Use HfApi to get the namespace when not provide in the hf endpoint name

docs/cli_reference.md

@@ -288,7 +288,7 @@ llama stack list-distributions
 |--------------------------------|---------------------------------------|-------------------------------------------------------------------------------------------|
 | local-plus-tgi-inference       | {                                     | Use TGI (local or with [Hugging Face Inference Endpoints](https://huggingface.co/         |
 |                                |   "inference": "remote::tgi",         | inference-endpoints/dedicated)) for running LLM inference. When using HF Inference        |
-|                                |   "safety": "meta-reference",         | Endpoints, please provide hf_namespace (username or organization name) and endpoint name. |
+|                                |   "safety": "meta-reference",         | Endpoints, you must provide the name of the endpoint.                                     |
 |                                |   "agentic_system": "meta-reference", |                                                                                           |
 |                                |   "memory": "meta-reference-faiss"    |                                                                                           |
 |                                | }                                     |                                                                                           |

llama_toolchain/inference/adapters/tgi/config.py

@@ -6,6 +6,7 @@
 
 from typing import Optional
 
+from huggingface_hub import HfApi
 from llama_models.schema_utils import json_schema_type
 from pydantic import BaseModel, Field
 
@@ -20,17 +21,16 @@ class TGIImplConfig(BaseModel):
         default=None,
         description="The HF token for Hugging Face Inference Endpoints (will default to locally saved token if not provided)",
     )
-    hf_namespace: Optional[str] = Field(
-        default=None,
-        description="The username/organization name for the Hugging Face Inference Endpoint",
-    )
     hf_endpoint_name: Optional[str] = Field(
         default=None,
-        description="The name of the Hugging Face Inference Endpoint",
+        description="The name of the Hugging Face Inference Endpoint : can be either in the format of '{namespace}/{endpoint_name}' (namespace can be the username or organization name) or just '{endpoint_name}' if logged into the same account as the namespace",
     )
 
     def is_inference_endpoint(self) -> bool:
-        return self.hf_namespace is not None and self.hf_endpoint_name is not None
+        return self.hf_endpoint_name is not None
+
+    def get_namespace(self) -> str:
+        return HfApi().whoami()["name"]
 
     def is_local_tgi(self) -> bool:
         return self.url is not None and self.url.startswith("http://localhost")

llama_toolchain/inference/adapters/tgi/tgi.py

@@ -235,7 +235,19 @@ class TGIAdapter(Inference):
 class InferenceEndpointAdapter(TGIAdapter):
     def __init__(self, config: TGIImplConfig) -> None:
         super().__init__(config)
-        self.config.url = f"https://api.endpoints.huggingface.cloud/v2/endpoint/{config.hf_namespace}/{config.hf_endpoint_name}"
+        self.config.url = self._construct_endpoint_url(config.hf_endpoint_name)
+
+    def _construct_endpoint_url(self, hf_endpoint_name: str) -> str:
+        assert hf_endpoint_name.count("/") <= 1, (
+            "Endpoint name must be in the format of 'namespace/endpoint_name' "
+            "or 'endpoint_name'"
+        )
+        if "/" not in hf_endpoint_name:
+            hf_namespace: str = self.config.get_namespace()
+            endpoint_path = f"{hf_namespace}/{hf_endpoint_name}"
+        else:
+            endpoint_path = hf_endpoint_name
+        return f"https://api.endpoints.huggingface.cloud/v2/endpoint/{endpoint_path}"
 
     @property
     def client(self) -> InferenceClient: