Fix a bug with pagination and orderby with and without modern pagination

langchain_iris/vectorstores.py

@@ -521,22 +521,37 @@ def similarity_search_with_score_by_vector(
 
         # Execute the query and fetch the results
         with Session(self._conn) as session:
-            results: Sequence[Row] = (
+            # Create the distance column explicitly to avoid textual label reference issues
+            distance_expr = (
+                self.distance_strategy(embedding)
+                if self.native_vector
+                else self.table.c.embedding.func(
+                    self.distance_strategy, embedding
+                )
+            )
+
+            distance_col = distance_expr.label("distance")
+
+            # Note: For IRIS without modern pagination support, using .limit() with .order_by()
+            # doesn't include ORDER BY in the SQL (it only generates TOP N).
+            # So we fetch all results ordered and limit in Python.
+            query = (
                 session.query(
                     self.table,
-                    (
-                        self.distance_strategy(embedding).label("distance")
-                        if self.native_vector
-                        else self.table.c.embedding.func(
-                            self.distance_strategy, embedding
-                        ).label("distance")
-                    ),
+                    distance_col,
                 )
                 .filter(filter_by)
-                .order_by(asc("distance"))
-                .limit(k)
-                .all()
+                .order_by(distance_expr)
             )
+
+            # Only add limit to SQL if dialect supports modern pagination
+            if self._conn.dialect.supports_modern_pagination:
+                query = query.limit(k)
+                results: Sequence[Row] = query.all()
+            else:
+                # For legacy pagination, fetch all and limit in Python
+                all_results = query.all()
+                results = all_results[:k]
 
         documents_with_scores = [
             (

requirements-dev.txt

@@ -1,2 +1,5 @@
 pytest
 testcontainers-iris>=1.3.0
+langchain
+langchain-community
+iris-embedded-python-wrapper