Move deep gemm related arguments to `sglang.srt.environ` (#11547)

docs/basic_usage/deepseek.md

@@ -144,7 +144,7 @@ With data parallelism attention enabled, we have achieved up to **1.9x** decodin
 
 - **DeepGEMM**: The [DeepGEMM](https://github.com/deepseek-ai/DeepGEMM) kernel library optimized for FP8 matrix multiplications.
 
-**Usage**: The activation and weight optimization above are turned on by default for DeepSeek V3 models. DeepGEMM is enabled by default on NVIDIA Hopper GPUs and disabled by default on other devices. DeepGEMM can also be manually turned off by setting the environment variable `SGL_ENABLE_JIT_DEEPGEMM=0`.
+**Usage**: The activation and weight optimization above are turned on by default for DeepSeek V3 models. DeepGEMM is enabled by default on NVIDIA Hopper GPUs and disabled by default on other devices. DeepGEMM can also be manually turned off by setting the environment variable `SGLANG_ENABLE_JIT_DEEPGEMM=0`.
 
 Before serving the DeepSeek model, precompile the DeepGEMM kernels using:
 ```bash

docs/references/environment_variables.md

@@ -32,9 +32,9 @@ SGLang supports various environment variables that can be used to configure its
 
 | Environment Variable | Description | Default Value |
 | --- | --- | --- |
-| `SGL_ENABLE_JIT_DEEPGEMM` | Enable Just-In-Time compilation of DeepGEMM kernels | `"true"` |
-| `SGL_JIT_DEEPGEMM_PRECOMPILE` | Enable precompilation of DeepGEMM kernels | `"true"` |
-| `SGL_JIT_DEEPGEMM_COMPILE_WORKERS` | Number of workers for parallel DeepGEMM kernel compilation | `4` |
+| `SGLANG_ENABLE_JIT_DEEPGEMM` | Enable Just-In-Time compilation of DeepGEMM kernels | `"true"` |
+| `SGLANG_JIT_DEEPGEMM_PRECOMPILE` | Enable precompilation of DeepGEMM kernels | `"true"` |
+| `SGLANG_JIT_DEEPGEMM_COMPILE_WORKERS` | Number of workers for parallel DeepGEMM kernel compilation | `4` |
 | `SGL_IN_DEEPGEMM_PRECOMPILE_STAGE` | Indicator flag used during the DeepGEMM precompile script | `"false"` |
 | `SGL_DG_CACHE_DIR` | Directory for caching compiled DeepGEMM kernels | `~/.cache/deep_gemm` |
 | `SGL_DG_USE_NVRTC` | Use NVRTC (instead of Triton) for JIT compilation (Experimental) | `"0"` |

docs/references/multi_node_deployment/lws_pd/lws-examples/d.yaml

@@ -80,7 +80,7 @@ spec:
             value: "true"
           - name: SGLANG_MOONCAKE_TRANS_THREAD
             value: "16"
-          - name: SGL_ENABLE_JIT_DEEPGEMM
+          - name: SGLANG_ENABLE_JIT_DEEPGEMM
             value: "1"
           - name: NCCL_IB_HCA
             value: ^=mlx5_0,mlx5_5,mlx5_6
@@ -217,7 +217,7 @@ spec:
             value: "5"
           - name: SGLANG_MOONCAKE_TRANS_THREAD
             value: "16"
-          - name: SGL_ENABLE_JIT_DEEPGEMM
+          - name: SGLANG_ENABLE_JIT_DEEPGEMM
             value: "1"
           - name: NCCL_IB_HCA
             value: ^=mlx5_0,mlx5_5,mlx5_6

docs/references/multi_node_deployment/lws_pd/lws-examples/p.yaml

@@ -71,7 +71,7 @@ spec:
             value: "1"
           - name: SGLANG_SET_CPU_AFFINITY
             value: "true"
-          - name: SGL_ENABLE_JIT_DEEPGEMM
+          - name: SGLANG_ENABLE_JIT_DEEPGEMM
             value: "1"
           - name: NCCL_IB_QPS_PER_CONNECTION
             value: "8"
@@ -224,7 +224,7 @@ spec:
             value: "0"
           - name: SGLANG_MOONCAKE_TRANS_THREAD
             value: "8"
-          - name: SGL_ENABLE_JIT_DEEPGEMM
+          - name: SGLANG_ENABLE_JIT_DEEPGEMM
             value: "1"
           - name: SGL_CHUNKED_PREFIX_CACHE_THRESHOLD
             value: "0"

docs/references/multi_node_deployment/lws_pd/lws_pd_deploy.md

@@ -98,7 +98,7 @@ spec:
             value: "1"
           - name: SGLANG_SET_CPU_AFFINITY
             value: "true"
-          - name: SGL_ENABLE_JIT_DEEPGEMM
+          - name: SGLANG_ENABLE_JIT_DEEPGEMM
             value: "1"
           - name: NCCL_IB_QPS_PER_CONNECTION
             value: "8"
@@ -257,7 +257,7 @@ spec:
             value: "0"
           - name: SGLANG_MOONCAKE_TRANS_THREAD
             value: "8"
-          - name: SGL_ENABLE_JIT_DEEPGEMM
+          - name: SGLANG_ENABLE_JIT_DEEPGEMM
             value: "1"
           - name: SGL_CHUNKED_PREFIX_CACHE_THRESHOLD
