# 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