dify/api/models/dataset.py

import base64
import hashlib
import hmac
import json
import logging
import os
import pickle
import re
import time
from json import JSONDecodeError

from flask import current_app
from sqlalchemy import func
from sqlalchemy.dialects.postgresql import JSONB

from core.rag.retrieval.retrival_methods import RetrievalMethod
from extensions.ext_database import db
from extensions.ext_storage import storage
from models import StringUUID
from models.account import Account
from models.model import App, Tag, TagBinding, UploadFile


class Dataset(db.Model):
    __tablename__ = 'datasets'
    __table_args__ = (
        db.PrimaryKeyConstraint('id', name='dataset_pkey'),
        db.Index('dataset_tenant_idx', 'tenant_id'),
        db.Index('retrieval_model_idx', "retrieval_model", postgresql_using='gin')
    )

    INDEXING_TECHNIQUE_LIST = ['high_quality', 'economy', None]

    id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()'))
    tenant_id = db.Column(StringUUID, nullable=False)
    name = db.Column(db.String(255), nullable=False)
    description = db.Column(db.Text, nullable=True)
    provider = db.Column(db.String(255), nullable=False,
                         server_default=db.text("'vendor'::character varying"))
    permission = db.Column(db.String(255), nullable=False,
                           server_default=db.text("'only_me'::character varying"))
    data_source_type = db.Column(db.String(255))
    indexing_technique = db.Column(db.String(255), nullable=True)
    index_struct = db.Column(db.Text, nullable=True)
    created_by = db.Column(StringUUID, nullable=False)
    created_at = db.Column(db.DateTime, nullable=False,
                           server_default=db.text('CURRENT_TIMESTAMP(0)'))
    updated_by = db.Column(StringUUID, nullable=True)
    updated_at = db.Column(db.DateTime, nullable=False,
                           server_default=db.text('CURRENT_TIMESTAMP(0)'))
    embedding_model = db.Column(db.String(255), nullable=True)
    embedding_model_provider = db.Column(db.String(255), nullable=True)
    collection_binding_id = db.Column(StringUUID, nullable=True)
    retrieval_model = db.Column(JSONB, nullable=True)

    @property
    def dataset_keyword_table(self):
        dataset_keyword_table = db.session.query(DatasetKeywordTable).filter(
            DatasetKeywordTable.dataset_id == self.id).first()
        if dataset_keyword_table:
            return dataset_keyword_table

        return None

    @property
    def index_struct_dict(self):
        return json.loads(self.index_struct) if self.index_struct else None

    @property
    def created_by_account(self):
        return Account.query.get(self.created_by)

    @property
    def latest_process_rule(self):
        return DatasetProcessRule.query.filter(DatasetProcessRule.dataset_id == self.id) \
            .order_by(DatasetProcessRule.created_at.desc()).first()

    @property
    def app_count(self):
        return db.session.query(func.count(AppDatasetJoin.id)).filter(AppDatasetJoin.dataset_id == self.id,
                                                                      App.id == AppDatasetJoin.app_id).scalar()

    @property
    def document_count(self):
        return db.session.query(func.count(Document.id)).filter(Document.dataset_id == self.id).scalar()

    @property
    def available_document_count(self):
        return db.session.query(func.count(Document.id)).filter(
            Document.dataset_id == self.id,
            Document.indexing_status == 'completed',
            Document.enabled == True,
            Document.archived == False
        ).scalar()

    @property
    def available_segment_count(self):
        return db.session.query(func.count(DocumentSegment.id)).filter(
            DocumentSegment.dataset_id == self.id,
            DocumentSegment.status == 'completed',
            DocumentSegment.enabled == True
        ).scalar()

    @property
    def word_count(self):
        return Document.query.with_entities(func.coalesce(func.sum(Document.word_count))) \
            .filter(Document.dataset_id == self.id).scalar()

    @property
    def doc_form(self):
        document = db.session.query(Document).filter(
            Document.dataset_id == self.id).first()
        if document:
            return document.doc_form
        return None

    @property
    def retrieval_model_dict(self):
        default_retrieval_model = {
            'search_method': RetrievalMethod.SEMANTIC_SEARCH,
            'reranking_enable': False,
            'reranking_model': {
                'reranking_provider_name': '',
                'reranking_model_name': ''
            },
            'top_k': 2,
            'score_threshold_enabled': False
        }
        return self.retrieval_model if self.retrieval_model else default_retrieval_model

