optimization-engineer / requirements.txt
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# 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