requirements.txt

# This file was autogenerated by uv via the following command:
#    uv pip compile pyproject.toml -o requirements.txt
aiofiles==23.2.1
    # via gradio
aiohappyeyeballs==2.4.3
    # via aiohttp
aiohttp==3.10.10
    # via
    #   datasets
    #   fsspec
aiosignal==1.3.1
    # via aiohttp
annotated-types==0.7.0
    # via pydantic
anyio==4.6.0
    # via
    #   gradio
    #   httpx
    #   starlette
apscheduler==3.10.4
    # via open-japanese-llm-leaderboard (pyproject.toml)
async-timeout==4.0.3
    # via aiohttp
attrs==24.2.0
    # via aiohttp
certifi==2024.8.30
    # via
    #   httpcore
    #   httpx
    #   requests
charset-normalizer==3.4.0
    # via requests
click==8.1.7
    # via
    #   typer
    #   uvicorn
datasets==3.1.0
    # via open-japanese-llm-leaderboard (pyproject.toml)
dill==0.3.8
    # via
    #   datasets
    #   multiprocess
exceptiongroup==1.2.2
    # via anyio
fastapi==0.115.2
    # via gradio
ffmpy==0.4.0
    # via gradio
filelock==3.16.1
    # via
    #   datasets
    #   huggingface-hub
    #   torch
    #   transformers
    #   triton
frozenlist==1.4.1
    # via
    #   aiohttp
    #   aiosignal
fsspec==2024.6.1
    # via
    #   datasets
    #   gradio-client
    #   huggingface-hub
    #   torch
gradio==5.6.0
    # via open-japanese-llm-leaderboard (pyproject.toml)
gradio-client==1.4.3
    # via gradio
h11==0.14.0
    # via
    #   httpcore
    #   uvicorn
hf-transfer==0.1.8
    # via open-japanese-llm-leaderboard (pyproject.toml)
httpcore==1.0.6
    # via httpx
httpx==0.27.2
    # via
    #   gradio
    #   gradio-client
    #   safehttpx
huggingface-hub==0.25.2
    # via
    #   datasets
    #   gradio
    #   gradio-client
    #   tokenizers
    #   transformers
idna==3.10
    # via
    #   anyio
    #   httpx
    #   requests
    #   yarl
jinja2==3.1.4
    # via
    #   gradio
    #   torch
markdown-it-py==3.0.0
    # via rich
markupsafe==2.1.5
    # via
    #   gradio
    #   jinja2
mdurl==0.1.2
    # via markdown-it-py
mpmath==1.3.0
    # via sympy
multidict==6.1.0
    # via
    #   aiohttp
    #   yarl
multiprocess==0.70.16
    # via datasets
networkx==3.4.2
    # via torch
numpy==2.1.2
    # via
    #   datasets
    #   gradio
    #   pandas
    #   pyarrow
    #   transformers
nvidia-cublas-cu12==12.4.5.8
    # via
    #   nvidia-cudnn-cu12
    #   nvidia-cusolver-cu12
    #   torch
nvidia-cuda-cupti-cu12==12.4.127
    # via torch
nvidia-cuda-nvrtc-cu12==12.4.127
    # via torch
nvidia-cuda-runtime-cu12==12.4.127
    # via torch
nvidia-cudnn-cu12==9.1.0.70
    # via torch
nvidia-cufft-cu12==11.2.1.3
    # via torch
nvidia-curand-cu12==10.3.5.147
    # via torch
nvidia-cusolver-cu12==11.6.1.9
    # via torch
nvidia-cusparse-cu12==12.3.1.170
    # via
    #   nvidia-cusolver-cu12
    #   torch
nvidia-nccl-cu12==2.21.5
    # via torch
nvidia-nvjitlink-cu12==12.4.127
    # via
    #   nvidia-cusolver-cu12
    #   nvidia-cusparse-cu12
    #   torch
nvidia-nvtx-cu12==12.4.127
    # via torch
orjson==3.10.7
    # via gradio
packaging==24.1
    # via
    #   datasets
    #   gradio
    #   gradio-client
    #   huggingface-hub
    #   plotly
    #   transformers
pandas==2.2.3
    # via
    #   datasets
    #   gradio
pillow==10.4.0
    # via gradio
plotly==5.24.1
    # via open-japanese-llm-leaderboard (pyproject.toml)
propcache==0.2.0
    # via yarl
pyarrow==17.0.0
    # via datasets
pydantic==2.9.2
    # via
    #   fastapi
    #   gradio
pydantic-core==2.23.4
    # via pydantic
pydub==0.25.1
    # via gradio
pygments==2.18.0
    # via rich
python-dateutil==2.9.0.post0
    # via pandas
python-multipart==0.0.12
    # via gradio
pytz==2024.2
    # via
    #   apscheduler
    #   pandas
pyyaml==6.0.2
    # via
    #   datasets
    #   gradio
    #   huggingface-hub
    #   transformers
regex==2024.9.11
    # via transformers
requests==2.32.3
    # via
    #   datasets
    #   huggingface-hub
    #   transformers
rich==13.9.2
    # via typer
ruff==0.6.9
    # via gradio
safehttpx==0.1.1
    # via gradio
safetensors==0.4.5
    # via transformers
semantic-version==2.10.0
    # via gradio
shellingham==1.5.4
    # via typer
six==1.16.0
    # via
    #   apscheduler
    #   python-dateutil
sniffio==1.3.1
    # via
    #   anyio
    #   httpx
starlette==0.40.0
    # via
    #   fastapi
    #   gradio
sympy==1.13.1
    # via torch
tenacity==9.0.0
    # via plotly
tokenizers==0.20.1
    # via transformers
tomlkit==0.12.0
    # via gradio
torch==2.5.1
    # via open-japanese-llm-leaderboard (pyproject.toml)
tqdm==4.66.5
    # via
    #   datasets
    #   huggingface-hub
    #   transformers
transformers==4.46.2
    # via open-japanese-llm-leaderboard (pyproject.toml)
triton==3.1.0
    # via torch
typer==0.12.5
    # via gradio
typing-extensions==4.12.2
    # via
    #   anyio
    #   fastapi
    #   gradio
    #   gradio-client
    #   huggingface-hub
    #   multidict
    #   pydantic
    #   pydantic-core
    #   rich
    #   torch
    #   typer
    #   uvicorn
tzdata==2024.2
    # via pandas
tzlocal==5.2
    # via apscheduler
urllib3==2.2.3
    # via requests
uvicorn==0.31.1
    # via gradio
websockets==12.0
    # via gradio-client
xxhash==3.5.0
    # via datasets
yarl==1.15.0
    # via aiohttp