[Core] Remove prompt string from engine core data structures (#17214)

Signed-off-by: Nick Hill <nhill@redhat.com>

tests/tokenization/test_detokenize.py

@@ -60,8 +60,8 @@ def _run_incremental_decode(tokenizer,
         skip_special_tokens=skip_special_tokens,
         spaces_between_special_tokens=spaces_between_special_tokens,
     )
-    request = EngineCoreRequest("", "", prompt_token_ids, None, None, None,
-                                params, None, 0.0, None)
+    request = EngineCoreRequest("", prompt_token_ids, None, None, None, params,
+                                None, 0.0, None)
 
     if fast is None:
         detokenizer = IncrementalDetokenizer.from_new_request(

tests/v1/core/test_kv_cache_utils.py

@@ -37,7 +37,6 @@ def make_request(request_id,
 
     return Request(
         request_id=request_id,
-        prompt=None,
         prompt_token_ids=prompt_token_ids,
         multi_modal_inputs=multi_modal_inputs,
         multi_modal_hashes=mm_hashes,

tests/v1/core/test_prefix_caching.py

@@ -29,7 +29,6 @@ def make_request(request_id,
 
     return Request(
         request_id=request_id,
-        prompt=None,
         prompt_token_ids=prompt_token_ids,
         multi_modal_inputs=multi_modal_inputs,
         multi_modal_hashes=mm_hashes,

tests/v1/core/test_scheduler.py

@@ -132,7 +132,6 @@ def create_requests(num_requests: int,
             mm_inputs = None
         request = Request(
             request_id=f"{i}",
-            prompt=None,
             prompt_token_ids=[i] * num_tokens,
             sampling_params=sampling_params,
             multi_modal_inputs=mm_inputs,

tests/v1/engine/test_engine_core.py

@@ -31,8 +31,7 @@ PROMPT_TOKENS = TOKENIZER(PROMPT).input_ids
 
 def make_request() -> EngineCoreRequest:
     return EngineCoreRequest(
-        request_id=uuid.uuid4(),
-        prompt=PROMPT,
+        request_id=str(uuid.uuid4()),
         prompt_token_ids=PROMPT_TOKENS,
         mm_inputs=None,
         mm_hashes=None,

tests/v1/engine/test_engine_core_client.py

@@ -35,7 +35,6 @@ PROMPT_TOKENS = TOKENIZER(PROMPT).input_ids
 def make_request(params: SamplingParams) -> EngineCoreRequest:
     return EngineCoreRequest(
         request_id=str(uuid.uuid4()),
-        prompt=PROMPT,
         prompt_token_ids=PROMPT_TOKENS,
         mm_inputs=None,
         mm_hashes=None,

tests/v1/engine/test_output_processor.py

@@ -50,7 +50,6 @@ def test_incremental_detokenization(request_output_kind: RequestOutputKind,
     # Make N requests.
     requests = [
         EngineCoreRequest(request_id=f"request-{idx}",
-                          prompt=prompt,
                           prompt_token_ids=prompt_tokens,
                           arrival_time=0,
                           mm_inputs=None,
@@ -64,14 +63,13 @@ def test_incremental_detokenization(request_output_kind: RequestOutputKind,
                               output_kind=request_output_kind,
                               stop=[],
                               include_stop_str_in_output=False,
-                          )) for idx, (prompt, prompt_tokens) in enumerate(
-                              zip(dummy_test_vectors.prompt_strings,
-                                  dummy_test_vectors.prompt_tokens))
+                          ))
+        for idx, prompt_tokens in enumerate(dummy_test_vectors.prompt_tokens)
     ]
 
     # Add requests to the detokenizer.
-    for request in requests:
-        output_processor.add_request(request)
+    for request, prompt in zip(requests, dummy_test_vectors.prompt_strings):
+        output_processor.add_request(request, prompt)
 
     gen_strings = {}
     gen_tokens = {}
@@ -398,7 +396,6 @@ def test_logprobs_processor(request_output_kind: RequestOutputKind,
     ]
     requests = [
         EngineCoreRequest(request_id=request_id_list[idx],
-                          prompt=prompt,
                           prompt_token_ids=prompt_tokens,
                           arrival_time=0,
                           mm_inputs=None,
@@ -414,14 +411,13 @@ def test_logprobs_processor(request_output_kind: RequestOutputKind,
                               include_stop_str_in_output=False,
                               logprobs=num_sample_logprobs,
                               prompt_logprobs=num_prompt_logprobs,
-                          )) for idx, (prompt, prompt_tokens) in enumerate(
-                              zip(dummy_test_vectors.prompt_strings,
-                                  dummy_test_vectors.prompt_tokens))
+                          ))
+        for idx, prompt_tokens in enumerate(dummy_test_vectors.prompt_tokens)
     ]
 
