2023-05-15 08:51:32 +08:00
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import json
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import pickle
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from json import JSONDecodeError
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from sqlalchemy import func
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from sqlalchemy.dialects.postgresql import UUID
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from extensions.ext_database import db
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from models.account import Account
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from models.model import App, UploadFile
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2023-08-12 00:57:00 +08:00
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2023-05-15 08:51:32 +08:00
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class Dataset(db.Model):
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__tablename__ = 'datasets'
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__table_args__ = (
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db.PrimaryKeyConstraint('id', name='dataset_pkey'),
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db.Index('dataset_tenant_idx', 'tenant_id'),
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)
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INDEXING_TECHNIQUE_LIST = ['high_quality', 'economy']
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id = db.Column(UUID, server_default=db.text('uuid_generate_v4()'))
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tenant_id = db.Column(UUID, nullable=False)
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name = db.Column(db.String(255), nullable=False)
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description = db.Column(db.Text, nullable=True)
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provider = db.Column(db.String(255), nullable=False,
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server_default=db.text("'vendor'::character varying"))
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permission = db.Column(db.String(255), nullable=False,
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server_default=db.text("'only_me'::character varying"))
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data_source_type = db.Column(db.String(255))
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indexing_technique = db.Column(db.String(255), nullable=True)
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index_struct = db.Column(db.Text, nullable=True)
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created_by = db.Column(UUID, nullable=False)
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created_at = db.Column(db.DateTime, nullable=False,
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server_default=db.text('CURRENT_TIMESTAMP(0)'))
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updated_by = db.Column(UUID, nullable=True)
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updated_at = db.Column(db.DateTime, nullable=False,
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server_default=db.text('CURRENT_TIMESTAMP(0)'))
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2023-08-29 03:37:45 +08:00
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embedding_model = db.Column(db.String(255), nullable=True)
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embedding_model_provider = db.Column(db.String(255), nullable=True)
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2023-05-15 08:51:32 +08:00
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@property
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def dataset_keyword_table(self):
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dataset_keyword_table = db.session.query(DatasetKeywordTable).filter(
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DatasetKeywordTable.dataset_id == self.id).first()
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if dataset_keyword_table:
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return dataset_keyword_table
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return None
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@property
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def index_struct_dict(self):
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return json.loads(self.index_struct) if self.index_struct else None
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@property
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def created_by_account(self):
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return Account.query.get(self.created_by)
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@property
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def latest_process_rule(self):
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return DatasetProcessRule.query.filter(DatasetProcessRule.dataset_id == self.id) \
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.order_by(DatasetProcessRule.created_at.desc()).first()
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@property
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def app_count(self):
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return db.session.query(func.count(AppDatasetJoin.id)).filter(AppDatasetJoin.dataset_id == self.id).scalar()
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@property
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def document_count(self):
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return db.session.query(func.count(Document.id)).filter(Document.dataset_id == self.id).scalar()
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2023-06-25 16:49:14 +08:00
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@property
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def available_document_count(self):
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return db.session.query(func.count(Document.id)).filter(
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Document.dataset_id == self.id,
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Document.indexing_status == 'completed',
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Document.enabled == True,
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Document.archived == False
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).scalar()
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@property
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def available_segment_count(self):
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return db.session.query(func.count(DocumentSegment.id)).filter(
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DocumentSegment.dataset_id == self.id,
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DocumentSegment.status == 'completed',
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DocumentSegment.enabled == True
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).scalar()
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2023-05-15 08:51:32 +08:00
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@property
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def word_count(self):
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return Document.query.with_entities(func.coalesce(func.sum(Document.word_count))) \
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.filter(Document.dataset_id == self.id).scalar()
