Chinese Notes Dictionary App and Translation Portal
A Go web application and text processing library for translation from Chinese to
English that is adaptable to different dictionaries and corpora, powering
these use cases
- A web site for Chinese-English dictionary lookup and language tools for
language learning and reference
- A password protected translation portal for a team of translators
- A software library for Chinese text processing
Features include:
- Chinese-English dictionary word lookup
- Chinese text tokenization
- Translation memory (optional)
- Full text search of a Chinese corpus (optional)
- Password proection (optional)
- Integration with a rich JavaScript web client (optional)
- Integration with a backend SQL databsae (optional)
- Go module with Go and JSON APIs for interactive Chinese text processing
- as opposed to batch processing of a corpus for indexing
A screenshot of dictionary lookup of multiple terms with text tokenization is
shown below.
The web app drives the https://chinesenotes.com, https://ntireader.org, and
https://hbreader.org web site and a private translation portal
developed for Fo Guang Shan, working together with the
Fo Guang Shan Institute of Humanistic Buddhism and
Nan Tien Institute.
The items above marked as optional require some special set-up, as described
below.
Setup
Install Go.
Quickstart
In a terminal, run the commands to get the command line app and download the
dicitonary
go get github.com/alexamies/cnreader
go run github.com/alexamies/cnreader -download_dict
Set an environment variable to let the app know where its home is
export CNWEB_HOME=.
Run the app
go run github.com/alexamies/chinesenotes-go
When you see the output
...
Starting http server on port :8080
navigate to http://localhost:8080 with your browser. Enter some Chinese words
and see the English equivalents. With no environment settings the dictionary
will be loaded from the Net.
Basic Usage
The repo contains a number of file that allow for customization of the app. To
get them, clone this repo:
git clone https://github.com/alexamies/chinesenotes-go.git
Then cd into the directory cloned:
cd chinesenotes-go
Build the app
go build
Run the web server
./chinesenotes-go
Navigate to http://localhost:8080
You can change styles by changing the CSS settings in the file web/styles.css
.
The webconfig.yaml file and HTML tempates in /templates allow some additional
customization. The HTML interface is very basic, just enough for minimal
testing. See the web-resources directory for
customization of template files. Make sure that the TemplateDir
parameter is
set in the webconfig.yaml
file for this to take effect.
Another approach is to use AJAX communicate with the web app with complete
customization of the web user interface, as in
https://github.com/alexamies/chinesenotes.com .
Development testing
In another terminal
curl http://localhost:8080/find/?query=邃古
You should see JSON encoded data sent back.
Features
Chinese-English dictionary word lookup
The data/testdict.tsv file gives an example file that illustrates the
structure of the dictionary. The dictionary is indexed by both simplified and
traditional Chinese. Lookup by Chinese word is supported in file mode.
You will need to install and setup the database to do lookup by English word
Hanyu pinyin.
Chinese text tokenization
Given a string of Chinese text, the web app will segment it into words or
multiword expressions contained in the dictionary. This saves a lot of time
for readers who look up many words or discover how the words in a phrase are
grouped, since there are no spaces in Chinese sentences. The presence of the
dictionary files is needed for this. They can be loaded either from the file
system or from the database by the web app.
Translation memory
Tanslation memory search find the closest matching term based on multiple
criteria, including how many characters match, similarity of the character
order, Pinyin match, and inclusion of the query in the notes. This depends on
compilation of the translation memory index and loading it into the database.
Full text search of a Chinese corpus
Full text search of a Chinese corpus allows users to search a monolingual
Chinese corpus. First, you need
- Have a corpus following the layout conventions
of Chinese Notes.
- Compile the index, which computes word and bigram frequencies for each
document with the cnreader command
- Load the index files into the database
- Load the corpus files into Google Cloud Storage
For the corpus structure see
https://github.com/alexamies/chinesenotes.com/tree/master/data/corpus
Integration with a rich JavaScript web client (optional)
For web resources to give a higher quality user experience than the basic Go
HTML templates using Material Design Web, see
(Material Design Web Resources)[web_resources/README.md].
