[Bugfix] Enable V1 usage stats

vllm/v1/engine/async_llm.py

@@ -36,6 +36,7 @@
 from vllm.v1.metrics.loggers import (LoggingStatLogger, PrometheusStatLogger,
                                      StatLoggerBase)
 from vllm.v1.metrics.stats import IterationStats, SchedulerStats
+from vllm.v1.utils import report_usage_stats
 
 logger = init_logger(__name__)
 
@@ -114,6 +115,9 @@ def __init__(
         except RuntimeError:
             pass
 
+        # If usage stat is enabled, collect relevant info.
+        report_usage_stats(vllm_config, usage_context)
+
     @classmethod
     def from_vllm_config(
         cls,

vllm/v1/engine/llm_engine.py

@@ -28,6 +28,7 @@
 from vllm.v1.engine.parallel_sampling import ParentRequest
 from vllm.v1.engine.processor import Processor
 from vllm.v1.executor.abstract import Executor
+from vllm.v1.utils import report_usage_stats
 
 logger = init_logger(__name__)
 
@@ -99,6 +100,9 @@ def __init__(
             # for v0 compatibility
             self.model_executor = self.engine_core.engine_core.model_executor  # type: ignore
 
+        # If usage stat is enabled, collect relevant info.
+        report_usage_stats(vllm_config, usage_context)
+
     @classmethod
     def from_vllm_config(
         cls,

vllm/v1/utils.py

@@ -201,3 +201,51 @@ def copy_slice(from_tensor: torch.Tensor, to_tensor: torch.Tensor,
     Returns the sliced target tensor.
     """
     return to_tensor[:length].copy_(from_tensor[:length], non_blocking=True)
+
+
+def report_usage_stats(vllm_config, usage_context: str) -> None:
+    """Report usage statistics if enabled.
+
+    Args:
+        vllm_config: The vLLM configuration object containing model_config, 
+                    cache_config, parallel_config, etc.
+        usage_context: The context string for usage reporting
+    """
+    from vllm.usage.usage_lib import is_usage_stats_enabled, usage_message
+
+    if is_usage_stats_enabled():
+        from vllm.model_executor.model_loader import (
+            get_architecture_class_name)
+
+        usage_message.report_usage(
+            get_architecture_class_name(vllm_config.model_config),
+            usage_context,
+            extra_kvs={
+                # Common configuration
+                "dtype":
+                str(vllm_config.model_config.dtype),
+                "tensor_parallel_size":
+                vllm_config.parallel_config.tensor_parallel_size,
+                "block_size":
+                vllm_config.cache_config.block_size,
+                "gpu_memory_utilization":
+                vllm_config.cache_config.gpu_memory_utilization,
+
+                # Quantization
+                "quantization":
+                vllm_config.model_config.quantization,
+                "kv_cache_dtype":
+                str(vllm_config.cache_config.cache_dtype),
+
+                # Feature flags
+                "enable_lora":
+                bool(vllm_config.lora_config),
+                "enable_prompt_adapter":
+                bool(vllm_config.prompt_adapter_config),
+                "enable_prefix_caching":
+                vllm_config.cache_config.enable_prefix_caching,
+                "enforce_eager":
+                vllm_config.model_config.enforce_eager,
+                "disable_custom_all_reduce":
+                vllm_config.parallel_config.disable_custom_all_reduce,
+            })