[V1][Metrics] Implement vllm:request_params_max_tokens

This just observes SamplingParams.max_tokens values in a histogram.

Signed-off-by: Mark McLoughlin <[email protected]>

Author: markmc

tests/entrypoints/openai/test_metrics.py

@@ -242,6 +242,9 @@ async def test_metrics_counts(server: RemoteOpenAIServer,
     "vllm:request_params_n_sum",
     "vllm:request_params_n_bucket",
     "vllm:request_params_n_count",
+    "vllm:request_params_max_tokens_sum",
+    "vllm:request_params_max_tokens_bucket",
+    "vllm:request_params_max_tokens_count",
     "vllm:time_to_first_token_seconds_sum",
     "vllm:time_to_first_token_seconds_bucket",
     "vllm:time_to_first_token_seconds_count",

vllm/v1/engine/output_processor.py

@@ -36,6 +36,7 @@ def __init__(
         prompt_token_ids: list[int],
         logprobs_processor: LogprobsProcessor,
         detokenizer: IncrementalDetokenizer,
+        max_tokens_param: Optional[int],
         arrival_time: float,
         queue: Optional[asyncio.Queue[RequestOutput]],
         log_stats: bool,
@@ -50,6 +51,7 @@ def __init__(
         self.prompt_len = len(prompt_token_ids)
         self.logprobs_processor = logprobs_processor
         self.detokenizer = detokenizer
+        self.max_tokens_param = max_tokens_param
         self.is_prefilling = True
         self.queue = queue
 
@@ -83,6 +85,8 @@ def from_new_request(
                 tokenizer=tokenizer,
                 request=request,
             ),
+            max_tokens_param=(request.sampling_params.max_tokens if
+                              request.sampling_params is not None else None),
             arrival_time=request.arrival_time,
             queue=queue,
             log_stats=log_stats,
@@ -354,6 +358,7 @@ def _update_stats_from_finished(self, req_state: RequestState,
         iteration_stats.update_from_finished_request(
             finish_reason=finish_reason,
             num_prompt_tokens=len(req_state.prompt_token_ids),
+            max_tokens_param=req_state.max_tokens_param,
             req_stats=req_state.stats)
         self.lora_states.finish_request(req_state)
 

vllm/v1/metrics/loggers.py

@@ -206,6 +206,13 @@ def __init__(self, vllm_config: VllmConfig):
                 buckets=[1, 2, 5, 10, 20],
                 labelnames=labelnames).labels(*labelvalues)
 
+        self.histogram_max_tokens_request = \
+            prometheus_client.Histogram(
+                name="vllm:request_params_max_tokens",
+                documentation="Histogram of the max_tokens request parameter.",
+                buckets=build_1_2_5_buckets(max_model_len),
+                labelnames=labelnames).labels(*labelvalues)
+
         #
         # Histogram of timing intervals
         #
@@ -357,6 +364,8 @@ def log(self, scheduler_stats: SchedulerStats,
                 finished_request.num_prompt_tokens)
             self.histogram_num_generation_tokens_request.observe(
                 finished_request.num_generation_tokens)
+            self.histogram_max_tokens_request.observe(
+                finished_request.max_tokens_param)
 
         if self.gauge_lora_info is not None:
             running_lora_adapters = \

vllm/v1/metrics/stats.py

@@ -66,6 +66,7 @@ class FinishedRequestStats:
     e2e_latency: float = 0.0
     num_prompt_tokens: int = 0
     num_generation_tokens: int = 0
+    max_tokens_param: Optional[int] = None
     queued_time: float = 0.0
     prefill_time: float = 0.0
     inference_time: float = 0.0
@@ -152,6 +153,7 @@ def update_from_events(self, req_id: str, events: list["EngineCoreEvent"],
 
     def update_from_finished_request(self, finish_reason: "FinishReason",
                                      num_prompt_tokens: int,
+                                     max_tokens_param: Optional[int],
                                      req_stats: RequestStateStats):
         e2e_latency = self._time_since(req_stats.arrival_time)
 
@@ -175,6 +177,7 @@ def update_from_finished_request(self, finish_reason: "FinishReason",
                                  e2e_latency=e2e_latency,
                                  num_prompt_tokens=num_prompt_tokens,
                                  num_generation_tokens=req_stats.num_generation_tokens,
+                                 max_tokens_param=max_tokens_param,
                                  queued_time=queued_time,
                                  prefill_time=prefill_time,
                                  inference_time=inference_time,