    @property
    def tags(self):
        tags = db.session.query(Tag).join(
            TagBinding,
            Tag.id == TagBinding.tag_id
        ).filter(
            TagBinding.target_id == self.id,
            TagBinding.tenant_id == self.tenant_id,
            Tag.tenant_id == self.tenant_id,
            Tag.type == 'knowledge'
        ).all()

        return tags if tags else []

    @staticmethod
    def gen_collection_name_by_id(dataset_id: str) -> str:
        normalized_dataset_id = dataset_id.replace("-", "_")
        return f'Vector_index_{normalized_dataset_id}_Node'


class DatasetProcessRule(db.Model):
    __tablename__ = 'dataset_process_rules'
    __table_args__ = (
        db.PrimaryKeyConstraint('id', name='dataset_process_rule_pkey'),
        db.Index('dataset_process_rule_dataset_id_idx', 'dataset_id'),
    )

    id = db.Column(StringUUID, nullable=False,
                   server_default=db.text('uuid_generate_v4()'))
    dataset_id = db.Column(StringUUID, nullable=False)
    mode = db.Column(db.String(255), nullable=False,
                     server_default=db.text("'automatic'::character varying"))
    rules = db.Column(db.Text, nullable=True)
    created_by = db.Column(StringUUID, nullable=False)
    created_at = db.Column(db.DateTime, nullable=False,
                           server_default=db.text('CURRENT_TIMESTAMP(0)'))

    MODES = ['automatic', 'custom']
    PRE_PROCESSING_RULES = ['remove_stopwords', 'remove_extra_spaces', 'remove_urls_emails']
    AUTOMATIC_RULES = {
        'pre_processing_rules': [
            {'id': 'remove_extra_spaces', 'enabled': True},
            {'id': 'remove_urls_emails', 'enabled': False}
        ],
        'segmentation': {
            'delimiter': '\n',
            'max_tokens': 500,
            'chunk_overlap': 50
        }
    }

    def to_dict(self):
        return {
            'id': self.id,
            'dataset_id': self.dataset_id,
            'mode': self.mode,
            'rules': self.rules_dict,
            'created_by': self.created_by,
            'created_at': self.created_at,
        }

    @property
    def rules_dict(self):
        try:
            return json.loads(self.rules) if self.rules else None
        except JSONDecodeError:
            return None


class Document(db.Model):
    __tablename__ = 'documents'
    __table_args__ = (
        db.PrimaryKeyConstraint('id', name='document_pkey'),
        db.Index('document_dataset_id_idx', 'dataset_id'),
        db.Index('document_is_paused_idx', 'is_paused'),
        db.Index('document_tenant_idx', 'tenant_id'),
    )

    # initial fields
    id = db.Column(StringUUID, nullable=False,
                   server_default=db.text('uuid_generate_v4()'))
    tenant_id = db.Column(StringUUID, nullable=False)
    dataset_id = db.Column(StringUUID, nullable=False)
    position = db.Column(db.Integer, nullable=False)
    data_source_type = db.Column(db.String(255), nullable=False)
    data_source_info = db.Column(db.Text, nullable=True)
    dataset_process_rule_id = db.Column(StringUUID, nullable=True)
    batch = db.Column(db.String(255), nullable=False)
    name = db.Column(db.String(255), nullable=False)
    created_from = db.Column(db.String(255), nullable=False)
    created_by = db.Column(StringUUID, nullable=False)
    created_api_request_id = db.Column(StringUUID, nullable=True)
    created_at = db.Column(db.DateTime, nullable=False,
                           server_default=db.text('CURRENT_TIMESTAMP(0)'))

    # start processing
    processing_started_at = db.Column(db.DateTime, nullable=True)

    # parsing
    file_id = db.Column(db.Text, nullable=True)
    word_count = db.Column(db.Integer, nullable=True)
    parsing_completed_at = db.Column(db.DateTime, nullable=True)

    # cleaning
    cleaning_completed_at = db.Column(db.DateTime, nullable=True)

    # split
    splitting_completed_at = db.Column(db.DateTime, nullable=True)

    # indexing
    tokens = db.Column(db.Integer, nullable=True)
    indexing_latency = db.Column(db.Float, nullable=True)
    completed_at = db.Column(db.DateTime, nullable=True)