     # Add requests to the detokenizer.
-    for request in requests:
-        output_processor.add_request(request)
+    for request, prompt in zip(requests, dummy_test_vectors.prompt_strings):
+        output_processor.add_request(request, prompt)
 
     gen_tokens = {}
     gen_logprobs = {}
@@ -562,7 +558,6 @@ def test_stop_token(include_stop_str_in_output: bool,
     request_id = "request-0"
     request = EngineCoreRequest(
         request_id=request_id,
-        prompt=prompt_string,
         prompt_token_ids=prompt_tokens,
         arrival_time=0,
         mm_inputs=None,
@@ -583,7 +578,7 @@ def test_stop_token(include_stop_str_in_output: bool,
         ))
 
     # Add request to the detokenizer.
-    output_processor.add_request(request)
+    output_processor.add_request(request, prompt_string)
 
     # Loop over engine core steps; run output processor
     gen_string = ""
@@ -659,7 +654,6 @@ def test_stop_string(include_stop_str_in_output: bool,
     requests = [
         EngineCoreRequest(
             request_id=request_id_list[idx],
-            prompt=prompt,
             prompt_token_ids=prompt_tokens,
             arrival_time=0,
             mm_inputs=None,
@@ -675,14 +669,13 @@ def test_stop_string(include_stop_str_in_output: bool,
                 include_stop_str_in_output=include_stop_str_in_output,
                 logprobs=num_sample_logprobs,
                 prompt_logprobs=None,
-            )) for idx, (prompt, prompt_tokens) in enumerate(
-                zip(dummy_test_vectors.prompt_strings,
-                    dummy_test_vectors.prompt_tokens))
+            ))
+        for idx, prompt_tokens in enumerate(dummy_test_vectors.prompt_tokens)
     ]
 
     # Add requests to the detokenizer.
-    for request in requests:
-        output_processor.add_request(request)
+    for request, prompt in zip(requests, dummy_test_vectors.prompt_strings):
+        output_processor.add_request(request, prompt)
 
     gen_strings = {}
     gen_tokens = {}
@@ -774,7 +767,6 @@ def test_iteration_stats(dummy_test_vectors):
     requests = [
         EngineCoreRequest(
             request_id=f"request-{idx}",
-            prompt=prompt,
             prompt_token_ids=prompt_tokens,
             arrival_time=0,
             mm_inputs=None,
@@ -783,15 +775,13 @@ def test_iteration_stats(dummy_test_vectors):
             eos_token_id=None,
             lora_request=None,
             sampling_params=SamplingParams(),
-        ) for idx, (prompt, prompt_tokens) in enumerate(
-            zip(dummy_test_vectors.prompt_strings,
-                dummy_test_vectors.prompt_tokens))
+        ) for idx, prompt_tokens in enumerate(dummy_test_vectors.prompt_tokens)
     ]
 
     # Add all requests except one to the OutputProcessor.
     num_active = len(dummy_test_vectors.generation_tokens) - 1
     for request in requests[:num_active]:
-        output_processor.add_request(request)
+        output_processor.add_request(request, None)
     inactive_request = requests[num_active]
 
     # First iteration has 2 prefills.
@@ -817,7 +807,7 @@ def test_iteration_stats(dummy_test_vectors):
     assert iteration_stats.num_generation_tokens == num_active
 
     # Add a new request - prefill and 2 decodes in this step.
-    output_processor.add_request(inactive_request)
+    output_processor.add_request(inactive_request, None)
     num_active += 1
     outputs = engine_core.get_outputs()[:num_active]
     iteration_stats = IterationStats()

tests/v1/tpu/worker/test_tpu_model_runner.py

@@ -77,7 +77,6 @@ def _schedule_new_request(*req_ids: str) -> SchedulerOutput:
             NewRequestData(
                 req_id=req_id,
                 prompt_token_ids=[1, 2, 3],
-                prompt="test",
                 mm_inputs=[],
                 mm_hashes=[],
                 mm_positions=[],

tests/v1/worker/test_gpu_input_batch.py

@@ -195,7 +195,6 @@ def _construct_cached_request_state(req_id_suffix: int):
     return CachedRequestState(
         req_id=f"req_id_{req_id_suffix}",
         prompt_token_ids=prompt_token_ids,
-        prompt=None,
         sampling_params=_create_sampling_params(),
         mm_inputs=[],
         mm_positions=[],

tests/v1/worker/test_gpu_model_runner.py

@@ -50,7 +50,6 @@ def _schedule_new_request(*req_ids: str) -> SchedulerOutput:
             NewRequestData(
                 req_id=req_id,
                 prompt_token_ids=[1, 2, 3],
-                prompt="test",
                 mm_inputs=[],
                 mm_hashes=[],
                 mm_positions=[],

