Logion 2

A professional AI-powered Computer-Assisted Translation (CAT) tool built with FastAPI and React. Logion 2 combines Translation Memory, Glossary Management, and RAG-based context retrieval with LLM-powered translation workflows.

Features

• Multi-file project management — DOCX, XLIFF, TMX, RTF, PDF support
• AI Translation Workflows — Pre-analysis, batch translation, sequential translation, optimization
• Translation Memory (TM) — Automatic TM with semantic search via Voyage AI embeddings
• Glossary Management — Manual and AI-extracted glossaries with auto-enforcement
• RAG Context — Legal, background, and reference documents enrich translations
• Track Changes — DOCX revision tracking preserved through translation
• Inline Editing — Tiptap-based rich text editor with XML tag preservation
• Backup System — Automatic project backups with configurable intervals

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Prerequisites

Dependency	Version	Notes
Python	3.13+	Backend runtime
Node.js	18+	Frontend build (22+ recommended)
PostgreSQL	15+	Primary database
pip	latest	Python package manager

Installing Prerequisites

macOS (using Homebrew):

brew install python@3.13 node postgresql@15
brew services start postgresql@15

Windows:

1. Python: Download from python.org. During installation, check "Add Python to PATH".
2. Node.js: Download LTS from nodejs.org.
3. PostgreSQL: Download from postgresql.org. The installer includes pgAdmin. Remember the password you set for the postgres user.

Linux (Ubuntu/Debian):

sudo apt update
sudo apt install python3.13 python3.13-venv nodejs npm postgresql postgresql-contrib
sudo systemctl start postgresql

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Database Setup

Create the database. Logion 2 will auto-create all tables on first startup.

macOS / Linux:

createdb logion2

Windows (in pgAdmin or psql):

CREATE DATABASE logion2;

If your PostgreSQL uses a different user/password than the defaults (postgres/postgres), note them for the .env file below.

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Backend Setup

1. Create and activate a virtual environment

macOS / Linux:

cd backend
python3 -m venv venv
source venv/bin/activate

Windows (Command Prompt):

cd backend
python -m venv venv
venv\Scripts\activate

Windows (PowerShell):

cd backend
python -m venv venv
.\venv\Scripts\Activate.ps1

2. Install Python dependencies

pip install -r requirements.txt

This installs FastAPI, SQLAlchemy, LangChain, Voyage AI, Google Generative AI, spaCy, sentence-transformers, and all other dependencies. The installation may take a few minutes due to PyTorch and transformer models.

3. Configure environment variables

Copy the example file and fill in your values:

# From the project root (not backend/)
cp .env.example .env

Edit .env with your settings:

# --- Database (PostgreSQL) ---
DB_HOST=localhost
DB_PORT=5432
DB_NAME=logion2
DB_USER=postgres
DB_PASS=postgres

# --- File Storage ---
# Local filesystem path for project files (source docs, TM, references).
# Default: ./projectdata (relative to backend/ directory)
# STORAGE_ROOT=./projectdata

# --- AI API Keys ---

# Google Gemini (translation, optimization, chat)
# Get yours at: https://aistudio.google.com/apikey
GOOGLE_API_KEY=your-google-api-key-here

# Anthropic Claude (translation, chat — optional, needed for Claude models)
# Get yours at: https://console.anthropic.com/
ANTHROPIC_API_KEY=your-anthropic-api-key-here

# Voyage AI (semantic embeddings & reranking — required for RAG)
# Get yours at: https://www.voyageai.com/
VOYAGE_API_KEY=your-voyage-api-key-here
VOYAGE_MODEL=voyage-3-large

Required keys:

• GOOGLE_API_KEY — needed for Gemini models (default translation engine)
• VOYAGE_API_KEY — needed for semantic search (TM, glossary, context retrieval)

Optional keys:

• ANTHROPIC_API_KEY — only needed if you want to use Claude models for translation/chat

4. Configure AI Models

The available AI models are defined in backend/ai_models.json. The default configuration includes:

Model	Provider	Purpose
Gemini 3.1 Pro Preview	Google	Translation (default)
Gemini 3 Pro Preview	Google	Translation
Gemini 3 Flash Preview	Google	Translation (fast)
Gemini 2.5 Pro	Google	Translation (stable)
Gemini 2.5 Flash	Google	Translation (fast)
Claude Opus 4.6	Anthropic	Translation (premium)
Claude Sonnet 4.6	Anthropic	Translation
Voyage 3 Large	Voyage	Embeddings
Rerank 2.5	Voyage	Reranking

