docker: set CUDA_HOME for pip-installed vllm in Cookbook (#228)

When Cookbook installs vllm via `pip install --user vllm`, pip pulls in
nvidia-cuda-* wheels under /app/.local but doesn't set CUDA_HOME or
create /usr/local/cuda. vllm 0.22+ then crashes during engine init:

  RuntimeError: Could not find nvcc and default cuda_home='/usr/local/cuda' doesn't exist

After that, the mixed cuda-nvcc 13.3 / cuda-runtime 13.0 wheel combo
fails FlashInfer's JIT sampler with:

  error: "CUDA compiler and CUDA toolkit headers are incompatible"

Detect the pip-installed nvcc on startup, point CUDA_HOME at it, and
default VLLM_USE_FLASHINFER_SAMPLER=0 (sampler only, no attention
impact) so the engine boots. No-op when vllm isn't installed.

Fixes #214.

Co-authored-by: sirs <sirs@local>

docker/entrypoint.sh

@@ -46,6 +46,24 @@ for dir in /app /app/data /app/logs; do
     fi
 done
 
+# Cookbook installs vllm/etc. via `pip install --user`, which pulls
+# nvidia-cuda-* wheels into /app/.local but does not set CUDA_HOME or
+# symlink /usr/local/cuda. vllm 0.22+ then crashes during engine init
+# when FlashInfer tries to JIT a sampler kernel ("Could not find nvcc",
+# then "CUDA compiler and toolkit headers are incompatible" on the
+# mixed cuda-nvcc 13.3 / cuda-runtime 13.0 wheel combo).
+#
+# Auto-set CUDA_HOME if a pip-installed nvcc is present, and disable the
+# FlashInfer JIT sampler — sampler only, no impact on attention path.
+# No-op when vllm isn't installed.
+for cu in /app/.local/lib/python*/site-packages/nvidia/cu13; do
+    if [ -x "$cu/bin/nvcc" ]; then
+        export CUDA_HOME="$cu"
+        export VLLM_USE_FLASHINFER_SAMPLER="${VLLM_USE_FLASHINFER_SAMPLER:-0}"
+        break
+    fi
+done
+
 # Drop root and run the actual app. `gosu` is preferred over `su` /
 # `sudo` because it cleans up the process tree (no extra shell layer)
 # so signals (SIGTERM from `docker stop`) reach uvicorn directly.