vllm/v1/core/sched/output.py

@@ -22,7 +22,6 @@ class NewRequestData:
 
     req_id: str
     prompt_token_ids: list[int]
-    prompt: Optional[str]
     mm_inputs: list[MultiModalKwargs]
     mm_hashes: list[str]
     mm_positions: list[PlaceholderRange]
@@ -40,7 +39,6 @@ class NewRequestData:
         return cls(
             req_id=request.request_id,
             prompt_token_ids=request.prompt_token_ids,
-            prompt=request.prompt,
             mm_inputs=request.mm_inputs,
             mm_hashes=request.mm_hashes,
             mm_positions=request.mm_positions,

vllm/v1/engine/__init__.py

@@ -49,9 +49,6 @@ class EngineCoreRequest(
     # due to circular imports and typing we have in data.py
 
     request_id: str
-    # NOTE(ywang96): original text prompt is needed when a request is added to
-    # Detokenizer, but set to None when it is added to EngineCoreClient.
-    prompt: Optional[str]
     prompt_token_ids: list[int]
     mm_inputs: Optional[Sequence[Optional[MultiModalKwargs]]]
     mm_hashes: Optional[list[str]]

vllm/v1/engine/async_llm.py

@@ -217,14 +217,12 @@ class AsyncLLM(EngineClient):
         queue = RequestOutputCollector(output_kind=params.output_kind)
 
         # Convert Input --> Request.
-        request = self.processor.process_inputs(request_id, prompt, params,
-                                                arrival_time, lora_request,
-                                                trace_headers,
-                                                prompt_adapter_request,
-                                                priority)
+        prompt_str, request = self.processor.process_inputs(
+            request_id, prompt, params, arrival_time, lora_request,
+            trace_headers, prompt_adapter_request, priority)
 
         if params.n == 1:
-            await self._add_request(request, None, 0, queue)
+            await self._add_request(request, prompt_str, None, 0, queue)
             return queue
 
         # Fan out child requests (for n>1).
@@ -234,15 +232,18 @@ class AsyncLLM(EngineClient):
             child_request = request if idx == params.n - 1 else copy(request)
             child_request.request_id = request_id
             child_request.sampling_params = params
-            await self._add_request(child_request, parent_request, idx, queue)
+            await self._add_request(child_request, prompt_str, parent_request,
+                                    idx, queue)
         return queue
 
     async def _add_request(self, request: EngineCoreRequest,
+                           prompt: Optional[str],
                            parent_req: Optional[ParentRequest], index: int,
                            queue: RequestOutputCollector):
 
         # Add the request to OutputProcessor (this process).
-        self.output_processor.add_request(request, parent_req, index, queue)
+        self.output_processor.add_request(request, prompt, parent_req, index,
+                                          queue)
 
         # Add the EngineCoreRequest to EngineCore (separate process).
         await self.engine_core.add_request_async(request)

vllm/v1/engine/core_client.py

@@ -583,9 +583,6 @@ class SyncMPClient(MPClient):
         return future.result()
 
     def add_request(self, request: EngineCoreRequest) -> None:
-        # NOTE: text prompt is not needed in the core engine as it has been
-        # tokenized.
-        request.prompt = None
         self._send_input(EngineCoreRequestType.ADD, request)
 
     def abort_requests(self, request_ids: list[str]) -> None:
@@ -772,9 +769,6 @@ class AsyncMPClient(MPClient):
         return await future
 
     async def add_request_async(self, request: EngineCoreRequest) -> None:
-        # NOTE: text prompt is not needed in the core engine as it has been
-        # tokenized.
-        request.prompt = None
         await self._send_input(EngineCoreRequestType.ADD, request)
         self._ensure_output_queue_task()
 
@@ -867,9 +861,6 @@ class DPAsyncMPClient(AsyncMPClient):
         ]))[0]
 
     async def add_request_async(self, request: EngineCoreRequest) -> None:
-        # NOTE: text prompt is not needed in the core engine as it has been
-        # tokenized.
-        request.prompt = None
         request.current_wave = self.current_wave
 
         chosen_engine = self.get_core_engine_for_request()

vllm/v1/engine/llm_engine.py

@@ -180,17 +180,15 @@ class LLMEngine:
         priority: int = 0,
     ) -> None:
         # Process raw inputs into the request.
-        request = self.processor.process_inputs(request_id, prompt, params,
-                                                arrival_time, lora_request,
-                                                trace_headers,
-                                                prompt_adapter_request,
-                                                priority)
+        prompt_str, request = self.processor.process_inputs(
+            request_id, prompt, params, arrival_time, lora_request,
+            trace_headers, prompt_adapter_request, priority)
 
         n = params.n if isinstance(params, SamplingParams) else 1
 
         if n == 1:
             # Make a new RequestState and queue.
-            self.output_processor.add_request(request, None, 0)
+            self.output_processor.add_request(request, prompt_str, None, 0)
             # Add the request to EngineCore.
             self.engine_core.add_request(request)
             return
@@ -204,7 +202,8 @@ class LLMEngine:
             child_request.sampling_params = params
 