For an implementation where the communication with the backend uses AJAX, see
the web files at
https://github.com/alexamies/chinesenotes.com/tree/master/web-resources
FAQ
Q: Why would I use a dictionary and translation memory to translate Chinese
text instead of machine translation?
A: This project is based around the idea of using linguistic assets, including
a dictionary, named entity database, and translation memory, to aid in
translation. To translate literature, especially classical literature and
Buddhist texts, and to prepare for publishing you will need to thoroughly
understand what you are the source Chinese text.
Q: Can I use the Chinese Notes Translation Portal software for my own project?
A: Yes, please do that. It is also adaptable to your own dictionary, glossary,
and corpus of source text.
Architecture
This project is designed to be easy to setup with minimal dependencies but
also run in a production architecture like shown below.
Various flavors are possible depending on how it is configured. It can
interoperate with the other components in the Chinese Notes family
- cnreader - Command line utility
for generating indexes and HTML files for the reader
- chinesedict-js - JavaScript
package for browser module for the dictionary and text parser
- chinesenotes-python -
Pyhton utilities for Chinese text analysis
- chinesenotes.com -
Chinese-English dictionary and corpus of historic Chinese literature
- buddhist-dictionary -
Buddhist dictionary extensions to the Chinese-English dictionary and
structure to present the Taisho Tripitaka as a digital library for
ntireader.org
Database Setup
The prepared statements in the Go code assuming a MySQL driver. Maria
is compatible with MySQL. The local development instructions assume a Mariadb
database running in Docker. For full details about the database see the
Mariadb Documentation.
Install Docker if you have not already.
Translation memory files
The command to download the dictionary files was given above. Generate the
translation memory index files with the command
go run github.com/alexamies/cnreader -tmindex
The index files are saved in the index
directory.
Mariadb Docker Image
See the documentation at Mariadb Image
Documentation and Installing and using
MariaDB via Docker.
To start a Docker container with Mariadb and connect to it from a MySQL command
line client execute the command below. First, set environment variable
MYSQL_ROOT_PASSWORD
. Also, create a directory outside the container to use as a
permanent Docker volume for the database files. In addition, mount volumes for
the tabe separated data to be loaded into Mariadb. See
Manage data in Docker and
Use volumes for details on volume
and mount management with Docker. In another terminal, create a Maria DB
database with the commands
cd ..
mkdir mariadb
cd mariadb
MYSQL_ROOT_PASSWORD=[your password]
CNREADER_HOME=../chinesenotes-go
mkdir mariadb-data
docker run --name mariadb -p 3306:3306 \
-e MYSQL_ROOT_PASSWORD=$MYSQL_ROOT_PASSWORD -d \
-v "$(pwd)"/mariadb-data:/var/lib/mysql \
--mount type=bind,source="$CNREADER_HOME"/data,target=/cndata \
--mount type=bind,source="$CNREADER_HOME"/index,target=/cnindex \
mariadb:10
The data in the database is persistent even if the container is deleted. To
restart the database use the command
docker restart mariadb
To load data from other sources connect to the database container
or start up a mysql-client
docker exec -it mariadb bash
In the container command line
mysql --local-infile=1 -h localhost -u root -p
Load dictionary data into the database
The first time you run this execute the commands in first_time_setup.sql.
Create the table definitions
source cndata/chinesenotes.ddl
are in the index
directory.
Load the data into the database
use cnotest_test;
LOAD DATA LOCAL INFILE 'cndata/grammar.txt' INTO TABLE grammar CHARACTER SET utf8mb4 LINES TERMINATED BY '\n';
LOAD DATA LOCAL INFILE 'cndata/topics.txt' INTO TABLE topics CHARACTER SET utf8mb4 LINES TERMINATED BY '\n';
LOAD DATA LOCAL INFILE 'cndata/words.txt' INTO TABLE words CHARACTER SET utf8mb4 LINES TERMINATED BY '\n' IGNORE 1 LINES;
LOAD DATA LOCAL INFILE 'cnindex/tmindex_uni_domain.tsv' INTO TABLE tmindex_uni_domain CHARACTER SET utf8mb4 LINES TERMINATED BY '\n';
LOAD DATA LOCAL INFILE 'cnindex/tmindex_unigram.tsv' INTO TABLE tmindex_unigram CHARACTER SET utf8mb4 LINES TERMINATED BY '\n';
Quit from the Maria DB client session
quit
Run against a databsae
Restart the web application server.
export DBUSER=app_user
export DBPASSWORD="[your password]"
export DATABASE=cnotest_test
export DBHOST=localhost
./chinesenotes-go
From the command line in a new shell you should be able to do a query like
curl http://localhost:8080/find/?query=antiquity
You should see JSON returned.
