# This file was autogenerated by uv via the following command: # uv pip compile pyproject.toml --output-file requirements.txt accelerate==1.7.0 # via model-benchmark-agent (pyproject.toml) aiofiles==24.1.0 # via gradio aiohappyeyeballs==2.6.1 # via aiohttp aiohttp==3.12.12 # via fsspec aiosignal==1.3.2 # via aiohttp annotated-types==0.7.0 # via pydantic anyio==4.9.0 # via # gradio # httpx # mcp # sse-starlette # starlette attrs==25.3.0 # via aiohttp certifi==2025.4.26 # via # httpcore # httpx # requests charset-normalizer==3.4.2 # via requests click==8.2.1 # via # typer # uvicorn datasets==3.6.0 # via model-benchmark-agent (pyproject.toml) dill==0.3.8 # via # datasets # multiprocess fastapi==0.115.12 # via gradio ffmpy==0.6.0 # via gradio filelock==3.18.0 # via # datasets # huggingface-hub # torch # transformers frozenlist==1.7.0 # via # aiohttp # aiosignal fsspec==2025.3.0 # via # datasets # gradio-client # huggingface-hub # torch gradio==5.33.1 # via model-benchmark-agent (pyproject.toml) gradio-client==1.10.3 # via gradio groovy==0.1.2 # via gradio h11==0.16.0 # via # httpcore # uvicorn hf-xet==1.1.3 # via huggingface-hub httpcore==1.0.9 # via httpx httpx==0.28.1 # via # gradio # gradio-client # mcp # safehttpx httpx-sse==0.4.0 # via mcp huggingface-hub==0.32.5 # via # accelerate # datasets # gradio # gradio-client # optimum-quanto # tokenizers # transformers idna==3.10 # via # anyio # httpx # requests # yarl jinja2==3.1.6 # via # gradio # torch markdown-it-py==3.0.0 # via rich markupsafe==3.0.2 # via # gradio # jinja2 mcp==1.9.3 # via model-benchmark-agent (pyproject.toml) mdurl==0.1.2 # via markdown-it-py mpmath==1.3.0 # via sympy multidict==6.4.4 # via # aiohttp # yarl multiprocess==0.70.16 # via datasets narwhals==1.42.0 # via plotly networkx==3.4.2 # via torch ninja==1.11.1.4 # via optimum-quanto numpy==2.2.6 # via # model-benchmark-agent (pyproject.toml) # accelerate # datasets # gradio # optimum-quanto # pandas # transformers optimum-quanto==0.2.7 # via model-benchmark-agent (pyproject.toml) orjson==3.10.18 # via gradio packaging==25.0 # via # accelerate # datasets # gradio # gradio-client # huggingface-hub # plotly # transformers pandas==2.3.0 # via # model-benchmark-agent (pyproject.toml) # datasets # gradio pillow==11.2.1 # via gradio plotly==6.1.2 # via model-benchmark-agent (pyproject.toml) propcache==0.3.2 # via # aiohttp # yarl psutil==7.0.0 # via # model-benchmark-agent (pyproject.toml) # accelerate pyarrow==20.0.0 # via datasets pydantic==2.11.5 # via # model-benchmark-agent (pyproject.toml) # fastapi # gradio # mcp # pydantic-settings pydantic-core==2.33.2 # via pydantic pydantic-settings==2.9.1 # via mcp pydub==0.25.1 # via gradio pygments==2.19.1 # via rich python-dateutil==2.9.0.post0 # via pandas python-dotenv==1.1.0 # via pydantic-settings python-multipart==0.0.20 # via # gradio # mcp pytz==2025.2 # via pandas pyyaml==6.0.2 # via # accelerate # datasets # gradio # huggingface-hub # transformers regex==2024.11.6 # via transformers requests==2.32.4 # via # datasets # huggingface-hub # transformers rich==14.0.0 # via typer ruff==0.11.13 # via gradio safehttpx==0.1.6 # via gradio safetensors==0.5.3 # via # accelerate # optimum-quanto # transformers semantic-version==2.10.0 # via gradio setuptools==80.9.0 # via torch shellingham==1.5.4 # via typer six==1.17.0 # via python-dateutil sniffio==1.3.1 # via anyio sse-starlette==2.3.6 # via mcp starlette==0.46.2 # via # fastapi # gradio # mcp sympy==1.14.0 # via torch tokenizers==0.21.1 # via transformers tomlkit==0.13.3 # via gradio torch==2.7.1 # via # model-benchmark-agent (pyproject.toml) # accelerate # optimum-quanto tqdm==4.67.1 # via # datasets # huggingface-hub # transformers transformers==4.52.4 # via model-benchmark-agent (pyproject.toml) typer==0.16.0 # via gradio typing-extensions==4.14.0 # via # anyio # fastapi # gradio # gradio-client # huggingface-hub # pydantic # pydantic-core # torch # typer # typing-inspection typing-inspection==0.4.1 # via # pydantic # pydantic-settings tzdata==2025.2 # via pandas urllib3==2.4.0 # via requests uvicorn==0.34.3 # via # gradio # mcp websockets==15.0.1 # via gradio-client xxhash==3.5.0 # via datasets yarl==1.20.1 # via aiohttp