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What driver is “missing”?

  • You need the NVIDIA proprietary GPU driver on the host with CUDA 12.x support, plus the NVIDIA Container Toolkit.
  • Recommended driver branch: R550+ (or at least R535+) so it’s compatible with CUDA 12.x images used by Milvus GPU and NIM.
  • Also required: nvidia-container-toolkit configured with Docker so the nvidia runtime is available.
    If you’re on WSL2/Windows: install the Windows NVIDIA driver with WSL2 GPU support and enable GPU for Docker Desktop/WSL. The error “WSL environment detected but no adapters were found” means no GPU is exposed to WSL/Docker.

Summary

  • The failure is due to a GPU-required service (Milvus GPU) with no GPU available to Docker.
  • Required driver: NVIDIA Linux driver R550+/R535+ and NVIDIA Container Toolkit (or the Windows WSL2 NVIDIA driver if on WSL).
  • You can run CPU-only by switching to pgvector or Milvus CPU image and relying on NVIDIA AI Endpoints for models via NVIDIA_API_KEY.

… command : docker compose up -d --build NVIDIA#329

Added detailed information at GenerativeAIExamples/RAG/examples/basic_rag/langchain/README.md

Summary
- The failure is due to a GPU-required service (Milvus GPU) with no GPU available to Docker.
- Required driver: NVIDIA Linux driver R550+/R535+ and NVIDIA Container Toolkit (or the Windows WSL2 NVIDIA driver if on WSL).
- You can run CPU-only by switching to pgvector or Milvus CPU image and relying on NVIDIA AI Endpoints for models via NVIDIA_API_KEY.
Reformatted the requirements section for clarity and added numbering for better readability.
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