    # pause
    is_paused = db.Column(db.Boolean, nullable=True, server_default=db.text('false'))
    paused_by = db.Column(StringUUID, nullable=True)
    paused_at = db.Column(db.DateTime, nullable=True)

    # error
    error = db.Column(db.Text, nullable=True)
    stopped_at = db.Column(db.DateTime, nullable=True)

    # basic fields
    indexing_status = db.Column(db.String(
        255), nullable=False, server_default=db.text("'waiting'::character varying"))
    enabled = db.Column(db.Boolean, nullable=False,
                        server_default=db.text('true'))
    disabled_at = db.Column(db.DateTime, nullable=True)
    disabled_by = db.Column(StringUUID, nullable=True)
    archived = db.Column(db.Boolean, nullable=False,
                         server_default=db.text('false'))
    archived_reason = db.Column(db.String(255), nullable=True)
    archived_by = db.Column(StringUUID, nullable=True)
    archived_at = db.Column(db.DateTime, nullable=True)
    updated_at = db.Column(db.DateTime, nullable=False,
                           server_default=db.text('CURRENT_TIMESTAMP(0)'))
    doc_type = db.Column(db.String(40), nullable=True)
    doc_metadata = db.Column(db.JSON, nullable=True)
    doc_form = db.Column(db.String(
        255), nullable=False, server_default=db.text("'text_model'::character varying"))
    doc_language = db.Column(db.String(255), nullable=True)

    DATA_SOURCES = ['upload_file', 'notion_import', 'website_crawl']

    @property
    def display_status(self):
        status = None
        if self.indexing_status == 'waiting':
            status = 'queuing'
        elif self.indexing_status not in ['completed', 'error', 'waiting'] and self.is_paused:
            status = 'paused'
        elif self.indexing_status in ['parsing', 'cleaning', 'splitting', 'indexing']:
            status = 'indexing'
        elif self.indexing_status == 'error':
            status = 'error'
        elif self.indexing_status == 'completed' and not self.archived and self.enabled:
            status = 'available'
        elif self.indexing_status == 'completed' and not self.archived and not self.enabled:
            status = 'disabled'
        elif self.indexing_status == 'completed' and self.archived:
            status = 'archived'
        return status

    @property
    def data_source_info_dict(self):
        if self.data_source_info:
            try:
                data_source_info_dict = json.loads(self.data_source_info)
            except JSONDecodeError:
                data_source_info_dict = {}

            return data_source_info_dict
        return None

    @property
    def data_source_detail_dict(self):
        if self.data_source_info:
            if self.data_source_type == 'upload_file':
                data_source_info_dict = json.loads(self.data_source_info)
                file_detail = db.session.query(UploadFile). \
                    filter(UploadFile.id == data_source_info_dict['upload_file_id']). \
                    one_or_none()
                if file_detail:
                    return {
                        'upload_file': {
                            'id': file_detail.id,
                            'name': file_detail.name,
                            'size': file_detail.size,
                            'extension': file_detail.extension,
                            'mime_type': file_detail.mime_type,
                            'created_by': file_detail.created_by,
                            'created_at': file_detail.created_at.timestamp()
                        }
                    }
            elif self.data_source_type == 'notion_import' or self.data_source_type == 'website_crawl':
                return json.loads(self.data_source_info)
        return {}

    @property
    def average_segment_length(self):
        if self.word_count and self.word_count != 0 and self.segment_count and self.segment_count != 0:
            return self.word_count // self.segment_count
        return 0

    @property
    def dataset_process_rule(self):
        if self.dataset_process_rule_id:
            return DatasetProcessRule.query.get(self.dataset_process_rule_id)
        return None

    @property
    def dataset(self):
        return db.session.query(Dataset).filter(Dataset.id == self.dataset_id).one_or_none()

    @property
    def segment_count(self):
        return DocumentSegment.query.filter(DocumentSegment.document_id == self.id).count()

