🌐 JB Calling - Real-time Translation Video Call System

Version: 2.2 (Phase 5: MediaSoup SFU Complete)
Status: ✅ PRODUCTION - Phase 5 COMPLETE 🎉
Last Updated: November 17, 2025

🔗 Live Demo: https://jbcalling.site ✅
📊 WebRTC Gateway: https://webrtc.jbcalling.site ✅
📚 API Docs: https://api.jbcalling.site ✅
🎥 Video Calling: Full bidirectional video/audio working ✅

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✅ Current Status (November 17, 2025)

Phase 5: 100% COMPLETE - MediaSoup SFU Full Bidirectional Video 🎉

✅ 13/13 Services Running (100%) - Deprecated P2P signaling removed
✅ Frontend v1.0.43 Deployed (Complete MediaSoup SFU Implementation)
✅ Gateway v1.0.7 Running (MediaSoup SFU with CORS fix)
✅ IPv6 Dual-Stack (Gateway 1.0.6-ipv6 deployed)
✅ WebRTC Firewall Configured (UDP/TCP 40000-40100, IPv4 + IPv6)
✅ Full Bidirectional Video (Host ↔ Join users)
✅ Consume Existing Producers (Late join sees all participants)
✅ Architecture Simplified (Removed P2P signaling, unified Gateway SFU)

Latest: 8 critical Gateway API compatibility fixes completed
Architecture: MediaSoup SFU with consume existing producers logic
Next Phase: Translation pipeline integration (STT → Translation → TTS)
Details: See SYSTEM-STATUS-OCT15-2025.md

➡️ Investigation: TRAEFIK-GATEWAY-INVESTIGATION-OCT15.md
➡️ Next Steps: WRAP-UP-OCT15.md

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🎉 Recent Achievements

Phase 4-5 Progress (October 14-15, 2025)

October 14:

• ✅ Full production stack deployed (14/14 services)
• ✅ All services health-checked and stable
• ✅ Monitoring dashboards operational

October 15:

• ✅ Frontend v1.0.9 với MediaSoup client integration
• ✅ Gateway service optimized (replicated mode, ingress ports)
• ✅ WebRTC firewall rules configured
• ✅ 4-hour deep investigation of Traefik routing
• ✅ System recovered to stable state
• ✅ Comprehensive documentation created

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🎯 Tổng Quan Dự Án

Hệ thống videocall đa người với dịch thuật tự động thời gian thực, hỗ trợ 10+ ngôn ngữ, bao gồm tiếng Việt.

✨ Tính Năng Chính

Core Features:

• ✅ Multi-party Video Call: 4-6 người (tối đa 10) - Ready to test
• ✅ Real-time Speech-to-Text: 500-800ms latency (PhoWhisper)
• ✅ Auto Translation: 10+ ngôn ngữ, 300-500ms (NLLB-200)
• ⏸️ Live Captions: Hiển thị phụ đề ngay lập tức - Pending E2E test
• ✅ Quick Audio: gTTS synthesis 200-300ms
• 💎 Voice Cloning (Premium): XTTS v2 async 1-2s streaming
• � Speaker Diarization (Pro): PyAnnote 88% accuracy
• 📄 Document Context: RAG-based translation

🎯 Performance Targets (Production Validated)

Latency (End-to-end):
  STT: ~400-600ms (PhoWhisper streaming)
  Translation: ~300-500ms (NLLB-200 cached)
  TTS: ~1.2s first chunk, ~80ms streaming (XTTS v2)
  Total: <1.5s (meets target)

Accuracy (Benchmarks):
  STT: >90% (PhoWhisper Vietnamese)
  Translation: BLEU >35 (NLLB-200)
  Voice similarity: >80% (XTTS v2)

Capacity (Current):
  Concurrent rooms: 5-10 rooms
  Users per room: 4-6 (optimal), max 10
  Total concurrent: 20-60 users
  WebRTC: 2 MediaSoup workers (translation02)

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📊 Architecture v2.1 - Production Stack

⚠️ Key Revisions từ Feasibility Study

✅ What We've Validated

Research Sources: Nature 2024, ICLR 2024, IWSLT 2024, production GitHub issues

• ✅ faster-whisper: 7.8x realtime on CPU (1m42s for 13min audio)
• ✅ NLLB-200: 44% improvement over previous SOTA (Nature 2024)
• ✅ MediaSoup: 400-600 concurrent users capacity (battle-tested)
• ✅ PhoWhisper: 9.35% WER for Vietnamese (SOTA)
• ✅ XTTS v2: 30-60s on CPU (async only), MOS 4.0-4.5 quality
• ✅ End-to-end: 1.5s latency faster than human interpreters (2-3s)

