import numpy as np

from pgvector.sqlalchemy import Vector

import pytest

from sqlalchemy import create_engine, select, text, MetaData, Table, Column, Index, Integer

from sqlalchemy.exc import StatementError

from sqlalchemy.orm import declarative_base, Session

engine = create_engine('postgresql+psycopg2://localhost/pgvector_python_test', future=True)

with engine.connect() as con:

con.execute(text('CREATE EXTENSION IF NOT EXISTS vector'))

con.commit()

Base = declarative_base()

class Item(Base):

__tablename__ = 'orm_item'

id = Column(Integer, primary_key=True)

factors = Column(Vector(3))

Base.metadata.drop_all(engine)

Base.metadata.create_all(engine)

def create_items():

vectors = [

[1, 1, 1],

[2, 2, 2],

[1, 1, 2]

]

session = Session(engine)

for i, v in enumerate(vectors):

session.add(Item(id=i + 1, factors=v))

session.commit()

class TestSqlalchemy:

def setup_method(self, test_method):

with Session(engine) as session:

session.query(Item).delete()

session.commit()

def test_core(self):

metadata = MetaData()

item_table = Table(

'core_item',

metadata,

Column('id', Integer, primary_key=True),

Column('factors', Vector(3))

)

metadata.drop_all(engine)

metadata.create_all(engine)

index = Index(

'my_core_index',

item_table.c.factors,

postgresql_using='ivfflat',

postgresql_with={'lists': 1},

postgresql_ops={'factors': 'vector_l2_ops'}

)

index.create(engine)

def test_orm(self):

item = Item(factors=np.array([1.5, 2, 3]))

item2 = Item(factors=[4, 5, 6])

item3 = Item()

session = Session(engine)

session.add(item)

session.add(item2)

session.add(item3)

session.commit()

stmt = select(Item)

with Session(engine) as session:

items = [v[0] for v in session.execute(stmt).all()]

assert items[0].id == 1

assert items[1].id == 2

assert items[2].id == 3

assert np.array_equal(items[0].factors, np.array([1.5, 2, 3]))

assert items[0].factors.dtype == np.float32

assert np.array_equal(items[1].factors, np.array([4, 5, 6]))

assert items[1].factors.dtype == np.float32

assert items[2].factors is None

def test_l2_distance(self):

create_items()

with Session(engine) as session:

items = session.query(Item).order_by(Item.factors.l2_distance([1, 1, 1])).all()

assert [v.id for v in items] == [1, 3, 2]

def test_max_inner_product(self):

create_items()

with Session(engine) as session:

items = session.query(Item).order_by(Item.factors.max_inner_product([1, 1, 1])).all()

assert [v.id for v in items] == [2, 3, 1]

def test_cosine_distance(self):

create_items()

with Session(engine) as session:

items = session.query(Item).order_by(Item.factors.cosine_distance([1, 1, 1])).all()

assert [v.id for v in items] == [1, 2, 3]

def test_bad_dimensions(self):

item = Item(factors=[1, 2])

session = Session(engine)

session.add(item)

with pytest.raises(StatementError, match='expected 3 dimensions, not 2'):

session.commit()

def test_bad_ndim(self):

item = Item(factors=np.array([[1, 2, 3]]))

session = Session(engine)

session.add(item)

with pytest.raises(StatementError, match='expected ndim to be 1'):

session.commit()

def test_bad_dtype(self):

item = Item(factors=np.array(['one', 'two', 'three']))

session = Session(engine)

session.add(item)

with pytest.raises(StatementError, match='dtype must be numeric'):

session.commit()