Fix tgi adapter (#796)

# What does this PR do?

- Fix TGI adapter

## Test Plan

<img width="851" alt="image"
src="https://github.com/user-attachments/assets/0084cbc6-6713-4079-b87b-0befd9aca0b0"
/>

- most inference working
- agent test failure due to model outputs

## Sources

Please link relevant resources if necessary.


## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Ran pre-commit to handle lint / formatting issues.
- [ ] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.

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

@@ -15,10 +15,6 @@ class TGIImplConfig(BaseModel):
     url: str = Field(
         description="The URL for the TGI serving endpoint",
     )
-    api_token: Optional[SecretStr] = Field(
-        default=None,
-        description="A bearer token if your TGI endpoint is protected.",
-    )
 
     @classmethod
     def sample_run_config(cls, url: str = "${env.TGI_URL}", **kwargs):

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

@@ -128,6 +128,12 @@ class _HfAdapter(Inference, ModelsProtocolPrivate):
         fmt: ResponseFormat = None,
     ):
         options = get_sampling_options(sampling_params)
+        # TGI does not support temperature=0 when using greedy sampling
+        # We set it to 1e-3 instead, anything lower outputs garbage from TGI
+        # We can use top_p sampling strategy to specify lower temperature
+        if abs(options["temperature"]) < 1e-10:
+            options["temperature"] = 1e-3
+
         # delete key "max_tokens" from options since its not supported by the API
         options.pop("max_tokens", None)
         if fmt:
@@ -289,7 +295,7 @@ class TGIAdapter(_HfAdapter):
     async def initialize(self, config: TGIImplConfig) -> None:
         log.info(f"Initializing TGI client with url={config.url}")
         self.client = AsyncInferenceClient(
-            model=config.url, token=config.api_token.get_secret_value()
+            model=config.url,
         )
         endpoint_info = await self.client.get_endpoint_info()
         self.max_tokens = endpoint_info["max_total_tokens"]

tests/client-sdk/agents/test_agents.py

@@ -98,7 +98,7 @@ def agent_config(llama_stack_client):
         instructions="You are a helpful assistant",
         sampling_params={
             "strategy": {
-                "type": "greedy",
+                "type": "top_p",
                 "temperature": 1.0,
                 "top_p": 0.9,
             },