Fix some blockings

libs/astradb/langchain_astradb/utils/astradb.py

@@ -425,9 +425,9 @@ async def _asetup_db(
         except DataAPIException as data_api_exception:
             # possibly the collection is preexisting and may have legacy,
             # or custom, indexing settings: verify
-            collection_descriptors = [
-                coll_desc async for coll_desc in self.async_database.list_collections()
-            ]
+            collection_descriptors = list(
+                await asyncio.to_thread(self.database.list_collections)
+            )
             try:
                 if not self._validate_indexing_policy(
                     collection_descriptors=collection_descriptors,

libs/astradb/tests/integration_tests/test_graphvectorstore.py

@@ -5,6 +5,7 @@
 
 from __future__ import annotations
 
+import asyncio
 from typing import TYPE_CHECKING, Any
 
 import pytest
@@ -400,7 +401,9 @@ async def test_gvs_similarity_search_async(
         request: pytest.FixtureRequest,
     ) -> None:
         """Simple (non-graph) similarity search on a graph vector store."""
-        g_store: AstraDBGraphVectorStore = request.getfixturevalue(store_name)
+        g_store: AstraDBGraphVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, store_name
+        )
         query = "universe" if is_vectorize else "[2, 10]"
         embedding = [2.0, 10.0]
 
@@ -421,8 +424,10 @@ async def test_gvs_similarity_search_async(
             assert ss_by_v_labels == ["AR", "A0"]
 
         if is_autodetected:
-            assert_all_flat_docs(
-                g_store.vector_store.astra_env.collection, is_vectorize=is_vectorize
+            await asyncio.to_thread(
+                assert_all_flat_docs,
+                g_store.vector_store.astra_env.collection,
+                is_vectorize=is_vectorize,
             )
 
     @pytest.mark.parametrize(
@@ -488,7 +493,9 @@ async def test_gvs_traversal_search_async(
         request: pytest.FixtureRequest,
     ) -> None:
         """Graph traversal search on a graph vector store."""
-        g_store: AstraDBGraphVectorStore = request.getfixturevalue(store_name)
+        g_store: AstraDBGraphVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, store_name
+        )
         query = "universe" if is_vectorize else "[2, 10]"
 
         # this is a set, as some of the internals of trav.search are set-driven
@@ -499,8 +506,10 @@ async def test_gvs_traversal_search_async(
         }
         assert ts_labels == {"AR", "A0", "BR", "B0", "TR", "T0"}
         if is_autodetected:
-            assert_all_flat_docs(
-                g_store.vector_store.astra_env.collection, is_vectorize=is_vectorize
+            await asyncio.to_thread(
+                assert_all_flat_docs,
+                g_store.vector_store.astra_env.collection,
+                is_vectorize=is_vectorize,
             )
 
     @pytest.mark.parametrize(
@@ -572,7 +581,9 @@ async def test_gvs_mmr_traversal_search_async(
         request: pytest.FixtureRequest,
     ) -> None:
         """MMR Graph traversal search on a graph vector store."""
-        g_store: AstraDBGraphVectorStore = request.getfixturevalue(store_name)
+        g_store: AstraDBGraphVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, store_name
+        )
         query = "universe" if is_vectorize else "[2, 10]"
 
         mt_labels = [
@@ -589,8 +600,10 @@ async def test_gvs_mmr_traversal_search_async(
 
         assert mt_labels == ["AR", "BR"]
         if is_autodetected:
-            assert_all_flat_docs(
-                g_store.vector_store.astra_env.collection, is_vectorize=is_vectorize
+            await asyncio.to_thread(
+                assert_all_flat_docs,
+                g_store.vector_store.astra_env.collection,
+                is_vectorize=is_vectorize,
             )
 
     @pytest.mark.parametrize(
@@ -652,7 +665,9 @@ async def test_gvs_metadata_search_async(
         request: pytest.FixtureRequest,
     ) -> None:
         """Metadata search on a graph vector store."""
-        g_store: AstraDBGraphVectorStore = request.getfixturevalue(store_name)
+        g_store: AstraDBGraphVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, store_name
+        )
         mt_response = await g_store.ametadata_search(
             filter={"label": "T0"},
             n=2,
@@ -726,7 +741,9 @@ async def test_gvs_get_by_document_id_async(
         request: pytest.FixtureRequest,
     ) -> None:
         """Get by document_id on a graph vector store."""
-        g_store: AstraDBGraphVectorStore = request.getfixturevalue(store_name)
+        g_store: AstraDBGraphVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, store_name
+        )
         doc = await g_store.aget_by_document_id(document_id="FL")
         assert doc is not None
         assert doc.metadata["label"] == "FL"
@@ -816,7 +833,9 @@ async def test_gvs_from_texts_async(
         collection_fixture_name: str,
         request: pytest.FixtureRequest,
     ) -> None:
-        collection_name: str = request.getfixturevalue(collection_fixture_name)
+        collection_name: str = asyncio.to_thread(
+            request.getfixturevalue, collection_fixture_name
+        )
         init_kwargs: dict[str, Any]
         if is_vectorize:
             init_kwargs = {
@@ -915,7 +934,9 @@ async def test_gvs_from_documents_containing_ids_async(
         collection_fixture_name: str,
         request: pytest.FixtureRequest,
     ) -> None:
-        collection_name: str = request.getfixturevalue(collection_fixture_name)
+        collection_name: str = await asyncio.to_thread(
+            request.getfixturevalue, collection_fixture_name
+        )
         init_kwargs: dict[str, Any]
         if is_vectorize:
             init_kwargs = {
@@ -1005,7 +1026,9 @@ async def test_gvs_add_nodes_async(
         store_name: str,
         request: pytest.FixtureRequest,
     ) -> None:
-        g_store: AstraDBGraphVectorStore = request.getfixturevalue(store_name)
+        g_store: AstraDBGraphVectorStore = asyncio.to_thread(
+            request.getfixturevalue, store_name
+        )
         links0 = [
             Link(kind="kA", direction="out", tag="tA"),
             Link(kind="kB", direction="bidir", tag="tB"),

