dify/api/controllers/console/datasets/datasets.py

512 lines
20 KiB
Python

# -*- coding:utf-8 -*-
import flask_restful
import services
from controllers.console import api
from controllers.console.apikey import api_key_fields, api_key_list
from controllers.console.app.error import ProviderNotInitializeError
from controllers.console.datasets.error import DatasetNameDuplicateError
from controllers.console.setup import setup_required
from controllers.console.wraps import account_initialization_required
from core.errors.error import LLMBadRequestError, ProviderTokenNotInitError
from core.indexing_runner import IndexingRunner
from core.model_runtime.entities.model_entities import ModelType
from core.provider_manager import ProviderManager
from extensions.ext_database import db
from fields.app_fields import related_app_list
from fields.dataset_fields import dataset_detail_fields, dataset_query_detail_fields
from fields.document_fields import document_status_fields
from flask import current_app, request
from flask_login import current_user
from flask_restful import Resource, marshal, marshal_with, reqparse
from libs.login import login_required
from models.dataset import Dataset, Document, DocumentSegment
from models.model import ApiToken, UploadFile
from services.dataset_service import DatasetService, DocumentService
from werkzeug.exceptions import Forbidden, NotFound
def _validate_name(name):
if not name or len(name) < 1 or len(name) > 40:
raise ValueError('Name must be between 1 to 40 characters.')
return name
def _validate_description_length(description):
if len(description) > 400:
raise ValueError('Description cannot exceed 400 characters.')
return description
class DatasetListApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self):
page = request.args.get('page', default=1, type=int)
limit = request.args.get('limit', default=20, type=int)
ids = request.args.getlist('ids')
provider = request.args.get('provider', default="vendor")
if ids:
datasets, total = DatasetService.get_datasets_by_ids(ids, current_user.current_tenant_id)
else:
datasets, total = DatasetService.get_datasets(page, limit, provider,
current_user.current_tenant_id, current_user)
# check embedding setting
provider_manager = ProviderManager()
configurations = provider_manager.get_configurations(
tenant_id=current_user.current_tenant_id
)
embedding_models = configurations.get_models(
model_type=ModelType.TEXT_EMBEDDING,
only_active=True
)
model_names = []
for embedding_model in embedding_models:
model_names.append(f"{embedding_model.model}:{embedding_model.provider.provider}")
data = marshal(datasets, dataset_detail_fields)
for item in data:
if item['indexing_technique'] == 'high_quality':
item_model = f"{item['embedding_model']}:{item['embedding_model_provider']}"
if item_model in model_names:
item['embedding_available'] = True
else:
item['embedding_available'] = False
else:
item['embedding_available'] = True
response = {
'data': data,
'has_more': len(datasets) == limit,
'limit': limit,
'total': total,
'page': page
}
return response, 200
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('name', nullable=False, required=True,
help='type is required. Name must be between 1 to 40 characters.',
type=_validate_name)
parser.add_argument('indexing_technique', type=str, location='json',
choices=Dataset.INDEXING_TECHNIQUE_LIST,
nullable=True,
help='Invalid indexing technique.')
args = parser.parse_args()
# The role of the current user in the ta table must be admin or owner
if not current_user.is_admin_or_owner:
raise Forbidden()
try:
dataset = DatasetService.create_empty_dataset(
tenant_id=current_user.current_tenant_id,
name=args['name'],
indexing_technique=args['indexing_technique'],
account=current_user
)
except services.errors.dataset.DatasetNameDuplicateError:
raise DatasetNameDuplicateError()
return marshal(dataset, dataset_detail_fields), 201
class DatasetApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, dataset_id):
dataset_id_str = str(dataset_id)
dataset = DatasetService.get_dataset(dataset_id_str)
if dataset is None:
raise NotFound("Dataset not found.")
try:
DatasetService.check_dataset_permission(
dataset, current_user)
except services.errors.account.NoPermissionError as e:
raise Forbidden(str(e))
data = marshal(dataset, dataset_detail_fields)
# check embedding setting
provider_manager = ProviderManager()
configurations = provider_manager.get_configurations(
tenant_id=current_user.current_tenant_id
)
embedding_models = configurations.get_models(
model_type=ModelType.TEXT_EMBEDDING,
only_active=True
)
model_names = []
for embedding_model in embedding_models:
model_names.append(f"{embedding_model.model}:{embedding_model.provider.provider}")
if data['indexing_technique'] == 'high_quality':
item_model = f"{data['embedding_model']}:{data['embedding_model_provider']}"
if item_model in model_names:
data['embedding_available'] = True
else:
data['embedding_available'] = False
else:
data['embedding_available'] = True
return data, 200
@setup_required
@login_required
@account_initialization_required
def patch(self, dataset_id):
dataset_id_str = str(dataset_id)
dataset = DatasetService.get_dataset(dataset_id_str)
if dataset is None:
raise NotFound("Dataset not found.")
