Migrations using Vector type from pgvector

[sanchezdiegog]

Hi everyone.
There is a solution for Vector type when I make a flask db migrate - "blabla" under migration->version->xxxxxxxxxxxxxx.py
appears
def upgrade():
# ### commands auto generated by Alembic - please adjust! ###
with op.batch_alter_table('documentos', schema=None) as batch_op:
batch_op.add_column(sa.Column('vec01', pgvector.sqlalchemy.vector.VECTOR(dim=3072), nullable=True))
batch_op.drop_column('embedding')
I need to import this
from pgvector.sqlalchemy import Vector

and modify to this.
sa.Column('vec01', Vector(dim=3072), nullable=True),

after this modification works perfect, as you know, if I need modify every model manually it's a waste of time and impossible to manage with hundred of tables.
Sorry for my english and thank you in advance.

[miguelgrinberg]

The question that you have is for Alembic. Flask-Migrate is just an integration, the actual migrations are generated by Alembic.

And here is the relevant section of the Alembic documentation:

For user-defined types, that is, any custom type that is not within the sqlalchemy. module namespace, by default Alembic will use the value of __module__ for the custom type:

Column("my_column", myapp.models.utils.types.MyCustomType())

The imports for the above type again must be made present within the migration, either manually, or by adding it to script.py.mako.