fix nightly docker build (#13386)

docker/Dockerfile

@@ -19,11 +19,13 @@ ARG PIP_DEFAULT_INDEX
 ARG UBUNTU_MIRROR
 ARG GITHUB_ARTIFACTORY=github.com
 ARG INSTALL_FLASHINFER_JIT_CACHE=0
+ARG FLASHINFER_VERSION=0.5.2
 
 ENV DEBIAN_FRONTEND=noninteractive \
     CUDA_HOME=/usr/local/cuda \
     GDRCOPY_HOME=/usr/src/gdrdrv-${GDRCOPY_VERSION}/ \
-    NVSHMEM_DIR=/sgl-workspace/nvshmem/install
+    NVSHMEM_DIR=/sgl-workspace/nvshmem/install \
+    FLASHINFER_VERSION=${FLASHINFER_VERSION}
 # Add GKE default lib and bin locations.
 ENV PATH="${PATH}:/usr/local/nvidia/bin" \
     LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/nvidia/lib:/usr/local/nvidia/lib64"
@@ -130,8 +132,8 @@ RUN --mount=type=cache,target=/root/.cache/pip  python3 -m pip install --upgrade
    fi \
  && python3 -m pip install -e "python[${BUILD_TYPE}]" --extra-index-url https://download.pytorch.org/whl/cu${CUINDEX} \
  && if [ "$INSTALL_FLASHINFER_JIT_CACHE" = "1" ]; then \
-      python3 -m pip install flashinfer-jit-cache==0.5.0 --index-url https://flashinfer.ai/whl/cu${CUINDEX} ; \
+      python3 -m pip install flashinfer-jit-cache==${FLASHINFER_VERSION} --index-url https://flashinfer.ai/whl/cu${CUINDEX} ; \
-    fi \
+   fi \
  && if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
       python3 -m pip install nvidia-nccl-cu12==2.28.3 --force-reinstall --no-deps ; \
     elif [ "${CUDA_VERSION%%.*}" = "13" ]; then \

python/pyproject.toml

@@ -26,7 +26,7 @@ dependencies = [
   "datasets",
   "einops",
   "fastapi",
-  "flashinfer_python==0.5.2",
+  "flashinfer_python==0.5.2", # keep it aligned with jit-cache version in Dockerfile
   "flashinfer_cubin==0.5.2",
   "gguf",
   "hf_transfer",