Economic Model Validated:

• Infrastructure: $600/month (3 instances)
• Breakeven: 120 premium users @ $5/month
• Target: 300-500 users (profitable)

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🏗️ Tech Stack (100% Free & Open-source)

Core Technologies

💪 Architecture Principles

• Progressive Enhancement: Text → Quick audio → Premium audio
• Graceful Degradation: Multiple fallback layers
• Async by Design: Long tasks don't block UI
• Tiered Features: Free gets value, Premium gets quality
• CPU-Optimized: No GPU required (quantization + batching)
• Cost-Effective: $600/month infrastructure, scales horizontally

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📋 Infrastructure (Available on Google Cloud)

3 Instances (No GPU - CPU Only)

⚠️ UPDATED: Cấu hình thực tế (Oct 4, 2025)

Instance 1 (translation01):
  Type: c4d-standard-4 (⚠️ REDUCED from c2d-highcpu-8)
  CPU: 4 vCPUs (AMD Turin)
  RAM: 15 GB
  Disk: 100GB Hyperdisk Balanced
  Location: asia-southeast1-a
  Public IP: 34.143.235.114
  Internal IP: 10.148.0.5
  Role: Manager + AI Processing
  ⚠️ Risk: Chỉ 2GB RAM overhead, cần monitor sát

Instance 2 (translation02):
  Type: c2d-standard-4 (⚠️ REDUCED from c2d-highcpu-8)
  CPU: 4 vCPUs (AMD Milan)
  RAM: 16 GB
  Disk: 100GB SSD persistent
  Location: asia-southeast1-b
  Public IP: 34.142.190.250
  Internal IP: 10.148.0.3
  Role: Worker + WebRTC Gateway
  ⚠️ Capacity: 2 workers (thay vì 6), ~1000 consumers

Instance 3 (translation03):
  Type: c2d-highcpu-4
  CPU: 4 vCPUs
  RAM: 8 GB
  Disk: 50GB SSD persistent
  Location: asia-southeast1-c (TBD)
  Role: Worker + Monitoring

⚠️ Capacity Adjustments (Due to 4 vCPU Limit)

Original Target (8 vCPU):
  Concurrent rooms: 3-5
  MediaSoup workers: 6
  Total consumers: 3000
  
Adjusted Reality (4 vCPU):
  Concurrent rooms: 1-2 (MVP safe)
  MediaSoup workers: 2
  Total consumers: ~1000
  STT latency: ~1.5-2s (slower)
  
⚠️ Recommendation: 
  - Start with 1 room, 4-6 users
  - Monitor performance closely
  - Upgrade to 8 vCPU if need to scale

Software Requirements

• Docker Engine 20.10+
• Docker Compose 2.0+
• Python 3.10+ (cho development)
• Node.js 18+ (cho development)

⚠️ Thông Tin Cần Cung Cấp Trước Khi Bắt Đầu

CRITICAL: Điền thông tin thực vào docs/00-REQUIRED-INFO.md

• Hugging Face API Token (để download models)
• IP addresses của 3 instances
• SSH keys và credentials
• Domain names (nếu có)
• SSL certificates (production)
• Database passwords
• Redis passwords
• JWT secret keys
• SMTP settings (cho email notifications)

Xem chi tiết: docs/00-REQUIRED-INFO.md

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🚀 Quick Start

📖 Đọc Tài Liệu Theo Thứ Tự

1. FEASIBILITY-SUMMARY.md (5 phút) - Overview nhanh
2. UPDATE-SUMMARY.md (10 phút) - Những thay đổi v2.0
3. 01-ARCHITECTURE.md (20 phút) - Kiến trúc chi tiết
4. 05-AI-MODELS.md (15 phút) - Models và implementation
5. 12-FEASIBILITY-ANALYSIS.md (30 phút) - Research đầy đủ

🎯 Decision Point

Sau khi đọc tài liệu, quyết định:

• ✅ Chấp nhận kiến trúc v2.0 → Điền 00-REQUIRED-INFO.md → Bắt đầu Phase 1
• ❌ Từ chối → Thảo luận adjustments → Revise lại

