Move helper into impl file + fix merging conflicts

llama_toolchain/core/distribution_registry.py

@@ -59,10 +59,10 @@ def available_distribution_specs() -> List[DistributionSpec]:
             },
         ),
         DistributionSpec(
-            distribution_id="local-plus-tgi-inference",
+            distribution_type="local-plus-tgi-inference",
             description="Use TGI for running LLM inference",
             providers={
-                Api.inference: remote_provider_id("tgi"),
+                Api.inference: remote_provider_type("tgi"),
                 Api.safety: "meta-reference",
                 Api.agentic_system: "meta-reference",
                 Api.memory: "meta-reference-faiss",
@@ -72,7 +72,9 @@ def available_distribution_specs() -> List[DistributionSpec]:
 
 
 @lru_cache()
-def resolve_distribution_spec(distribution_type: str) -> Optional[DistributionSpec]:
+def resolve_distribution_spec(
+    distribution_type: str,
+) -> Optional[DistributionSpec]:
     for spec in available_distribution_specs():
         if spec.distribution_type == distribution_type:
             return spec

llama_toolchain/inference/adapters/tgi/config.py

@@ -6,8 +6,6 @@
 
 from typing import Optional
 
-from huggingface_hub import HfApi
-
 from llama_models.schema_utils import json_schema_type
 from pydantic import BaseModel, Field
 
@@ -29,6 +27,3 @@ class TGIImplConfig(BaseModel):
 
     def is_inference_endpoint(self) -> bool:
         return self.hf_endpoint_name is not None
-
-    def get_namespace(self) -> str:
-        return HfApi().whoami()["name"]

llama_toolchain/inference/adapters/tgi/tgi.py

@@ -5,20 +5,15 @@
 # the root directory of this source tree.
 
 
-from typing import AsyncGenerator
+from typing import Any, AsyncGenerator, Dict
 
 import requests
-from huggingface_hub import InferenceClient
+
+from huggingface_hub import HfApi, InferenceClient
 from llama_models.llama3.api.chat_format import ChatFormat
 from llama_models.llama3.api.datatypes import StopReason
 from llama_models.llama3.api.tokenizer import Tokenizer
-
-from llama_toolchain.inference.api import *
-from llama_toolchain.inference.api.api import (  # noqa: F403
-    ChatCompletionRequest,
-    ChatCompletionResponse,
-    ChatCompletionResponseStreamChunk,
-)
+from llama_toolchain.inference.api import *  # noqa: F403
 from llama_toolchain.inference.prepare_messages import prepare_messages
 
 from .config import TGIImplConfig
@@ -31,7 +26,6 @@ HF_SUPPORTED_MODELS = {
 
 
 class TGIAdapter(Inference):
-
     def __init__(self, config: TGIImplConfig) -> None:
         self.config = config
         self.tokenizer = Tokenizer.get_instance()
@@ -42,7 +36,10 @@ class TGIAdapter(Inference):
         return InferenceClient(model=self.config.url, token=self.config.api_token)
 
     def _get_endpoint_info(self) -> Dict[str, Any]:
-        return {**self.client.get_endpoint_info(), "inference_url": self.config.url}
+        return {
+            **self.client.get_endpoint_info(),
+            "inference_url": self.config.url,
+        }
 
     async def initialize(self) -> None:
         try:
@@ -68,7 +65,7 @@ class TGIAdapter(Inference):
             import traceback
 
             traceback.print_exc()
-            raise RuntimeError(f"Error initializing TGIAdapter: {e}")
+            raise RuntimeError(f"Error initializing TGIAdapter: {e}") from e
 
     async def shutdown(self) -> None:
         pass
@@ -244,12 +241,15 @@ class InferenceEndpointAdapter(TGIAdapter):
             "or 'endpoint_name'"
         )
         if "/" not in hf_endpoint_name:
-            hf_namespace: str = self.config.get_namespace()
+            hf_namespace: str = self.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}"
 
+    def get_namespace(self) -> str:
+        return HfApi().whoami()["name"]
+
     @property
     def client(self) -> InferenceClient:
         return InferenceClient(model=self.inference_url, token=self.config.api_token)