    @property
    def hit_count(self):
        return DocumentSegment.query.with_entities(func.coalesce(func.sum(DocumentSegment.hit_count))) \
            .filter(DocumentSegment.document_id == self.id).scalar()

    def to_dict(self):
        return {
            'id': self.id,
            'tenant_id': self.tenant_id,
            'dataset_id': self.dataset_id,
            'position': self.position,
            'data_source_type': self.data_source_type,
            'data_source_info': self.data_source_info,
            'dataset_process_rule_id': self.dataset_process_rule_id,
            'batch': self.batch,
            'name': self.name,
            'created_from': self.created_from,
            'created_by': self.created_by,
            'created_api_request_id': self.created_api_request_id,
            'created_at': self.created_at,
            'processing_started_at': self.processing_started_at,
            'file_id': self.file_id,
            'word_count': self.word_count,
            'parsing_completed_at': self.parsing_completed_at,
            'cleaning_completed_at': self.cleaning_completed_at,
            'splitting_completed_at': self.splitting_completed_at,
            'tokens': self.tokens,
            'indexing_latency': self.indexing_latency,
            'completed_at': self.completed_at,
            'is_paused': self.is_paused,
            'paused_by': self.paused_by,
            'paused_at': self.paused_at,
            'error': self.error,
            'stopped_at': self.stopped_at,
            'indexing_status': self.indexing_status,
            'enabled': self.enabled,
            'disabled_at': self.disabled_at,
            'disabled_by': self.disabled_by,
            'archived': self.archived,
            'archived_reason': self.archived_reason,
            'archived_by': self.archived_by,
            'archived_at': self.archived_at,
            'updated_at': self.updated_at,
            'doc_type': self.doc_type,
            'doc_metadata': self.doc_metadata,
            'doc_form': self.doc_form,
            'doc_language': self.doc_language,
            'display_status': self.display_status,
            'data_source_info_dict': self.data_source_info_dict,
            'average_segment_length': self.average_segment_length,
            'dataset_process_rule': self.dataset_process_rule.to_dict() if self.dataset_process_rule else None,
            'dataset': self.dataset.to_dict() if self.dataset else None,
            'segment_count': self.segment_count,
            'hit_count': self.hit_count
        }

    @classmethod
    def from_dict(cls, data: dict):
        return cls(
            id=data.get('id'),
            tenant_id=data.get('tenant_id'),
            dataset_id=data.get('dataset_id'),
            position=data.get('position'),
            data_source_type=data.get('data_source_type'),
            data_source_info=data.get('data_source_info'),
            dataset_process_rule_id=data.get('dataset_process_rule_id'),
            batch=data.get('batch'),
            name=data.get('name'),
            created_from=data.get('created_from'),
            created_by=data.get('created_by'),
            created_api_request_id=data.get('created_api_request_id'),
            created_at=data.get('created_at'),
            processing_started_at=data.get('processing_started_at'),
            file_id=data.get('file_id'),
            word_count=data.get('word_count'),
            parsing_completed_at=data.get('parsing_completed_at'),
            cleaning_completed_at=data.get('cleaning_completed_at'),
            splitting_completed_at=data.get('splitting_completed_at'),
            tokens=data.get('tokens'),
            indexing_latency=data.get('indexing_latency'),
            completed_at=data.get('completed_at'),
            is_paused=data.get('is_paused'),
            paused_by=data.get('paused_by'),
            paused_at=data.get('paused_at'),
            error=data.get('error'),
            stopped_at=data.get('stopped_at'),
            indexing_status=data.get('indexing_status'),
            enabled=data.get('enabled'),
            disabled_at=data.get('disabled_at'),
            disabled_by=data.get('disabled_by'),
            archived=data.get('archived'),
            archived_reason=data.get('archived_reason'),
            archived_by=data.get('archived_by'),
            archived_at=data.get('archived_at'),
            updated_at=data.get('updated_at'),
            doc_type=data.get('doc_type'),
            doc_metadata=data.get('doc_metadata'),
            doc_form=data.get('doc_form'),
            doc_language=data.get('doc_language')
        )

class DocumentSegment(db.Model):
    __tablename__ = 'document_segments'
    __table_args__ = (
        db.PrimaryKeyConstraint('id', name='document_segment_pkey'),
        db.Index('document_segment_dataset_id_idx', 'dataset_id'),
        db.Index('document_segment_document_id_idx', 'document_id'),
        db.Index('document_segment_tenant_dataset_idx', 'dataset_id', 'tenant_id'),
        db.Index('document_segment_tenant_document_idx', 'document_id', 'tenant_id'),
        db.Index('document_segment_dataset_node_idx', 'dataset_id', 'index_node_id'),
        db.Index('document_segment_tenant_idx', 'tenant_id'),
    )

