This is a submission for the GitHub Copilot CLI Challenge
What I Built
I built Document Localization Studio — a terminal-first + UI-powered app that localizes documents beyond basic translation.
Instead of treating localization as “just translate text,” this project tackles the real-world complexity teams hit in enterprise docs:
- 🌐 Language + terminology adaptation (custom glossary + reusable term memory)
- 🗓️ Date/time + timezone conversion (e.g., America/New_York → Europe/Berlin)
- 💱 Currency + FX conversion (USD → EUR/JPY/BRL/… with locale defaults you can edit)
- 📏 Unit conversion (mi→km, lb→kg, °F→°C)
- 📬 Address/phone/postal tweaks (locale labels + phone formatting)
- 🧾 Tax label adaptation (Sales Tax → VAT/GST-style labels)
- 🔒 Legal clause lock/protection (
[[LOCK]]...[[/LOCK]]+ auto-protect legal-ish sentences) - ✅ Structure-aware QA (placeholders preserved, length-change warnings, cross-ref/TOC flags, workflow gating)
Supported file types 🧩
.txt.docx-
.pdf- layout-preserving mode for editable PDFs (when available)
- screenshots/images:
.png,.jpg,.jpegvia OCR
Supported locales 🗺️
de_de, es_es, fr_fr, it_it, ja_jp, ko_kr, pt_br, zh_cn, zh_tw
Run locally 🧪
cd "/Users/swatigoyal/Documents/New project/document_localizer_challenge"
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
streamlit run app.py
CLI example 🧰
python -m localizer.cli input.pdf output.pdf \ --locale de_de \ --source-timezone America/New_York \ --tone legal
Demo
- Repo: https://github.com/swatigoyal911/document_localizer_challenge
- Live demo: https://youtu.be/yX4bfBfwlMk
Walkthrough idea (video/screenshots) 🎬
- Upload a real invoice/contract PDF (or a DOCX).
- Pick a target locale (ex:
de_de) and watch the default FX rate auto-load (editable). - Toggle components (units, tax labels, legal lock, term memory).
- Run localization.
- Show the outputs:
- 📊 Before/After scorecards
- 🔎 Side-by-side visual diff
- 🌡️ Layout risk heatmap
- 🧾 QA report (JSON)
- Download the localized file + QA report.
Stack / Libraries 🧱🐍
Built with a “free stack”:
-
streamlit(UI dashboard) -
python-docx(DOCX read/write) -
pypdf(PDF text extraction) -
pymupdf(PyMuPDF — layout-preserving PDF localization mode) -
reportlab(PDF re-render fallback when layout mode isn’t available) -
pillow+pytesseract(OCR pipeline for screenshots/images)
OCR note: screenshot localization requires a local Tesseract binary in addition to
pytesseract(ex: macOSbrew install tesseract).
My Experience with GitHub Copilot CLI 🤝⚡
I used GitHub Copilot CLI as a coding partner directly in the terminal to:
- 🏗️ scaffold modules quickly (pipeline, PDF/DOCX/image IO, CLI wiring)
- 🧠 iterate on regex-heavy transformations (dates, currency, units, placeholders)
- 🧩 design locale profiles/defaults and keep the logic consistent
- 🎛️ wire Streamlit controls to the backend config without breaking flow
- 🧪 add QA heuristics + sensible fallback paths for PDFs/OCR
- 🧹 speed up refactors while keeping the project clean and extensible
The biggest win: fast iteration on non-trivial logic (PDF handling + transformation rules + feature toggles) without leaving the terminal.
What’s Next / Improvements 🚀🤖
This is a strong prototype — and there’s a lot we can level-up with AI integration later:
- 🧠 LLM-backed translation (while keeping deterministic transforms + locks)
- 📚 smarter terminology alignment (context-aware term choice + consistency scoring)
- 🧾 stronger compliance checks (policy packs per industry/locale)
- 🧩 plug-in architecture for new transforms + QA rules
- 🖼️ better OCR layout reconstruction (tables, columns, headers/footers)
If you’ve worked on localization, I’d love your feedback: what transformations or QA checks would you trust most in production?




Top comments (15)
This is a really interesting take on localization — especially the focus on going beyond translation into structural and contextual adaptation. Handling things like units, currency, legal clauses, and QA checks makes this feel much closer to a real production workflow than a simple translation tool.
I also like the “terminal-first + UI-powered” approach — it feels practical for developers while still being accessible to non-technical users.
One thing I’m curious about is how you see AI-based translation fitting into this pipeline long-term — as the primary engine, or more as an assistive layer alongside deterministic transformations and glossary enforcement?
Projects like this highlight how localization is really a data-consistency and context-preservation problem, not just a language problem. Great prototype and direction!
Thank you Sagar
This highlights how localization is really about preserving meaning and context across regions, not just converting words. The structured pipeline approach makes a lot of sense for real-world documents. Interesting approach to document localization. Do you see this evolving into something like CI/CD for multilingual documentation, where localization checks run automatically during releases?
Thank you Deepak
Impressive work 👏
Document Localization Studio goes far beyond basic translation by handling terminology, legal locks, FX/unit conversion, and structure-aware QA — that’s real enterprise-level thinking. Clean execution, strong feature depth, and great use of GitHub Copilot CLI for rapid iteration. 🚀
Thank you Savita
Hmm, interesting
I've subscribed for updates
Thank you Alex
Impressive!!
Thank you Annu
I like how this frames localization as a workflow problem rather than just a translation problem. Tools that combine automation, QA, and usability could really simplify global document management.
Thank you Gaurav
Wow, that’s a great set of functionalities you’ve provided — really well thought out and comprehensive! 👏
Nice project - I like how you're treating localisation as a structured workflow instead of just translation and how you used github copilot cli to achieve it.
Thank You Vikas