loctran 0.1.1b3

Local-first document translation and conversion toolkit

Loctran — private AI PDF translator

Translate PDFs locally. No cloud. No API key. Just Ollama.

Features

What it does	Why it matters
Rasterises PDFs with pypdfium2	No Poppler / Ghostscript dependency
Dual-pass OCR (Tesseract + inverted image)	Catches light-on-dark and low-contrast text
Batched LLM translation via Ollama	Works with any local chat model
HTML overlay output	Translations positioned over the original layout
Web UI with real-time progress	Upload and translate from any browser
PDF compression	Reduce file size without proprietary tools
100 % local — files never leave your machine	Full privacy, no API keys, works offline

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Screenshots

1. Home	1.1 PDF Upload

2. Translation Configured	2.1 Translation In Progress

3. Result	3.1 Translation Complete

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30-second install

pip install "loctran[ocr,server]"
ollama pull glm-ocr
ollama pull translategemma:4b
loctran
# opens Web UI at http://127.0.0.1:8000

# CLI translation example
loctran translate document.pdf --lang French

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How it works

PDF
 └─► rasterise pages (pypdfium2)
      └─► dual-pass OCR (Tesseract normal + inverted)
           └─► deduplicate & group words into segments
                └─► batch translate (Ollama LLM)
                     └─► HTML overlay output

Each page becomes an image with absolutely-positioned translation boxes sized to match the original text bounding boxes. For PDFs with a digital text layer, pdfplumber extracts text directly — no OCR needed.

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Requirements

• OS: macOS, Linux, or Windows
• Python ≥ 3.9
• Ollama running locally — download
• Tesseract — brew install tesseract tesseract-lang (macOS) or apt install tesseract-ocr tesseract-ocr-all (Linux)

Run loctran doctor to check everything at once:

loctran-doctor v0.1.1b1
─────────────────────────────────────
✓  Python         3.11.9
✓  Tesseract      5.3.4  (langs: eng fra deu jpn +47)
✓  Ollama         0.3.1  (running)
✓  glm-ocr        pulled (2.2 GB)
✓  translategemma:4b pulled (3.3 GB)
─────────────────────────────────────
All required dependencies satisfied.

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Web UI

Start the server and open your browser:

loctran serve
# → http://localhost:8000

Upload a PDF, choose a target language and model, then watch the real-time progress bar. The translated HTML opens automatically when done.

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CLI reference

Usage: loctran [OPTIONS] COMMAND [ARGS]...

Commands:
  serve      Run the local web UI server.
  translate  Translate a file or folder using local OCR + Ollama.
  doctor     Run environment diagnostics for dependencies and models.

# Translate to Spanish using a higher-quality translation model
loctran translate report.pdf --lang Spanish --model translategemma:12b

# Extract text only, save to custom folder
loctran translate scan.pdf --extract-only --output ~/Desktop/extracted

# Use smaller batches to avoid context overflow on long documents
loctran translate book.pdf --lang German --batch-size 3

# Run dependency diagnostics
loctran doctor

Updating README screenshots

pip install -e ".[dev,server]"
python -m playwright install chromium
make screenshots

This writes screenshots to docs/screenshots/ using scripts/capture_screenshots.py.

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FAQ

Does this send my documents anywhere? No. Everything runs locally on your machine. Loctran talks only to Ollama at localhost:11434. No telemetry, no analytics, no cloud.

Which Ollama models work? Any locally installed Ollama model appears in the Loctran model picker automatically. Run ollama list to see what is available. For this project, use glm-ocr for OCR and translategemma:4b for translation. On 16 GB+ machines, translategemma:12b is the higher-quality option.

What about scanned PDFs? Loctran automatically detects whether a PDF has a digital text layer. If it does, pdfplumber extracts text directly (fast, accurate). If not — or if you pass --force-ocr — Tesseract runs a dual-pass OCR (normal + inverted image) to catch light-on-dark text. Pass --use-ai-ocr to route OCR through an Ollama vision model for the highest accuracy on complex layouts.

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Docker

docker run -p 8000:8000 -v ~/Documents:/docs ghcr.io/anzalks/loctran

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Contributing

See CONTRIBUTING.md for development setup, running tests, and submitting PRs.

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License

Apache 2.0 — © 2026 Anzal K Shahul