             value: "0"
@@ -421,7 +421,7 @@ spec:
             value: "true"
           - name: SGLANG_MOONCAKE_TRANS_THREAD
             value: "16"
-          - name: SGL_ENABLE_JIT_DEEPGEMM
+          - name: SGLANG_ENABLE_JIT_DEEPGEMM
             value: "1"
           - name: NCCL_IB_HCA
             value: ^=mlx5_0,mlx5_5,mlx5_6
@@ -560,7 +560,7 @@ spec:
             value: "5"
           - name: SGLANG_MOONCAKE_TRANS_THREAD
             value: "16"
-          - name: SGL_ENABLE_JIT_DEEPGEMM
+          - name: SGLANG_ENABLE_JIT_DEEPGEMM
             value: "1"
           - name: NCCL_IB_HCA
             value: ^=mlx5_0,mlx5_5,mlx5_6

python/sglang/compile_deep_gemm.py

@@ -19,6 +19,7 @@ import requests
 
 from sglang.srt.disaggregation.utils import FAKE_BOOTSTRAP_HOST
 from sglang.srt.entrypoints.http_server import launch_server
+from sglang.srt.environ import envs
 from sglang.srt.managers.io_struct import GenerateReqInput
 from sglang.srt.managers.tokenizer_manager import TokenizerManager
 from sglang.srt.server_args import ServerArgs
@@ -28,9 +29,9 @@ from sglang.srt.warmup import warmup
 multiprocessing.set_start_method("spawn", force=True)
 
 # Reduce warning
-os.environ["SGL_IN_DEEPGEMM_PRECOMPILE_STAGE"] = "1"
+envs.SGLANG_IN_DEEPGEMM_PRECOMPILE_STAGE.set(True)
 # Force enable deep gemm
-os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "1"
+envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(True)
 # Force enable mha chunked kv for DeepSeek V3 to avoid missing kv_b_proj DeepGEMM case
 os.environ["SGL_CHUNKED_PREFIX_CACHE_THRESHOLD"] = "0"
 

python/sglang/srt/environ.py

@@ -180,6 +180,7 @@ class Envs:
     SGLANG_EXPERT_LOCATION_UPDATER_CANARY = EnvBool(False)
     SGLANG_EXPERT_LOCATION_UPDATER_LOG_METRICS = EnvBool(False)
     SGLANG_LOG_EXPERT_LOCATION_METADATA = EnvBool(False)
+    SGLANG_EXPERT_DISTRIBUTION_RECORDER_DIR = EnvStr("/tmp")
 
     # TBO
     SGLANG_TBO_DEBUG = EnvBool(False)

python/sglang/srt/eplb/expert_distribution.py

@@ -16,21 +16,20 @@ from __future__ import annotations
 
 import logging
 import math
-import os
 import time
 from abc import ABC
 from collections import deque
 from contextlib import contextmanager
-from pathlib import Path
 from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Tuple, Type
 
 import einops
 import torch
 import torch.distributed
 
+from sglang.srt.environ import envs
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
 from sglang.srt.server_args import ServerArgs
-from sglang.srt.utils import Withable, get_bool_env_var, is_npu
+from sglang.srt.utils import Withable, is_npu
 
 _is_npu = is_npu()
 
@@ -839,7 +838,7 @@ class _StatAccumulator(_UtilizationRateAccumulatorMixin):
 
 
 def _dump_to_file(name, data):
-    save_dir = Path(os.environ.get("SGLANG_EXPERT_DISTRIBUTION_RECORDER_DIR", "/tmp"))
+    save_dir = envs.SGLANG_EXPERT_DISTRIBUTION_RECORDER_DIR.get()
     path_output = save_dir / name
     logger.info(f"Write expert distribution to {path_output}")
     if not save_dir.exists():

python/sglang/srt/layers/quantization/deep_gemm_wrapper/compile_utils.py

@@ -7,11 +7,12 @@ from typing import Dict, List, Tuple
 import torch
 from tqdm import tqdm
 
+from sglang.srt.environ import envs
 from sglang.srt.layers.quantization.deep_gemm_wrapper.configurer import (
     ENABLE_JIT_DEEPGEMM,
 )
 from sglang.srt.server_args import ServerArgs
-from sglang.srt.utils import ceil_div, get_bool_env_var, get_int_env_var
+from sglang.srt.utils import ceil_div, get_bool_env_var
 
 logger = logging.getLogger(__name__)
 
@@ -20,12 +21,9 @@ if ENABLE_JIT_DEEPGEMM:
 
 
 _BUILTIN_M_LIST = list(range(1, 1024 * 16 + 1))
-_ENABLE_JIT_DEEPGEMM_PRECOMPILE = get_bool_env_var(
-    "SGL_JIT_DEEPGEMM_PRECOMPILE", "true"
-)
+_ENABLE_JIT_DEEPGEMM_PRECOMPILE = envs.SGLANG_JIT_DEEPGEMM_PRECOMPILE.get()
 _DO_COMPILE_ALL = True
 _IS_FIRST_RANK_ON_NODE = get_bool_env_var("SGL_IS_FIRST_RANK_ON_NODE", "true")
-_COMPILE_WORKERS = get_int_env_var("SGL_JIT_DEEPGEMM_COMPILE_WORKERS", 4)
 _IN_PRECOMPILE_STAGE = get_bool_env_var("SGL_IN_DEEPGEMM_PRECOMPILE_STAGE", "false")
 
 # Force redirect deep_gemm cache_dir

python/sglang/srt/layers/quantization/deep_gemm_wrapper/configurer.py

