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dep: bump pgvecto-rs client from 0.1.x to 0.2.x (#6891)

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This commit is contained in:
Bowen Liang
2024-08-02 15:51:23 +08:00
committed by GitHub
parent 7ab04e17e7
commit 6aa02f8c63
5 changed files with 19 additions and 20 deletions
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4
api/core/rag/datasource/vdb/pgvecto_rs/pgvecto_rs.py
View File

@@ -4,7 +4,7 @@ from typing import Any
from uuid import UUID, uuid4
from numpy import ndarray
from pgvecto_rs.sqlalchemy import Vector
from pgvecto_rs.sqlalchemy import VECTOR
from pydantic import BaseModel, model_validator
from sqlalchemy import Float, String, create_engine, insert, select, text
from sqlalchemy import text as sql_text
@@ -67,7 +67,7 @@ class PGVectoRS(BaseVector):
)
text: Mapped[str] = mapped_column(String)
meta: Mapped[dict] = mapped_column(postgresql.JSONB)
vector: Mapped[ndarray] = mapped_column(Vector(dim))
vector: Mapped[ndarray] = mapped_column(VECTOR(dim))
self._table = _Table
self._distance_op = "<=>"

8
api/core/rag/datasource/vdb/relyt/relyt_vector.py
View File

@@ -105,7 +105,7 @@ class RelytVector(BaseVector):
redis_client.set(collection_exist_cache_key, 1, ex=3600)
def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs):
from pgvecto_rs.sqlalchemy import Vector
from pgvecto_rs.sqlalchemy import VECTOR
ids = [str(uuid.uuid1()) for _ in documents]
metadatas = [d.metadata for d in documents]
@@ -118,7 +118,7 @@ class RelytVector(BaseVector):
self._collection_name,
Base.metadata,
Column("id", TEXT, primary_key=True),
Column("embedding", Vector(len(embeddings[0]))),
Column("embedding", VECTOR(len(embeddings[0]))),
Column("document", String, nullable=True),
Column("metadata", JSON, nullable=True),
extend_existing=True,
@@ -169,7 +169,7 @@ class RelytVector(BaseVector):
Args:
ids: List of ids to delete.
"""
from pgvecto_rs.sqlalchemy import Vector
from pgvecto_rs.sqlalchemy import VECTOR
if ids is None:
raise ValueError("No ids provided to delete.")
@@ -179,7 +179,7 @@ class RelytVector(BaseVector):
self._collection_name,
Base.metadata,
Column("id", TEXT, primary_key=True),
Column("embedding", Vector(self.embedding_dimension)),
Column("embedding", VECTOR(self.embedding_dimension)),
Column("document", String, nullable=True),
Column("metadata", JSON, nullable=True),
extend_existing=True,