chore: vLLM, kernels, and flashinfer upgrades

pyproject.toml

@@ -113,10 +113,10 @@ engine = [
 cpu = [
   "accelerate>=1.1.0",
   "bitsandbytes>=0.46.1",
-  "flashinfer-python==0.6.8.post1; sys_platform=='linux'",
-  "flashinfer-cubin==0.6.8.post1; sys_platform=='linux'",
+  "flashinfer-python==0.6.13; sys_platform=='linux'",
+  "flashinfer-cubin==0.6.13; sys_platform=='linux'",
   "gliner",
-  "kernels>=0.12.1,<0.15",
+  "kernels>=0.12.1,<0.17",
   "peft>=0.18.0",
   "opacus",
   "sentence-transformers",
@@ -130,18 +130,18 @@ cpu = [
   "transformers>=5.6,<6",
   "triton>=2.0.0; sys_platform=='linux'",
   "trl>=0.23.0",
-  "vllm==0.20.0; sys_platform=='linux'",
+  "vllm==0.24.0; sys_platform=='linux'",
   "xgrammar>=0.2.0; sys_platform=='linux'",
 ]
 
 cu129 = [
   "accelerate>=1.1.0",
   "bitsandbytes>=0.46.1",
-  "flashinfer-python==0.6.8.post1; sys_platform == 'linux'",
-  "flashinfer-cubin==0.6.8.post1; sys_platform == 'linux'",
-  "flashinfer-jit-cache==0.6.8.post1+cu129; sys_platform == 'linux'",
+  "flashinfer-python==0.6.13; sys_platform == 'linux'",
+  "flashinfer-cubin==0.6.13; sys_platform == 'linux'",
+  "flashinfer-jit-cache==0.6.13+cu129; sys_platform == 'linux'",
   "gliner",
-  "kernels>=0.12.1,<0.15",
+  "kernels>=0.12.1,<0.17",
   "nvidia-cublas-cu12; sys_platform == 'linux'",
   "nvidia-ml-py; sys_platform == 'linux'",
   "opacus",
@@ -155,7 +155,7 @@ cu129 = [
   "transformers>=5.6,<6",
   "triton>=2.0.0; sys_platform == 'linux'",
   "trl>=0.23.0",
-  "vllm==0.20.0+cu129; sys_platform == 'linux'",
+  "vllm==0.24.0; sys_platform == 'linux'",
   "xgrammar>=0.2.0; sys_platform == 'linux'",
 ]
 
@@ -180,8 +180,8 @@ conflicts = [
 
 
 override-dependencies = [
-    "flashinfer-python==0.6.8.post1; sys_platform != 'darwin'",
-    "flashinfer-cubin==0.6.8.post1; sys_platform != 'darwin'",
+    "flashinfer-python==0.6.13; sys_platform != 'darwin'",
+    "flashinfer-cubin==0.6.13; sys_platform != 'darwin'",
 ]
 
 environments = [
@@ -225,7 +225,7 @@ constraint-dependencies = [
   # here we specifiy the dep's source from which UV should attempt to resolve
   triton = { index = "pytorch-cu129", extra = "cu129" }
   vllm = [
-    { index = "vllm-v0-20-0-cu129", marker = "sys_platform == 'linux'", extra = "cu129" },
+    { index = "vllm-v0-24-0-cu129", marker = "sys_platform == 'linux'", extra = "cu129" },
   ]
 # for torch - we have a "cpu" dep set and "cu129" dep set, specified in the optional dependencies above
   torch = [
@@ -319,8 +319,8 @@ url = "https://flashinfer.ai/whl/cu129"
 explicit = true
 
 [[tool.uv.index]]
-name = "vllm-v0-20-0-cu129"
-url = "https://wheels.vllm.ai/88d34c6409e9fb3c7b8ca0c04756f061d2099eb1/cu129"
+name = "vllm-v0-24-0-cu129"
+url = "https://wheels.vllm.ai/ee0da84ab9e04ac7610e28580af62c365e898389/cu129"
 explicit = true
 
 [[tool.uv.index]]

src/nemo_safe_synthesizer/generation/vllm_backend.py

@@ -298,6 +298,7 @@ def initialize(self, **kwargs) -> None:
             self.llm = vLLM(
                 model=model_ref.target(),
                 gpu_memory_utilization=max_vram,
+                max_model_len=self.model_metadata.max_seq_length,
                 enable_lora=True,
                 max_lora_rank=self.config.training.lora_r,
                 structured_outputs_config=structured_outputs_config,

tests/generation/test_vllm_backend.py

@@ -393,6 +393,7 @@ def test_initialize_passes_cached_snapshot_target_and_trust_to_vllm(
 
         assert backend.llm is mock_llm
         assert mock_vllm.call_args.kwargs["model"] == str(snapshot)
+        assert mock_vllm.call_args.kwargs["max_model_len"] == mock_model_metadata.max_seq_length
         assert mock_vllm.call_args.kwargs["trust_remote_code"] is True
 
     def test_initialize_caches_engine_runtime_config(