libs/astradb/tests/integration_tests/test_storage.py

@@ -44,7 +44,7 @@ async def astra_db_empty_store_async(
     astra_db_credentials: AstraDBCredentials,
     collection_idxid: Collection,
 ) -> AstraDBStore:
-    collection_idxid.delete_many({})
+    await collection_idxid.to_async().delete_many({})
     return AstraDBStore(
         collection_name=collection_idxid.name,
         token=StaticTokenProvider(astra_db_credentials["token"]),
@@ -364,7 +364,7 @@ async def test_store_indexing_on_legacy_async(
         database: Database,
     ) -> None:
         """Test of instantiation against a legacy collection, async version."""
-        database.create_collection(
+        await database.to_async().create_collection(
             EPHEMERAL_LEGACY_IDX_NAME,
             indexing=None,
             check_exists=False,
@@ -413,7 +413,7 @@ async def test_store_indexing_on_custom_async(
         database: Database,
     ) -> None:
         """Test of instantiation against a legacy collection, async version."""
-        database.create_collection(
+        await database.to_async().create_collection(
             EPHEMERAL_CUSTOM_IDX_NAME,
             indexing={"deny": ["useless", "forgettable"]},
             check_exists=False,

libs/astradb/tests/integration_tests/test_vectorstore.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import asyncio
 import json
 import math
 import os
@@ -371,7 +372,9 @@ async def test_astradb_vectorstore_from_texts_async(
         request: pytest.FixtureRequest,
     ) -> None:
         """from_texts methods and the associated warnings, async version."""
-        collection: Collection = request.getfixturevalue(collection_fixture_name)
+        collection: Collection = await asyncio.to_thread(
+            request.getfixturevalue, collection_fixture_name
+        )
         init_kwargs: dict[str, Any]
         if is_vectorize:
             init_kwargs = {
@@ -481,7 +484,9 @@ async def test_astradb_vectorstore_from_documents_async(
         from_documents, esp. the various handling of ID-in-doc vs external.
         Async version.
         """
-        collection: Collection = request.getfixturevalue(collection_fixture_name)
+        collection: Collection = await asyncio.to_thread(
+            request.getfixturevalue, collection_fixture_name
+        )
         pc1, pc2 = page_contents
         init_kwargs: dict[str, Any]
         if is_vectorize:
@@ -509,7 +514,7 @@ async def test_astradb_vectorstore_from_documents_async(
         assert len(hits) == 1
         assert hits[0].page_content == pc2
         assert hits[0].metadata == {"m": 3}
-        v_store.clear()
+        await v_store.aclear()
 
         # IDs passed separately.
         with pytest.warns(DeprecationWarning) as rec_warnings:
@@ -536,7 +541,7 @@ async def test_astradb_vectorstore_from_documents_async(
         assert hits[0].page_content == pc2
         assert hits[0].metadata == {"m": 3}
         assert hits[0].id == "idx3"
-        v_store_2.clear()
+        await v_store_2.aclear()
 
         # IDs in documents.
         v_store_3 = await AstraDBVectorStore.afrom_documents(
@@ -557,7 +562,7 @@ async def test_astradb_vectorstore_from_documents_async(
         assert hits[0].page_content == pc2
         assert hits[0].metadata == {"m": 3}
         assert hits[0].id == "idx3"
-        v_store_3.clear()
+        await v_store_3.aclear()
 
