antoinelouis
commited on
Commit
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Parent(s):
9158c03
Add app files
Browse files- README.md +8 -5
- app.py +26 -0
- checkpoints/doc_embeddings.pt +3 -0
- requirements.txt +4 -0
README.md
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---
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title: Legislation Search
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emoji:
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colorFrom:
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sdk: gradio
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sdk_version: 3.0.24
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app_file: app.py
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pinned: false
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license: cc-by-nc-sa-4.0
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---
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-
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---
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title: Legislation Search
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emoji: 🇧🇪
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colorFrom: yellow
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colorTo: yellow
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sdk: gradio
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app_file: app.py
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pinned: false
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license: cc-by-nc-sa-4.0
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---
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This is a demo for the paper: "A Statutory Article Retrieval Dataset in French" (ACL 2022)
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- Paper: https://aclanthology.org/2022.acl-long.468/
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- Code: https://github.com/maastrichtlawtech/bsard
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- Data: https://huggingface.co/datasets/antoiloui/bsard
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app.py
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import gradio as gr
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import pandas as pd
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import torch
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from datasets import load_dataset
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from sentence_transformers import SentenceTransformer, util
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q_encoder = SentenceTransformer("checkpoints/q_encoder")
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doc_embeddings = torch.load('checkpoints/doc_embeddings.pt')
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docs = pd.DataFrame(load_dataset("antoiloui/bsard", data_files="articles_fr.csv")['train'])
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def search(query):
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q_emb = q_encoder.encode(query, convert_to_tensor=True)
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hits = util.semantic_search(q_emb, doc_embeddings, top_k=100, score_function=util.cos_sim)[0]
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return {docs.loc[h['corpus_id'], 'article']: f"Art. {docs.loc[h['corpus_id'], 'article_no']}, {docs.loc[h['corpus_id'], 'code']}" for h in hits[:5]}
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gr.Interface(
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fn=search,
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inputs=gr.Textbox(label="Question", placeholder=""),
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outputs=[gr.Textbox(lines=5, label="Result"),gr.Textbox(label="Reference")],
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title="Legislation Search 🇧🇪",
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description="",
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flagging_options=["👍","👎"],
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examples=["Qu'est-ce que je risque si je viole le secret professionnel ?", "Mon employeur peut-il me licencier alors que je suis malade ?"]
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).launch(share=False, enable_queue=False)
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checkpoints/doc_embeddings.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:3dc0b8cb264f836bfa266ea91736b71acbdc16d4306708aa958392d283b55004
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size 69529323
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requirements.txt
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pandas==1.3.5
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sentence-transformers==2.1.0
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torch==1.10.1
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datasets==1.18.3
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