fix: Resolve issue regrading not having Vector column type defined when using vector search

Issue happens when search is called in a session without previously adding data or creating tables as an import of Vector column type was missing

Fix

cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py

@@ -24,19 +24,6 @@ class IndexSchema(DataPoint):
         "index_fields": ["text"]
     }
 
-def singleton(class_):
-    # Note: Using this singleton as a decorator to a class removes
-    # the option to use class methods for that class
-    instances = {}
-
-    def getinstance(*args, **kwargs):
-        if class_ not in instances:
-            instances[class_] = class_(*args, **kwargs)
-        return instances[class_]
-
-    return getinstance
-
-@singleton
 class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
 
     def __init__(
@@ -51,6 +38,11 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
         self.engine = create_async_engine(self.db_uri)
         self.sessionmaker = async_sessionmaker(bind=self.engine, expire_on_commit=False)
 
+        # Has to be imported at class level
+        # Functions reading tables from database need to know what a Vector column type is
+        from pgvector.sqlalchemy import Vector
+        self.Vector = Vector
+
     async def embed_data(self, data: list[str]) -> list[list[float]]:
         return await self.embedding_engine.embed_text(data)
 
@@ -70,7 +62,6 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
 
         if not await self.has_collection(collection_name):
 
-            from pgvector.sqlalchemy import Vector
             class PGVectorDataPoint(Base):
                 __tablename__ = collection_name
                 __table_args__ = {"extend_existing": True}
@@ -80,7 +71,7 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
                 )
                 id: Mapped[data_point_types["id"]]
                 payload = Column(JSON)
-                vector = Column(Vector(vector_size))
+                vector = Column(self.Vector(vector_size))
 
                 def __init__(self, id, payload, vector):
                     self.id = id
@@ -108,7 +99,6 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
 
         vector_size = self.embedding_engine.get_vector_size()
 
-        from pgvector.sqlalchemy import Vector
         class PGVectorDataPoint(Base):
             __tablename__ = collection_name
             __table_args__ = {"extend_existing": True}
@@ -118,7 +108,7 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
             )
             id: Mapped[type(data_points[0].id)]
             payload = Column(JSON)
-            vector = Column(Vector(vector_size))
+            vector = Column(self.Vector(vector_size))
 
             def __init__(self, id, payload, vector):
                 self.id = id