• LegalQA using SentenceKoBART
  • Setup
  • Index
  • Search
    • With REST API
      • Approximate KNN Search with AnnLite
    • Production Ready Neural Search with HNSWPostgresIndexer
  • Presentation
  • Demo
  • Links
  • FAQ
    • Why this dataset?
    • LFS quota is exceeded
  • Citation
  • License

LegalQA using SentenceKoBART

Implementation of legal QA system based on SentenceKoBART

• How to train SentenceKoBART
• Based on Neural Search Engine Jina v2.0
• Provide Korean legal QA data(1,830 pairs)
• Apply approximate KNN search with Faiss, Annoy, Hnswlib.

Setup

# install git lfs , https://github.com/git-lfs/git-lfs/wiki/Installation
curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
sudo apt install git-lfs
git clone https://github.com/haven-jeon/LegalQA.git
cd LegalQA
git lfs pull
# If the lfs quota is exceeded, please download it with the command below.
# https://drive.google.com/file/d/1DJFMknxT7OAAWYFV_WGW2UcCxmuf3cp_/view?usp=sharing
# mv SentenceKoBART.bin model/
# pip install --use-deprecated=legacy-resolver  -r requirements.txt 
pip install -r requirements.txt

Index

python app.py -t index

GPU-based indexing available as an option

• device: cuda

Search

With REST API

To start the Jina server for REST API:

# python app.py -t query_restful --flow flows/query_numpy.yml
python app.py -t query_restful

Then use a client to query:

curl --request POST -d '{"parameters": {"limit": 1},  "data": ["상속 관련 문의"]}' -H 'Content-Type: application/json' 'http://0.0.0.0:1234/search'

From the terminal

# python app.py -t query --flow flows/query_numpy.yml
python app.py -t query

Approximate KNN Search with AnnLite

python app.py -t index --flow flows/index_annlite.yml

python app.py -t query --flow flows/query_annlite.yml

• Retrieval time(sec.)
  • AMD Ryzen 5 PRO 4650U, 16 GB Memory
  • Average of 100 searches
  • Excluding BertReRanker

Production Ready Neural Search with HNSWPostgresIndexer

docker run -e POSTGRES_PASSWORD=123456 -p 127.0.0.1:5432:5432/tcp postgres:13.2
python app.py -t index --flow flows/index_psqlhnsw.yml

python app.py -t query --flow flows/query_psqlhnsw.yml

Presentation

• Neural IR 101

Demo

• Working!

Links

• [AI 모델 탐험기] #13 Neural Search를 이용하여 제작된 법률 QA 검색 시스템, Legal QA

FAQ

Why this dataset?

Legal data is composed of technical terms, so it is difficult to search if you are not familiar with these terms. Because of these characteristics, I thought it was a good example to show the effectiveness of neural IR.

LFS quota is exceeded

You can download SentenceKoBART.bin from one of the two links below.

• https://drive.google.com/file/d/1DJFMknxT7OAAWYFV_WGW2UcCxmuf3cp_/view?usp=sharing

Citation

Model training, data crawling, and demo system were all supported by the AWS Hero program.

@misc{heewon2021,
author = {Heewon Jeon},
title = {LegalQA using SentenceKoBART},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/haven-jeon/LegalQA}}

License

• QA data data/legalqa.jsonlines is crawled in www.freelawfirm.co.kr based on robots.txt. Commercial use other than academic use is prohibited.
• We are not responsible for any legal decisions we make based on the resources provided here.