 import logging
 
-from sglang.srt.utils import get_bool_env_var, get_device_sm, is_blackwell
+from sglang.srt.environ import envs
+from sglang.srt.utils import get_device_sm, is_blackwell
 
 logger = logging.getLogger(__name__)
 
@@ -15,7 +16,7 @@ def _compute_enable_deep_gemm():
     except ImportError:
         return False
 
-    return get_bool_env_var("SGL_ENABLE_JIT_DEEPGEMM", default="true")
+    return envs.SGLANG_ENABLE_JIT_DEEPGEMM.get()
 
 
 ENABLE_JIT_DEEPGEMM = _compute_enable_deep_gemm()

test/srt/ep/test_eplb.py

@@ -5,6 +5,7 @@ from pathlib import Path
 from types import SimpleNamespace
 
 import sglang as sgl
+from sglang.srt.environ import envs
 from sglang.srt.utils import kill_process_tree
 from sglang.test.run_eval import run_eval
 from sglang.test.test_utils import (
@@ -23,44 +24,43 @@ class _BaseTestDynamicEPLB(CustomTestCase):
     def setUpClass(cls):
         cls.model = DEFAULT_MLA_MODEL_NAME_FOR_TEST
         cls.base_url = DEFAULT_URL_FOR_TEST
-        cls.process = popen_launch_server(
-            cls.model,
-            cls.base_url,
-            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-            other_args=[
-                "--trust-remote-code",
-                "--tp",
-                "2",
-                "--dp",
-                "2",
-                "--enable-dp-attention",
-                "--moe-a2a-backend",
-                "deepep",
-                "--deepep-mode",
-                "normal",
-                "--disable-cuda-graph",
-                "--enable-eplb",
-                "--ep-num-redundant-experts",
-                "4",
-                "--eplb-rebalance-num-iterations",
-                "50",
-                "--expert-distribution-recorder-buffer-size",
-                "50",
-                # TODO pr-chain: enable later
-                # "--enable-expert-distribution-metrics",
-                # TODO auto determine these flags
-                "--expert-distribution-recorder-mode",
-                "stat",
-                "--ep-dispatch-algorithm",
-                "static",
-                *cls.extra_args,
-            ],
-            env={
-                "SGL_ENABLE_JIT_DEEPGEMM": "0",
-                "SGLANG_EXPERT_LOCATION_UPDATER_CANARY": "1",
-                **os.environ,
-            },
-        )
+        with (
+            envs.SGLANG_ENABLE_JIT_DEEPGEMM.override(False),
+            envs.SGLANG_EXPERT_LOCATION_UPDATER_CANARY.override(True),
+        ):
+            cls.process = popen_launch_server(
+                cls.model,
+                cls.base_url,
+                timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+                other_args=[
+                    "--trust-remote-code",
+                    "--tp",
+                    "2",
+                    "--dp",
+                    "2",
+                    "--enable-dp-attention",
+                    "--moe-a2a-backend",
+                    "deepep",
+                    "--deepep-mode",
+                    "normal",
+                    "--disable-cuda-graph",
+                    "--enable-eplb",
+                    "--ep-num-redundant-experts",
+                    "4",
+                    "--eplb-rebalance-num-iterations",
+                    "50",
+                    "--expert-distribution-recorder-buffer-size",
+                    "50",
+                    # TODO pr-chain: enable later
+                    # "--enable-expert-distribution-metrics",
+                    # TODO auto determine these flags
+                    "--expert-distribution-recorder-mode",
+                    "stat",
+                    "--ep-dispatch-algorithm",
+                    "static",
+                    *cls.extra_args,
+                ],
+            )
 
     @classmethod
     def tearDownClass(cls):
@@ -89,7 +89,7 @@ class TestDynamicEPLBMultiChunk(_BaseTestDynamicEPLB):
 
 class TestStaticEPLB(CustomTestCase):
     def test_save_expert_distribution_and_init_expert_location(self):
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "0"
+        envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
 