    # initial fields
    id = db.Column(StringUUID, nullable=False,
                   server_default=db.text('uuid_generate_v4()'))
    tenant_id = db.Column(StringUUID, nullable=False)
    dataset_id = db.Column(StringUUID, nullable=False)
    document_id = db.Column(StringUUID, nullable=False)
    position = db.Column(db.Integer, nullable=False)
    content = db.Column(db.Text, nullable=False)
    answer = db.Column(db.Text, nullable=True)
    word_count = db.Column(db.Integer, nullable=False)
    tokens = db.Column(db.Integer, nullable=False)

    # indexing fields
    keywords = db.Column(db.JSON, nullable=True)
    index_node_id = db.Column(db.String(255), nullable=True)
    index_node_hash = db.Column(db.String(255), nullable=True)

    # basic fields
    hit_count = db.Column(db.Integer, nullable=False, default=0)
    enabled = db.Column(db.Boolean, nullable=False,
                        server_default=db.text('true'))
    disabled_at = db.Column(db.DateTime, nullable=True)
    disabled_by = db.Column(StringUUID, nullable=True)
    status = db.Column(db.String(255), nullable=False,
                       server_default=db.text("'waiting'::character varying"))
    created_by = db.Column(StringUUID, nullable=False)
    created_at = db.Column(db.DateTime, nullable=False,
                           server_default=db.text('CURRENT_TIMESTAMP(0)'))
    updated_by = db.Column(StringUUID, nullable=True)
    updated_at = db.Column(db.DateTime, nullable=False,
                           server_default=db.text('CURRENT_TIMESTAMP(0)'))
    indexing_at = db.Column(db.DateTime, nullable=True)
    completed_at = db.Column(db.DateTime, nullable=True)
    error = db.Column(db.Text, nullable=True)
    stopped_at = db.Column(db.DateTime, nullable=True)

    @property
    def dataset(self):
        return db.session.query(Dataset).filter(Dataset.id == self.dataset_id).first()

    @property
    def document(self):
        return db.session.query(Document).filter(Document.id == self.document_id).first()

    @property
    def previous_segment(self):
        return db.session.query(DocumentSegment).filter(
            DocumentSegment.document_id == self.document_id,
            DocumentSegment.position == self.position - 1
        ).first()

    @property
    def next_segment(self):
        return db.session.query(DocumentSegment).filter(
            DocumentSegment.document_id == self.document_id,
            DocumentSegment.position == self.position + 1
        ).first()

    def get_sign_content(self):
        pattern = r"/files/([a-f0-9\-]+)/image-preview"
        text = self.content
        matches = re.finditer(pattern, text)
        signed_urls = []
        for match in matches:
            upload_file_id = match.group(1)
            nonce = os.urandom(16).hex()
            timestamp = str(int(time.time()))
            data_to_sign = f"image-preview|{upload_file_id}|{timestamp}|{nonce}"
            secret_key = current_app.config['SECRET_KEY'].encode()
            sign = hmac.new(secret_key, data_to_sign.encode(), hashlib.sha256).digest()
            encoded_sign = base64.urlsafe_b64encode(sign).decode()

            params = f"timestamp={timestamp}&nonce={nonce}&sign={encoded_sign}"
            signed_url = f"{match.group(0)}?{params}"
            signed_urls.append((match.start(), match.end(), signed_url))

        # Reconstruct the text with signed URLs
        offset = 0
        for start, end, signed_url in signed_urls:
            text = text[:start + offset] + signed_url + text[end + offset:]
            offset += len(signed_url) - (end - start)

        return text



class AppDatasetJoin(db.Model):
    __tablename__ = 'app_dataset_joins'
    __table_args__ = (
        db.PrimaryKeyConstraint('id', name='app_dataset_join_pkey'),
        db.Index('app_dataset_join_app_dataset_idx', 'dataset_id', 'app_id'),
    )

    id = db.Column(StringUUID, primary_key=True, nullable=False, server_default=db.text('uuid_generate_v4()'))
    app_id = db.Column(StringUUID, nullable=False)
    dataset_id = db.Column(StringUUID, nullable=False)
    created_at = db.Column(db.DateTime, nullable=False, server_default=db.func.current_timestamp())

