.service_api.wraps import DatasetApiResource, cloud_edition_billing_resource_check
from core.errors.error import LLMBadRequestError, ProviderTokenNotInitError
from core.model_manager import ModelManager
from core.model_runtime.entities.model_entities import ModelType
from extensions.ext_database import db
from fields.segment_fields import segment_fields
from flask_login import current_user
from flask_restful import marshal, reqparse
from models.dataset import Dataset, DocumentSegment
from services.dataset_service import DatasetService, DocumentService, SegmentService
from werkzeug.exceptions import NotFound
class SegmentApi(DatasetApiResource):
"""Resource for segments."""
@cloud_edition_billing_resource_check('vector_space', 'dataset')
def post(self, tenant_id, dataset_id, document_id):
"""Create single segment."""
# check dataset
dataset_id = str(dataset_id)
tenant_id = str(tenant_id)
dataset = db.session.query(Dataset).filter(
Dataset.tenant_id == tenant_id,
Dataset.id == dataset_id
).first()
if not dataset:
raise NotFound('Dataset not found.')
# check document
document_id = str(document_id)
document = DocumentService.get_document(dataset.id, document_id)
if not document:
raise NotFound('Document not found.')
# check embedding model setting
if dataset.indexing_technique == 'high_quality':
try:
model_manager = ModelManager()
model_manager.get_model_instance(
tenant_id=current_user.current_tenant_id,
provider=dataset.embedding_model_provider,
model_type=ModelType.TEXT_EMBEDDING,
model=dataset.embedding_model
)
except LLMBadRequestError:
raise ProviderNotInitializeError(
f"No Embedding Model available. Please configure a valid provider "
f"in the Settings -> Model Provider.")
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
# validate args
parser = reqparse.RequestParser()
parser.add_argument('segments', type=list, required=False, nullable=True, location='json')
args = parser.parse_args()
for args_item in args['segments']:
SegmentService.segment_create_args_validate(args_item, document)
segments = SegmentService.multi_create_segment(args['segments'], document, dataset)
return {
'data': marshal(segments, segment_fields),
'doc_form': document.doc_form
}, 200
def get(self, tenant_id, dataset_id, document_id):
"""Create single segment."""
# check dataset
dataset_id = str(dataset_id)
tenant_id = str(tenant_id)
dataset = db.session.query(Dataset).filter(
Dataset.tenant_id == tenant_id,
Dataset.id == dataset_id
).first()
if not dataset:
raise NotFound('Dataset not found.')
# check document
document_id = str(document_id)
document = DocumentService.get_document(dataset.id, document_id)
if not document:
raise NotFound('Document not found.')
# check embedding model setting
if dataset.indexing_technique == 'high_quality':
try:
model_manager = ModelManager()
model_manager.get_model_instance(
tenant_id=current_user.current_tenant_id,
provider=dataset.embedding_model_provider,
model_type=ModelType.TEXT_EMBEDDING,
model=dataset.embedding_model
)
except LLMBadRequestError:
raise ProviderNotInitializeError(
f"No Embedding Model available. Please configure a valid provider "
f"in the Settings -> Model Provider.")
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
parser = reqparse.RequestParser()
parser.add_argument('status', type=str,
action='append', default=[], location='args')
parser.add_argument('keyword', type=str, default=None, location='args')
args = parser.parse_args()
status_list = args['status']
keyword = args['keyword']
query = DocumentSegment.query.filter(
DocumentSegment.document_id == str(document_id),
DocumentSegment.tenant_id == current_user.current_tenant_id
)
if status_list:
query = query.filter(DocumentSegment.status.in_(status_list))
if keyword:
query = query.where(DocumentSegment.content.ilike(f'%{keyword}%'))
total = query.count()
segments = query.order_by(DocumentSegment.position).all()
return {
'data': marshal(segments, segment_fields),
'doc_form': document.doc_form,
'total': total
}, 200
class DatasetSegmentApi(DatasetApiResource):
def delete(self, tenant_id, dataset_id, document_id, segment_id):
# check dataset
dataset_id = str(dataset_id)
tenant_id = str(tenant_id)
dataset = db.session.query(Dataset).filter(
Dataset.tenant_id == tenant_id,
Dataset.id == dataset_id
).first()
if not dataset:
raise NotFound('Dataset not found.')
# check user's model setting
DatasetService.check_dataset_model_setting(dataset)
# check document
document_id = str(document_id)
document = DocumentService.get_document(dataset_id, document_id)
if not document:
raise NotFound('Document not found.')
# check segment
segment = DocumentSegment.query.filter(
DocumentSegment.id == str(segment_id),
DocumentSegment.tenant_id == current_user.current_tenant_id
).first()
if not segment:
raise NotFound('Segment not found.')
SegmentService.delete_segment(segment, document, dataset)
return {'result': 'success'}, 200
@cloud_edition_billing_resource_check('vector_space', 'dataset')
def post(self, tenant_id, dataset_id, document_id, segment_id):
# check dataset
dataset_id = str(dataset_id)
tenant_id = str(tenant_id)
dataset = db.session.query(Dataset).filter(
Dataset.tenant_id == tenant_id,
Dataset.id == dataset_id
).first()
if not dataset:
raise NotFound('Dataset not found.')
# check user's model setting
DatasetService.check_dataset_model_setting(dataset)
# check document
document_id = str(document_id)
document = DocumentService.get_document(dataset_id, document_id)
if not document:
raise NotFound('Document not found.')
if dataset.indexing_technique == 'high_quality':
# check embedding model setting
try:
model_manager = ModelManager()
model_manager.get_model_instance(
tenant_id=current_user.current_tenant_id,
provider=dataset.embedding_model_provider,
model_type=ModelType.TEXT_EMBEDDING,
model=dataset.embedding_model
)
except LLMBadRequestError:
raise ProviderNotInitializeError(
f"No Embedding Model available. Please configure a valid provider "
f"in the Settings -> Model Provider.")
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
# check segment
segment_id = str(segment_id)
segment = DocumentSegment.query.filter(
DocumentSegment.id == str(segment_id),
DocumentSegment.tenant_id == current_user.current_tenant_id
).first()
if not segment:
raise NotFound('Segment not found.')
# validate args
parser = reqparse.RequestParser()
parser.add_argument('segments', type=dict, required=False, nullable=True, location='json')
args = parser.parse_args()
SegmentService.segment_create_args_validate(args['segments'], document)
segment = SegmentService.update_segment(args['segments'], segment, document, dataset)
return {
'data': marshal(segment, segment_fields),
'doc_form': document.doc_form
}, 200
api.add_resource(SegmentApi, '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/segments')
api.add_resource(DatasetSegmentApi, '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/segments/<uuid:segment_id>')