# check user's model setting
DatasetService.check_dataset_model_setting(dataset)
parser = reqparse.RequestParser()
parser.add_argument('name', nullable=False,
help='type is required. Name must be between 1 to 40 characters.',
type=_validate_name)
parser.add_argument('description',
location='json', store_missing=False,
type=_validate_description_length)
parser.add_argument('indexing_technique', type=str, location='json',
choices=Dataset.INDEXING_TECHNIQUE_LIST,
nullable=True,
help='Invalid indexing technique.')
parser.add_argument('permission', type=str, location='json', choices=(
'only_me', 'all_team_members'), help='Invalid permission.')
parser.add_argument('retrieval_model', type=dict, location='json', help='Invalid retrieval model.')
args = parser.parse_args()
# The role of the current user in the ta table must be admin or owner
if not current_user.is_admin_or_owner:
raise Forbidden()
dataset = DatasetService.update_dataset(
dataset_id_str, args, current_user)
if dataset is None:
raise NotFound("Dataset not found.")
return marshal(dataset, dataset_detail_fields), 200
@setup_required
@login_required
@account_initialization_required
def delete(self, dataset_id):
dataset_id_str = str(dataset_id)
# The role of the current user in the ta table must be admin or owner
if not current_user.is_admin_or_owner:
raise Forbidden()
if DatasetService.delete_dataset(dataset_id_str, current_user):
return {'result': 'success'}, 204
else:
raise NotFound("Dataset not found.")
class DatasetQueryApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, dataset_id):
dataset_id_str = str(dataset_id)
dataset = DatasetService.get_dataset(dataset_id_str)
if dataset is None:
raise NotFound("Dataset not found.")
try:
DatasetService.check_dataset_permission(dataset, current_user)
except services.errors.account.NoPermissionError as e:
raise Forbidden(str(e))
page = request.args.get('page', default=1, type=int)
limit = request.args.get('limit', default=20, type=int)
dataset_queries, total = DatasetService.get_dataset_queries(
dataset_id=dataset.id,
page=page,
per_page=limit
)
response = {
'data': marshal(dataset_queries, dataset_query_detail_fields),
'has_more': len(dataset_queries) == limit,
'limit': limit,
'total': total,
'page': page
}
return response, 200
class DatasetIndexingEstimateApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument('info_list', type=dict, required=True, nullable=True, location='json')
parser.add_argument('process_rule', type=dict, required=True, nullable=True, location='json')
parser.add_argument('indexing_technique', type=str, required=True,
choices=Dataset.INDEXING_TECHNIQUE_LIST,
nullable=True, location='json')
parser.add_argument('doc_form', type=str, default='text_model', required=False, nullable=False, location='json')
parser.add_argument('dataset_id', type=str, required=False, nullable=False, location='json')
parser.add_argument('doc_language', type=str, default='English', required=False, nullable=False,
location='json')
args = parser.parse_args()
# validate args
DocumentService.estimate_args_validate(args)
if args['info_list']['data_source_type'] == 'upload_file':
file_ids = args['info_list']['file_info_list']['file_ids']
file_details = db.session.query(UploadFile).filter(
UploadFile.tenant_id == current_user.current_tenant_id,
UploadFile.id.in_(file_ids)
).all()
if file_details is None:
raise NotFound("File not found.")
indexing_runner = IndexingRunner()
try:
response = indexing_runner.file_indexing_estimate(current_user.current_tenant_id, file_details,
args['process_rule'], args['doc_form'],
args['doc_language'], args['dataset_id'],
args['indexing_technique'])
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)
elif args['info_list']['data_source_type'] == 'notion_import':
indexing_runner = IndexingRunner()
try:
response = indexing_runner.notion_indexing_estimate(current_user.current_tenant_id,
args['info_list']['notion_info_list'],
args['process_rule'], args['doc_form'],
args['doc_language'], args['dataset_id'],
args['indexing_technique'])
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)
else:
raise ValueError('Data source type not support')
return response, 200
class DatasetRelatedAppListApi(Resource):
@setup_required
@login_required
@account_initialization_required
@marshal_with(related_app_list)
def get(self, dataset_id):
dataset_id_str = str(dataset_id)
dataset = DatasetService.get_dataset(dataset_id_str)
if dataset is None:
raise NotFound("Dataset not found.")