🛠️ Nếu Chấp Nhận - Bắt Đầu Phase 1

# Clone repository
git clone <repo-url>
cd jbcalling_translation_realtime

# Điền thông tin thực
nano docs/00-REQUIRED-INFO.md

# Setup Docker Swarm (trên translation01)
./scripts/setup/init-swarm.sh

# Deploy stack
docker stack deploy -c infrastructure/swarm/stack.yml translation

# Verify
docker service ls
docker stack ps translation

Chi tiết: Xem docs/02-SETUP-GUIDE.md (sẽ update sau)

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📚 Documentation Structure

📁 Core Documents (UPDATED to v2.0)

📁 Implementation Guides (Cần Update)

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🗺️ Roadmap (5 Phases)

Phase 0: Research & Planning ✅ COMPLETED

• ✅ Feasibility research
• ✅ Architecture design v2.0
• ✅ Documentation (15+ files)
• Duration: 2 weeks
• Status: DONE

Phase 1: Infrastructure (Week 3-4)

• Docker Swarm setup
• Monitoring stack (Prometheus + Grafana)
• Database setup (PostgreSQL)
• Redis setup
• Duration: 2 weeks
• Status: NOT STARTED

Phase 2: WebRTC Foundation (Week 5-6)

• MediaSoup deployment
• Basic video call (no translation)
• Frontend UI/UX
• Duration: 2 weeks

Phase 3: Core Translation (Week 7-10)

• Whisper STT integration
• NLLB translation
• gTTS quick audio
• Live captions
• Duration: 4 weeks

Phase 4: Premium Features (Week 11-14)

• XTTS voice cloning (async)
• Celery background jobs
• User tier system
• Payment integration (optional)
• Duration: 4 weeks

Phase 5: Optimization (Week 15-21)

• PhoWhisper Vietnamese
• PyAnnote diarization (Pro tier)
• Redis caching layers
• Performance tuning
• Load testing
• Duration: 7 weeks

Total: 21 weeks (~5 months)

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📊 Success Metrics

🎯 Technical KPIs

Performance:
  Text latency: <900ms (target: 650ms avg)
  Audio latency: <1.5s (target: 1.3s avg)
  Concurrent rooms: 3-5 per instance
  Uptime: >99.5%

Accuracy:
  STT WER: <10% (English), <15% (Vietnamese)
  Translation BLEU: >30 (industry standard)
  Voice similarity: >80% (user satisfaction)

Capacity:
  Users per room: 4-6 (optimal)
  Total concurrent: 15-50 (MVP), 100-200 (Growth)
  CPU usage: <80% sustained
  Memory usage: <70% sustained

💰 Business KPIs

MVP Target (3 months):
  Free users: 100-300
  Premium users: 20-50
  Revenue: $100-250/month
  Cost: $600/month
  Status: Loss acceptable (validation phase)

Growth Target (6 months):
  Free users: 500-1000
  Premium users: 120-200
  Revenue: $600-1000/month
  Cost: $600-800/month
  Status: Breakeven

Scale Target (12 months):
  Free users: 2000-5000
  Premium users: 300-500
  Pro users: 20-50
  Revenue: $2500-4000/month
  Cost: $1200-1500/month
  Status: Profitable 2x

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🤝 Contributing

Vui lòng đọc docs/01-ARCHITECTURE.md và .github/copilot-instructions.md trước khi contribute.

📝 Code Style

• Python: PEP 8, type hints, docstrings tiếng Việt
• JavaScript: ESLint + Prettier
• Comments: Tiếng Việt cho logic phức tạp
• Commits: Conventional commits (tiếng Việt OK)

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📞 Support & Contact

• Documentation: docs/ folder
• Issues: GitHub Issues
• Questions: Discussions tab

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📄 License

[Chưa xác định - TBD]

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🙏 Acknowledgments

Research Papers:

• Nature 2024: "No Language Left Behind" (NLLB-200)
• ICLR 2024: "PhoWhisper: Vietnamese Speech Recognition"
• IWSLT 2024: "Simultaneous Translation with AlignAtt"

Open-source Projects:

• OpenAI Whisper
• Hugging Face Transformers
• MediaSoup WebRTC SFU
• Coqui TTS (XTTS v2)
• PyAnnote Audio

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Last Updated: 2025-01-04
Version: 2.0
Status: ✅ Feasibility Validated - Ready for Implementation

Trước khi setup, bạn cần chuẩn bị:

1. Hugging Face Token (Required)

   • Đăng ký: https://huggingface.co/join
   • Accept license: https://huggingface.co/pyannote/speaker-diarization-3.1
   • Tạo token: https://huggingface.co/settings/tokens

2. Instance IPs

   • External IPs của 3 instances
   • Internal IPs của 3 instances

3. Domain Name (Recommended)

   • Để sử dụng SSL
   • Cho production deployment

4. Secrets

   • PostgreSQL password
   • Redis password
   • JWT secret key
   • Grafana admin password

🚀 Quick Start

1. Clone Repository

git clone <REPOSITORY_URL>
cd jbcalling_translation_realtime

2. Đọc Documentation

BẮT BUỘC đọc các documents theo thứ tự:

docs/
├── 01-ARCHITECTURE.md      # Hiểu kiến trúc hệ thống
├── 02-SETUP-GUIDE.md        # Hướng dẫn setup chi tiết
├── 05-AI-MODELS.md          # Thông tin về AI models
└── 11-ROADMAP.md            # Kế hoạch phát triển

3. Setup Development Environment

# Install dependencies
pip install -r requirements.txt
npm install

# Setup pre-commit hooks
pre-commit install

# Run tests
pytest
npm test

4. Deploy to Production

Follow: docs/02-SETUP-GUIDE.md

📚 Documentation

Core Documents

• 01-ARCHITECTURE.md - Kiến trúc hệ thống chi tiết
• 02-SETUP-GUIDE.md - Hướng dẫn cài đặt từng bước
• 03-DOCKER-SWARM.md - Chi tiết về Docker Swarm
• 04-SERVICES.md - Chi tiết từng microservice
• 05-AI-MODELS.md - Thông tin AI models và configuration

Operational Documents

• 06-WEBRTC.md - WebRTC configuration và troubleshooting
• 07-API-REFERENCES.md - API documentation
• 08-DEPLOYMENT.md - CI/CD và deployment strategies
• 09-MONITORING.md - Monitoring và alerting
• 10-TROUBLESHOOTING.md - Common issues và fixes

Network & Infrastructure

• 11-IPV6-SETUP-GUIDE.md 🆕 - IPv6 dual-stack configuration (full guide)
• IPV6-QUICK-START.md 🆕 - IPv6 quick reference (TL;DR)

Planning Documents

• 11-ROADMAP.md - Kế hoạch phát triển chi tiết
• .github/copilot-instructions.md - Hướng dẫn cho AI Agent

🏛️ Kiến trúc

┌─────────────────────────────────────────┐
│         Load Balancer (Traefik)         │
└────────────┬────────────────────────────┘
             │
      ┌──────┴──────┐
      │             │
      ▼             ▼
┌──────────┐  ┌──────────┐
│ Frontend │  │   API    │
│  React   │  │ FastAPI  │
└──────────┘  └─────┬────┘
                    │
        ┌───────────┼───────────┐
        │           │           │
        ▼           ▼           ▼
    ┌────────┐ ┌────────┐ ┌────────┐
    │WebRTC  │ │ Redis  │ │Postgres│
    │Gateway │ │ Queue  │ │   DB   │
    └────┬───┘ └────┬───┘ └────────┘
         │          │
         └────┬─────┘
              │
     ┌────────┼────────┐
     │        │        │
     ▼        ▼        ▼
┌─────────┐ ┌─────┐ ┌──────┐
│Whisper  │ │NLLB │ │XTTS  │
│ (STT)   │ │(TL) │ │(TTS) │
└─────────┘ └─────┘ └──────┘

Xem chi tiết: docs/01-ARCHITECTURE.md

🔧 Development

Project Structure

jbcalling_translation_realtime/
├── .github/                    # GitHub workflows, copilot instructions
├── docs/                       # Documentation
├── services/                   # Microservices
│   ├── api/                   # API Gateway (FastAPI)
│   ├── transcription/         # Speech-to-text service
│   ├── translation/           # Translation service
│   ├── voice-cloning/         # Voice synthesis service
│   ├── diarization/           # Speaker diarization
│   ├── gateway/               # WebRTC gateway (MediaSoup)
│   ├── frontend/              # React frontend
│   └── monitoring/            # Monitoring stack
├── shared/                     # Shared code
│   ├── models/                # Data models
│   ├── utils/                 # Utilities
│   └── config/                # Configurations
├── infrastructure/             # Infrastructure as Code
│   ├── docker-compose.yml     # Development compose
│   └── swarm/                 # Production stack files
├── scripts/                    # Automation scripts
│   ├── setup/                 # Setup scripts
│   ├── deploy/                # Deployment scripts
│   └── maintenance/           # Maintenance scripts
└── tests/                      # Test suites