Updating the dictionary
If you add more words to the dictionary, you can update it with the SQ commands:
use cnotest_test;
DELETE FROM words;
Restart the web application.
Deploy to Cloud Run with a Cloud SQL databsae
The steps here describe how to deploy and run on Google Cloud with Cloud Run,
Cloud SQL, and Cloud Storage. This assumes that you have a Google Cloud project.
Set up a Cloud SQL Database
New: Replacing management of the Mariadb database in a Kubernetes cluster
Follow instructions in
Cloud SQL Quickstart
using the Cloud Console.
Create a Cloud SQL instance with the Cloud Console user interface. Then log into
it in the Cloud Shell with the command
DB_INSTANCE=[your instance]
gcloud sql connect $DB_INSTANCE --user=root
In the MySQL client create a database and add an app user with the commands in
data/firt_time_setup.sql. Create the tables with the commands in
chinesenotes.ddl, and add test data as needed. You can clone this Git project
to get the same data files.
Cloud Storage
If you are using full text search, create a GCS bucket and copy your corpus
files to it. You the environment variable TEXT_BUCKET inform the web app of
the bucket name.
TEXT_BUCKET=[Your GCS bucket name]
gsutil mb gs://$TEXT_BUCKET
gsutil -m rsync -d -r corpus gs://$TEXT_BUCKET
Cloud Run
Use
Cloud Build
to build the Docker image and upload it to the Google Container Registry:
export PROJECT_ID=[Your project]
BUILD_ID=r001
gcloud builds submit --config cloudbuild.yaml . \
--substitutions=_IMAGE_TAG="$BUILD_ID"
Then deploy to Cloud Run with the command
IMAGE=gcr.io/${PROJECT_ID}/cn-portal-image:${BUILD_ID}
SERVICE=cn-portal
REGION=us-central1
INSTANCE_CONNECTION_NAME=[Your connection]
DBUSER=[Your database user]
DBPASSWORD=[Your database password]
DATABASE=[Your database name]
MEMORY=400Mi
TEXT_BUCKET=[Your GCS bucket name for text files]
CNWEB_HOME=.
gcloud run deploy --platform=managed $SERVICE \
--image $IMAGE \
--region=$REGION \
--memory="$MEMORY" \
--add-cloudsql-instances $INSTANCE_CONNECTION_NAME \
--set-env-vars INSTANCE_CONNECTION_NAME="$INSTANCE_CONNECTION_NAME" \
--set-env-vars DBUSER="$DBUSER" \
--set-env-vars DBPASSWORD="$DBPASSWORD" \
--set-env-vars DATABASE="$DATABASE" \
--set-env-vars TEXT_BUCKET="$TEXT_BUCKET" \
--set-env-vars CNWEB_HOME="/" \
--set-env-vars CNREADER_HOME="/"
Password protecting the web app
To set up the translation portal with password protection, first configure
the database:
docker exec -it mariadb bash
In the container command line
mysql --local-infile=1 -h localhost -u root -p
In the mysql client give the app runtime permission to update and add an admin
user
USE mysql;
GRANT SELECT, INSERT, UPDATE ON cnotest_test.* TO 'app_user'@'%';
use cnotest_test;
INSERT INTO
user (UserID, UserName, Email, FullName, Role, PasswordNeedsReset, Organization, Position, Location)
VALUES (1, 'admin', "admin@email.com", "Privileged User", "admin", 0, "Test", "Developer", "Home");
INSERT INTO passwd (UserID, Password)
VALUES (1, '[your hashed password]');
Note that the password needs to be SHA-256 hashed before inserting. If the user
forgets their password, there is a password recovery function, which requires
setup of a SendGrid account and generation of an
API, which is stored in the env variable SENDGRID_API_KEY.
