all providers

llama_stack/providers/inline/inference/vllm/vllm.py

@@ -201,7 +201,7 @@ class VLLMInferenceImpl(Inference, ModelsProtocolPrivate):
         response = OpenAICompatCompletionResponse(
             choices=[choice],
         )
-        return process_chat_completion_response(response, self.formatter)
+        return process_chat_completion_response(response, self.formatter, request)
 
     async def _stream_chat_completion(
         self, request: ChatCompletionRequest, results_generator: AsyncGenerator
@@ -227,7 +227,7 @@ class VLLMInferenceImpl(Inference, ModelsProtocolPrivate):
                 )
 
         stream = _generate_and_convert_to_openai_compat()
-        async for chunk in process_chat_completion_stream_response(stream, self.formatter):
+        async for chunk in process_chat_completion_stream_response(stream, self.formatter, request):
             yield chunk
 
     async def embeddings(self, model_id: str, contents: List[InterleavedContent]) -> EmbeddingsResponse:

llama_stack/providers/remote/inference/bedrock/bedrock.py

@@ -134,7 +134,7 @@ class BedrockInferenceAdapter(ModelRegistryHelper, Inference):
         )
 
         response = OpenAICompatCompletionResponse(choices=[choice])
-        return process_chat_completion_response(response, self.formatter)
+        return process_chat_completion_response(response, self.formatter, request)
 
     async def _stream_chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
         params = await self._get_params_for_chat_completion(request)
@@ -152,7 +152,7 @@ class BedrockInferenceAdapter(ModelRegistryHelper, Inference):
                 yield OpenAICompatCompletionResponse(choices=[choice])
 
         stream = _generate_and_convert_to_openai_compat()
-        async for chunk in process_chat_completion_stream_response(stream, self.formatter):
+        async for chunk in process_chat_completion_stream_response(stream, self.formatter, request):
             yield chunk
 
     async def _get_params_for_chat_completion(self, request: ChatCompletionRequest) -> Dict:

llama_stack/providers/remote/inference/cerebras/cerebras.py

@@ -155,14 +155,14 @@ class CerebrasInferenceAdapter(ModelRegistryHelper, Inference):
 
         r = await self.client.completions.create(**params)
 
-        return process_chat_completion_response(r, self.formatter)
+        return process_chat_completion_response(r, self.formatter, request)
 
     async def _stream_chat_completion(self, request: CompletionRequest) -> AsyncGenerator:
         params = await self._get_params(request)
 
         stream = await self.client.completions.create(**params)
 
-        async for chunk in process_chat_completion_stream_response(stream, self.formatter):
+        async for chunk in process_chat_completion_stream_response(stream, self.formatter, request):
             yield chunk
 
     async def _get_params(self, request: Union[ChatCompletionRequest, CompletionRequest]) -> dict:

llama_stack/providers/remote/inference/databricks/databricks.py

@@ -112,7 +112,7 @@ class DatabricksInferenceAdapter(ModelRegistryHelper, Inference):
     ) -> ChatCompletionResponse:
         params = self._get_params(request)
         r = client.completions.create(**params)
-        return process_chat_completion_response(r, self.formatter)
+        return process_chat_completion_response(r, self.formatter, request)
 
     async def _stream_chat_completion(self, request: ChatCompletionRequest, client: OpenAI) -> AsyncGenerator:
         params = self._get_params(request)

llama_stack/providers/remote/inference/ollama/ollama.py

@@ -304,7 +304,7 @@ class OllamaInferenceAdapter(Inference, ModelsProtocolPrivate):
         response = OpenAICompatCompletionResponse(
             choices=[choice],
         )
-        return process_chat_completion_response(response, self.formatter)
+        return process_chat_completion_response(response, self.formatter, request)
 
     async def _stream_chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
         params = await self._get_params(request)
@@ -330,7 +330,7 @@ class OllamaInferenceAdapter(Inference, ModelsProtocolPrivate):
                 )
 
         stream = _generate_and_convert_to_openai_compat()
-        async for chunk in process_chat_completion_stream_response(stream, self.formatter):
+        async for chunk in process_chat_completion_stream_response(stream, self.formatter, request):
             yield chunk
 