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class DatasetProcessRule(db.Model):
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__tablename__ = 'dataset_process_rules'
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__table_args__ = (
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db.PrimaryKeyConstraint('id', name='dataset_process_rule_pkey'),
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db.Index('dataset_process_rule_dataset_id_idx', 'dataset_id'),
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)
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id = db.Column(UUID, nullable=False,
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server_default=db.text('uuid_generate_v4()'))
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dataset_id = db.Column(UUID, nullable=False)
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mode = db.Column(db.String(255), nullable=False,
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server_default=db.text("'automatic'::character varying"))
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rules = db.Column(db.Text, nullable=True)
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created_by = db.Column(UUID, nullable=False)
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created_at = db.Column(db.DateTime, nullable=False,
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server_default=db.text('CURRENT_TIMESTAMP(0)'))
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MODES = ['automatic', 'custom']
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PRE_PROCESSING_RULES = ['remove_stopwords', 'remove_extra_spaces', 'remove_urls_emails']
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AUTOMATIC_RULES = {
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'pre_processing_rules': [
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{'id': 'remove_extra_spaces', 'enabled': True},
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{'id': 'remove_urls_emails', 'enabled': False}
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],
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'segmentation': {
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'delimiter': '\n',
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'max_tokens': 1000
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}
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}
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def to_dict(self):
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return {
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'id': self.id,
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'dataset_id': self.dataset_id,
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'mode': self.mode,
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'rules': self.rules_dict,
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'created_by': self.created_by,
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'created_at': self.created_at,
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}
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@property
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def rules_dict(self):
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try:
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return json.loads(self.rules) if self.rules else None
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except JSONDecodeError:
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return None
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class Document(db.Model):
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__tablename__ = 'documents'
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__table_args__ = (
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db.PrimaryKeyConstraint('id', name='document_pkey'),
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db.Index('document_dataset_id_idx', 'dataset_id'),
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db.Index('document_is_paused_idx', 'is_paused'),
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)
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# initial fields
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id = db.Column(UUID, nullable=False,
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server_default=db.text('uuid_generate_v4()'))
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tenant_id = db.Column(UUID, nullable=False)
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dataset_id = db.Column(UUID, nullable=False)
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position = db.Column(db.Integer, nullable=False)
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data_source_type = db.Column(db.String(255), nullable=False)
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data_source_info = db.Column(db.Text, nullable=True)
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dataset_process_rule_id = db.Column(UUID, nullable=True)
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batch = db.Column(db.String(255), nullable=False)
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name = db.Column(db.String(255), nullable=False)
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created_from = db.Column(db.String(255), nullable=False)
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created_by = db.Column(UUID, nullable=False)
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created_api_request_id = db.Column(UUID, nullable=True)
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created_at = db.Column(db.DateTime, nullable=False,
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server_default=db.text('CURRENT_TIMESTAMP(0)'))
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# start processing
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processing_started_at = db.Column(db.DateTime, nullable=True)
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# parsing
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file_id = db.Column(db.Text, nullable=True)
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word_count = db.Column(db.Integer, nullable=True)
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parsing_completed_at = db.Column(db.DateTime, nullable=True)
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# cleaning
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cleaning_completed_at = db.Column(db.DateTime, nullable=True)
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# split
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splitting_completed_at = db.Column(db.DateTime, nullable=True)
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# indexing
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tokens = db.Column(db.Integer, nullable=True)
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indexing_latency = db.Column(db.Float, nullable=True)
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completed_at = db.Column(db.DateTime, nullable=True)
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# pause
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is_paused = db.Column(db.Boolean, nullable=True, server_default=db.text('false'))
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paused_by = db.Column(UUID, nullable=True)
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paused_at = db.Column(db.DateTime, nullable=True)
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# error
