Do not send an empty 'tools' param to remote vllm

Fixes: #1955

Since 0.2.0, the vLLM gets an empty list (vs ``None`` in 0.1.9 and
before) when there are no tools configured which causes the issue described
in #1955. This patch avoids sending the 'tools' param to the vLLM altogether
instead of an empty list.

It also adds a small unit test to avoid regressions.

Signed-off-by: Daniel Alvarez <dalvarez@redhat.com>

llama_stack/providers/remote/inference/vllm/vllm.py

@@ -374,7 +374,8 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
             options["max_tokens"] = self.config.max_tokens
 
         input_dict: dict[str, Any] = {}
-        if isinstance(request, ChatCompletionRequest) and request.tools is not None:
+        # Only include the 'tools' param if there is any. It can break things if an empty list is sent to the vLLM.
+        if isinstance(request, ChatCompletionRequest) and request.tools:
             input_dict = {"tools": _convert_to_vllm_tools_in_request(request.tools)}
 
         if isinstance(request, ChatCompletionRequest):

tests/unit/providers/inference/test_remote_vllm.py

@@ -26,7 +26,12 @@ from openai.types.chat.chat_completion_chunk import (
 )
 from openai.types.model import Model as OpenAIModel
 
-from llama_stack.apis.inference import ToolChoice, ToolConfig
+from llama_stack.apis.inference import (
+    ChatCompletionRequest,
+    ToolChoice,
+    ToolConfig,
+    UserMessage,
+)
 from llama_stack.apis.models import Model
 from llama_stack.models.llama.datatypes import StopReason
 from llama_stack.providers.remote.inference.vllm.config import VLLMInferenceAdapterConfig
@@ -232,3 +237,14 @@ def test_chat_completion_doesnt_block_event_loop(caplog):
     # above.
     asyncio_warnings = [record.message for record in caplog.records if record.name == "asyncio"]
     assert not asyncio_warnings
+
+
+@pytest.mark.asyncio
+async def test_get_params_empty_tools(vllm_inference_adapter):
+    request = ChatCompletionRequest(
+        tools=[],
+        model="test_model",
+        messages=[UserMessage(content="test")],
+    )
+    params = await vllm_inference_adapter._get_params(request)
+    assert "tools" not in params