         with tempfile.TemporaryDirectory() as tmp_dir:
             engine_kwargs = dict(
@@ -108,7 +108,7 @@ class TestStaticEPLB(CustomTestCase):
             )
 
             print(f"Action: start engine")
-            os.environ["SGLANG_EXPERT_DISTRIBUTION_RECORDER_DIR"] = tmp_dir
+            envs.SGLANG_EXPERT_DISTRIBUTION_RECORDER_DIR.set(tmp_dir)
             engine = sgl.Engine(
                 **engine_kwargs,
                 disable_overlap_schedule=True,

test/srt/ep/test_moe_deepep.py

@@ -3,6 +3,7 @@ import os
 import unittest
 from types import SimpleNamespace
 
+from sglang.srt.environ import envs
 from sglang.srt.utils import kill_process_tree
 from sglang.test.run_eval import run_eval
 from sglang.test.test_utils import (
@@ -55,48 +56,45 @@ class TestDPAttn(unittest.TestCase):
     def setUpClass(cls):
         cls.model = DEFAULT_MLA_MODEL_NAME_FOR_TEST
         cls.base_url = DEFAULT_URL_FOR_TEST
-        cls.process = popen_launch_server(
-            cls.model,
-            cls.base_url,
-            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-            other_args=[
-                "--trust-remote-code",
-                "--tp",
-                "2",
-                "--dp",
-                "2",
-                "--enable-dp-attention",
-                "--moe-a2a-backend",
-                "deepep",
-                "--deepep-mode",
-                "normal",
-                "--disable-cuda-graph",
-                # Test custom config
-                "--deepep-config",
-                json.dumps(
-                    {
-                        "normal_dispatch": {
-                            "num_sms": 20,
-                            "num_max_nvl_chunked_send_tokens": 16,
-                            "num_max_nvl_chunked_recv_tokens": 256,
-                            "num_max_rdma_chunked_send_tokens": 6,
-                            "num_max_rdma_chunked_recv_tokens": 128,
-                        },
-                        "normal_combine": {
-                            "num_sms": 20,
-                            "num_max_nvl_chunked_send_tokens": 6,
-                            "num_max_nvl_chunked_recv_tokens": 256,
-                            "num_max_rdma_chunked_send_tokens": 6,
-                            "num_max_rdma_chunked_recv_tokens": 128,
-                        },
-                    }
-                ),
-            ],
-            env={
-                "SGL_ENABLE_JIT_DEEPGEMM": "0",
-                **os.environ,
-            },
-        )
+        with envs.SGLANG_ENABLE_JIT_DEEPGEMM.override(False):
+            cls.process = popen_launch_server(
+                cls.model,
+                cls.base_url,
+                timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+                other_args=[
+                    "--trust-remote-code",
+                    "--tp",
+                    "2",
+                    "--dp",
+                    "2",
+                    "--enable-dp-attention",
+                    "--moe-a2a-backend",
+                    "deepep",
+                    "--deepep-mode",
+                    "normal",
+                    "--disable-cuda-graph",
+                    # Test custom config
+                    "--deepep-config",
+                    json.dumps(
+                        {
+                            "normal_dispatch": {
+                                "num_sms": 20,
+                                "num_max_nvl_chunked_send_tokens": 16,
+                                "num_max_nvl_chunked_recv_tokens": 256,
+                                "num_max_rdma_chunked_send_tokens": 6,
+                                "num_max_rdma_chunked_recv_tokens": 128,
+                            },
+                            "normal_combine": {
+                                "num_sms": 20,
+                                "num_max_nvl_chunked_send_tokens": 6,
+                                "num_max_nvl_chunked_recv_tokens": 256,
+                                "num_max_rdma_chunked_send_tokens": 6,
+                                "num_max_rdma_chunked_recv_tokens": 128,
