WIP

# PR LEGISLATION

Making the legislation process in puerto rico more transparent 

## Scrape legislation past and present

<http://www.tucamarapr.org/dnncamara/web/ActividadLegislativa/tramitelegislativo.aspx?measureid=XXXX>

contents to be retrieved and stored as JSON files to be processed later
save as documents/{measure_name}.es.json

    measure {
        Measure Name :: string
        Date Filed :: date
        Authors :: string[]
        Heading :: string
        History :: History[]
    }

    History {
        Date :: date
        Description :: string 
        Document :: string (url)
    }

## download all associated documents

save contents to folders ouput/documents/{measure_name}/{history_date}.{history_description}.pdf

## Scrape vote date ??? how to find vote IDs?

<http://www.tucamarapr.org/dnncamara/web/ActividadLegislativa/votaciones.aspx?measureid=XXX&voteid=???>

## Translation

translate documents/{measure_name}.es.json into documents/{measure_name}.en.json
using rust-bert

## create table html

index page for es/en
filter by measure id/heading substring/authors

## generate html for each measure

convert json files into static html and md files for es/en

## gotchas

Translation is currently using a local build of rust-bert

To get it to work I updated openssl to 3.0 via the experimental ubuntu repo
downloaded from `https://download.pytorch.org/libtorch/cu113/libtorch-shared-with-deps-1.11.0%2Bcu113.zip` `libtorch-cxx11-abi-shared-with-deps-1.11.0+cu113.zip` and extracted it locally, pointed LIBTORCH at it (following instructions via rust-bert)
cloned rust-bert and built it via `cargo build` and pointed my translate cargo.toml to the extracted directory

It's currently running on CPU for the translation so if you have a real you can update it to target GPU

    @inproceedings{becquin-2020-end,
        title = "End-to-end {NLP} Pipelines in Rust",
        author = "Becquin, Guillaume",
        booktitle = "Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS)",
        year = "2020",
        publisher = "Association for Computational Linguistics",
        url = "<https://www.aclweb.org/anthology/2020.nlposs-1.4">,
        pages = "20--25",
    }