From 109927cdb29b3b7b1255b9561f21e21f1be41640 Mon Sep 17 00:00:00 2001
From: Hristo Stoychev <hnstoychev@gmail.com>
Date: Tue, 2 May 2023 06:58:22 +0300
Subject: [PATCH] Make project compatible with SQLAlchemy 1.3.* (#3862)

Related to [this
issue.](https://github.com/hwchase17/langchain/issues/3655#issuecomment-1529415363)

The `Mapped` SQLAlchemy class is introduced in SQLAlchemy 1.4 but the
migration from 1.3 to 1.4 is quite challenging so, IMO, it's better to
keep backwards compatibility and not change the SQLAlchemy requirements
just because of type annotations.
---
 langchain/vectorstores/analyticdb.py | 4 ++--
 langchain/vectorstores/pgvector.py   | 4 ++--
 pyproject.toml                       | 2 +-
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/langchain/vectorstores/analyticdb.py b/langchain/vectorstores/analyticdb.py
index 6ed8e5b0..6ec5fbad 100644
--- a/langchain/vectorstores/analyticdb.py
+++ b/langchain/vectorstores/analyticdb.py
@@ -8,7 +8,7 @@ from typing import Any, Dict, Iterable, List, Optional, Tuple
 import sqlalchemy
 from sqlalchemy import REAL, Index
 from sqlalchemy.dialects.postgresql import ARRAY, JSON, UUID
-from sqlalchemy.orm import Mapped, Session, declarative_base, relationship
+from sqlalchemy.orm import Session, declarative_base, relationship
 from sqlalchemy.sql.expression import func
 
 from langchain.docstore.document import Document
@@ -70,7 +70,7 @@ class CollectionStore(BaseModel):
 class EmbeddingStore(BaseModel):
     __tablename__ = "langchain_pg_embedding"
 
-    collection_id: Mapped[UUID] = sqlalchemy.Column(
+    collection_id = sqlalchemy.Column(
         UUID(as_uuid=True),
         sqlalchemy.ForeignKey(
             f"{CollectionStore.__tablename__}.uuid",
diff --git a/langchain/vectorstores/pgvector.py b/langchain/vectorstores/pgvector.py
index d0101771..a128241d 100644
--- a/langchain/vectorstores/pgvector.py
+++ b/langchain/vectorstores/pgvector.py
@@ -9,7 +9,7 @@ from typing import Any, Dict, Iterable, List, Optional, Tuple, Type
 import sqlalchemy
 from pgvector.sqlalchemy import Vector
 from sqlalchemy.dialects.postgresql import JSON, UUID
-from sqlalchemy.orm import Mapped, Session, declarative_base, relationship
+from sqlalchemy.orm import Session, declarative_base, relationship
 
 from langchain.docstore.document import Document
 from langchain.embeddings.base import Embeddings
@@ -70,7 +70,7 @@ class CollectionStore(BaseModel):
 class EmbeddingStore(BaseModel):
     __tablename__ = "langchain_pg_embedding"
 
-    collection_id: Mapped[UUID] = sqlalchemy.Column(
+    collection_id = sqlalchemy.Column(
         UUID(as_uuid=True),
         sqlalchemy.ForeignKey(
             f"{CollectionStore.__tablename__}.uuid",
diff --git a/pyproject.toml b/pyproject.toml
index 5606e649..29e7be5a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,7 +13,7 @@ langchain-server = "langchain.server:main"
 [tool.poetry.dependencies]
 python = ">=3.8.1,<4.0"
 pydantic = "^1"
-SQLAlchemy = ">1.4,<3"
+SQLAlchemy = ">=1.3,<3"
 requests = "^2"
 PyYAML = ">=5.4.1"
 numpy = "^1"