Tgi fixture (#519)

# What does this PR do?

* Add a test fixture for tgi
* Fixes the logic to correctly pass the llama model for chat completion

Fixes #514

## Test Plan

pytest -k "tgi"
llama_stack/providers/tests/inference/test_text_inference.py --env
TGI_URL=http://localhost:$INFERENCE_PORT --env TGI_API_TOKEN=$HF_TOKEN

llama_stack/providers/remote/inference/tgi/tgi.py

@@ -89,8 +89,9 @@ class _HfAdapter(Inference, ModelsProtocolPrivate):
         stream: Optional[bool] = False,
         logprobs: Optional[LogProbConfig] = None,
     ) -> AsyncGenerator:
+        model = await self.model_store.get_model(model_id)
         request = CompletionRequest(
-            model=model_id,
+            model=model.provider_resource_id,
             content=content,
             sampling_params=sampling_params,
             response_format=response_format,
@@ -194,8 +195,9 @@ class _HfAdapter(Inference, ModelsProtocolPrivate):
         stream: Optional[bool] = False,
         logprobs: Optional[LogProbConfig] = None,
     ) -> AsyncGenerator:
+        model = await self.model_store.get_model(model_id)
         request = ChatCompletionRequest(
-            model=model_id,
+            model=model.provider_resource_id,
             messages=messages,
             sampling_params=sampling_params,
             tools=tools or [],
@@ -249,7 +251,7 @@ class _HfAdapter(Inference, ModelsProtocolPrivate):
 
     def _get_params(self, request: ChatCompletionRequest) -> dict:
         prompt, input_tokens = chat_completion_request_to_model_input_info(
-            request, self.formatter
+            request, self.register_helper.get_llama_model(request.model), self.formatter
         )
         return dict(
             prompt=prompt,

llama_stack/providers/tests/inference/fixtures.py

@@ -20,6 +20,7 @@ from llama_stack.providers.remote.inference.bedrock import BedrockConfig
 from llama_stack.providers.remote.inference.fireworks import FireworksImplConfig
 from llama_stack.providers.remote.inference.nvidia import NVIDIAConfig
 from llama_stack.providers.remote.inference.ollama import OllamaImplConfig
+from llama_stack.providers.remote.inference.tgi import TGIImplConfig
 from llama_stack.providers.remote.inference.together import TogetherImplConfig
 from llama_stack.providers.remote.inference.vllm import VLLMInferenceAdapterConfig
 from llama_stack.providers.tests.resolver import construct_stack_for_test
@@ -156,6 +157,22 @@ def inference_nvidia() -> ProviderFixture:
     )
 
 
+@pytest.fixture(scope="session")
+def inference_tgi() -> ProviderFixture:
+    return ProviderFixture(
+        providers=[
+            Provider(
+                provider_id="tgi",
+                provider_type="remote::tgi",
+                config=TGIImplConfig(
+                    url=get_env_or_fail("TGI_URL"),
+                    api_token=os.getenv("TGI_API_TOKEN", None),
+                ).model_dump(),
+            )
+        ],
+    )
+
+
 def get_model_short_name(model_name: str) -> str:
     """Convert model name to a short test identifier.
 
@@ -190,6 +207,7 @@ INFERENCE_FIXTURES = [
     "remote",
     "bedrock",
     "nvidia",
+    "tgi",
 ]