بَحْر (BAHR) - Arabic Poetry Analysis Platform

نظام ذكي لتحليل الشعر العربي
Intelligent Arabic Poetry Analysis System

English | العربية

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🌟 Overview

BAHR (بَحْر, meaning "sea" or "meter" in Arabic) is a comprehensive platform for analyzing and understanding Arabic classical poetry through advanced NLP techniques and prosodic analysis.

🚀 Live Demo

✨ The platform is LIVE in production!

• 🌐 Try it now: https://frontend-production-6416.up.railway.app/
• 📚 API Documentation: https://backend-production-c17c.up.railway.app/docs
• 💚 Health Status: https://backend-production-c17c.up.railway.app/health

Production Stats:

• ✅ 98.1% meter detection accuracy
• ✅ 16 classical Arabic meters supported
• ✅ Redis caching (5-10x speedup)
• ✅ 220 passing tests, 99% coverage

✨ Key Features

• 🎼 Meter Detection - Automatic identification of Arabic poetic meters (البحور)
• 📊 Syllable Segmentation - Precise prosodic analysis using CAMeL Tools
• ✨ Rhyme Analysis - Pattern extraction and validation
• 🌐 RTL-First UI - Beautiful Arabic-first interface with Next.js 16
• 🔍 Real-time Analysis - Instant feedback on poetry structure
• 📚 Golden Dataset - 52 annotated classical verses for testing

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🚀 Quick Start

Frontend (Next.js 16)

cd src/frontend
npm install
npm run dev

Visit: http://localhost:3000

Backend (FastAPI)

cd src/backend

# Install as editable package (recommended)
pip install -e .

# Or install dependencies directly
pip install -r requirements.txt

# Start server
uvicorn app.main:app --reload

Visit: http://localhost:8000/docs

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🏗️ Tech Stack

Frontend

• Framework: Next.js 16.0.1 with App Router
• Language: TypeScript (strict mode)
• Styling: Tailwind CSS v4
• Components: shadcn/ui (New York style)
• Fonts: Cairo (UI) + Amiri (poetry) via next/font/google
• RTL: Native dir="rtl" support

Backend

• Framework: FastAPI 0.115+
• Language: Python 3.11+
• NLP: CAMeL Tools for Arabic processing
• Database: PostgreSQL 15+ with SQLAlchemy
• Cache: Redis 7+
• Migration: Alembic

DevOps

• Containerization: Docker + Docker Compose
• CI/CD: GitHub Actions
• Deployment: Railway (backend) + Vercel (frontend)

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📂 Project Structure

BAHR/
├── src/
│   ├── backend/           # FastAPI backend
│   │   ├── app/          # Application code
│   │   │   ├── api/      # API routes
│   │   │   ├── core/     # Core prosody engine
│   │   │   ├── ml/       # ML models & training
│   │   │   └── db/       # Database models
│   │   ├── alembic/      # Database migrations
│   │   └── tests/        # Backend unit tests
│   └── frontend/          # Next.js 16 frontend
│       ├── src/
│       │   ├── app/      # App Router pages
│       │   └── components/ # React components
│       └── public/        # Static assets
├── data/
│   ├── raw/              # Raw ML datasets (158 JSONL files)
│   ├── processed/        # Processed datasets & golden set
│   └── interim/          # Intermediate processing files
├── docs/
│   ├── api/              # API documentation
│   ├── research/         # Research documentation
│   ├── technical/        # Technical specs
│   ├── deployment/       # Deployment guides
│   ├── refactor/         # Refactoring documentation
│   └── releases/         # Release notes
├── results/
│   ├── ml/               # ML training results
│   ├── evaluations/      # Model evaluations
│   └── diagnostics/      # Analysis outputs
├── tests/
│   └── integration/      # Integration tests
├── scripts/
│   ├── ml/               # ML training scripts
│   ├── ml_pipeline/      # ML pipeline & training
│   ├── tools/            # Development tools
│   ├── data_processing/  # Data processing scripts
│   ├── setup/            # Environment setup
│   └── refactor/         # Migration scripts
├── models/                # Trained ML models
├── infrastructure/        # Docker & deployment
└── archive/               # Historical documentation
    ├── phases/           # Phase reports
    └── sessions/         # Session summaries

Note: Repository was refactored on November 14, 2025 for production readiness. Backward compatibility symlinks removed after successful migration. See docs/refactor/ for details.

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📖 Documentation

🎯 Essential Guides

• 🚀 Quick Start Guide - Get up and running in 5 minutes
• 📖 API Documentation - Complete API reference and guides
• 🏗️ Technical Specifications - Architecture and implementation details
• 🚢 Deployment Guide - Railway deployment instructions
• 🔧 Refactoring Docs - Repository structure and migration details

📂 Documentation Structure

• /docs/api/ - API guides and specifications
• /docs/research/ - Research documentation and datasets
• /docs/technical/ - Technical implementation details
• /docs/deployment/ - Deployment and DevOps guides
• /docs/refactor/ - Refactoring documentation
• /archive/ - Historical documentation and phase reports

📋 November 14, 2025 Update: Repository refactored for production readiness.
See docs/refactor/Repo_Refactor_Plan.md for complete details.

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🎯 Current Status

🎉 PHASE 1 COMPLETE - LIVE IN PRODUCTION!

