[Feature] Warn about unrecognized environment variables (#33581)

Signed-off-by: Gregory Shtrasberg <Gregory.Shtrasberg@amd.com>

tests/config/test_config_generation.py

@@ -78,3 +78,27 @@ def test_ray_runtime_env(monkeypatch: pytest.MonkeyPatch):
     )
 
     ray.shutdown()
+
+
+def test_unrecognized_env():
+    import os
+
+    # Test that if fail_on_environ_validation is True, then an error
+    # is raised when an unrecognized vLLM environment variable is set
+    os.environ["VLLM_UNRECOGNIZED_ENV_VAR"] = "some_value"
+    engine_args = EngineArgs(
+        fail_on_environ_validation=True,
+    )
+    with pytest.raises(ValueError, match="Unknown vLLM environment variable detected"):
+        engine_args.create_engine_config()
+
+    # Test that if fail_on_environ_validation is False, then no error is raised
+    engine_args = EngineArgs()
+    engine_args.create_engine_config()
+
+    # Test that when the unrecognized env var is removed, no error is raised
+    os.environ.pop("VLLM_UNRECOGNIZED_ENV_VAR", None)
+    engine_args = EngineArgs(
+        fail_on_environ_validation=True,
+    )
+    engine_args.create_engine_config()

vllm/engine/arg_utils.py

@@ -593,6 +593,8 @@ class EngineArgs:
         "weight_transfer_config",
     )
 
+    fail_on_environ_validation: bool = False
+
     def __post_init__(self):
         # support `EngineArgs(compilation_config={...})`
         # without having to manually construct a
@@ -1239,6 +1241,14 @@ class EngineArgs:
             help="Log aggregate rather than per-engine statistics "
             "when using data parallelism.",
         )
+
+        parser.add_argument(
+            "--fail-on-environ-validation",
+            help="If set, the engine will raise an error if "
+            "environment validation fails.",
+            default=False,
+            action=argparse.BooleanOptionalAction,
+        )
         return parser
 
     @classmethod
@@ -1396,6 +1406,8 @@ class EngineArgs:
 
         device_config = DeviceConfig(device=cast(Device, current_platform.device_type))
 
+        envs.validate_environ(self.fail_on_environ_validation)
+
         # Check if the model is a speculator and override model/tokenizer/config
         # BEFORE creating ModelConfig, so the config is created with the target model
         # Skip speculator detection for cloud storage models (eg: S3, GCS) since

vllm/envs.py

@@ -1606,6 +1606,15 @@ def is_set(name: str):
     raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
 
 
+def validate_environ(hard_fail: bool) -> None:
+    for env in os.environ:
+        if env.startswith("VLLM_") and env not in environment_variables:
+            if hard_fail:
+                raise ValueError(f"Unknown vLLM environment variable detected: {env}")
+            else:
+                logger.warning("Unknown vLLM environment variable detected: %s", env)
+
+
 def compile_factors() -> dict[str, object]:
     """Return env vars used for torch.compile cache keys.