feat: Add get_by_ids and aget_by_ids to vectorstore

src/langchain_google_cloud_sql_pg/async_vectorstore.py

@@ -291,6 +291,49 @@ async def __aadd_embeddings(
 
         return ids
 
+    async def aget_by_ids(self, ids: Sequence[str]) -> list[Document]:
+        """Get documents by ids."""
+
+        quoted_ids = [f"'{id_val}'" for id_val in ids]
+        id_list_str = ", ".join(quoted_ids)
+
+        columns = self.metadata_columns + [
+            self.id_column,
+            self.content_column,
+        ]
+        if self.metadata_json_column:
+            columns.append(self.metadata_json_column)
+
+        column_names = ", ".join(f'"{col}"' for col in columns)
+
+        query = f'SELECT {column_names} FROM "{self.schema_name}"."{self.table_name}" WHERE "{self.id_column}" IN ({id_list_str});'
+
+        async with self.pool.connect() as conn:
+            result = await conn.execute(text(query))
+            result_map = result.mappings()
+            results = result_map.fetchall()
+
+        documents = []
+        for row in results:
+            metadata = (
+                row[self.metadata_json_column]
+                if self.metadata_json_column and row[self.metadata_json_column]
+                else {}
+            )
+            for col in self.metadata_columns:
+                metadata[col] = row[col]
+            documents.append(
+                (
+                    Document(
+                        page_content=row[self.content_column],
+                        metadata=metadata,
+                        id=row[self.id_column],
+                    )
+                )
+            )
+
+        return documents
+
     async def aadd_texts(
         self,
         texts: Iterable[str],
@@ -772,6 +815,11 @@ async def is_valid_index(
 
         return bool(len(results) == 1)
 
+    def get_by_ids(self, ids: Sequence[str]) -> list[Document]:
+        raise NotImplementedError(
+            "Sync methods are not implemented for AsyncPostgresVectorStore. Use PostgresVectorStore interface instead."
+        )
+
     def similarity_search(
         self,
         query: str,

src/langchain_google_cloud_sql_pg/vectorstore.py

@@ -15,7 +15,7 @@
 # TODO: Remove below import when minimum supported Python version is 3.10
 from __future__ import annotations
 
-from typing import Any, Callable, Iterable, Optional
+from typing import Any, Callable, Iterable, Optional, Sequence
 
 import numpy as np
 from langchain_core.documents import Document
@@ -813,3 +813,11 @@ def is_valid_index(
     ) -> bool:
         """Check if index exists in the table."""
         return self._engine._run_as_sync(self.__vs.is_valid_index(index_name))
+
+    async def aget_by_ids(self, ids: Sequence[str]) -> list[Document]:
+        """Get documents by ids."""
+        return await self._engine._run_as_async(self.__vs.aget_by_ids(ids=ids))
+
+    def get_by_ids(self, ids: Sequence[str]) -> list[Document]:
+        """Get documents by ids."""
+        return self._engine._run_as_sync(self.__vs.aget_by_ids(ids=ids))

tests/test_async_vectorstore_search.py

@@ -28,6 +28,7 @@
 DEFAULT_TABLE = "test_table" + str(uuid.uuid4()).replace("-", "_")
 CUSTOM_TABLE = "test_table_custom" + str(uuid.uuid4()).replace("-", "_")
 VECTOR_SIZE = 768
+sync_method_exception_str = "Sync methods are not implemented for AsyncPostgresVectorStore. Use PostgresVectorStore interface instead."
 
 embeddings_service = DeterministicFakeEmbedding(size=VECTOR_SIZE)
 
@@ -269,3 +270,20 @@ async def test_max_marginal_relevance_search_vector_score(self, vs_custom):
             embedding, lambda_mult=0.75, fetch_k=10
         )
         assert results[0][0] == Document(page_content="bar", id=ids[1])
+
+    async def test_aget_by_ids(self, vs):
+        test_ids = [ids[0]]
+        results = await vs.aget_by_ids(ids=test_ids)
+
+        assert results[0] == Document(page_content="foo", id=ids[0])
+
+    async def test_aget_by_ids_custom_vs(self, vs_custom):
+        test_ids = [ids[0]]
+        results = await vs_custom.aget_by_ids(ids=test_ids)
+
+        assert results[0] == Document(page_content="foo", id=ids[0])
+
+    def test_get_by_ids(self, vs):
+        test_ids = [ids[0]]
+        with pytest.raises(Exception, match=sync_method_exception_str):
+            vs.get_by_ids(ids=test_ids)

tests/test_vectorstore_search.py

@@ -228,6 +228,18 @@ async def test_amax_marginal_relevance_search_vector_score(self, vs):
         )
         assert results[0][0] == Document(page_content="bar", id=ids[1])
 
+    async def test_aget_by_ids(self, vs):
+        test_ids = [ids[0]]
+        results = await vs.aget_by_ids(ids=test_ids)
+
+        assert results[0] == Document(page_content="foo", id=ids[0])
+
+    async def test_aget_by_ids_custom_vs(self, vs_custom):
+        test_ids = [ids[0]]
+        results = await vs_custom.aget_by_ids(ids=test_ids)
+
+        assert results[0] == Document(page_content="foo", id=ids[0])
+
 
 class TestVectorStoreSearchSync:
     @pytest.fixture(scope="module")
@@ -331,3 +343,9 @@ def test_max_marginal_relevance_search_vector_score(self, vs_custom):
             embedding, lambda_mult=0.75, fetch_k=10
         )
         assert results[0][0] == Document(page_content="bar", id=ids[1])
+
+    def test_get_by_ids_custom_vs(self, vs_custom):
+        test_ids = [ids[0]]
+        results = vs_custom.get_by_ids(ids=test_ids)
+
+        assert results[0] == Document(page_content="foo", id=ids[0])