Convert online APIs to use Renderer (#34084)

Signed-off-by: Reagan Lee <“reaganjlee@gmail.com”>
Co-authored-by: Reagan Lee <“reaganjlee@gmail.com”>

vllm/entrypoints/openai/speech_to_text/speech_to_text.py

@@ -471,15 +471,31 @@ class OpenAISpeechToText(OpenAIServing):
                 lora_request=lora_request,
             )
 
-            list_result_generator = [
-                self.engine_client.generate(
+            trace_headers = (
+                None
+                if raw_request is None
+                else await self._get_trace_headers(raw_request.headers)
+            )
+
+            list_result_generator = []
+            for i, prompt in enumerate(prompts):
+                request_id_item = f"{request_id}_{i}"
+                engine_request = self.input_processor.process_inputs(
+                    request_id_item,
                     prompt,
                     sampling_params,
-                    f"{request_id}_{i}",
                     lora_request=lora_request,
+                    trace_headers=trace_headers,
+                    priority=0,
+                )
+                list_result_generator.append(
+                    self.engine_client.generate(
+                        engine_request,
+                        sampling_params,
+                        request_id_item,
+                        lora_request=lora_request,
+                    )
                 )
-                for i, prompt in enumerate(prompts)
-            ]
         except ValueError as e:
             return self.create_error_response(e)
 

vllm/entrypoints/serve/disagg/serving.py

@@ -99,8 +99,6 @@ class ServingTokens(OpenAIServing):
         if raw_request:
             raw_request.state.request_metadata = request_metadata
 
-        # TODO(NickLucche): Change to EngineCoreRequest once Renderer work is
-        # completed
         engine_prompts = await self._preprocess_completion(
             request,
             prompt_input=request.token_ids,
@@ -132,16 +130,26 @@ class ServingTokens(OpenAIServing):
             tok_params = request.build_tok_params(self.model_config)
             tokenization_kwargs = tok_params.get_encode_kwargs()
 
-            result_generator = self.engine_client.generate(
+            engine_request = self.input_processor.process_inputs(
+                request_id,
                 engine_prompt,
                 sampling_params,
-                request_id,
                 lora_request=lora_request,
                 tokenization_kwargs=tokenization_kwargs,
                 trace_headers=trace_headers,
                 priority=request.priority,
             )
 
+            result_generator = self.engine_client.generate(
+                engine_request,
+                sampling_params,
+                request_id,
+                lora_request=lora_request,
+                trace_headers=trace_headers,
+                priority=request.priority,
+                tokenization_kwargs=tokenization_kwargs,
+            )
+
         except ValueError as e:
             return self.create_error_response(str(e))