ai-agent

OpusCleaner: Streamline MT Data Prep for Faster Model Launches

Name: OpusCleaner: Streamline MT Data Prep for Faster Model Launches
Author: hplt-project

A web UI that lets founders quickly select, clean, and schedule parallel corpora, cutting data‑prep time and boosting translation model quality.

From the repo · “OpusCleaner is a web interface that helps you select, clean and schedule your data for training machine translation models.”

58 stars16 forksPythonGuide quality 8/10 · reviewed Oct 11Updated 2/3/2026100% free · open source

What it does

OpusCleaner is a web interface that helps you select, clean, and schedule your data for training machine translation models.

When to use it

•You need to preprocess large datasets for machine translation models
•Your data contains noise or inconsistent formatting that affects model performance
•You want to automate the data cleaning and scheduling process for your machine translation workflow

Ready-to-paste prompt

To clean a dataset named 'example.csv', use the following command in the OpusCleaner web interface: `opuscleaner clean example.csv --output cleaned_example.csv`

Heads up: Make sure you have Docker and Docker Compose installed on your system, as OpusCleaner relies on these to run the web interface and process data

Saves to your device

Use with Claude

New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

✅ Light setup

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install

Claude Code

mkdir -p ~/.claude/skills/opuscleaner && curl -fsSL https://workflowstacks.com/api/skills/opuscleaner/claude-skill -o ~/.claude/skills/opuscleaner/SKILL.md

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How OpusCleaner: Streamline MT Data Prep for Faster Model Launches works

Codeflow

Free to inspect

OpusCleaner: Streamline MT Data Prep for Faster Model Launches is a medium Python project (~8.8k lines across 91 code files, plus 2 test files). Setup is light: runs with Docker. Last commit 9 months ago, no license file, has a test suite.

Size

Medium codebase

~8.8k lines · 91 code files · ~1 h to skim

Setup

Light setup

Runs with Docker.

Runs on

Python · Docker

No API keys detected

Python 71%Vue 17%JavaScript 7%Perl 4%

Where to start reading

1
README.md
Start here — what it does and how to install it
2
opuscleaner/server.py
Where the program starts running
3
pyproject.toml
Dependencies and the commands it exposes
4
opuscleaner/__init__.py
Inside opuscleaner/ — the main logic begins here

What's in each folder

opuscleaner/Core code — the actual logic94 files

frontend/Frontend / UI48 files

placeholders/Folder7 files

utils/Helper scripts5 files

.github/CI / automation (GitHub Actions)6 files

test/Tests — proof it works5 files

.vscode/Editor / agent settings1 files

READMEHas testsDocumentedCI checksDocker readyNo licenseLast update 9 mo ago

Use with Claude

New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

✅ Light setup

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install

Claude Code

mkdir -p ~/.claude/skills/opuscleaner && curl -fsSL https://workflowstacks.com/api/skills/opuscleaner/claude-skill -o ~/.claude/skills/opuscleaner/SKILL.md

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

Quick Actions

Details

Creator

hplt-project

Language

Python