Include more information about the caller

Currently, when making calls to AstraDB, we include a `User-Agent`
header identifying the API caller. This header is currently set to
"langchain" by default at the moment. This change threads the
`caller_name` parameter throughout the API and appends a suffix
identifying which class created the API client:

* langchain/cache
* langchain/chat_message_history
* langchain/document_loader
* langchain/graph_vectorstore
* langchain/semantic_cache
* langchain/vectorstore

This metadata will be useful for debugging and tracking utilization of
different library features.

libs/astradb/langchain_astradb/cache.py

@@ -109,6 +109,7 @@ def __init__(
         namespace: str | None = None,
         pre_delete_collection: bool = False,
         setup_mode: SetupMode = SetupMode.SYNC,
+        caller_name: str = "langchain/cache",
     ):
         """Cache that uses Astra DB as a backend.
 
@@ -159,6 +160,7 @@ def __init__(
             namespace=namespace,
             setup_mode=setup_mode,
             pre_delete_collection=pre_delete_collection,
+            caller_name=caller_name,
         )
         self.collection = self.astra_env.collection
         self.async_collection = self.astra_env.async_collection
@@ -326,6 +328,7 @@ def __init__(
         embedding: Embeddings,
         metric: str | None = None,
         similarity_threshold: float = ASTRA_DB_SEMANTIC_CACHE_DEFAULT_THRESHOLD,
+        caller_name: str = "langchain/semantic_cache",
     ):
         """Astra DB semantic cache.
 
@@ -416,6 +419,7 @@ async def _acache_embedding(text: str) -> list[float]:
             pre_delete_collection=pre_delete_collection,
             embedding_dimension=embedding_dimension,
             metric=metric,
+            caller_name=caller_name,
         )
         self.collection = self.astra_env.collection
         self.async_collection = self.astra_env.async_collection

libs/astradb/langchain_astradb/chat_message_histories.py

@@ -40,6 +40,7 @@ def __init__(
         namespace: str | None = None,
         setup_mode: SetupMode = SetupMode.SYNC,
         pre_delete_collection: bool = False,
+        caller_name: str = "langchain/chat_message_history",
     ) -> None:
         """Chat message history that stores history in Astra DB.
 
@@ -84,6 +85,7 @@ def __init__(
             namespace=namespace,
             setup_mode=setup_mode,
             pre_delete_collection=pre_delete_collection,
+            caller_name=caller_name,
         )
 
         self.collection = self.astra_env.collection

libs/astradb/langchain_astradb/document_loaders.py

@@ -49,6 +49,7 @@ def __init__(
         nb_prefetched: int = _NOT_SET,  # type: ignore[assignment]
         page_content_mapper: Callable[[dict], str] = json.dumps,
         metadata_mapper: Callable[[dict], dict[str, Any]] | None = None,
+        caller_name: str = "langchain/document_loader",
     ) -> None:
         """Load DataStax Astra DB documents.
 
@@ -101,6 +102,7 @@ def __init__(
             async_astra_db_client=async_astra_db_client,
             namespace=namespace,
             setup_mode=SetupMode.OFF,
+            caller_name=caller_name,
         )
         self.astra_db_env = astra_db_env
         self.filter = filter_criteria

libs/astradb/langchain_astradb/graph_vectorstores.py

@@ -54,6 +54,7 @@ def __init__(
         metadata_indexing_include: Iterable[str] | None = None,
         metadata_indexing_exclude: Iterable[str] | None = None,
         collection_indexing_policy: dict[str, Any] | None = None,
+        caller_name: str = "langchain/graph_vectorstore",
         **kwargs: Any,
     ):
         """Create a new Graph Vector Store backed by AstraDB."""
@@ -68,6 +69,7 @@ def __init__(
             metadata_indexing_include=metadata_indexing_include,
             metadata_indexing_exclude=metadata_indexing_exclude,
             collection_indexing_policy=collection_indexing_policy,
+            caller_name=caller_name,
             **kwargs,
         )
 

libs/astradb/langchain_astradb/utils/astradb.py

@@ -94,6 +94,7 @@ def __init__(
         astra_db_client: AstraDB | None = None,
         async_astra_db_client: AsyncAstraDB | None = None,
         namespace: str | None = None,
+        caller_name: str = "langchain",
     ) -> None:
         self.token: str | TokenProvider | None
         self.api_endpoint: str | None
@@ -221,7 +222,6 @@ def __init__(
             raise ValueError(msg)
 
         # create the clients
-        caller_name = "langchain"
         caller_version = getattr(langchain_core, "__version__", None)
 
         self.data_api_client = DataAPIClient(
@@ -256,6 +256,7 @@ def __init__(
         default_indexing_policy: dict[str, Any] | None = None,
         collection_vector_service_options: CollectionVectorServiceOptions | None = None,
         collection_embedding_api_key: str | EmbeddingHeadersProvider | None = None,
+        caller_name: str = "langchain",
     ) -> None:
         super().__init__(
             token=token,
@@ -264,6 +265,7 @@ def __init__(
             astra_db_client=astra_db_client,
             async_astra_db_client=async_astra_db_client,
             namespace=namespace,
+            caller_name=caller_name,
         )
         self.collection_name = collection_name
         self.collection = self.database.get_collection(

libs/astradb/langchain_astradb/vectorstores.py

@@ -389,6 +389,7 @@ def __init__(
         content_field: str | None = None,
         ignore_invalid_documents: bool = False,
         autodetect_collection: bool = False,
+        caller_name: str = "langchain/vectorstore",
     ) -> None:
         """Wrapper around DataStax Astra DB for vector-store workloads.
 
@@ -664,6 +665,7 @@ def __init__(
             default_indexing_policy=DEFAULT_INDEXING_OPTIONS,
             collection_vector_service_options=self.collection_vector_service_options,
             collection_embedding_api_key=self.collection_embedding_api_key,
+            caller_name=caller_name,
         )
 
     def _get_safe_embedding(self) -> Embeddings: