Spaces:
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Fer Aguirre
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Parent(s):
b0f265a
Initial commit
Browse files- app.py +86 -0
- foia_sample.csv +0 -0
- requirements.txt +129 -0
app.py
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import streamlit as st
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import pandas as pd
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from datasets import Dataset
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from sentence_transformers import SentenceTransformer
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from sentence_transformers.util import semantic_search
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import torch
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model = SentenceTransformer("sentence-transformers/gtr-t5-large")
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# Read files
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url = "https://gist.githubusercontent.com/fer-aguirre/b6bdcf59ecae41f84765f72114de9fd1/raw/b4e029fe236c1f38275621686429b2c7aaa3d18b/embeddings.csv"
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df_emb = pd.read_csv(url, index_col=0)
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df = pd.read_csv('./foia_sample.csv')
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dataset = Dataset.from_pandas(df_emb)
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dataset_embeddings = torch.from_numpy(dataset.to_pandas().to_numpy()).to(torch.float)
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st.markdown("**Inserta una solicitud de información para generar recomendaciones de dependencias**")
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if request := st.text_area("", value=""):
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output = model.encode(request)
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query_embeddings = torch.FloatTensor(output)
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hits = semantic_search(query_embeddings, dataset_embeddings, top_k=3)
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id1 = hits[0][0]['corpus_id']
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id2 = hits[0][1]['corpus_id']
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id3 = hits[0][2]['corpus_id']
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rec1 = df.iloc[id1].str.split(pat="/")[0]
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rec2 = df.iloc[id2].str.split(pat="/")[0]
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rec3 = df.iloc[id3].str.split(pat="/")[0]
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list_rec = [rec1, rec2, rec3]
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unique_list = []
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for string in list_rec:
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if string not in unique_list:
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unique_list.append(string)
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st.markdown(f'Recomendaciones:')
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for rec in unique_list:
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st.markdown(f':green[{rec[0]}]')
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st.markdown("""---""")
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if st.button('Genera un ejemplo random'):
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test_example = df['combined'].sample(n=1)
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index = test_example.index
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idx = index[0]
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original = df.iloc[idx].str.split(pat="/")[0]
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request = test_example.to_string(index=False)
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st.text(f'{idx}, {request}')
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output = model.encode(request)
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query_embeddings = torch.FloatTensor(output)
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hits = semantic_search(query_embeddings, dataset_embeddings, top_k=3)
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id1 = hits[0][0]['corpus_id']
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id2 = hits[0][1]['corpus_id']
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id3 = hits[0][2]['corpus_id']
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rec1 = df.iloc[id1].str.split(pat="/")[0]
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rec2 = df.iloc[id2].str.split(pat="/")[0]
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rec3 = df.iloc[id3].str.split(pat="/")[0]
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list_rec = [rec1, rec2, rec3]
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unique_list = []
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for string in list_rec:
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if string not in unique_list:
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unique_list.append(string)
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st.markdown(f'Recomendaciones:')
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for rec in unique_list:
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st.markdown(f':green[{rec[0]}]')
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st.markdown(f'Dependencia original:')
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st.markdown(f':red[{original[0]}]')
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foia_sample.csv
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The diff for this file is too large to render.
