[[V0 deprecation]]Remove VLLM_USE_V1 env

.buildkite/scripts/hardware_ci/run-cpu-test.sh

@@ -76,7 +76,7 @@ function cpu_tests() {
   # Run AWQ test
   # docker exec cpu-test-"$NUMA_NODE" bash -c "
   #   set -e
-  #   VLLM_USE_V1=0 pytest -x -s -v \
+  #   pytest -x -s -v \
   #   tests/quantization/test_ipex_quant.py"
 
   # Run multi-lora tests

examples/offline_inference/mlpspeculator.py

@@ -4,8 +4,7 @@
 This file demonstrates the usage of text generation with an LLM model,
 comparing the performance with and without speculative decoding.
 
-Note that still not support `v1`:
-VLLM_USE_V1=0 python examples/offline_inference/mlpspeculator.py
+Note that this example is out of date and not supported in vLLM v1.
 """
 
 import gc

examples/offline_inference/qwen2_5_omni/README.md

@@ -11,12 +11,10 @@ python examples/offline_inference/qwen2_5_omni/only_thinker.py \
 
 # Read vision and audio inputs from a single video file
 # NOTE: V1 engine does not support interleaved modalities yet.
-VLLM_USE_V1=0 \
 python examples/offline_inference/qwen2_5_omni/only_thinker.py \
     -q use_audio_in_video
 
