https://github.com/czcorpus/wag
WaG - install your own word profile generator out of diverse data resources
https://github.com/czcorpus/wag
corpora data-aggregation dictionaries language-resources linguistics portal react rxjs typescript visualization
Last synced: about 2 months ago
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WaG - install your own word profile generator out of diverse data resources
- Host: GitHub
- URL: https://github.com/czcorpus/wag
- Owner: czcorpus
- License: apache-2.0
- Created: 2018-10-19T10:23:15.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2026-01-21T23:44:27.000Z (2 months ago)
- Last Synced: 2026-01-22T04:10:26.371Z (2 months ago)
- Topics: corpora, data-aggregation, dictionaries, language-resources, linguistics, portal, react, rxjs, typescript, visualization
- Language: TypeScript
- Homepage:
- Size: 13.9 MB
- Stars: 9
- Watchers: 4
- Forks: 2
- Open Issues: 34
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Word at a Glance (WaG) v2
WaG is a highly configurable frontend for creating word profile portals based on corpus resources compatible with the Manatee-open search engine. It provides comprehensive visualizations of linguistic data through seamless integration with our API services.
## Table of Contents
- [Core Components](#core-components)
- [Features](#features)
- [Getting Started with Docker](#getting-started-with-docker)
- [Prerequisites](#prerequisites)
- [Quick Start (Production)](#quick-start-production)
- [Development Setup](#development-setup)
- [Available Services](#available-services)
- [Docker Architecture](#docker-architecture)
- [How to cite WaG](#how-to-cite-wag)
## Core Components
WaG integrates with the following backend services:
* **[MQuery](https://github.com/czcorpus/mquery)** - General corpora analysis including concordances, frequency distributions, and collocations
* **[Frodo](https://github.com/czcorpus/frodo)** - Corpus-driven dictionaries
* **[WSServer](https://github.com/czcorpus/wsserver)** - Syntax-based collocations and word similarities
WaG operates in conjunction with [APIGuard](https://github.com/czcorpus/apiguard), our specialized HTTP API proxy and virtual API endpoint provider.
## Features
With WaG, you can:
1. **Analyze linguistic data** for:
- Single words
- Comparative analysis of two or more words
- Word translations
2. **Explore comprehensive linguistics insights** including:
- Text statistics
- Time-based trends
- Collocations
- Geographical data
- And much more
3. **Combine data from multiple resources** for enriched analysis
## Getting Started with Docker
The easiest way to run WaG is using Docker Compose, which sets up all required services including WaG, APIGuard, MQuery, Frodo, Redis, MariaDB, and Nginx.
### Prerequisites
- Docker
- Docker Compose
### Quick Start (Production)
1. **Configure environment** (optional):
The project includes a [.env](.env) file with working defaults that point to example configurations in [install/docker/](install/docker/). You can use it as-is or customize the paths if needed:
```bash
WAG_CONFIG_PATH=./install/docker/conf
APIGUARD_CONF=./install/docker/apiguard.json
MQUERY_CONF=./install/docker/mquery.json
FRODO_CONF=./install/docker/frodo.json
CORPORA_CONF=./install/docker/corpora
VERT_TAGEXTRACT_CONF=./install/docker/vert-tagextract
```
2. **Start all services:**
```bash
docker compose up -d
```
3. **Access WaG** at `http://localhost:8080`
### Development Setup
For development with hot-reloading:
1. **Configure environment** (optional):
For development, you'll need to specify paths to local checkouts of the backend services. Add these to your [.env](.env) file:
```bash
APIGUARD_PATH=/path/to/apiguard
MQUERY_PATH=/path/to/mquery
FRODO_PATH=/path/to/frodo
```
The other variables from the production setup are reused.
2. **Start development environment:**
```bash
docker compose -f docker-compose.dev.yml up
```
3. **Access WaG** at `http://localhost:8080` (frontend dev server at `http://localhost:9001`)
### Available Services
The Docker setup includes:
- **WaG** (main application)
- **APIGuard** (`localhost:8081`) - API proxy
- **MQuery** (`localhost:8082`) - Corpus analysis
- **Frodo** (`localhost:8083`) - Dictionary services
- **Nginx** (`localhost:8080`) - Web server
- **Redis** - Caching
- **MariaDB** - Database
### Docker Architecture
The project uses custom Dockerfiles located in the [dockerfiles/](dockerfiles/) directory:
- `Dockerfile.wag` - Production WaG build
- `Dockerfile.wag.dev` - Development build with hot-reloading
- `Dockerfile.apiguard`, `Dockerfile.mquery`, `Dockerfile.frodo` - Backend services
## How to cite WaG
Tomáš Machálek (2020): Word at a Glance: Modular Word Profile Aggregator. In: [Proceedings of LREC 2020](http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.866.pdf), s. 7011–7016.
```bibtex
@InProceedings{machalek2020lrec,
author = {Tomáš Machálek},
title = "{Word at a Glance: Modular Word Profile Aggregator.}",
booktitle = {Proceedings of the Twelfth International Conference on Language Resources and Evaluation (LREC 2020)},
year = {2020},
publisher = {European Language Resources Association (ELRA)},
language = {english}
}
```