try:
DatasetService.check_dataset_permission(dataset, current_user)
except services.errors.account.NoPermissionError as e:
raise Forbidden(str(e))
app_dataset_joins = DatasetService.get_related_apps(dataset.id)
related_apps = []
for app_dataset_join in app_dataset_joins:
app_model = app_dataset_join.app
if app_model:
related_apps.append(app_model)
return {
'data': related_apps,
'total': len(related_apps)
}, 200
class DatasetIndexingStatusApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, dataset_id):
dataset_id = str(dataset_id)
documents = db.session.query(Document).filter(
Document.dataset_id == dataset_id,
Document.tenant_id == current_user.current_tenant_id
).all()
documents_status = []
for document in documents:
completed_segments = DocumentSegment.query.filter(DocumentSegment.completed_at.isnot(None),
DocumentSegment.document_id == str(document.id),
DocumentSegment.status != 're_segment').count()
total_segments = DocumentSegment.query.filter(DocumentSegment.document_id == str(document.id),
DocumentSegment.status != 're_segment').count()
document.completed_segments = completed_segments
document.total_segments = total_segments
documents_status.append(marshal(document, document_status_fields))
data = {
'data': documents_status
}
return data
class DatasetApiKeyApi(Resource):
max_keys = 10
token_prefix = 'dataset-'
resource_type = 'dataset'
@setup_required
@login_required
@account_initialization_required
@marshal_with(api_key_list)
def get(self):
keys = db.session.query(ApiToken). \
filter(ApiToken.type == self.resource_type, ApiToken.tenant_id == current_user.current_tenant_id). \
all()
return {"items": keys}
@setup_required
@login_required
@account_initialization_required
@marshal_with(api_key_fields)
def post(self):
# The role of the current user in the ta table must be admin or owner
if not current_user.is_admin_or_owner:
raise Forbidden()
current_key_count = db.session.query(ApiToken). \
filter(ApiToken.type == self.resource_type, ApiToken.tenant_id == current_user.current_tenant_id). \
count()
if current_key_count >= self.max_keys:
flask_restful.abort(
400,
message=f"Cannot create more than {self.max_keys} API keys for this resource type.",
code='max_keys_exceeded'
)
key = ApiToken.generate_api_key(self.token_prefix, 24)
api_token = ApiToken()
api_token.tenant_id = current_user.current_tenant_id
api_token.token = key
api_token.type = self.resource_type
db.session.add(api_token)
db.session.commit()
return api_token, 200
class DatasetApiDeleteApi(Resource):
resource_type = 'dataset'
@setup_required
@login_required
@account_initialization_required
def delete(self, api_key_id):
api_key_id = str(api_key_id)
# The role of the current user in the ta table must be admin or owner
if not current_user.is_admin_or_owner:
raise Forbidden()
key = db.session.query(ApiToken). \
filter(ApiToken.tenant_id == current_user.current_tenant_id, ApiToken.type == self.resource_type,
ApiToken.id == api_key_id). \
first()
if key is None:
flask_restful.abort(404, message='API key not found')
db.session.query(ApiToken).filter(ApiToken.id == api_key_id).delete()
db.session.commit()
return {'result': 'success'}, 204
class DatasetApiBaseUrlApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self):
return {
'api_base_url': (current_app.config['SERVICE_API_URL'] if current_app.config['SERVICE_API_URL']
else request.host_url.rstrip('/')) + '/v1'
}
class DatasetRetrievalSettingApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self):
vector_type = current_app.config['VECTOR_STORE']
if vector_type == 'milvus':
return {
'retrieval_method': [
'semantic_search'
]
}
elif vector_type == 'qdrant' or vector_type == 'weaviate':
return {
'retrieval_method': [
'semantic_search', 'full_text_search', 'hybrid_search'
]
}
else:
raise ValueError("Unsupported vector db type.")
class DatasetRetrievalSettingMockApi(Resource):
@setup_required
@login_required
@account_initialization_required
def get(self, vector_type):
if vector_type == 'milvus':
return {
'retrieval_method': [
'semantic_search'
]
}
elif vector_type == 'qdrant' or vector_type == 'weaviate':
return {
'retrieval_method': [
'semantic_search', 'full_text_search', 'hybrid_search'
]
}
else:
raise ValueError("Unsupported vector db type.")
api.add_resource(DatasetListApi, '/datasets')
api.add_resource(DatasetApi, '/datasets/<uuid:dataset_id>')
api.add_resource(DatasetQueryApi, '/datasets/<uuid:dataset_id>/queries')
api.add_resource(DatasetIndexingEstimateApi, '/datasets/indexing-estimate')
api.add_resource(DatasetRelatedAppListApi, '/datasets/<uuid:dataset_id>/related-apps')
api.add_resource(DatasetIndexingStatusApi, '/datasets/<uuid:dataset_id>/indexing-status')
api.add_resource(DatasetApiKeyApi, '/datasets/api-keys')
api.add_resource(DatasetApiDeleteApi, '/datasets/api-keys/<uuid:api_key_id>')
api.add_resource(DatasetApiBaseUrlApi, '/datasets/api-base-info')
api.add_resource(DatasetRetrievalSettingApi, '/datasets/retrieval-setting')
api.add_resource(DatasetRetrievalSettingMockApi, '/datasets/retrieval-setting/<string:vector_type>')