DeepTrans Studio is an enterprise-grade translation platform that combines AI-powered translation, localization engineering, and team collaboration capabilities. Built for professional translators and localization teams, it provides comprehensive end-to-end translation workflow management.
DeepTrans Studio User Interface
- Intelligent Editor: Segment-aligned parallel editing with version control and keyboard shortcuts
- Multi-Agent Collaboration: Coordinate multiple AI agents for complex translation tasks
- Real-time Preview: Instant document preview with formatting preservation
- Multi-Engine Support: Integration with OpenAI and custom AI models
- Terminology Extraction: Automated domain-specific term extraction
- Quality Assessment: AI-driven grammar, syntax, and discourse evaluation
- Translation Memory: Vector-based semantic search using Milvus
- Project Dictionaries: Project-specific terminology databases
- Translation Memory: Import/export translation memory in TMX, CSV, XLSX formats
- Semantic Search: Vector similarity search powered by Milvus
- Visual Management: Attu UI for vector database inspection
- Queue-Based Processing: BullMQ-driven asynchronous task processing
- Batch Operations: Bulk translation, evaluation, and quality checks
- Document Parsing: PDF, DOCX, XLSX document parsing with PDFMath service
- Status Tracking: Complete translation lifecycle management
- Open Architecture: Modular design with MinIO, Milvus, Redis integration
- API Gateway: RESTful APIs for external integration
- Custom Agents: Extensible AI agent framework
- Plugin System: Support for custom translation engines and processing pipelines
DeepTrans Studio adopts a modern full-stack architecture based on Next.js App Router with distributed queue processing:
graph TD
Browser[Web Browser] -->|HTTPS| Traefik[Traefik Proxy]
Traefik -->|HTTP 3000| Studio[Next.js Studio]
Traefik --> Attu[Attu UI]
Studio -->|Server Actions| Postgres[(PostgreSQL)]
Studio -->|Task Queue| Redis[(Redis)]
Studio -->|API Calls| PDFMath[PDFMath Service]
Worker[Worker Service] -->|Consume Tasks| Redis
Worker -->|ORM| Postgres
Worker -->|Vector Ops| Milvus[(Milvus)]
Worker -->|Object Storage| MinIO[(MinIO)]
Milvus --> etcd[(etcd)]
| Component | Technology | Purpose |
|---|---|---|
| Studio | Next.js 15, React 19, TypeScript | Frontend UI, Server Actions, Authentication |
| Worker | Node.js, BullMQ | Background job processing, batch operations |
| Database | PostgreSQL, Prisma 6 | Relational data storage and ORM |
| Cache | Redis | Session management, task queues |
| Vector DB | Milvus + etcd | Semantic search, translation memory |
| Storage | MinIO (S3-compatible) | Document and asset storage |
| Parser | PDFMath Service | PDF and mathematical document parsing |
| Gateway | Traefik | Reverse proxy, SSL/TLS termination |
- Node.js ≥ 18.18 (Recommended: use
corepackto manage Yarn 1.22.22) - Yarn (Enable via
corepack enable) - Docker & Docker Compose (For services and deployment)
- Git
# Enable corepack and setup Yarn
corepack enable
corepack prepare yarn@1.22.22 --activate
# Install dependencies
yarn installCreate .env.local file with the following configuration:
# Database & Cache
DATABASE_URL="postgresql://postgres:password@localhost:5432/deeptrans"
REDIS_URL="redis://127.0.0.1:6379"
# Authentication & Site
AUTH_SECRET="your-secret-key-here" # Generate with: openssl rand -base64 32
NEXTAUTH_URL="http://localhost:3000"
NODE_ENV=development
# AI Service Configuration
OPENAI_API_KEY="sk-xxxx"
OPENAI_BASE_URL="https://api.openai.com/v1"
OPENAI_API_MODEL="gpt-4o-mini"
# Object Storage
MINIO_ACCESS_KEY=minioadmin
MINIO_SECRET_KEY=minioadmin
MINIO_BUCKET=deeptrans
# Services
STUDIO_HOST=localhost
# Optional: GitHub OAuth, SMTP, etc.
# GITHUB_ID=your-github-oauth-id
# GITHUB_SECRET=your-github-oauth-secret💡 Security Note: For production deployments, use dedicated instances for databases and properly secure all credentials.
