TBL - Translate Books with LLMs

A desktop app that translates books, subtitles, and documents with AI - local or cloud. Drop a file, pick a language, get the result.

Formats: EPUB, SRT, DOCX, TXT

• No size limit. Process documents of any length - from a single page to thousand-page novels. The intelligent chunking system handles unlimited content while preserving context between segments.
• Perfect preservation. Your documents come out exactly as they went in: EPUB formatting, styles, and structure remain intact. SRT timecodes stay perfectly synchronized. Every tag, every timestamp, every formatting detail is preserved.
• Resume anytime. Interrupted translation? Pick up exactly where you left off. The checkpoint system saves progress automatically.

Translation Quality Benchmarks - Find the best model for your target language.

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Quick Start

1. Download the release for your platform (buttons above), or grab it from the releases page.
2. Extract the archive.
3. Run TranslateBook.exe (Windows) or ./TranslateBook (macOS).
4. Open http://localhost:5000 in your browser.

That's it. On first launch, you choose a translation provider:

• Free & local - Install Ollama and pull a model (e.g. ollama pull qwen3:14b). Nothing leaves your machine.
• Cloud (often free tier available) - Paste an API key from one of the providers below.

Note: First run creates a TranslateBook_Data folder with your settings.

macOS: On first launch, go to System Settings > Privacy & Security and click Open Anyway.

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Providers

                    

Provider	Type	Get started
Ollama	Local	ollama.com
Poe ⭐	Cloud (Recommended - easy setup, multiple models)	poe.com/api_key
OpenAI-Compatible	Local (llama.cpp, LM Studio, vLLM, LocalAI...)	Point to your server's endpoint
OpenRouter	Cloud (200+ models)	openrouter.ai/keys
OpenAI	Cloud	platform.openai.com
Mistral	Cloud	console.mistral.ai
DeepSeek	Cloud	platform.deepseek.com
Gemini	Cloud	Google AI Studio
NVIDIA NIM	Cloud	build.nvidia.com

See docs/PROVIDERS.md for detailed setup instructions.

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Troubleshooting

Problem	Solution
Ollama won't connect	Check Ollama is running, test curl http://localhost:11434/api/tags
Model not found	Run ollama list, then ollama pull model-name

See docs/TROUBLESHOOTING.md for more solutions.

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Advanced

Install from source

Prerequisites: Python 3.8+, Ollama, Git

git clone https://github.com/hydropix/TranslateBooksWithLLMs.git
cd TranslateBookWithLLM
ollama pull qwen3:14b    # Download a model

# Windows
start.bat

# Mac/Linux
chmod +x start.sh && ./start.sh

The web interface opens at http://localhost:5000.

Command line

# Basic (auto-generates "book (Chinese).epub")
python translate.py -i book.epub -sl English -tl Chinese

# With OpenRouter
python translate.py -i book.txt --provider openrouter \
    --openrouter_api_key YOUR_KEY -m anthropic/claude-sonnet-4 -tl French

# With OpenAI
python translate.py -i book.txt --provider openai \
    --openai_api_key YOUR_KEY -m gpt-4o -tl French

# With Gemini
python translate.py -i book.txt --provider gemini \
    --gemini_api_key YOUR_KEY -m gemini-2.0-flash -tl French

# With Mistral
python translate.py -i book.txt --provider mistral \
    --mistral_api_key YOUR_KEY -m mistral-large-latest -tl French

# With DeepSeek
python translate.py -i book.txt --provider deepseek \
    --deepseek_api_key YOUR_KEY -m deepseek-v4-pro -tl French

# With Poe
python translate.py -i book.txt --provider poe \
    --poe_api_key YOUR_KEY -m Claude-Sonnet-4 -tl French

# With NVIDIA NIM
python translate.py -i book.txt --provider nim \
    --nim_api_key YOUR_KEY -m meta/llama-3.1-8b-instruct -tl French

# With local OpenAI-compatible server (llama.cpp, LM Studio, vLLM, etc.)
python translate.py -i book.txt --provider openai \
    --api_endpoint http://localhost:8080/v1/chat/completions -m your-model -tl French

Main options

Option	Description	Default
-i, --input	Input file	Required
-o, --output	Output file	Auto: {name} ({lang}).{ext}
-sl, --source_lang	Source language	English
-tl, --target_lang	Target language	Chinese
-m, --model	Model name	qwen3:14b
--provider	ollama/openrouter/openai/gemini/mistral/deepseek/poe/nim	ollama
--text-cleanup	OCR/typographic cleanup	disabled
--refine	Second pass for literary polish	disabled
--tts	Generate audio (Edge-TTS)	disabled

See docs/CLI.md for all options (TTS voices, rates, formats, etc.).

Configuration (.env)

Copy .env.example to .env and edit:

# Provider
LLM_PROVIDER=ollama

# Ollama
API_ENDPOINT=http://localhost:11434/api/generate
DEFAULT_MODEL=qwen3:14b

# API Keys (if using cloud providers)
OPENROUTER_API_KEY=sk-or-v1-...
OPENAI_API_KEY=sk-...
GEMINI_API_KEY=...
MISTRAL_API_KEY=...
DEEPSEEK_API_KEY=...
POE_API_KEY=...
NIM_API_KEY=...

# Performance
REQUEST_TIMEOUT=900
MAX_TOKENS_PER_CHUNK=450  # Token-based chunking (default: 450 tokens)

Multiple API keys? Any *_API_KEY variable accepts a comma-separated list (e.g. GEMINI_API_KEY=key1,key2,key3). The system rotates between keys automatically when one hits a rate limit - useful to chain free-tier accounts. See docs/API_KEY_ROTATION.md.

Long jobs? Get a push notification on your phone (via ntfy), Discord, Slack, gotify, or any HTTP endpoint when a translation finishes. Set NOTIFY_WEBHOOK_URL in .env. See docs/NOTIFICATIONS.md.

Docker

docker build -t translatebook .
docker run -p 5000:5000 -v $(pwd)/translated_files:/app/translated_files translatebook

See docs/DOCKER.md for more options.

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Documentation

Guide	Description
docs/PROVIDERS.md	Detailed provider setup (Ollama, LM Studio, OpenRouter, OpenAI, Gemini)
docs/API_KEY_ROTATION.md	Use multiple API keys per provider with automatic failover on rate-limit
docs/NOTIFICATIONS.md	Webhook notifications on completion (ntfy, gotify, Discord, Slack, custom)
docs/GLOSSARY.md	Force consistent term translations across a book (Web UI + CLI, auto-extract via NER)
docs/CLI.md	Complete CLI reference
docs/TROUBLESHOOTING.md	Problem solutions
docs/DOCKER.md	Docker deployment guide

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License: AGPL-3.0