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error = db.Column(db.Text, nullable=True)
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stopped_at = db.Column(db.DateTime, nullable=True)
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# basic fields
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indexing_status = db.Column(db.String(
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255), nullable=False, server_default=db.text("'waiting'::character varying"))
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enabled = db.Column(db.Boolean, nullable=False,
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server_default=db.text('true'))
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disabled_at = db.Column(db.DateTime, nullable=True)
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disabled_by = db.Column(UUID, nullable=True)
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archived = db.Column(db.Boolean, nullable=False,
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server_default=db.text('false'))
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archived_reason = db.Column(db.String(255), nullable=True)
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archived_by = db.Column(UUID, nullable=True)
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archived_at = db.Column(db.DateTime, nullable=True)
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updated_at = db.Column(db.DateTime, nullable=False,
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server_default=db.text('CURRENT_TIMESTAMP(0)'))
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doc_type = db.Column(db.String(40), nullable=True)
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doc_metadata = db.Column(db.JSON, nullable=True)
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2023-07-28 20:47:15 +08:00
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doc_form = db.Column(db.String(
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255), nullable=False, server_default=db.text("'text_model'::character varying"))
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2023-08-18 17:37:31 +08:00
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doc_language = db.Column(db.String(255), nullable=True)
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2023-05-15 08:51:32 +08:00
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2023-06-16 21:47:51 +08:00
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DATA_SOURCES = ['upload_file', 'notion_import']
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2023-05-15 08:51:32 +08:00
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@property
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def display_status(self):
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status = None
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if self.indexing_status == 'waiting':
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status = 'queuing'
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elif self.indexing_status not in ['completed', 'error', 'waiting'] and self.is_paused:
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status = 'paused'
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elif self.indexing_status in ['parsing', 'cleaning', 'splitting', 'indexing']:
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status = 'indexing'
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elif self.indexing_status == 'error':
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status = 'error'
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elif self.indexing_status == 'completed' and not self.archived and self.enabled:
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status = 'available'
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elif self.indexing_status == 'completed' and not self.archived and not self.enabled:
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status = 'disabled'
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elif self.indexing_status == 'completed' and self.archived:
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status = 'archived'
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return status
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@property
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def data_source_info_dict(self):
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if self.data_source_info:
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try:
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data_source_info_dict = json.loads(self.data_source_info)
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except JSONDecodeError:
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data_source_info_dict = {}
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return data_source_info_dict
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return None
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@property
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def data_source_detail_dict(self):
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if self.data_source_info:
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if self.data_source_type == 'upload_file':
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data_source_info_dict = json.loads(self.data_source_info)
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file_detail = db.session.query(UploadFile). \
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filter(UploadFile.id == data_source_info_dict['upload_file_id']). \
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one_or_none()
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if file_detail:
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return {
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'upload_file': {
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'id': file_detail.id,
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'name': file_detail.name,
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'size': file_detail.size,
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'extension': file_detail.extension,
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'mime_type': file_detail.mime_type,
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'created_by': file_detail.created_by,
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'created_at': file_detail.created_at.timestamp()
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}
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}
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2023-06-16 21:47:51 +08:00
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elif self.data_source_type == 'notion_import':
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return json.loads(self.data_source_info)
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2023-05-15 08:51:32 +08:00
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return {}
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@property
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def average_segment_length(self):
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if self.word_count and self.word_count != 0 and self.segment_count and self.segment_count != 0:
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2023-08-12 00:57:00 +08:00
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return self.word_count // self.segment_count