Set the environment variable PROTECTED, the SITEDOMAIN variable for cookies:
export PROTECTED=true
export SITEDOMAIN=localhost
./chinesenotes-go
Note that you need to have HTTPS enabled for cookies to be sent with most
browsers. You can create a self-signed certificate, run locally without one,
or deploy to a managed service like Cloud Run.
For deployment to Cloud Run use the command
PROTECTED=true
SITEDOMAIN=[your domain]
IMAGE=gcr.io/${PROJECT_ID}/cn-portal-image:${BUILD_ID}
SERVICE=cn-portal
REGION=us-central1
INSTANCE_CONNECTION_NAME=[Your connection]
DBUSER=[Your database user]
DBPASSWORD=[Your database password]
DATABASE=[Your database name]
MEMORY=400Mi
TEXT_BUCKET=[Your GCS bucket name for text files]
CNWEB_HOME=.
SENDGRID_API_KEY=[Your API key]
gcloud run deploy --platform=managed $SERVICE \
--image $IMAGE \
--region=$REGION \
--memory="$MEMORY" \
--allow-unauthenticated \
--add-cloudsql-instances $INSTANCE_CONNECTION_NAME \
--set-env-vars INSTANCE_CONNECTION_NAME="$INSTANCE_CONNECTION_NAME" \
--set-env-vars DBUSER="$DBUSER" \
--set-env-vars DBPASSWORD="$DBPASSWORD" \
--set-env-vars DATABASE="$DATABASE" \
--set-env-vars TEXT_BUCKET="$TEXT_BUCKET" \
--set-env-vars CNWEB_HOME="/" \
--set-env-vars CNREADER_HOME="/" \
--set-env-vars PROTECTED="$PROTECTED" \
--set-env-vars SITEDOMAIN="$SITEDOMAIN" \
--set-env-vars SENDGRID_API_KEY="$SENDGRID_API_KEY"
You will need to add the users manually using SQL statements. There is no
user interface to add users yet.
For additional customization you can change the title of the portal with the
Title
variable in the webconfig.yaml file, edit the styles.css
sheet, or
edit the templates under the /templates directory.
For the even more customization, just use the portal server JSON API to driver
a JavaScript client.
Corpus content and full text search
Full text search requires an forward and reverse indexes: The forward index
is like a table of contents describing the titles and files of the text
documents. There is a three level structure:
corpus
-- collection
-- document
This gives a way of organizing a corpus of documents in a book library like
structure with, say, one book per collection, one chapter per document. The
structure also provides a way to construct links for users to navigate search
results.
The reverse index is based on unigrams and bigrams with a BM25 formula to give
the most relevant documents for a given text search.
To generate the reverse index install the cnreader
command
line tool
https://github.com/alexamies/chinesenotes.com/tree/master/go/src/cnreader
Run the command with no flags
mkdir -p web/example_collection/
mkdir -p web/analysis/example_collection
export CNREADER_HOME=.
go run github.com/alexamies/cnreader
This will write the full text index files into the index
directory and
marked up HTML files in the example_collection
directory. Add a link in the
library.html
template to the page /web/texts.html
. After starting the web
server again you should be able to navigate to the list of texts and see
Chinese words marked up with English equivalents on mouseover. You can change
the config.yaml VocabFormat
variable to create other markup options, including
hyperlinks to dictionary pages and dialog boxes.
For full text search, you will need to load the document indexes into the
database. There are sample forward index files in the data/corpus
directory
which can be used for testing. Load them all into the databsae with the SQL
commands
use [your database];
LOAD DATA LOCAL INFILE 'cndata/corpus/collections.csv' INTO TABLE collection CHARACTER SET utf8mb4 LINES TERMINATED BY '\n' IGNORE 1 LINES;
LOAD DATA LOCAL INFILE 'cndata/corpus/example_collection.tsv' INTO TABLE document CHARACTER SET utf8mb4 LINES TERMINATED BY '\n' IGNORE 1 LINES;;
LOAD DATA LOCAL INFILE 'cnindex/word_freq_doc.txt' INTO TABLE word_freq_doc CHARACTER SET utf8mb4 LINES TERMINATED BY '\n';
LOAD DATA LOCAL INFILE 'cnindex/bigram_freq_doc.txt' INTO TABLE bigram_freq_doc CHARACTER SET utf8mb4 LINES TERMINATED BY '\n';
If the site is password protected then copy the generated HTML files to the
translation_portal
directory. If the site is open then copy the HTML files
to GCS with a load balancer in front, as per the instructions at
https://github.com/alexamies/chinesenotes.com
Copy the plain text files to the GCS text directory with environment variable
TEXT_BUCKET
.
