requirements.txt

# This file was autogenerated by uv via the following command:
#    uv pip compile requirements.in -o requirements.txt
aiofiles==23.2.1
    # via gradio
aiohttp==3.9.5
    # via
    #   datasets
    #   fsspec
aiosignal==1.3.1
    # via aiohttp
altair==5.3.0
    # via gradio
annotated-types==0.7.0
    # via pydantic
anyio==4.4.0
    # via
    #   httpx
    #   starlette
    #   watchfiles
apscheduler==3.10.4
    # via -r requirements.in
arxiv==2.1.0
    # via -r requirements.in
attrs==23.2.0
    # via
    #   aiohttp
    #   jsonschema
    #   referencing
cachetools==5.3.3
    # via -r requirements.in
certifi==2024.6.2
    # via
    #   httpcore
    #   httpx
    #   requests
charset-normalizer==3.3.2
    # via requests
click==8.1.7
    # via
    #   typer
    #   uvicorn
contourpy==1.2.1
    # via matplotlib
cycler==0.12.1
    # via matplotlib
datasets==2.14.4
    # via
    #   evaluate
    #   setfit
dill==0.3.7
    # via
    #   datasets
    #   evaluate
    #   multiprocess
dnspython==2.6.1
    # via email-validator
email-validator==2.1.1
    # via fastapi
evaluate==0.4.2
    # via setfit
fastapi==0.111.0
    # via gradio
fastapi-cli==0.0.4
    # via fastapi
feedparser==6.0.10
    # via arxiv
ffmpy==0.3.2
    # via gradio
filelock==3.14.0
    # via
    #   huggingface-hub
    #   torch
    #   transformers
fonttools==4.53.0
    # via matplotlib
frozenlist==1.4.1
    # via
    #   aiohttp
    #   aiosignal
fsspec==2024.6.0
    # via
    #   datasets
    #   evaluate
    #   gradio-client
    #   huggingface-hub
    #   torch
gradio==4.36.1
    # via -r requirements.in
gradio-client==1.0.1
    # via gradio
h11==0.14.0
    # via
    #   httpcore
    #   uvicorn
hf-transfer==0.1.6
    # via -r requirements.in
httpcore==1.0.5
    # via httpx
httptools==0.6.1
    # via uvicorn
httpx==0.27.0
    # via
    #   fastapi
    #   gradio
    #   gradio-client
huggingface-hub==0.23.3
    # via
    #   datasets
    #   evaluate
    #   gradio
    #   gradio-client
    #   sentence-transformers
    #   setfit
    #   tokenizers
    #   transformers
idna==3.7
    # via
    #   anyio
    #   email-validator
    #   httpx
    #   requests
    #   yarl
importlib-resources==6.4.0
    # via gradio
jinja2==3.1.4
    # via
    #   altair
    #   fastapi
    #   gradio
    #   torch
joblib==1.4.2
    # via scikit-learn
jsonschema==4.22.0
    # via altair
jsonschema-specifications==2023.12.1
    # via jsonschema
kiwisolver==1.4.5
    # via matplotlib
markdown-it-py==3.0.0
    # via rich
markupsafe==2.1.5
    # via
    #   gradio
    #   jinja2
matplotlib==3.9.0
    # via gradio
mdurl==0.1.2
    # via markdown-it-py
mpmath==1.3.0
    # via sympy
multidict==6.0.5
    # via
    #   aiohttp
    #   yarl
multiprocess==0.70.15
    # via
    #   datasets
    #   evaluate
networkx==3.3
    # via torch
numpy==1.26.4
    # via
    #   altair
    #   contourpy
    #   datasets
    #   evaluate
    #   gradio
    #   matplotlib
    #   pandas
    #   pyarrow
    #   scikit-learn
    #   scipy
    #   sentence-transformers
    #   transformers
orjson==3.10.3
    # via
    #   fastapi
    #   gradio
packaging==24.1
    # via
    #   altair
    #   datasets
    #   evaluate
    #   gradio
    #   gradio-client
    #   huggingface-hub
    #   matplotlib
    #   setfit
    #   transformers
pandas==2.2.2
    # via
    #   altair
    #   datasets
    #   evaluate
    #   gradio
pillow==10.3.0
    # via
    #   gradio
    #   matplotlib
    #   sentence-transformers
pyarrow==16.1.0
    # via datasets
pydantic==2.7.3
    # via
    #   fastapi
    #   gradio
pydantic-core==2.18.4
    # via pydantic
pydub==0.25.1
    # via gradio
pygments==2.18.0
    # via rich
pyparsing==3.1.2
    # via matplotlib
python-dateutil==2.9.0.post0
    # via
    #   matplotlib
    #   pandas
python-dotenv==1.0.1
    # via uvicorn
python-multipart==0.0.9
    # via
    #   fastapi
    #   gradio
pytz==2024.1
    # via
    #   apscheduler
    #   pandas
pyyaml==6.0.1
    # via
    #   datasets
    #   gradio
    #   huggingface-hub
    #   transformers
    #   uvicorn
referencing==0.35.1
    # via
    #   jsonschema
    #   jsonschema-specifications
regex==2024.5.15
    # via transformers
requests==2.31.0
    # via
    #   arxiv
    #   datasets
    #   evaluate
    #   huggingface-hub
    #   transformers
rich==13.7.1
    # via typer
rpds-py==0.18.1
    # via
    #   jsonschema
    #   referencing
ruff==0.4.8
    # via gradio
safetensors==0.4.3
    # via transformers
scikit-learn==1.2.2
    # via
    #   -r requirements.in
    #   sentence-transformers
    #   setfit
scipy==1.13.1
    # via
    #   scikit-learn
    #   sentence-transformers
semantic-version==2.10.0
    # via gradio
sentence-transformers==3.0.1
    # via setfit
setfit==1.0.3
    # via -r requirements.in
sgmllib3k==1.0.0
    # via feedparser
shellingham==1.5.4
    # via typer
six==1.16.0
    # via
    #   apscheduler
    #   python-dateutil
sniffio==1.3.1
    # via
    #   anyio
    #   httpx
stamina==24.2.0
    # via -r requirements.in
starlette==0.37.2
    # via fastapi
sympy==1.12.1
    # via torch
tenacity==8.3.0
    # via stamina
threadpoolctl==3.5.0
    # via scikit-learn
tokenizers==0.19.1
    # via transformers
tomlkit==0.12.0
    # via gradio
toolz==0.12.1
    # via altair
torch==2.3.1
    # via sentence-transformers
tqdm==4.66.4
    # via
    #   datasets
    #   evaluate
    #   huggingface-hub
    #   sentence-transformers
    #   transformers
transformers==4.41.2
    # via sentence-transformers
typer==0.12.3
    # via
    #   fastapi-cli
    #   gradio
typing-extensions==4.12.2
    # via
    #   fastapi
    #   gradio
    #   gradio-client
    #   huggingface-hub
    #   pydantic
    #   pydantic-core
    #   torch
    #   typer
tzdata==2024.1
    # via pandas
tzlocal==5.2
    # via apscheduler
ujson==5.10.0
    # via fastapi
urllib3==2.2.1
    # via
    #   gradio
    #   requests
uvicorn==0.30.1
    # via
    #   fastapi
    #   gradio
uvloop==0.19.0
    # via uvicorn
watchfiles==0.22.0
    # via uvicorn
websockets==11.0.3
    # via
    #   gradio-client
    #   uvicorn
xxhash==3.4.1
    # via
    #   datasets
    #   evaluate
yarl==1.9.4
    # via aiohttp