 # Multiple audios
-VLLM_USE_V1=0 \
 python examples/offline_inference/qwen2_5_omni/only_thinker.py \
     -q multi_audios
 ```

examples/offline_inference/qwen2_5_omni/only_thinker.py

@@ -7,7 +7,6 @@
 
 from typing import NamedTuple
 
-import vllm.envs as envs
 from vllm import LLM, SamplingParams
 from vllm.assets.audio import AudioAsset
 from vllm.assets.image import ImageAsset
@@ -72,11 +71,7 @@ def get_use_audio_in_video_query() -> QueryResult:
     )
     asset = VideoAsset(name="baby_reading", num_frames=16)
     audio = asset.get_audio(sampling_rate=16000)
-    assert not envs.VLLM_USE_V1, (
-        "V1 does not support use_audio_in_video. "
-        "Please launch this example with "
-        "`VLLM_USE_V1=0`."
-    )
+
     return QueryResult(
         inputs={
             "prompt": prompt,

examples/others/lmcache/cpu_offload_lmcache.py

@@ -37,7 +37,7 @@
 from vllm.engine.arg_utils import EngineArgs
 
 
-def setup_environment_variables(vllm_version: str):
+def setup_environment_variables():
     # LMCache-related environment variables
     # Use experimental features in LMCache
     os.environ["LMCACHE_USE_EXPERIMENTAL"] = "True"
@@ -47,34 +47,23 @@ def setup_environment_variables(vllm_version: str):
     os.environ["LMCACHE_LOCAL_CPU"] = "True"
     # Set local CPU memory limit to 5.0 GB
     os.environ["LMCACHE_MAX_LOCAL_CPU_SIZE"] = "5.0"
-    if vllm_version == "v0":
-        os.environ["VLLM_USE_V1"] = "0"
 
 
 @contextlib.contextmanager
-def build_llm_with_lmcache(lmcache_connector: str, model: str, vllm_version: str):
+def build_llm_with_lmcache(lmcache_connector: str, model: str):
     ktc = KVTransferConfig(
         kv_connector=lmcache_connector,
         kv_role="kv_both",
     )
     # Set GPU memory utilization to 0.8 for an A40 GPU with 40GB
     # memory. Reduce the value if your GPU has less memory.
     # Note: LMCache supports chunked prefill (see vLLM#14505, LMCache#392).
-    if vllm_version == "v0":
-        llm_args = EngineArgs(
-            model=model,
-            kv_transfer_config=ktc,
-            max_model_len=8000,
-            gpu_memory_utilization=0.8,
-            enable_chunked_prefill=True,  # Only in v0
-        )
-    else:
-        llm_args = EngineArgs(
-            model=model,
-            kv_transfer_config=ktc,
-            max_model_len=8000,
-            gpu_memory_utilization=0.8,
-        )
+    llm_args = EngineArgs(
+        model=model,
+        kv_transfer_config=ktc,
+        max_model_len=8000,
+        gpu_memory_utilization=0.8,
+    )
 
     llm = LLM(**asdict(llm_args))
     try:
@@ -116,18 +105,10 @@ def parse_args():
 
 
 def main():
-    args = parse_args()
-
-    if args.version == "v0":
-        lmcache_connector = "LMCacheConnector"
-        model = "mistralai/Mistral-7B-Instruct-v0.2"
-    else:
-        lmcache_connector = "LMCacheConnectorV1"
-        model = "meta-llama/Meta-Llama-3.1-8B-Instruct"
-
-    setup_environment_variables(args.version)
-
-    with build_llm_with_lmcache(lmcache_connector, model, args.version) as llm:
+    lmcache_connector = "LMCacheConnectorV1"
+    model = "meta-llama/Meta-Llama-3.1-8B-Instruct"
+    setup_environment_variables()
+    with build_llm_with_lmcache(lmcache_connector, model) as llm:
         # This example script runs two requests with a shared prefix.
         # Define the shared prompt and specific prompts
         shared_prompt = "Hello, how are you?" * 1000

tests/entrypoints/openai/test_orca_metrics.py

@@ -22,9 +22,6 @@ def monkeypatch_module():
 
 @pytest.fixture(scope="module", params=[True])
 def server(request, monkeypatch_module):
-    use_v1 = request.param
-    monkeypatch_module.setenv("VLLM_USE_V1", "1" if use_v1 else "0")
-
     args = [
         "--dtype",
         "bfloat16",

vllm/envs.py

@@ -99,7 +99,6 @@
     VLLM_SKIP_P2P_CHECK: bool = False
     VLLM_DISABLED_KERNELS: list[str] = []
     VLLM_DISABLE_PYNCCL: bool = False
-    VLLM_USE_V1: bool = True
     VLLM_ROCM_USE_AITER: bool = False
     VLLM_ROCM_USE_AITER_PAGED_ATTN: bool = False
     VLLM_ROCM_USE_AITER_LINEAR: bool = True
@@ -874,8 +873,6 @@ def get_vllm_port() -> int | None:
     "VLLM_DISABLE_PYNCCL": lambda: (
         os.getenv("VLLM_DISABLE_PYNCCL", "False").lower() in ("true", "1")
     ),
-    # If set, use the V1 code path.
-    "VLLM_USE_V1": lambda: bool(int(os.getenv("VLLM_USE_V1", "1"))),
     # Disable aiter ops unless specifically enabled.
     # Acts as a parent switch to enable the rest of the other operations.
     "VLLM_ROCM_USE_AITER": lambda: (
@@ -1510,16 +1507,6 @@ def is_set(name: str):
     raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
 
 
-def set_vllm_use_v1(use_v1: bool):
-    if is_set("VLLM_USE_V1"):
-        raise ValueError(
-            "Should not call set_vllm_use_v1() if VLLM_USE_V1 is set "
-            "explicitly by the user. Please raise this as a Github "
-            "Issue and explicitly set VLLM_USE_V1=0 or 1."
-        )
-    os.environ["VLLM_USE_V1"] = "1" if use_v1 else "0"
-
-
 def compute_hash() -> str:
     """
     WARNING: Whenever a new key is added to this environment

vllm/usage/usage_lib.py

@@ -42,7 +42,6 @@
     "VLLM_USE_FLASHINFER_SAMPLER",
     "VLLM_PP_LAYER_PARTITION",
     "VLLM_USE_TRITON_AWQ",
-    "VLLM_USE_V1",
     "VLLM_ENABLE_V1_MULTIPROCESSING",
 ]