# Run database migrations
yarn prisma migrate deploy
# Generate Prisma Client
yarn prisma generate
# (Optional) Seed with sample data
yarn db:seedOption 1: Using Docker Compose (Recommended)
# Start all services
docker compose up -d db redis etcd milvus minio pdfmath worker
# Start Next.js development server
yarn dev
# Access the application at http://localhost:3000Option 2: Local Services
# Start Next.js dev server
yarn dev
# In another terminal, start worker
yarn dev:workerAdditional UIs:
- Studio: http://localhost:3000
- Attu (Milvus UI): http://localhost:8001
- Prisma Studio: Run
yarn prisma studio
# Configure environment
cp .env.example .env.production
# Edit .env.production with production values
# Build images
docker compose build studio worker pdfmath
# Deploy services
docker compose up -d traefik studio worker db redis milvus minio
# Services will be available on configured domain with SSL via Traefikdeeptrans-studio/
├── src/
│ ├── app/ # Next.js App Router
│ │ ├── (app)/ # Main application pages
│ │ ├── api/ # API routes (migrating to Server Actions)
│ │ └── layout.tsx # Root layout and providers
│ ├── actions/ # Server Actions (database, AI, files)
│ ├── agents/ # AI agent definitions and prompts
│ ├── components/ # Reusable UI components
│ ├── hooks/ # Custom React hooks
│ ├── lib/ # Utility functions and clients
│ ├── store/ # State management (Zustand)
│ ├── db/ # Database client and repositories
│ ├── types/ # TypeScript type definitions
│ └── worker/ # Background worker tasks
├── prisma/ # Database schema and migrations
│ ├── schema.prisma # Prisma schema definition
│ └── migrations/ # Database migration files
├── scripts/ # Development and utility scripts
├── public/ # Static assets
├── docker-compose.yml # Docker services orchestration
├── Dockerfile # Container image definition
└── package.json # Project dependencies
| Command | Description |
|---|---|
yarn dev |
Start Next.js development server with hot reload |
yarn dev:worker |
Start worker service locally (if not using Docker) |
yarn build |
Build production Next.js application |
yarn build:worker |
Compile worker service (esbuild → dist/worker.cjs) |
yarn start |
Start production Next.js server |
yarn lint |
Run ESLint code quality checks |
yarn type-check |
Run TypeScript type checking |
yarn prisma studio |
Open Prisma Studio database GUI |
yarn prisma generate |
Generate Prisma Client |
yarn db:push |
Push schema changes to database |
yarn db:seed |
Seed database with sample data |
yarn test:segment |
Test segmentation parsing |
yarn test:docx |
Test document parsing |
yarn queue:ui |
Launch Bull Board queue monitoring |
DeepTrans Studio uses next-intl for internationalization:
- Translation files:
src/i18n/en.json,src/i18n/zh.json - Usage:
useTranslations('namespace')hook - Supported languages: English, Chinese (extendable)
When adding new translations, ensure all language files are updated consistently.
We welcome contributions! Please follow these guidelines:
feat/*- New featuresfix/*- Bug fixeschore/*- Maintenance tasksdocs/*- Documentation updates
- Fork & Clone: Fork the repository and clone your fork
- Create Branch: Create a feature branch from
main - Code Changes: Make your changes following our coding standards
- Quality Checks: Run linting and type checking
yarn lint yarn type-check
- Commit: Use Conventional Commits format
feat: add translation memory import fix: resolve authentication bug docs: update installation guide - Pull Request: Submit PR with clear description
- Follow ESLint and Prettier configurations
- Write TypeScript with proper types (avoid
any) - Add JSDoc comments for complex functions
- Write unit tests for new features
- Update documentation as needed
This project is licensed under the MIT License - see the LICENSE file for details.
Built with modern technologies:
- Next.js - React framework
- Prisma - Database ORM
- Milvus - Vector database
- BullMQ - Job queues
- MinIO - Object storage
- Traefik - Reverse proxy
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Documentation: Check the
/docsfolder for detailed guides
Made with ❤️ for professional translators and localization teams
⭐ Star us on GitHub if you find this project useful!