Make Files API an optional dependency of faiss provider

Because we haven't updated every template to include a Files API
provider yet, this adjusts the Files API to be an optional dependency
instead of a required one of the Faiss provider.

Signed-off-by: Ben Browning <bbrownin@redhat.com>

llama_stack/providers/inline/vector_io/faiss/__init__.py

@@ -16,6 +16,6 @@ async def get_provider_impl(config: FaissVectorIOConfig, deps: dict[Api, Any]):
 
     assert isinstance(config, FaissVectorIOConfig), f"Unexpected config type: {type(config)}"
 
-    impl = FaissVectorIOAdapter(config, deps[Api.inference], deps[Api.files])
+    impl = FaissVectorIOAdapter(config, deps[Api.inference], deps.get(Api.files, None))
     await impl.initialize()
     return impl

llama_stack/providers/inline/vector_io/faiss/faiss.py

@@ -133,7 +133,7 @@ class FaissIndex(EmbeddingIndex):
 
 
 class FaissVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPrivate):
-    def __init__(self, config: FaissVectorIOConfig, inference_api: Inference, files_api: Files) -> None:
+    def __init__(self, config: FaissVectorIOConfig, inference_api: Inference, files_api: Files | None) -> None:
         self.config = config
         self.inference_api = inference_api
         self.files_api = files_api

llama_stack/providers/registry/vector_io.py

@@ -24,6 +24,7 @@ def available_providers() -> list[ProviderSpec]:
             config_class="llama_stack.providers.inline.vector_io.faiss.FaissVectorIOConfig",
             deprecation_warning="Please use the `inline::faiss` provider instead.",
             api_dependencies=[Api.inference],
+            optional_api_dependencies=[Api.files],
         ),
         InlineProviderSpec(
             api=Api.vector_io,
@@ -31,7 +32,8 @@ def available_providers() -> list[ProviderSpec]:
             pip_packages=["faiss-cpu"],
             module="llama_stack.providers.inline.vector_io.faiss",
             config_class="llama_stack.providers.inline.vector_io.faiss.FaissVectorIOConfig",
-            api_dependencies=[Api.inference, Api.files],
+            api_dependencies=[Api.inference],
+            optional_api_dependencies=[Api.files],
         ),
         # NOTE: sqlite-vec cannot be bundled into the container image because it does not have a
         # source distribution and the wheels are not available for all platforms.

llama_stack/providers/utils/memory/openai_vector_store_mixin.py

@@ -47,7 +47,7 @@ class OpenAIVectorStoreMixin(ABC):
 
     # These should be provided by the implementing class
     openai_vector_stores: dict[str, dict[str, Any]]
-    files_api: Files
+    files_api: Files | None
 
     @abstractmethod
     async def _save_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None:
@@ -425,6 +425,14 @@ class OpenAIVectorStoreMixin(ABC):
             vector_store_id=vector_store_id,
         )
 
+        if not self.files_api:
+            vector_store_file_object.status = "failed"
+            vector_store_file_object.last_error = VectorStoreFileLastError(
+                code="server_error",
+                message="Files API is not available",
+            )
+            return vector_store_file_object
+
         if isinstance(chunking_strategy, VectorStoreChunkingStrategyStatic):
             max_chunk_size_tokens = chunking_strategy.static.max_chunk_size_tokens
             chunk_overlap_tokens = chunking_strategy.static.chunk_overlap_tokens