Phase: All of Phase 1 (Weeks 1-8) ✅ COMPLETE Progress: 100% of MVP - DEPLOYED TO PRODUCTION Launch Date: November 10, 2025

✅ Completed

• Complete technical documentation (40+ files)
• Next.js 16 frontend with RTL + Arabic fonts
• Golden dataset v0.20 (52 annotated verses)
• FastAPI backend with CORS middleware
• Docker Compose configuration (PostgreSQL + Redis)
• CI/CD workflows (GitHub Actions)
• Prosody Engine Core (Week 1-2)
  • Text normalization with CAMeL Tools
  • Phonetic analysis (CV pattern extraction)
  • Taqti3 algorithm (syllable segmentation)
  • Bahr detection (4 meters: الطويل، الكامل، الرمل، الوافر)
  • 98.1% accuracy on test dataset ✅ (exceeds 90% target)
• Database & Infrastructure
  • Alembic migrations with 8 performance indexes
  • 16 Arabic meters + 8 prosodic feet seeded
  • PostgreSQL 15 running in Docker
• Testing & Quality
  • 220 passing tests
  • 99% code coverage
  • Accuracy test suite with golden dataset
• Production Readiness (Week 0)
  • Railway CLI installed
  • CORS policy configured
  • Database indexes documented (ADR-002)

� In Progress

• Railway project setup (CLI ready, need to create project)
• API endpoints implementation (Week 2)
• Frontend-Backend integration

📅 Upcoming

• Production deployment to Railway + Vercel
• Authentication & user management
• Performance optimization

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🛠️ Developer Productivity

Shell Aliases (Optional but Recommended)

BAHR includes a comprehensive set of shell aliases for common development tasks. To use them:

# Add to your ~/.zshrc
source /Users/YOUR_USERNAME/Desktop/Personal/BAHR/.bahr_aliases.sh

# Reload shell
source ~/.zshrc

Available commands:

• bahr-help - Show all available commands
• bahr-setup - Complete environment setup
• bahr-start/stop/restart - Manage Docker services
• bahr-migrate - Run database migrations
• bahr-test - Run tests with coverage
• bahr-backend/frontend - Start development servers
• Plus 30+ more utilities for navigation, testing, and database management

See the full command list by running bahr-help after sourcing the aliases file.

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🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Development Workflow

# 1. Fork and clone
git clone https://github.com/YOUR_USERNAME/BAHR.git
cd BAHR

# 2. Create feature branch
git checkout -b feature/your-feature-name

# 3. Make changes and test
npm test          # Frontend tests
pytest            # Backend tests

# 4. Commit and push
git commit -m "feat: add your feature"
git push origin feature/your-feature-name

# 5. Create Pull Request

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📊 Dataset

The project includes a Golden Dataset of 42 manually annotated classical Arabic verses:

• ✅ Schema-validated JSONL format
• ✅ Prosodic annotations (meters, feet, rhymes)
• ✅ Metadata (poet, era, source)
• ✅ Quality assurance reports

See dataset/evaluation/README.md

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🔐 Security

• 🔒 JWT-based authentication
• 🛡️ OWASP Top 10 compliance
• 🔐 Secrets management via Railway/Vercel
• 🚫 Rate limiting & DDoS protection

See docs/technical/SECURITY.md

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📄 License

This project is licensed under the MIT License - see LICENSE file for details.

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🙏 Acknowledgments

• CAMeL Tools - Arabic NLP toolkit
• shadcn/ui - Beautiful UI components
• Next.js Team - Amazing React framework
• FastAPI - High-performance Python framework

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📞 Contact & Support

• Documentation: docs/
• Issues: GitHub Issues
• Discussions: GitHub Discussions

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Built with ❤️ for Arabic Poetry Enthusiasts

⭐ Star us on GitHub | 📖 Read the Docs | 🐛 Report Bug

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🇸🇦 النسخة العربية

نظرة عامة

بَحْر هو منصة شاملة لتحليل وفهم الشعر العربي الكلاسيكي من خلال تقنيات معالجة اللغات الطبيعية المتقدمة والتحليل العروضي.

المميزات الرئيسية

• 🎼 كشف البحور الشعرية - تحديد تلقائي للأوزان العروضية
• 📊 التقطيع العروضي - تحليل دقيق للمقاطع الصوتية
• ✨ تحليل القوافي - استخراج والتحقق من أنماط القافية
• 🌐 واجهة عربية أصيلة - تصميم جميل يدعم العربية بالكامل
• 🔍 تحليل فوري - ردود فعل مباشرة على بنية القصيدة
• 📚 مجموعة بيانات ذهبية - 42 بيتًا كلاسيكيًا مُشَرَّحًا

البدء السريع

# الواجهة الأمامية
cd frontend && npm install && npm run dev

# الخلفية (قريبًا)
cd backend && pip install -r requirements.txt

الحالة الحالية

المرحلة: المرحلة 0 مكتملة ✅
التقدم: 60%

• ✅ التوثيق الكامل
• ✅ الواجهة الأمامية (Next.js 16)
• ✅ مجموعة البيانات الذهبية
• 🔄 تطوير الخلفية (الأسبوع 1)

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صُنع بحب ❤️ لعشاق الشعر العربي