+                            },
+                        }
+                    ),
+                ],
+            )
 
     @classmethod
     def tearDownClass(cls):

test/srt/test_disaggregation_different_tp.py

-import os
-import time
 import unittest
 from types import SimpleNamespace
 
+from sglang.srt.environ import envs
 from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
 from sglang.test.test_disaggregation_utils import TestDisaggregationBase
 from sglang.test.test_utils import (
@@ -18,8 +17,7 @@ class TestDisaggregationMooncakePrefillLargerTP(TestDisaggregationBase):
     def setUpClass(cls):
         super().setUpClass()
         # Temporarily disable JIT DeepGEMM
-        cls.original_jit_deepgemm = os.environ.get("SGL_ENABLE_JIT_DEEPGEMM")
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "false"
+        envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
 
         cls.model = DEFAULT_MODEL_NAME_FOR_TEST_MLA
 
@@ -90,8 +88,7 @@ class TestDisaggregationMooncakeDecodeLargerTP(TestDisaggregationBase):
     def setUpClass(cls):
         super().setUpClass()
         # Temporarily disable JIT DeepGEMM
-        cls.original_jit_deepgemm = os.environ.get("SGL_ENABLE_JIT_DEEPGEMM")
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "false"
+        envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
 
         cls.model = DEFAULT_MODEL_NAME_FOR_TEST_MLA
 
@@ -162,8 +159,7 @@ class TestDisaggregationMooncakeMHAPrefillLargerTP(TestDisaggregationBase):
     def setUpClass(cls):
         super().setUpClass()
         # Temporarily disable JIT DeepGEMM
-        cls.original_jit_deepgemm = os.environ.get("SGL_ENABLE_JIT_DEEPGEMM")
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "false"
+        envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
 
         cls.model = DEFAULT_MODEL_NAME_FOR_TEST
 
@@ -234,8 +230,7 @@ class TestDisaggregationMooncakeMHADecodeLargerTP(TestDisaggregationBase):
     def setUpClass(cls):
         super().setUpClass()
         # Temporarily disable JIT DeepGEMM
-        cls.original_jit_deepgemm = os.environ.get("SGL_ENABLE_JIT_DEEPGEMM")
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "false"
+        envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
 
         cls.model = DEFAULT_MODEL_NAME_FOR_TEST
 

test/srt/test_disaggregation_dp_attention.py

@@ -2,6 +2,7 @@ import os
 import unittest
 from types import SimpleNamespace
 
+from sglang.srt.environ import envs
 from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
 from sglang.test.test_disaggregation_utils import TestDisaggregationBase
 from sglang.test.test_utils import (
@@ -16,8 +17,7 @@ class TestDisaggregationDPAttention(TestDisaggregationBase):
     def setUpClass(cls):
         super().setUpClass()
         # Temporarily disable JIT DeepGEMM
-        cls.original_jit_deepgemm = os.environ.get("SGL_ENABLE_JIT_DEEPGEMM")
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "false"
+        envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
 
         cls.model = DEFAULT_MODEL_NAME_FOR_TEST_MLA
 

test/srt/test_expert_distribution.py

@@ -6,9 +6,9 @@ from pathlib import Path
 import requests
 import torch
 
+from sglang.srt.environ import envs
 from sglang.srt.utils import kill_process_tree
 from sglang.test.test_utils import (
-    DEFAULT_SMALL_MOE_MODEL_NAME_FOR_TEST_BASE,
     DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
     DEFAULT_URL_FOR_TEST,
     CustomTestCase,
@@ -32,7 +32,7 @@ class TestExpertDistribution(CustomTestCase):
     def _execute_core(self, model_path: str, mode: str = "stat", tp_size: int = 1):
         """Test expert distribution record endpoints"""
         with tempfile.TemporaryDirectory() as tmp_dir:
-            os.environ["SGLANG_EXPERT_DISTRIBUTION_RECORDER_DIR"] = tmp_dir
+            envs.SGLANG_EXPERT_DISTRIBUTION_RECORDER_DIR.set(tmp_dir)
 
             process = popen_launch_server(
                 model_path,

test/srt/test_fa3.py

-import os
 import unittest
 from types import SimpleNamespace
 
 import requests
 
+from sglang.srt.environ import envs
 from sglang.srt.utils import get_device_sm, kill_process_tree