     async def embeddings(

llama_stack/providers/remote/inference/runpod/runpod.py

@@ -99,7 +99,7 @@ class RunpodInferenceAdapter(ModelRegistryHelper, Inference):
     ) -> ChatCompletionResponse:
         params = self._get_params(request)
         r = client.completions.create(**params)
-        return process_chat_completion_response(r, self.formatter)
+        return process_chat_completion_response(r, self.formatter, request)
 
     async def _stream_chat_completion(self, request: ChatCompletionRequest, client: OpenAI) -> AsyncGenerator:
         params = self._get_params(request)
@@ -110,7 +110,7 @@ class RunpodInferenceAdapter(ModelRegistryHelper, Inference):
                 yield chunk
 
         stream = _to_async_generator()
-        async for chunk in process_chat_completion_stream_response(stream, self.formatter):
+        async for chunk in process_chat_completion_stream_response(stream, self.formatter, request):
             yield chunk
 
     def _get_params(self, request: ChatCompletionRequest) -> dict:

llama_stack/providers/remote/inference/sambanova/sambanova.py

@@ -159,7 +159,7 @@ class SambaNovaInferenceAdapter(ModelRegistryHelper, Inference):
                 yield chunk
 
         stream = _to_async_generator()
-        async for chunk in process_chat_completion_stream_response(stream, self.formatter):
+        async for chunk in process_chat_completion_stream_response(stream, self.formatter, request):
             yield chunk
 
     async def embeddings(

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

@@ -236,7 +236,7 @@ class _HfAdapter(Inference, ModelsProtocolPrivate):
         response = OpenAICompatCompletionResponse(
             choices=[choice],
         )
-        return process_chat_completion_response(response, self.formatter)
+        return process_chat_completion_response(response, self.formatter, request)
 
     async def _stream_chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
         params = await self._get_params(request)
@@ -252,7 +252,7 @@ class _HfAdapter(Inference, ModelsProtocolPrivate):
                 )
 
         stream = _generate_and_convert_to_openai_compat()
-        async for chunk in process_chat_completion_stream_response(stream, self.formatter):
+        async for chunk in process_chat_completion_stream_response(stream, self.formatter, request):
             yield chunk
 
     async def _get_params(self, request: ChatCompletionRequest) -> dict:

llama_stack/providers/remote/inference/together/together.py

@@ -220,7 +220,7 @@ class TogetherInferenceAdapter(ModelRegistryHelper, Inference, NeedsRequestProvi
             r = self._get_client().chat.completions.create(**params)
         else:
             r = self._get_client().completions.create(**params)
-        return process_chat_completion_response(r, self.formatter)
+        return process_chat_completion_response(r, self.formatter, request)
 
     async def _stream_chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
         params = await self._get_params(request)
@@ -235,7 +235,7 @@ class TogetherInferenceAdapter(ModelRegistryHelper, Inference, NeedsRequestProvi
                 yield chunk
 
         stream = _to_async_generator()
-        async for chunk in process_chat_completion_stream_response(stream, self.formatter):
+        async for chunk in process_chat_completion_stream_response(stream, self.formatter, request):
             yield chunk
 
     async def _get_params(self, request: Union[ChatCompletionRequest, CompletionRequest]) -> dict:

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

@@ -142,7 +142,7 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
     ) -> ChatCompletionResponse:
         params = await self._get_params(request)
         r = client.chat.completions.create(**params)
-        return process_chat_completion_response(r, self.formatter)
+        return process_chat_completion_response(r, self.formatter, request)
 
     async def _stream_chat_completion(self, request: ChatCompletionRequest, client: OpenAI) -> AsyncGenerator:
         params = await self._get_params(request)
@@ -155,7 +155,7 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
                 yield chunk
 
         stream = _to_async_generator()
-        async for chunk in process_chat_completion_stream_response(stream, self.formatter):
+        async for chunk in process_chat_completion_stream_response(stream, self.formatter, request):
             yield chunk
 
     async def _nonstream_completion(self, request: CompletionRequest) -> CompletionResponse: