added a index for the VEctor DB

This commit is contained in:
2026-06-13 20:14:20 -04:00
parent bb3c433b9d
commit 5e2252641d
3 changed files with 81 additions and 3 deletions
@@ -0,0 +1,54 @@
"""add 1024 ebook embedding cosine index.
Revision ID: c460105682d2
Revises: 2db132cace1a
Create Date: 2026-06-13 19:53:45.680289
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from alembic import op
from python.orm import RichieBase
if TYPE_CHECKING:
from collections.abc import Sequence
# revision identifiers, used by Alembic.
revision: str = "c460105682d2"
down_revision: str | None = "2db132cace1a"
branch_labels: str | Sequence[str] | None = None
depends_on: str | Sequence[str] | None = None
schema = RichieBase.schema_name
def upgrade() -> None:
"""Upgrade."""
# ### commands auto generated by Alembic - please adjust! ###
op.create_index(
"ix_ebook_chunk_embedding_1024_embedding_cosine",
"ebook_chunk_embedding_1024",
["embedding"],
unique=False,
schema=schema,
postgresql_using="hnsw",
postgresql_ops={"embedding": "vector_cosine_ops"},
)
# ### end Alembic commands ###
def downgrade() -> None:
"""Downgrade."""
# ### commands auto generated by Alembic - please adjust! ###
op.drop_index(
"ix_ebook_chunk_embedding_1024_embedding_cosine",
table_name="ebook_chunk_embedding_1024",
schema=schema,
postgresql_using="hnsw",
postgresql_ops={"embedding": "vector_cosine_ops"},
)
# ### end Alembic commands ###
+10 -2
View File
@@ -5,7 +5,7 @@ from __future__ import annotations
from datetime import datetime
from pgvector.sqlalchemy import Vector
from sqlalchemy import BigInteger, Boolean, DateTime, ForeignKey, String, UniqueConstraint
from sqlalchemy import BigInteger, Boolean, DateTime, ForeignKey, Index, String, UniqueConstraint
from sqlalchemy.orm import Mapped, mapped_column, relationship
from python.orm.richie.base import TableBase, TableBaseBig
@@ -101,7 +101,15 @@ class EbookChunkEmbedding1024(TableBaseBig):
"""1024-dimensional chunk embedding."""
__tablename__ = "ebook_chunk_embedding_1024"
__table_args__ = (UniqueConstraint("chunk_id", "model_id"),)
__table_args__ = (
UniqueConstraint("chunk_id", "model_id"),
Index(
"ix_ebook_chunk_embedding_1024_embedding_cosine",
"embedding",
postgresql_using="hnsw",
postgresql_ops={"embedding": "vector_cosine_ops"},
),
)
chunk_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_chunk.id", ondelete="CASCADE"))
model_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_embedding_model.id", ondelete="CASCADE"))