 from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
 from sglang.test.test_utils import (
@@ -77,14 +77,16 @@ class BaseFlashAttentionTest(CustomTestCase):
     def setUpClass(cls):
         # disable deep gemm precompile to make launch server faster
         # please don't do this if you want to make your inference workload faster
-        os.environ["SGL_JIT_DEEPGEMM_PRECOMPILE"] = "false"
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "false"
-        cls.process = popen_launch_server(
-            cls.model,
-            cls.base_url,
-            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-            other_args=cls.get_server_args(),
-        )
+        with (
+            envs.SGLANG_JIT_DEEPGEMM_PRECOMPILE.override(False),
+            envs.SGLANG_ENABLE_JIT_DEEPGEMM.override(False),
+        ):
+            cls.process = popen_launch_server(
+                cls.model,
+                cls.base_url,
+                timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+                other_args=cls.get_server_args(),
+            )
 
     @classmethod
     def tearDownClass(cls):

test/srt/test_hybrid_attn_backend.py

@@ -4,6 +4,7 @@ from types import SimpleNamespace
 
 import requests
 
+from sglang.srt.environ import envs
 from sglang.srt.utils import get_device_sm, kill_process_tree
 from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
 from sglang.test.test_utils import (
@@ -49,18 +50,20 @@ class TestHybridAttnBackendBase(CustomTestCase):
     def setUpClass(cls):
         # disable deep gemm precompile to make launch server faster
         # please don't do this if you want to make your inference workload faster
-        os.environ["SGL_JIT_DEEPGEMM_PRECOMPILE"] = "false"
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "false"
-        if cls.speculative_decode:
-            model = DEFAULT_EAGLE_TARGET_MODEL_FOR_TEST
-        else:
-            model = cls.model
-        cls.process = popen_launch_server(
-            model,
-            cls.base_url,
-            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-            other_args=cls.get_server_args(),
-        )
+        with (
+            envs.SGLANG_JIT_DEEPGEMM_PRECOMPILE.override(False),
+            envs.SGLANG_ENABLE_JIT_DEEPGEMM.override(False),
+        ):
+            if cls.speculative_decode:
+                model = DEFAULT_EAGLE_TARGET_MODEL_FOR_TEST
+            else:
+                model = cls.model
+            cls.process = popen_launch_server(
+                model,
+                cls.base_url,
+                timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+                other_args=cls.get_server_args(),
+            )
 
     @classmethod
     def tearDownClass(cls):

test/srt/test_ngram_speculative_decoding.py

-import os
 import unittest
 from types import SimpleNamespace
 
 import requests
 
+from sglang.srt.environ import envs
 from sglang.srt.utils import kill_process_tree
 from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
 from sglang.test.test_utils import (
@@ -47,8 +47,8 @@ class TestNgramSpeculativeDecodingBase(CustomTestCase):
     def setUpClass(cls):
         # disable deep gemm precompile to make launch server faster
         # please don't do this if you want to make your inference workload faster
-        os.environ["SGL_JIT_DEEPGEMM_PRECOMPILE"] = "false"
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "false"
+        envs.SGLANG_JIT_DEEPGEMM_PRECOMPILE.set(False)
+        envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
         model = cls.model
         cls.process = popen_launch_server(
             model,

test/srt/test_standalone_speculative_decoding.py

-import os
 import unittest
 from types import SimpleNamespace
 
 import requests
 
+from sglang.srt.environ import envs
 from sglang.srt.utils import kill_process_tree
 from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
 from sglang.test.test_utils import (
@@ -55,8 +55,8 @@ class TestStandaloneSpeculativeDecodingBase(CustomTestCase):
     def setUpClass(cls):
         # disable deep gemm precompile to make launch server faster