Start up the web app again and view the pages:
./chinesenotes-go
Copy the text files to an object store. The only one currently supported is
Google Cloud Storage (GCS):
TEXT_BUCKET={your txt bucket}
# First time
gsutil mb gs://$TEXT_BUCKET
gsutil -m rsync -d -r corpus gs://$TEXT_BUCKET
If you are using Cloud Run then the application automatically has access to GCS.
To enable the web application to access the storage system for other platforms,
create a service account with a GCS Storage Object Admin role and download the
JSON credentials file, as described in
Create service account credentials.
Assuming that you saved the file in the current working directory as
credentials.json, create a local environment variable for local testing
export GOOGLE_APPLICATION_CREDENTIALS=$PWD/credentials.json
Containerize the app and run locally against a databsae
If you are not using Google Cloud, you can follow these instructions to
build the Docker image for the Go application and run locally:
sudo docker build -t cn-portal-image .
Run it locally with minimal features (C-E dictionary lookp only) enabled
sudo docker run -it --rm -p 8080:8080 --name cn-portal \
-e CNWEB_HOME=$CNWEB_HOME \
cn-portal-image
Browse to the URL http://localhost:8080
Test basic lookup with curl
curl http://localhost:8080/find/?query=你好
Set up the database as per the instructions at
https://github.com/alexamies/chinesenotes.com Then you will be able to run
it locally with all features enabled
DBUSER=app_user
DBPASSWORD="***"
DATABASE=cnotest_test
docker run -itd --rm -p 8080:8080 --name cn-app --link mariadb \
-e DBHOST=mariadb \
-e DBUSER=$DBUSER \
-e DBPASSWORD=$DBPASSWORD \
-e DATABASE=$DATABASE \
-e SENDGRID_API_KEY="$SENDGRID_API_KEY" \
-e GOOGLE_APPLICATION_CREDENTIALS=/cnotes/credentials.json \
-e TEXT_BUCKET="$TEXT_BUCKET" \
--mount type=bind,source="$(pwd)",target=/cnotes \
cn-app-image
Test it
curl http://localhost:8080/find/?query=hello
English queries require a database connection. If everything is working ok, you
should see results like 您好, 哈嘍 and other variations of hello in Chinese.
Debug
docker exec -it cn-app bash
Stop it
docker stop cn-app
Push to Google Container Registry
docker tag cn-app-image gcr.io/$PROJECT/cn-app-image:$BUILD_ID
docker push gcr.io/$PROJECT/cn-app-image:$BUILD_ID
Go module for Chinese text processing
This GitHub project is a Go module. You can install it with the instructions at
the Go module reference, which just involves
importing the APIs and using them. It tries to fail gracefully if you do not
have a database setup and do what it can loading from text files. The API doc
is given at
https://pkg.go.dev/mod/github.com/alexamies/chinesenotes-go
Try the example below.
package main
import (
"context"
"fmt"
"github.com/alexamies/chinesenotes-go/dictionary"
"github.com/alexamies/chinesenotes-go/tokenizer"
)
func main() {
ctx := context.Background()
// Works even if you do not have a database
database, err := dictionary.InitDBCon()
if err != nil {
fmt.Printf("unable to connect to database: \n%v\n", err)
}
wdict, err := dictionary.LoadDict(ctx, database)
if err != nil {
fmt.Printf("unable to load dictionary: \n%v", err)
return
}
tokenizer := tokenizer.DictTokenizer{wdict}
tokens := tokenizer.Tokenize("戰國時代七雄")
for _, token := range tokens {
fmt.Printf("token: %s\n", token.Token)
}
}
Testing
Run unit tests with the command
go test ./... -cover
Run an integration test with the command
go test -integration ./... -cover