             # Make a new RequestState and queue.
-            self.output_processor.add_request(child_request, parent_req, idx)
+            self.output_processor.add_request(child_request, prompt_str,
+                                              parent_req, idx)
             # Add the request to EngineCore.
             self.engine_core.add_request(child_request)
 

vllm/v1/engine/output_processor.py

@@ -109,6 +109,7 @@ class RequestState:
         cls,
         tokenizer: AnyTokenizer,
         request: EngineCoreRequest,
+        prompt: Optional[str],
         parent_req: Optional[ParentRequest],
         request_index: int,
         queue: Optional[RequestOutputCollector],
@@ -123,7 +124,7 @@ class RequestState:
             lora_name=(request.lora_request.name
                        if request.lora_request is not None else None),
             output_kind=request.sampling_params.output_kind,
-            prompt=request.prompt,
+            prompt=prompt,
             prompt_token_ids=request.prompt_token_ids,
             logprobs_processor=LogprobsProcessor.from_new_request(
                 tokenizer=tokenizer,
@@ -267,6 +268,7 @@ class OutputProcessor:
     def add_request(
         self,
         request: EngineCoreRequest,
+        prompt: Optional[str],
         parent_req: Optional[ParentRequest] = None,
         request_index: int = 0,
         queue: Optional[RequestOutputCollector] = None,
@@ -278,6 +280,7 @@ class OutputProcessor:
         req_state = RequestState.from_new_request(
             tokenizer=self.tokenizer.get_lora_tokenizer(request.lora_request),
             request=request,
+            prompt=prompt,
             parent_req=parent_req,
             request_index=request_index,
             queue=queue,

vllm/v1/engine/processor.py

@@ -202,7 +202,7 @@ class Processor:
         trace_headers: Optional[Mapping[str, str]] = None,
         prompt_adapter_request: Optional[PromptAdapterRequest] = None,
         priority: int = 0,
-    ) -> EngineCoreRequest:
+    ) -> tuple[Optional[str], EngineCoreRequest]:
 
         # TODO(woosuk): Support pooling models.
         # TODO(woosuk): Support encoder-decoder models.
@@ -306,9 +306,8 @@ class Processor:
             else:
                 sorted_mm_inputs = orig_sorted_mm_inputs
 
-        return EngineCoreRequest(
+        return decoder_inputs.get("prompt"), EngineCoreRequest(
             request_id=request_id,
-            prompt=decoder_inputs.get("prompt"),
             prompt_token_ids=decoder_inputs["prompt_token_ids"],
             mm_inputs=sorted_mm_inputs,
             mm_hashes=sorted_mm_hashes,

vllm/v1/request.py

@@ -20,7 +20,6 @@ class Request:
     def __init__(
         self,
         request_id: str,
-        prompt: Optional[str],
         prompt_token_ids: list[int],
         multi_modal_inputs: Optional[list[MultiModalKwargs]],
         multi_modal_hashes: Optional[list[str]],
@@ -46,7 +45,6 @@ class Request:
         assert sampling_params.max_tokens is not None
         self.max_tokens = sampling_params.max_tokens
 
-        self.prompt = prompt
         self.prompt_token_ids = prompt_token_ids
         self.num_prompt_tokens = len(self.prompt_token_ids)
         self._output_token_ids: list[int] = []
@@ -81,7 +79,6 @@ class Request:
 
         return cls(
             request_id=request.request_id,
-            prompt=request.prompt,
             prompt_token_ids=request.prompt_token_ids,
             multi_modal_inputs=request.mm_inputs,
             multi_modal_hashes=request.mm_hashes,

vllm/v1/worker/gpu_input_batch.py

@@ -24,7 +24,6 @@ class CachedRequestState:
 
     req_id: str
     prompt_token_ids: list[int]
-    prompt: Optional[str]
     mm_inputs: list[MultiModalKwargs]
     mm_positions: list[PlaceholderRange]
     sampling_params: SamplingParams

vllm/v1/worker/gpu_model_runner.py

@@ -347,7 +347,6 @@ class GPUModelRunner(LoRAModelRunnerMixin):
             self.requests[req_id] = CachedRequestState(
                 req_id=req_id,
                 prompt_token_ids=new_req_data.prompt_token_ids,
-                prompt=new_req_data.prompt,
                 mm_inputs=new_req_data.mm_inputs,
                 mm_positions=new_req_data.mm_positions,
                 sampling_params=sampling_params,