feat(vllm): periodically refresh models (#2823)

Just like #2805 but for vLLM.

We also make VLLM_URL env variable optional (not required) -- if not
specified, the provider silently sits idle and yells eventually if
someone tries to call a completion on it. This is done so as to allow
this provider to be present in the `starter` distribution.

## Test Plan

Set up vLLM, copy the starter template and set `{ refresh_models: true,
refresh_models_interval: 10 }` for the vllm provider and then run:

```
ENABLE_VLLM=vllm VLLM_URL=http://localhost:8000/v1 \
  uv run llama stack run --image-type venv /tmp/starter.yaml
```

Verify that `llama-stack-client models list` brings up the model
correctly from vLLM.

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

@@ -29,6 +29,14 @@ class VLLMInferenceAdapterConfig(BaseModel):
         default=True,
         description="Whether to verify TLS certificates. Can be a boolean or a path to a CA certificate file.",
     )
+    refresh_models: bool = Field(
+        default=False,
+        description="Whether to refresh models periodically",
+    )
+    refresh_models_interval: int = Field(
+        default=300,
+        description="Interval in seconds to refresh models",
+    )
 
     @field_validator("tls_verify")
     @classmethod
@@ -46,7 +54,7 @@ class VLLMInferenceAdapterConfig(BaseModel):
     @classmethod
     def sample_run_config(
         cls,
-        url: str = "${env.VLLM_URL}",
+        url: str = "${env.VLLM_URL:=}",
         **kwargs,
     ):
         return {