AstraDB VectorStore: implement pre_delete_collection (#13780)

- **Description:** some vector stores have a flag for try deleting the
collection before creating it (such as ´vectorpg´). This is a useful
flag when prototyping indexing pipelines and also for integration tests.
Added the bool flag `pre_delete_collection ` to the constructor (default
False)
  - **Tag maintainer:** @hemidactylus 
  - **Twitter handle:** nicoloboschi

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

libs/langchain/langchain/vectorstores/astradb.py

@@ -78,7 +78,7 @@ class AstraDB(VectorStore):
                 vectorstore.add_texts(["Giraffes", "All good here"])
                 results = vectorstore.similarity_search("Everything's ok", k=1)
 
-    Constructor args (only keyword-arguments accepted):
+      Constructor Args (only keyword-arguments accepted):
           embedding (Embeddings): embedding function to use.
           collection_name (str): name of the Astra DB collection to create/use.
           token (Optional[str]): API token for Astra DB usage.
@@ -101,6 +101,9 @@ class AstraDB(VectorStore):
               threads in a batch to insert pre-existing entries.
           bulk_delete_concurrency (Optional[int]): Number of threads
               (for deleting multiple rows concurrently).
+          pre_delete_collection (Optional[bool]): whether to delete the collection
+              before creating it. If False and the collection already exists,
+              the collection will be used as is.
 
       A note on concurrency: as a rule of thumb, on a typical client machine
       it is suggested to keep the quantity
@@ -138,6 +141,7 @@ class AstraDB(VectorStore):
         bulk_insert_batch_concurrency: Optional[int] = None,
         bulk_insert_overwrite_concurrency: Optional[int] = None,
         bulk_delete_concurrency: Optional[int] = None,
+        pre_delete_collection: bool = False,
     ) -> None:
         """
         Create an AstraDB vector store object. See class docstring for help.
@@ -154,6 +158,7 @@ class AstraDB(VectorStore):
                 "Could not import a recent astrapy python package. "
                 "Please install it with `pip install --upgrade astrapy`."
             )
+
         # Conflicting-arg checks:
         if astra_db_client is not None:
             if token is not None or api_endpoint is not None:
@@ -191,7 +196,10 @@ class AstraDB(VectorStore):
                 api_endpoint=self.api_endpoint,
                 namespace=self.namespace,
             )
+        if not pre_delete_collection:
             self._provision_collection()
+        else:
+            self.clear()
 
         self.collection = LibAstraDBCollection(
             collection_name=self.collection_name,

libs/langchain/tests/integration_tests/vectorstores/test_astradb.py

@@ -148,6 +148,41 @@ class TestAstraDB:
         )
         v_store_2.delete_collection()
 
+    def test_astradb_vectorstore_pre_delete_collection(self) -> None:
+        """Create and delete."""
+        emb = SomeEmbeddings(dimension=2)
+        # creation by passing the connection secrets
+
+        v_store = AstraDB(
+            embedding=emb,
+            collection_name="lc_test_pre_del",
+            token=os.environ["ASTRA_DB_APPLICATION_TOKEN"],
+            api_endpoint=os.environ["ASTRA_DB_API_ENDPOINT"],
+            namespace=os.environ.get("ASTRA_DB_KEYSPACE"),
+        )
+        try:
+            v_store.add_texts(
+                texts=["aa"],
+                metadatas=[
+                    {"k": "a", "ord": 0},
+                ],
+                ids=["a"],
+            )
+            res1 = v_store.similarity_search("aa", k=5)
+            assert len(res1) == 1
+            v_store = AstraDB(
+                embedding=emb,
+                pre_delete_collection=True,
+                collection_name="lc_test_pre_del",
+                token=os.environ["ASTRA_DB_APPLICATION_TOKEN"],
+                api_endpoint=os.environ["ASTRA_DB_API_ENDPOINT"],
+                namespace=os.environ.get("ASTRA_DB_KEYSPACE"),
+            )
+            res1 = v_store.similarity_search("aa", k=5)
+            assert len(res1) == 0
+        finally:
+            v_store.delete_collection()
+
     def test_astradb_vectorstore_from_x(self) -> None:
         """from_texts and from_documents methods."""
         emb = SomeEmbeddings(dimension=2)