13 unstable releases
new 0.22.2 | Nov 6, 2024 |
---|---|
0.22.0 | Jul 15, 2024 |
0.20.0 | Jun 14, 2023 |
0.19.1 | Mar 7, 2023 |
0.3.0 | Feb 14, 2022 |
#1640 in Text processing
268 downloads per month
315KB
7.5K
SLoC
vaporetto_tantivy
Vaporetto is a fast and lightweight pointwise prediction based tokenizer. vaporetto_tantivy is a crate to use Vaporetto in Tantivy.
Example
use std::fs::File;
use std::io::{Read, BufReader};
use tantivy::schema::{IndexRecordOption, Schema, TextFieldIndexing, TextOptions};
use tantivy::Index;
use vaporetto::Model;
use vaporetto_tantivy::VaporettoTokenizer;
let mut schema_builder = Schema::builder();
let text_field_indexing = TextFieldIndexing::default()
.set_tokenizer("ja_vaporetto")
.set_index_option(IndexRecordOption::WithFreqsAndPositions);
let text_options = TextOptions::default()
.set_indexing_options(text_field_indexing)
.set_stored();
schema_builder.add_text_field("title", text_options);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
// Loads a model with decompression.
let mut f = BufReader::new(File::open("bccwj-suw+unidic.model.zst").unwrap());
let mut decoder = ruzstd::StreamingDecoder::new(&mut f).unwrap();
let mut buff = vec![];
decoder.read_to_end(&mut buff).unwrap();
let model = Model::read(&mut buff.as_slice()).unwrap();
// Creates VaporettoTokenizer with wsconst=DGR.
let tokenizer = VaporettoTokenizer::new(model, "DGR").unwrap();
index
.tokenizers()
.register("ja_vaporetto", tokenizer);
Dependencies
~26MB
~432K SLoC