chore: enable mypy type checking for sentence transformers

Fix method signature incompatibilities with InferenceProvider protocol:
 - Update completion() content parameter type to InterleavedContent
 - Reorder chat_completion() parameters to match protocol
 - Add type ignores for mixin inheritance conflicts

Signed-off-by: Mustafa Elbehery <melbeher@redhat.com>

llama_stack/providers/inline/inference/sentence_transformers/sentence_transformers.py

@@ -9,6 +9,7 @@ from collections.abc import AsyncGenerator
 from llama_stack.apis.inference import (
     CompletionResponse,
     InferenceProvider,
+    InterleavedContent,
     LogProbConfig,
     Message,
     ResponseFormat,
@@ -34,7 +35,7 @@ from .config import SentenceTransformersInferenceConfig
 log = get_logger(name=__name__, category="inference")
 
 
-class SentenceTransformersInferenceImpl(
+class SentenceTransformersInferenceImpl(  # type: ignore[misc]
     OpenAIChatCompletionToLlamaStackMixin,
     OpenAICompletionToLlamaStackMixin,
     SentenceTransformerEmbeddingMixin,
@@ -77,7 +78,7 @@ class SentenceTransformersInferenceImpl(
     async def completion(
         self,
         model_id: str,
-        content: str,
+        content: InterleavedContent,
         sampling_params: SamplingParams | None = None,
         response_format: ResponseFormat | None = None,
         stream: bool | None = False,
@@ -90,10 +91,10 @@ class SentenceTransformersInferenceImpl(
         model_id: str,
         messages: list[Message],
         sampling_params: SamplingParams | None = None,
-        response_format: ResponseFormat | None = None,
         tools: list[ToolDefinition] | None = None,
         tool_choice: ToolChoice | None = ToolChoice.auto,
         tool_prompt_format: ToolPromptFormat | None = None,
+        response_format: ResponseFormat | None = None,
         stream: bool | None = False,
         logprobs: LogProbConfig | None = None,
         tool_config: ToolConfig | None = None,

llama_stack/providers/registry/post_training.py

@@ -5,13 +5,13 @@
 # the root directory of this source tree.
 
 
-from typing import cast
+from typing import Any, cast
 
 from llama_stack.providers.datatypes import AdapterSpec, Api, InlineProviderSpec, ProviderSpec, remote_provider_spec
 
 # We provide two versions of these providers so that distributions can package the appropriate version of torch.
 # The CPU version is used for distributions that don't have GPU support -- they result in smaller container images.
-torchtune_def = dict(
+torchtune_def: dict[str, Any] = dict(
     api=Api.post_training,
     pip_packages=["numpy"],
     module="llama_stack.providers.inline.post_training.torchtune",

pyproject.toml

@@ -268,7 +268,6 @@ exclude = [
     "^llama_stack/models/llama/llama3/multimodal/model\\.py$",
     "^llama_stack/models/llama/llama4/",
     "^llama_stack/providers/inline/inference/meta_reference/quantization/fp8_impls\\.py$",
-    "^llama_stack/providers/inline/inference/sentence_transformers/sentence_transformers\\.py$",
     "^llama_stack/providers/inline/post_training/common/validator\\.py$",
     "^llama_stack/providers/inline/safety/code_scanner/",
     "^llama_stack/providers/inline/safety/llama_guard/",