fixes

src/llama_stack/providers/remote/inference/passthrough/passthrough.py

@@ -31,6 +31,12 @@ class PassthroughInferenceAdapter(NeedsRequestProviderData, Inference):
     def __init__(self, config: PassthroughImplConfig) -> None:
         self.config = config
 
+    async def initialize(self) -> None:
+        pass
+
+    async def shutdown(self) -> None:
+        pass
+
     async def unregister_model(self, model_id: str) -> None:
         pass
 
@@ -53,8 +59,27 @@ class PassthroughInferenceAdapter(NeedsRequestProviderData, Inference):
             response.raise_for_status()
 
             response_data = response.json()
-            # The response should be a list of Model objects
-            return [Model.model_validate(m) for m in response_data]
+            models_data = response_data["data"]
+
+            # Convert from OpenAI format to Llama Stack Model format
+            models = []
+            for model_data in models_data:
+                downstream_model_id = model_data["id"]
+                custom_metadata = model_data.get("custom_metadata", {})
+
+                # Prefix identifier with provider ID for local registry
+                local_identifier = f"{self.__provider_id__}/{downstream_model_id}"
+
+                model = Model(
+                    identifier=local_identifier,
+                    provider_id=self.__provider_id__,
+                    provider_resource_id=downstream_model_id,
+                    model_type=custom_metadata.get("model_type", "llm"),
+                    metadata=custom_metadata,
+                )
+                models.append(model)
+
+            return models
 
     async def should_refresh_models(self) -> bool:
         """Passthrough should refresh models since they come from downstream dynamically."""
@@ -159,23 +184,22 @@ class PassthroughInferenceAdapter(NeedsRequestProviderData, Inference):
                         if not data_str or data_str == "[DONE]":
                             continue
 
-                        try:
-                            data = json.loads(data_str)
-                            yield response_type.model_validate(data)
-                        except Exception:
-                            # Log and skip malformed chunks
-                            continue
+                        data = json.loads(data_str)
+
+                        # Fix OpenAI compatibility: finish_reason can be null in intermediate chunks
+                        # but our Pydantic model may not accept null
+                        if "choices" in data:
+                            for choice in data["choices"]:
+                                if choice.get("finish_reason") is None:
+                                    choice["finish_reason"] = ""
+
+                        yield response_type.model_validate(data)
 
     async def openai_completion(
         self,
         params: OpenAICompletionRequestWithExtraBody,
     ) -> OpenAICompletion:
-        model_obj = await self.model_store.get_model(params.model)
-
-        # Create a copy with the provider's model ID
-        params = params.model_copy()
-        params.model = model_obj.provider_resource_id
-
+        # params.model is already the provider_resource_id (router translated it)
         request_params = params.model_dump(exclude_none=True)
 
         return await self._make_request(
@@ -189,12 +213,7 @@ class PassthroughInferenceAdapter(NeedsRequestProviderData, Inference):
         self,
         params: OpenAIChatCompletionRequestWithExtraBody,
     ) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
-        model_obj = await self.model_store.get_model(params.model)
-
-        # Create a copy with the provider's model ID
-        params = params.model_copy()
-        params.model = model_obj.provider_resource_id
-
+        # params.model is already the provider_resource_id (router translated it)
         request_params = params.model_dump(exclude_none=True)
 
         return await self._make_request(
@@ -208,12 +227,7 @@ class PassthroughInferenceAdapter(NeedsRequestProviderData, Inference):
         self,
         params: OpenAIEmbeddingsRequestWithExtraBody,
     ) -> OpenAIEmbeddingsResponse:
-        model_obj = await self.model_store.get_model(params.model)
-
-        # Create a copy with the provider's model ID
-        params = params.model_copy()
-        params.model = model_obj.provider_resource_id
-
+        # params.model is already the provider_resource_id (router translated it)
         request_params = params.model_dump(exclude_none=True)
 
         return await self._make_request(