See raw diff
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requirements.txt
ADDED
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@@ -0,0 +1,129 @@
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| 1 |
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-e git+ssh://git@github.com/fer-aguirre/ai4foia.git@3469e89044d7f0ccfb440fb5762fd7cbd893fa82#egg=AI4FOIA
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aiohttp==3.8.4
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aiosignal==1.3.1
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altair==4.2.2
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asttokens==2.2.1
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async-timeout==4.0.2
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attrs==22.2.0
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backcall==0.2.0
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backports.zoneinfo==0.2.1
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blinker==1.5
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cachetools==5.3.0
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certifi==2022.12.7
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charset-normalizer==3.1.0
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click==8.1.3
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cmake==3.26.1
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comm==0.1.3
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datasets==2.11.0
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debugpy==1.6.6
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decorator==5.1.1
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dill==0.3.6
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distlib==0.3.6
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entrypoints==0.4
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executing==1.2.0
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fastjsonschema==2.16.3
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filelock==3.10.7
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frozenlist==1.3.3
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fsspec==2023.3.0
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gitdb==4.0.10
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GitPython==3.1.31
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huggingface-hub==0.13.3
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idna==3.4
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importlib-metadata==6.1.0
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importlib-resources==5.12.0
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ipykernel==6.22.0
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ipython==8.12.0
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jedi==0.18.2
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Jinja2==3.1.2
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joblib==1.2.0
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jsonschema==4.17.3
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jupyter_client==8.1.0
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jupyter_core==5.3.0
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lit==16.0.0
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markdown-it-py==2.2.0
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MarkupSafe==2.1.2
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matplotlib-inline==0.1.6
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mdurl==0.1.2
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mpmath==1.3.0
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multidict==6.0.4
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multiprocess==0.70.14
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nbformat==5.8.0
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nest-asyncio==1.5.6
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networkx==3.0
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nltk==3.8.1
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numpy==1.24.2
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nvidia-cublas-cu11==11.10.3.66
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nvidia-cuda-cupti-cu11==11.7.101
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nvidia-cuda-nvrtc-cu11==11.7.99
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nvidia-cuda-runtime-cu11==11.7.99
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nvidia-cudnn-cu11==8.5.0.96
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nvidia-cufft-cu11==10.9.0.58
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| 61 |
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nvidia-curand-cu11==10.2.10.91
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| 62 |
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nvidia-cusolver-cu11==11.4.0.1
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| 63 |
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nvidia-cusparse-cu11==11.7.4.91
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nvidia-nccl-cu11==2.14.3
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nvidia-nvtx-cu11==11.7.91
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packaging==23.0
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pandas==1.5.3
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| 68 |
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parso==0.8.3
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| 69 |
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pathlib==1.0.1
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| 70 |
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pbr==5.11.1
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| 71 |
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pexpect==4.8.0
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| 72 |
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pickleshare==0.7.5
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| 73 |
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Pillow==9.5.0
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| 74 |
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pipenv==2023.3.20
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pkgutil_resolve_name==1.3.10
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| 76 |
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platformdirs==3.2.0
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| 77 |
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prompt-toolkit==3.0.38
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| 78 |
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protobuf==3.20.3
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psutil==5.9.4
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ptyprocess==0.7.0
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| 81 |
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pure-eval==0.2.2
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| 82 |
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pyarrow==11.0.0
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| 83 |
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pydeck==0.8.0
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| 84 |
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Pygments==2.14.0
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| 85 |
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Pympler==1.0.1
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| 86 |
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pyprojroot==0.3.0
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| 87 |
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pyrsistent==0.19.3
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| 88 |
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python-dateutil==2.8.2
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| 89 |
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pytz==2023.3
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| 90 |
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pytz-deprecation-shim==0.1.0.post0
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| 91 |
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PyYAML==6.0
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| 92 |
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pyzmq==25.0.2
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| 93 |
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regex==2023.3.23
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| 94 |
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requests==2.28.2
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| 95 |
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responses==0.18.0
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| 96 |
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rich==13.3.3
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| 97 |
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scikit-learn==1.2.2
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| 98 |
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scipy==1.10.1
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| 99 |
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semver==2.13.0
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| 100 |
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sentence-transformers==2.2.2
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| 101 |
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sentencepiece==0.1.97
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| 102 |
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six==1.16.0
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| 103 |
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smmap==5.0.0
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| 104 |
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stack-data==0.6.2
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| 105 |
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streamlit==1.20.0
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| 106 |
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sympy==1.11.1
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| 107 |
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threadpoolctl==3.1.0
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| 108 |
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tokenizers==0.13.2
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| 109 |
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toml==0.10.2
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| 110 |
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toolz==0.12.0
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| 111 |
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torch==2.0.0
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| 112 |
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torchvision==0.15.1
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| 113 |
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tornado==6.2
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| 114 |
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tqdm==4.65.0
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| 115 |
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traitlets==5.9.0
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| 116 |
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transformers==4.27.4
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| 117 |
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triton==2.0.0
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| 118 |
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typing_extensions==4.5.0
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| 119 |
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tzdata==2023.3
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| 120 |
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tzlocal==4.3
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| 121 |
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urllib3==1.26.15
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| 122 |
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validators==0.20.0
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| 123 |
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virtualenv==20.21.0
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| 124 |
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virtualenv-clone==0.5.7
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| 125 |
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watchdog==3.0.0
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| 126 |
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wcwidth==0.2.6
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| 127 |
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xxhash==3.2.0
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| 128 |
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yarl==1.8.2
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| 129 |
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zipp==3.15.0
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