Files
eveAI/common/models/document.py
Josako bf6d91527b Add extra chunking information in Tenant schema
Add extra scripts for flask-migrate to support refactoring
2024-05-08 17:40:42 +02:00

110 lines
4.6 KiB
Python

from common.extensions import db
from .user import User, Tenant
from pgvector.sqlalchemy import Vector
class Document(db.Model):
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(100), nullable=False)
tenant_id = db.Column(db.Integer, db.ForeignKey(Tenant.id), nullable=False)
valid_from = db.Column(db.DateTime, nullable=True)
valid_to = db.Column(db.DateTime, nullable=True)
# Versioning Information
created_at = db.Column(db.DateTime, nullable=False, server_default=db.func.now())
created_by = db.Column(db.Integer, db.ForeignKey(User.id), nullable=False)
updated_at = db.Column(db.DateTime, nullable=False, server_default=db.func.now(), onupdate=db.func.now())
updated_by = db.Column(db.Integer, db.ForeignKey(User.id))
# Relations
languages = db.relationship('DocumentLanguage', backref='document', lazy=True)
def __repr__(self):
return f"<Document {self.id}: {self.name}>"
class DocumentLanguage(db.Model):
id = db.Column(db.Integer, primary_key=True)
document_id = db.Column(db.Integer, db.ForeignKey(Document.id), nullable=False)
language = db.Column(db.String(2), nullable=False)
user_context = db.Column(db.Text, nullable=True)
system_context = db.Column(db.Text, nullable=True)
latest_version_id = db.Column(db.Integer, db.ForeignKey('document_version.id'), nullable=True)
# Versioning Information
created_at = db.Column(db.DateTime, nullable=False, server_default=db.func.now())
created_by = db.Column(db.Integer, db.ForeignKey(User.id), nullable=False)
updated_at = db.Column(db.DateTime, nullable=False, server_default=db.func.now(), onupdate=db.func.now())
updated_by = db.Column(db.Integer, db.ForeignKey(User.id))
# Relations
versions = db.relationship(
'DocumentVersion',
backref='document_language',
lazy='joined',
foreign_keys='DocumentVersion.doc_lang_id'
)
latest_version = db.relationship(
'DocumentVersion',
uselist=False,
foreign_keys=[latest_version_id]
)
def __repr__(self):
return f"<DocumentLanguage {self.document_id}.{self.language}>"
class DocumentVersion(db.Model):
id = db.Column(db.Integer, primary_key=True)
doc_lang_id = db.Column(db.Integer, db.ForeignKey(DocumentLanguage.id), nullable=False)
url = db.Column(db.String(200), nullable=True)
file_location = db.Column(db.String(255), nullable=True)
file_name = db.Column(db.String(200), nullable=True)
file_type = db.Column(db.String(20), nullable=True)
# Versioning Information
created_at = db.Column(db.DateTime, nullable=False, server_default=db.func.now())
created_by = db.Column(db.Integer, db.ForeignKey(User.id))
updated_at = db.Column(db.DateTime, nullable=False, server_default=db.func.now(), onupdate=db.func.now())
updated_by = db.Column(db.Integer, db.ForeignKey(User.id))
# Processing Information
processing = db.Column(db.Boolean, nullable=False, default=False)
processing_started_at = db.Column(db.DateTime, nullable=True)
processing_finished_at = db.Column(db.DateTime, nullable=True)
processing_error = db.Column(db.String(255), nullable=True)
# Relations
embeddings = db.relationship('EmbeddingMistral', backref='document_version', lazy=True)
def __repr__(self):
return f"<DocumentVersion {self.document_language.document_id}.{self.document_language.language}>.{self.id}>"
def calc_file_location(self):
return f"{self.document_language.document.tenant_id}/{self.document_language.document.id}/{self.document_language.language}"
def calc_file_name(self):
return f"{self.id}.{self.file_type}"
class EmbeddingMistral(db.Model):
id = db.Column(db.Integer, primary_key=True)
doc_vers_id = db.Column(db.Integer, db.ForeignKey(DocumentVersion.id), nullable=False)
active = db.Column(db.Boolean, nullable=False, default=True)
chunk = db.Column(db.Text, nullable=False)
# 1024 is the MISTRAL Embedding dimension.
# If another embedding model is chosen, this dimension may need to be changed.
embedding = db.Column(Vector(1024), nullable=False)
class EmbeddingSmallOpenAI(db.Model):
id = db.Column(db.Integer, primary_key=True)
doc_vers_id = db.Column(db.Integer, db.ForeignKey(DocumentVersion.id), nullable=False)
active = db.Column(db.Boolean, nullable=False, default=True)
chunk = db.Column(db.Text, nullable=False)
# 1536 is the OpenAI Small Embedding dimension.
# If another embedding model is chosen, this dimension may need to be changed.
embedding = db.Column(Vector(1536), nullable=False)