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2023-05-15 08:51:32 +08:00
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return 0
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@property
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def dataset_process_rule(self):
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if self.dataset_process_rule_id:
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return DatasetProcessRule.query.get(self.dataset_process_rule_id)
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return None
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@property
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def dataset(self):
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2023-06-25 16:49:14 +08:00
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return db.session.query(Dataset).filter(Dataset.id == self.dataset_id).one_or_none()
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2023-05-15 08:51:32 +08:00
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@property
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def segment_count(self):
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return DocumentSegment.query.filter(DocumentSegment.document_id == self.id).count()
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@property
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def hit_count(self):
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return DocumentSegment.query.with_entities(func.coalesce(func.sum(DocumentSegment.hit_count))) \
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.filter(DocumentSegment.document_id == self.id).scalar()
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class DocumentSegment(db.Model):
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__tablename__ = 'document_segments'
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__table_args__ = (
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db.PrimaryKeyConstraint('id', name='document_segment_pkey'),
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db.Index('document_segment_dataset_id_idx', 'dataset_id'),
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db.Index('document_segment_document_id_idx', 'document_id'),
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db.Index('document_segment_tenant_dataset_idx', 'dataset_id', 'tenant_id'),
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db.Index('document_segment_tenant_document_idx', 'document_id', 'tenant_id'),
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db.Index('document_segment_dataset_node_idx', 'dataset_id', 'index_node_id'),
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)
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# initial fields
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id = db.Column(UUID, nullable=False,
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server_default=db.text('uuid_generate_v4()'))
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tenant_id = db.Column(UUID, nullable=False)
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dataset_id = db.Column(UUID, nullable=False)
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document_id = db.Column(UUID, nullable=False)
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position = db.Column(db.Integer, nullable=False)
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content = db.Column(db.Text, nullable=False)
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2023-07-28 20:47:15 +08:00
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answer = db.Column(db.Text, nullable=True)
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2023-05-15 08:51:32 +08:00
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word_count = db.Column(db.Integer, nullable=False)
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tokens = db.Column(db.Integer, nullable=False)
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# indexing fields
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keywords = db.Column(db.JSON, nullable=True)
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index_node_id = db.Column(db.String(255), nullable=True)
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index_node_hash = db.Column(db.String(255), nullable=True)
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# basic fields
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hit_count = db.Column(db.Integer, nullable=False, default=0)
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enabled = db.Column(db.Boolean, nullable=False,
|
|
|
|
server_default=db.text('true'))
|
|
|
|
disabled_at = db.Column(db.DateTime, nullable=True)
|
|
|
|
disabled_by = db.Column(UUID, nullable=True)
|
|
|
|
status = db.Column(db.String(255), nullable=False,
|
|
|
|
server_default=db.text("'waiting'::character varying"))
|
|
|
|
created_by = db.Column(UUID, nullable=False)
|
|
|
|
created_at = db.Column(db.DateTime, nullable=False,
|
|
|
|
server_default=db.text('CURRENT_TIMESTAMP(0)'))
|
2023-07-28 20:47:15 +08:00
|
|
|
updated_by = db.Column(UUID, nullable=True)
|
|
|
|
updated_at = db.Column(db.DateTime, nullable=False,
|
|
|
|
server_default=db.text('CURRENT_TIMESTAMP(0)'))
|
2023-05-15 08:51:32 +08:00
|
|
|
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()
|
|
|
|
|
|
|
|
|
|
|
|
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(UUID, primary_key=True, nullable=False, server_default=db.text('uuid_generate_v4()'))
|
|
|
|
app_id = db.Column(UUID, nullable=False)
|
|
|
|
dataset_id = db.Column(UUID, 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(UUID, primary_key=True, nullable=False, server_default=db.text('uuid_generate_v4()'))
|
|
|
|
dataset_id = db.Column(UUID, nullable=False)
|
|
|
|
content = db.Column(db.Text, nullable=False)
|
|
|
|
source = db.Column(db.String(255), nullable=False)
|
|
|
|
source_app_id = db.Column(UUID, nullable=True)
|
|
|
|
created_by_role = db.Column(db.String, nullable=False)
|
|
|
|
created_by = db.Column(UUID, 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(UUID, primary_key=True, server_default=db.text('uuid_generate_v4()'))
|
|
|
|
dataset_id = db.Column(UUID, nullable=False, unique=True)
|
|
|
|
keyword_table = db.Column(db.Text, nullable=False)
|
|
|
|
|
|
|
|
@property
|
|
|
|
def keyword_table_dict(self):
|
2023-06-25 16:49:14 +08:00
|
|
|
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
|
|
|
|
|
|
|
|
return json.loads(self.keyword_table, cls=SetDecoder) if self.keyword_table else None
|
2023-05-15 08:51:32 +08:00
|
|
|
|
|
|
|
|
|
|
|
class Embedding(db.Model):
|
|
|
|
__tablename__ = 'embeddings'
|
|
|
|
__table_args__ = (
|
|
|
|
db.PrimaryKeyConstraint('id', name='embedding_pkey'),
|
2023-08-12 00:57:00 +08:00
|
|
|
db.UniqueConstraint('model_name', 'hash', name='embedding_hash_idx')
|
2023-05-15 08:51:32 +08:00
|
|
|
)
|
|
|
|
|
|
|
|
id = db.Column(UUID, primary_key=True, server_default=db.text('uuid_generate_v4()'))
|
2023-08-12 00:57:00 +08:00
|
|
|
model_name = db.Column(db.String(40), nullable=False,
|
|
|
|
server_default=db.text("'text-embedding-ada-002'::character varying"))
|
2023-05-15 08:51:32 +08:00
|
|
|
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)'))
|
|
|
|
|
|
|
|
def set_embedding(self, embedding_data: list[float]):
|
|
|
|
self.embedding = pickle.dumps(embedding_data, protocol=pickle.HIGHEST_PROTOCOL)
|
|
|
|
|
|
|
|
def get_embedding(self) -> list[float]:
|
2023-08-12 00:57:00 +08:00
|
|
|
return pickle.loads(self.embedding)
|