Add connection args for pgvector vector store (#11930)

- **Description:** sqlalchemy create_engine() does not take into account
connect_args which are mandatory for managed PGSQL instances on cloud
providers (ssl_context for example).
Also re-enabled create_vector_extension at post_init for using pgvector
class seamlessly
- **Tag maintainer:** @baskaryan, @eyurtsev, @hwchase17.

---------

Co-authored-by: Sami Bargaoui <bargaoui.sam@gmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>

libs/langchain/langchain/vectorstores/pgvector.py

@@ -84,6 +84,7 @@ class PGVector(VectorStore):
         distance_strategy: The distance strategy to use. (default: COSINE)
         pre_delete_collection: If True, will delete the collection if it exists.
             (default: False). Useful for testing.
+        engine_args: SQLAlchemy's create engine arguments.
 
     Example:
         .. code-block:: python
@@ -114,6 +115,8 @@ class PGVector(VectorStore):
         pre_delete_collection: bool = False,
         logger: Optional[logging.Logger] = None,
         relevance_score_fn: Optional[Callable[[float], float]] = None,
+        *,
+        engine_args: Optional[dict[str, Any]] = None,
     ) -> None:
         self.connection_string = connection_string
         self.embedding_function = embedding_function
@@ -123,6 +126,7 @@ class PGVector(VectorStore):
         self.pre_delete_collection = pre_delete_collection
         self.logger = logger or logging.getLogger(__name__)
         self.override_relevance_score_fn = relevance_score_fn
+        self.engine_args = engine_args or {}
         self.__post_init__()
 
     def __post_init__(
@@ -132,7 +136,7 @@ class PGVector(VectorStore):
         Initialize the store.
         """
         self._conn = self.connect()
-        # self.create_vector_extension()
+        self.create_vector_extension()
         from langchain.vectorstores._pgvector_data_models import (
             CollectionStore,
             EmbeddingStore,
@@ -148,7 +152,7 @@ class PGVector(VectorStore):
         return self.embedding_function
 
     def connect(self) -> sqlalchemy.engine.Connection:
-        engine = sqlalchemy.create_engine(self.connection_string)
+        engine = sqlalchemy.create_engine(self.connection_string, **self.engine_args)
         conn = engine.connect()
         return conn
 
@@ -159,7 +163,7 @@ class PGVector(VectorStore):
                 session.execute(statement)
                 session.commit()
         except Exception as e:
-            self.logger.exception(e)
+            raise Exception(f"Failed to create vector extension: {e}") from e
 
     def create_tables_if_not_exists(self) -> None:
         with self._conn.begin():