    @property
    def app(self):
        return App.query.get(self.app_id)


class DatasetQuery(db.Model):
    __tablename__ = 'dataset_queries'
    __table_args__ = (
        db.PrimaryKeyConstraint('id', name='dataset_query_pkey'),
        db.Index('dataset_query_dataset_id_idx', 'dataset_id'),
    )

    id = db.Column(StringUUID, primary_key=True, nullable=False, server_default=db.text('uuid_generate_v4()'))
    dataset_id = db.Column(StringUUID, nullable=False)
    content = db.Column(db.Text, nullable=False)
    source = db.Column(db.String(255), nullable=False)
    source_app_id = db.Column(StringUUID, nullable=True)
    created_by_role = db.Column(db.String, nullable=False)
    created_by = db.Column(StringUUID, nullable=False)
    created_at = db.Column(db.DateTime, nullable=False, server_default=db.func.current_timestamp())


class DatasetKeywordTable(db.Model):
    __tablename__ = 'dataset_keyword_tables'
    __table_args__ = (
        db.PrimaryKeyConstraint('id', name='dataset_keyword_table_pkey'),
        db.Index('dataset_keyword_table_dataset_id_idx', 'dataset_id'),
    )

    id = db.Column(StringUUID, primary_key=True, server_default=db.text('uuid_generate_v4()'))
    dataset_id = db.Column(StringUUID, nullable=False, unique=True)
    keyword_table = db.Column(db.Text, nullable=False)
    data_source_type = db.Column(db.String(255), nullable=False,
                                 server_default=db.text("'database'::character varying"))

    @property
    def keyword_table_dict(self):
        class SetDecoder(json.JSONDecoder):
            def __init__(self, *args, **kwargs):
                super().__init__(object_hook=self.object_hook, *args, **kwargs)

            def object_hook(self, dct):
                if isinstance(dct, dict):
                    for keyword, node_idxs in dct.items():
                        if isinstance(node_idxs, list):
                            dct[keyword] = set(node_idxs)
                return dct

        # get dataset
        dataset = Dataset.query.filter_by(
            id=self.dataset_id
        ).first()
        if not dataset:
            return None
        if self.data_source_type == 'database':
            return json.loads(self.keyword_table, cls=SetDecoder) if self.keyword_table else None
        else:
            file_key = 'keyword_files/' + dataset.tenant_id + '/' + self.dataset_id + '.txt'
            try:
                keyword_table_text = storage.load_once(file_key)
                if keyword_table_text:
                    return json.loads(keyword_table_text.decode('utf-8'), cls=SetDecoder)
                return None
            except Exception as e:
                logging.exception(str(e))
                return None


class Embedding(db.Model):
    __tablename__ = 'embeddings'
    __table_args__ = (
        db.PrimaryKeyConstraint('id', name='embedding_pkey'),
        db.UniqueConstraint('model_name', 'hash', 'provider_name', name='embedding_hash_idx')
    )

    id = db.Column(StringUUID, primary_key=True, server_default=db.text('uuid_generate_v4()'))
    model_name = db.Column(db.String(40), nullable=False,
                           server_default=db.text("'text-embedding-ada-002'::character varying"))
    hash = db.Column(db.String(64), nullable=False)
    embedding = db.Column(db.LargeBinary, nullable=False)
    created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)'))
    provider_name = db.Column(db.String(40), nullable=False,
                              server_default=db.text("''::character varying"))

    def set_embedding(self, embedding_data: list[float]):
        self.embedding = pickle.dumps(embedding_data, protocol=pickle.HIGHEST_PROTOCOL)

    def get_embedding(self) -> list[float]:
        return pickle.loads(self.embedding)


class DatasetCollectionBinding(db.Model):
    __tablename__ = 'dataset_collection_bindings'
    __table_args__ = (
        db.PrimaryKeyConstraint('id', name='dataset_collection_bindings_pkey'),
        db.Index('provider_model_name_idx', 'provider_name', 'model_name')

    )

    id = db.Column(StringUUID, primary_key=True, server_default=db.text('uuid_generate_v4()'))
    provider_name = db.Column(db.String(40), nullable=False)
    model_name = db.Column(db.String(40), nullable=False)
    type = db.Column(db.String(40), server_default=db.text("'dataset'::character varying"), nullable=False)
    collection_name = db.Column(db.String(64), nullable=False)
    created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)'))