Coding Standards

• Python: PEP 8, type hints, async/await
• JavaScript: ESLint, Prettier, modern ES6+
• Comments: Tiếng Việt cho business logic
• Tests: >80% coverage required
• Documentation: Update docs với code changes

Xem chi tiết: .github/copilot-instructions.md

Running Locally

# Start core services
docker-compose up -d postgres redis

# Start API
cd services/api
uvicorn main:app --reload

# Start transcription service
cd services/transcription
python main.py

# Start frontend
cd services/frontend
npm run dev

Testing

# Unit tests
pytest tests/unit/

# Integration tests
pytest tests/integration/

# E2E tests
pytest tests/e2e/

# Load tests
locust -f tests/load/locustfile.py

🚢 Deployment

Development

docker-compose up -d

Production

# Deploy stack
docker stack deploy -c infrastructure/swarm/stack.yml translation

# Scale services
docker service scale translation_transcription=4

Xem chi tiết: docs/08-DEPLOYMENT.md

📊 Monitoring

Access monitoring dashboards:

• Grafana: http://<TRANSLATION03_IP>:3000
• Prometheus: http://<TRANSLATION03_IP>:9090
• Kibana: http://<TRANSLATION03_IP>:5601

Default credentials:

• Grafana: admin / <YOUR_GRAFANA_PASSWORD>

Xem chi tiết: docs/09-MONITORING.md

🐛 Troubleshooting

Common Issues

Service won't start

# Check logs
docker service logs translation_<service_name>

# Check events
docker events --filter 'type=service'

Out of memory

# Check usage
docker stats

# Scale down
docker service scale translation_transcription=1

Model loading fails

# Re-download models
docker exec -it <container> python scripts/download_models.py

Xem chi tiết: docs/10-TROUBLESHOOTING.md

🤝 Contributing

We welcome contributions! Please:

1. Fork repository
2. Create feature branch (git checkout -b feature/amazing-feature)
3. Commit changes (git commit -m 'feat: Add amazing feature')
4. Push to branch (git push origin feature/amazing-feature)
5. Open Pull Request

Commit Convention

feat: Add new feature
fix: Fix bug
docs: Update documentation
refactor: Code refactoring
test: Add tests
chore: Maintenance tasks

Messages in Vietnamese are encouraged for business logic changes.

📝 License

[Specify your license here]

🙏 Acknowledgments

• OpenAI Whisper: Best-in-class speech recognition
• Meta NLLB: Enabling 200 language translation
• Coqui XTTS: Amazing voice cloning technology
• PyAnnote: State-of-the-art diarization
• MediaSoup: Excellent WebRTC SFU
• Hugging Face: Free model hosting

📞 Support

• Documentation: Check docs/ folder
• Issues: Create GitHub issue
• Email: [Your contact email]
• Discussions: GitHub Discussions

📈 Roadmap

Architecture Version: 2.0
Implementation Status: Phase 0 Complete (Research & Planning)

✅ Phase 0 - Research & Planning (COMPLETED)

• Feasibility research (9 queries, 15+ docs)
• Architecture design v2.0
• Documentation foundation (20+ files)
• Validated benchmarks (Nature 2024, ICLR 2024, IWSLT 2024)
• Economic model ($600/month infrastructure)

🔄 Phase 1 - Infrastructure Setup (Week 3-4)

• Docker Swarm initialization
• Monitoring stack (Prometheus + Grafana + Loki)
• Database setup (PostgreSQL + pgvector)
• Redis cache/queue
• STUN/TURN server (coturn)

Phase 2 - WebRTC Foundation (Week 5-6)

• MediaSoup deployment (6 workers)
• Basic video call (no translation yet)
• Frontend UI/UX (React + Next.js)
• Room management
• Mobile responsive

Phase 3 - Production

• Performance optimization
• Security hardening
• Load testing
• User acceptance

Future

• Mobile app
• Recording feature
• Meeting highlights
• Custom model training

Xem chi tiết: docs/11-ROADMAP.md

🌟 Star History

If you find this project useful, please give it a ⭐!

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Built with ❤️ using only CPU and free software

Version: 2.0 | Last Updated: 2025-01-04