         # IDs both in documents and aside.
         with pytest.warns(DeprecationWarning) as rec_warnings:
@@ -692,7 +697,9 @@ async def test_astradb_vectorstore_crud_async(
         request: pytest.FixtureRequest,
     ) -> None:
         """Add/delete/update behaviour, async version."""
-        vstore: AstraDBVectorStore = request.getfixturevalue(vector_store)
+        vstore: AstraDBVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, vector_store
+        )
 
         res0 = await vstore.asimilarity_search("[-1,-1]", k=2)
         assert res0 == []
@@ -1242,13 +1249,15 @@ async def test_astradb_vectorstore_metadata_search_async(
         metadata_documents: list[Document],
     ) -> None:
         """Metadata Search"""
-        vstore: AstraDBVectorStore = request.getfixturevalue(vector_store)
+        vstore: AstraDBVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, vector_store
+        )
         await vstore.aadd_documents(metadata_documents)
         # no filters
         res0 = await vstore.ametadata_search(filter={}, n=10)
         assert {doc.metadata["letter"] for doc in res0} == set("qwreio")
         # single filter
-        res1 = vstore.metadata_search(
+        res1 = await vstore.ametadata_search(
             n=10,
             filter={"group": "vowel"},
         )
@@ -1313,7 +1322,9 @@ async def test_astradb_vectorstore_get_by_document_id_async(
         metadata_documents: list[Document],
     ) -> None:
         """Get by document_id"""
-        vstore: AstraDBVectorStore = request.getfixturevalue(vector_store)
+        vstore: AstraDBVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, vector_store
+        )
         await vstore.aadd_documents(metadata_documents)
         # invalid id
         invalid = await vstore.aget_by_document_id(document_id="z")
@@ -1398,7 +1409,9 @@ async def test_astradb_vectorstore_similarity_scale_async(
         request: pytest.FixtureRequest,
     ) -> None:
         """Scale of the similarity scores, async version."""
-        vstore: AstraDBVectorStore = request.getfixturevalue(vector_store)
+        vstore: AstraDBVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, vector_store
+        )
         await vstore.aadd_texts(
             texts=texts,
             ids=["near", "far"],
@@ -1432,7 +1445,9 @@ async def test_astradb_vectorstore_asimilarity_search_with_embedding(
         """asimilarity_search_with_embedding is used as the building
         block for other components (like AstraDBGraphVectorStore).
         """
-        vstore: AstraDBVectorStore = request.getfixturevalue(vector_store)
+        vstore: AstraDBVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, vector_store
+        )
         await vstore.aadd_documents(metadata_documents)
 
         query_embedding, results = await vstore.asimilarity_search_with_embedding(
@@ -1465,7 +1480,9 @@ async def test_astradb_vectorstore_asimilarity_search_with_embedding_by_vector(
         """asimilarity_search_with_embedding_by_vector is used as the building
         block for other components (like AstraDBGraphVectorStore).
         """
-        vstore: AstraDBVectorStore = request.getfixturevalue(vector_store)
+        vstore: AstraDBVectorStore = await asyncio.to_thread(
+            request.getfixturevalue, vector_store
+        )
         await vstore.aadd_documents(metadata_documents)
 
         vector_dimensions = 1536 if is_vectorize else 2
@@ -1748,7 +1765,7 @@ async def test_astradb_vectorstore_coreclients_init_async(
         Expect a deprecation warning from passing a (core) AstraDB class,
         but it must work. Async version.
         """
-        vector_store_d2.add_texts(["[1,2]"])
+        await vector_store_d2.aadd_texts(["[1,2]"])
 
         with pytest.warns(DeprecationWarning) as rec_warnings:
             v_store_init_core = AstraDBVectorStore(

libs/astradb/tests/integration_tests/test_vectorstore_ddl_tests.py

@@ -5,6 +5,7 @@
 
 from __future__ import annotations
 
+import asyncio
 import warnings
 from typing import TYPE_CHECKING
 
@@ -96,10 +97,13 @@ async def test_astradb_vectorstore_create_delete_async(
             namespace=astra_db_credentials["namespace"],
             environment=astra_db_credentials["environment"],
             metric="cosine",
+            setup_mode=SetupMode.ASYNC,
         )
         await v_store.aadd_texts(["[1,2]"])
         await v_store.adelete_collection()
-        assert ephemeral_collection_cleaner_d2 not in database.list_collection_names()
+        assert ephemeral_collection_cleaner_d2 not in await asyncio.to_thread(
+            database.list_collection_names
+        )
 
     async def test_astradb_vectorstore_create_delete_vectorize_async(
         self,
@@ -118,10 +122,13 @@ async def test_astradb_vectorstore_create_delete_vectorize_async(
             metric="cosine",
             collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS_HEADER,
             collection_embedding_api_key=openai_api_key,
+            setup_mode=SetupMode.ASYNC,
         )
         await v_store.aadd_texts(["[1,2]"])
         await v_store.adelete_collection()
-        assert ephemeral_collection_cleaner_vz not in database.list_collection_names()
+        assert ephemeral_collection_cleaner_vz not in await asyncio.to_thread(
+            database.list_collection_names
+        )
 
     def test_astradb_vectorstore_pre_delete_collection_sync(
         self,
@@ -340,7 +347,7 @@ async def test_astradb_vectorstore_indexing_legacy_async(
         Test of the vector store behaviour for various indexing settings,
         with an existing 'legacy' collection (i.e. unspecified indexing policy).
         """
-        database.create_collection(
+        await database.to_async().create_collection(
             EPHEMERAL_LEGACY_IDX_NAME_D2,
             dimension=2,
             check_exists=False,