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requirements.lock
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requirements.lock
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# generated by rye
# use `rye lock` or `rye sync` to update this lockfile
#
# last locked with the following flags:
# pre: false
# features: []
# all-features: false
# with-sources: false
# generate-hashes: false
# universal: false
-e file:.
aiohttp==3.9.5
# via datasets
# via fsspec
aiosignal==1.3.1
# via aiohttp
annotated-types==0.6.0
# via pydantic
anthropic==0.21.3
# via claude-memorization
anyio==4.3.0
# via anthropic
# via httpx
# via openai
asttokens==2.4.1
# via stack-data
async-timeout==4.0.3
# via aiohttp
attrs==23.2.0
# via aiohttp
# via jsonlines
# via outcome
# via trio
blobfile==2.1.1
# via claude-memorization
certifi==2024.2.2
# via httpcore
# via httpx
# via requests
# via selenium
charset-normalizer==3.3.2
# via requests
click==8.1.7
# via claude-memorization
comm==0.2.2
# via ipykernel
contourpy==1.2.0
# via matplotlib
cycler==0.12.1
# via matplotlib
datasets==2.19.2
# via claude-memorization
debugpy==1.8.1
# via ipykernel
decorator==5.1.1
# via ipython
dill==0.3.8
# via datasets
# via multiprocess
distro==1.9.0
# via anthropic
# via openai
exceptiongroup==1.2.2
# via anyio
# via ipython
# via pytest
# via trio
# via trio-websocket
executing==2.0.1
# via stack-data
filelock==3.13.3
# via blobfile
# via datasets
# via huggingface-hub
# via torch
# via transformers
# via triton
fonttools==4.50.0
# via matplotlib
frozenlist==1.4.1
# via aiohttp
# via aiosignal
fsspec==2024.3.1
# via datasets
# via huggingface-hub
# via torch
h11==0.14.0
# via httpcore
# via wsproto
httpcore==1.0.5
# via httpx
httpx==0.27.0
# via anthropic
# via openai
huggingface-hub==0.26.2
# via datasets
# via tokenizers
# via transformers
idna==3.6
# via anyio
# via httpx
# via requests
# via trio
# via yarl
iniconfig==2.0.0
# via pytest
ipykernel==6.29.4
# via claude-memorization
ipython==8.24.0
# via claude-memorization
# via ipykernel
jedi==0.19.1
# via ipython
jinja2==3.1.4
# via torch
jiter==0.6.1
# via openai
jsonlines==4.0.0
# via claude-memorization
jupyter-client==8.6.2
# via ipykernel
jupyter-core==5.7.2
# via ipykernel
# via jupyter-client
kiwisolver==1.4.5
# via matplotlib
lxml==4.9.4
# via blobfile
markupsafe==3.0.2
# via jinja2
matplotlib==3.8.3
# via claude-memorization
# via seaborn
matplotlib-inline==0.1.7
# via ipykernel
# via ipython
mpmath==1.3.0
# via sympy
multidict==6.0.5
# via aiohttp
# via yarl
multiprocess==0.70.16
# via datasets
nest-asyncio==1.6.0
# via ipykernel
networkx==3.4.2
# via torch
numpy==1.26.4
# via claude-memorization
# via contourpy
# via datasets
# via matplotlib
# via pandas
# via pyarrow
# via seaborn
# via transformers
nvidia-cublas-cu12==12.4.5.8
# via nvidia-cudnn-cu12
# via nvidia-cusolver-cu12
# via 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
# via torch
nvidia-nccl-cu12==2.21.5
# via torch
nvidia-nvjitlink-cu12==12.4.127
# via nvidia-cusolver-cu12
# via nvidia-cusparse-cu12
# via torch
nvidia-nvtx-cu12==12.4.127
# via torch
openai==1.51.2
# via claude-memorization
outcome==1.3.0.post0
# via trio
packaging==24.0
# via claude-memorization
# via datasets
# via huggingface-hub
# via ipykernel
# via matplotlib
# via pytest
# via transformers
pandas==2.2.2
# via datasets
# via seaborn
parso==0.8.4
# via jedi
pexpect==4.9.0
# via ipython
pillow==10.2.0
# via matplotlib
platformdirs==4.2.2
# via jupyter-core
pluggy==1.5.0
# via pytest
prompt-toolkit==3.0.43
# via ipython
psutil==5.9.8
# via ipykernel
ptyprocess==0.7.0
# via pexpect
pure-eval==0.2.2
# via stack-data
pyarrow==16.1.0
# via datasets
pyarrow-hotfix==0.6
# via datasets
pycryptodomex==3.20.0
# via blobfile
pydantic==2.6.4
# via anthropic
# via openai
pydantic-core==2.16.3
# via pydantic
pygments==2.18.0
# via ipython
pyparsing==3.1.2
# via matplotlib
pysocks==1.7.1
# via urllib3
pytest==8.3.3
# via claude-memorization
python-dateutil==2.9.0.post0
# via jupyter-client
# via matplotlib
# via pandas
pytz==2024.1
# via pandas
pyyaml==6.0.1
# via datasets
# via huggingface-hub
# via transformers
pyzmq==26.0.3
# via ipykernel
# via jupyter-client
regex==2024.5.15
# via tiktoken
# via transformers
requests==2.32.3
# via datasets
# via huggingface-hub
# via tiktoken
# via transformers
safetensors==0.4.5
# via transformers
seaborn==0.13.2
# via claude-memorization
selenium==4.24.0
# via claude-memorization
setuptools==69.5.1
# via claude-memorization
six==1.16.0
# via asttokens
# via python-dateutil
sniffio==1.3.1
# via anthropic
# via anyio
# via httpx
# via openai
# via trio
sortedcontainers==2.4.0
# via trio
stack-data==0.6.3
# via ipython
sympy==1.13.1
# via torch
tenacity==9.0.0
# via claude-memorization
tiktoken==0.6.0
# via claude-memorization
tokenizers==0.20.3
# via anthropic
# via transformers
tomli==2.0.1
# via pytest
torch==2.5.1
# via claude-memorization
tornado==6.4
# via ipykernel
# via jupyter-client
tqdm==4.66.2
# via claude-memorization
# via datasets
# via huggingface-hub
# via openai
# via transformers
traitlets==5.14.3
# via comm
# via ipykernel
# via ipython
# via jupyter-client
# via jupyter-core
# via matplotlib-inline
transformers==4.46.2
# via claude-memorization
trio==0.26.2
# via selenium
# via trio-websocket
trio-websocket==0.11.1
# via selenium
triton==3.1.0
# via torch
typing-extensions==4.12.2
# via anthropic
# via anyio
# via huggingface-hub
# via ipython
# via openai
# via pydantic
# via pydantic-core
# via selenium
# via torch
tzdata==2024.1
# via pandas
urllib3==2.2.1
# via blobfile
# via requests
# via selenium
uv==0.2.2
# via claude-memorization
wcwidth==0.2.13
# via prompt-toolkit
websocket-client==1.8.0
# via selenium
wsproto==1.2.0
# via trio-websocket
xxhash==3.4.1
# via datasets
yarl==1.9.4
# via aiohttp
zstandard==0.23.0
# via claude-memorization