         # please don't do this if you want to make your inference workload faster
-        os.environ["SGL_JIT_DEEPGEMM_PRECOMPILE"] = "false"
-        os.environ["SGL_ENABLE_JIT_DEEPGEMM"] = "false"
+        envs.SGLANG_JIT_DEEPGEMM_PRECOMPILE.set(False)
+        envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
         model = cls.model
         cls.process = popen_launch_server(
             model,

test/srt/test_two_batch_overlap.py

-import os
 import unittest
 from types import SimpleNamespace
 
 import requests
 
+from sglang.srt.environ import envs
 from sglang.srt.model_executor.forward_batch_info import ForwardMode
 from sglang.srt.two_batch_overlap import (
     compute_split_seq_index,
@@ -25,26 +25,26 @@ class TestTwoBatchOverlap(unittest.TestCase):
     def setUpClass(cls):
         cls.model = DEFAULT_MLA_MODEL_NAME_FOR_TEST
         cls.base_url = DEFAULT_URL_FOR_TEST
-        cls.process = popen_launch_server(
-            cls.model,
-            cls.base_url,
-            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-            other_args=[
-                "--trust-remote-code",
-                "--tp",
-                "2",
-                "--dp",
-                "2",
-                "--enable-dp-attention",
-                "--moe-a2a-backend",
-                "deepep",
-                "--deepep-mode",
-                "normal",
-                "--disable-cuda-graph",  # DeepEP normal does not support CUDA Graph
-                "--enable-two-batch-overlap",
-            ],
-            env={"SGL_ENABLE_JIT_DEEPGEMM": "0", **os.environ},
-        )
+        with envs.SGLANG_ENABLE_JIT_DEEPGEMM.override(False):
+            cls.process = popen_launch_server(
+                cls.model,
+                cls.base_url,
+                timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+                other_args=[
+                    "--trust-remote-code",
+                    "--tp",
+                    "2",
+                    "--dp",
+                    "2",
+                    "--enable-dp-attention",
+                    "--moe-a2a-backend",
+                    "deepep",
+                    "--deepep-mode",
+                    "normal",
+                    "--disable-cuda-graph",  # DeepEP normal does not support CUDA Graph
+                    "--enable-two-batch-overlap",
+                ],
+            )
 
     @classmethod
     def tearDownClass(cls):
@@ -126,26 +126,26 @@ class TestQwen3TwoBatchOverlap(TestTwoBatchOverlap):
         cls.model = DEFAULT_ENABLE_THINKING_MODEL_NAME_FOR_TEST
         cls.base_url = DEFAULT_URL_FOR_TEST
         cls.api_key = "sk-1234"
-        cls.process = popen_launch_server(
-            cls.model,
-            cls.base_url,
-            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-            other_args=[
-                "--trust-remote-code",
-                "--tp",
-                "2",
-                "--dp",
-                "2",
-                "--enable-dp-attention",
-                "--moe-a2a-backend",
-                "deepep",
-                "--deepep-mode",
-                "normal",
-                "--disable-cuda-graph",  # DeepEP normal does not support CUDA Graph
-                "--enable-two-batch-overlap",
-            ],
-            env={"SGL_ENABLE_JIT_DEEPGEMM": "0", **os.environ},
-        )
+        with envs.SGLANG_ENABLE_JIT_DEEPGEMM.override(False):
+            cls.process = popen_launch_server(
+                cls.model,
+                cls.base_url,
+                timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+                other_args=[
+                    "--trust-remote-code",
+                    "--tp",
+                    "2",
+                    "--dp",
+                    "2",
+                    "--enable-dp-attention",
+                    "--moe-a2a-backend",
+                    "deepep",
+                    "--deepep-mode",
+                    "normal",
+                    "--disable-cuda-graph",  # DeepEP normal does not support CUDA Graph
+                    "--enable-two-batch-overlap",
+                ],
+            )
 
 
 if __name__ == "__main__":