# Dependencies for the LLM response grader.
# torch is pinned so the cu126 preinstall in InstallLLMGraderRequirementsTask
# resolves to a fixed wheel; bump both together.
torch==2.10.0
transformers>=5.2
accelerate
# Prebuilt CUDA wheels (cu12 / torch 2.10 / cxx11abi, x86_64), so the pod does not need nvcc.
# One line per supported Python; bump together with the torch pin.
causal-conv1d @ https://github.com/Dao-AILab/causal-conv1d/releases/download/v1.7.0/causal_conv1d-1.7.0+cu12torch2.10cxx11abiTRUE-cp310-cp310-linux_x86_64.whl ; python_version == "3.10" and platform_machine == "x86_64"
causal-conv1d @ https://github.com/Dao-AILab/causal-conv1d/releases/download/v1.7.0/causal_conv1d-1.7.0+cu12torch2.10cxx11abiTRUE-cp311-cp311-linux_x86_64.whl ; python_version == "3.11" and platform_machine == "x86_64"
causal-conv1d @ https://github.com/Dao-AILab/causal-conv1d/releases/download/v1.7.0/causal_conv1d-1.7.0+cu12torch2.10cxx11abiTRUE-cp312-cp312-linux_x86_64.whl ; python_version == "3.12" and platform_machine == "x86_64"
causal-conv1d @ https://github.com/Dao-AILab/causal-conv1d/releases/download/v1.7.0/causal_conv1d-1.7.0+cu12torch2.10cxx11abiTRUE-cp313-cp313-linux_x86_64.whl ; python_version == "3.13" and platform_machine == "x86_64"
flash-linear-attention
packaging
requests
qai_hub
numpy
pydantic
typing-extensions