To add or remove models, edit backend/ai_models.json:

{
    "models": [
        {
            "id": "gemini-2.5-flash",
            "name": "Gemini 2.5 Flash",
            "provider": "google",
            "usage": "mt",
            "context_window": 1000000,
            "input_cost_per_m": 0.3,
            "output_cost_per_m": 2.5
        }
    ]
}

Fields:

• id — API model identifier (must match the provider's model ID)
• name — Display name in the UI
• provider — "google", "anthropic", or "voyage"
• usage — "mt" (machine translation / chat) or "bg" (background / embeddings)
• context_window — Max tokens
• input_cost_per_m / output_cost_per_m — Cost per million tokens (for usage tracking)

The first model in the list is used as the default if no model is selected in project settings.

5. Start the backend

cd backend
source venv/bin/activate   # macOS/Linux
# venv\Scripts\activate    # Windows

uvicorn app.main:app --reload --port 8000

The API will be available at http://127.0.0.1:8000. Tables are created automatically on first startup.

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Frontend Setup

1. Install Node dependencies

cd frontend
npm install

2. Start the development server

npm run dev

The UI will be available at http://localhost:5173.

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Running the Application

You need two terminal windows running simultaneously:

Terminal 1 — Backend:

cd backend
source venv/bin/activate   # macOS/Linux (or venv\Scripts\activate on Windows)
uvicorn app.main:app --reload --port 8000

Terminal 2 — Frontend:

cd frontend
npm run dev

Then open http://localhost:5173 in your browser.

---

Project Structure

logion2/
├── .env                          # Environment variables (not in git)
├── .env.example                  # Template for .env
├── backend/
│   ├── ai_models.json            # AI model definitions
│   ├── requirements.txt          # Python dependencies (pip-compiled)
│   ├── requirements.in           # Top-level Python dependencies
│   ├── app/
│   │   ├── main.py               # FastAPI app, CORS, startup events
│   │   ├── config.py             # AI model config loader
│   │   ├── database.py           # PostgreSQL connection (SQLAlchemy)
│   │   ├── storage.py            # Local file storage
│   │   ├── models.py             # SQLAlchemy models
│   │   ├── routers/              # API endpoints
│   │   │   ├── project.py        # Project CRUD, workflows
│   │   │   ├── segment.py        # Segment updates, propagation
│   │   │   ├── translate.py      # AI draft generation
│   │   │   ├── glossary.py       # Glossary CRUD
│   │   │   ├── chat.py           # Segment AI chat
│   │   │   └── settings.py       # Global app settings, backups
│   │   ├── services/             # Business logic
│   │   ├── workflows/            # Background workflows (translate, optimize, reingest)
│   │   ├── rag/                  # RAG pipeline (embeddings, retrieval, assembly)
│   │   └── parsers/              # Document parsers (DOCX, XLIFF, TMX, etc.)
│   └── projectdata/              # File storage (created at runtime)
├── frontend/
│   ├── package.json
│   ├── src/
│   │   ├── App.jsx               # Root component, routing
│   │   ├── api/client.js         # API client functions
│   │   ├── components/           # React components
│   │   │   ├── SplitView.jsx     # Main translation editor
│   │   │   ├── TiptapEditor.jsx  # Rich text editor with tag support
│   │   │   ├── ProjectList.jsx   # Project dashboard
│   │   │   └── settings/         # Settings tabs (AI, RAG, Glossary, Workflows)
│   │   ├── hooks/                # Custom React hooks
│   │   └── utils/                # Utilities (tag transforms, etc.)
│   └── public/
└── backups/                      # Auto-backup directory (configurable)

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Troubleshooting

PostgreSQL connection refused

• macOS: brew services start postgresql@15
• Linux: sudo systemctl start postgresql
• Windows: Check that the PostgreSQL service is running in Services (services.msc)

pip install fails on macOS (torch / C extensions)

Make sure you have Xcode Command Line Tools:

xcode-select --install

Port 8000 already in use

# Find and kill the process
lsof -i :8000  # macOS/Linux
# or
netstat -ano | findstr :8000  # Windows

CORS errors in browser

The backend allows requests from localhost:5173, 5174, 5175, and 3000. If your frontend runs on a different port, add it to the allow_origins list in backend/app/main.py.

Empty translations / API errors

• Check that your API keys are set correctly in .env
• Verify the keys work by checking the provider's console (Google AI Studio, Anthropic Console, Voyage dashboard)
• Check the backend terminal for error messages