Resume-Matcher Structure

Project Tree Structure with Design Pattern Mapping

resume-matcher/
β”œβ”€β”€ πŸ“ backend/                         # FastAPI Backend Service
β”‚   β”œβ”€β”€ πŸ“ app/                         # Main Application Package
β”‚   β”‚   β”œβ”€β”€ πŸ“ core/                    # 🎭 FACADE + πŸ—οΈ FACTORY + βš™οΈ CONFIG
β”‚   β”‚   β”‚   β”œβ”€β”€ facade.py               # Facade Pattern (unified API interface)
β”‚   β”‚   β”‚   β”œβ”€β”€ config.py               # Configuration Pattern
β”‚   β”‚   β”‚   └── dependencies.py         # Dependency injection
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ parsers/                 # 🏭 FACTORY + πŸ”Œ ADAPTER PATTERNS
β”‚   β”‚   β”‚   β”œβ”€β”€ base_parser.py          # Abstract base for all parsers
β”‚   β”‚   β”‚   β”œβ”€β”€ parser_factory.py       # Factory Pattern (document type selection)
β”‚   β”‚   β”‚   β”œβ”€β”€ pdf_parser.py           # Adapter: PDF document processing
β”‚   β”‚   β”‚   β”œβ”€β”€ docx_parser.py          # Adapter: DOCX document processing
β”‚   β”‚   β”‚   β”œβ”€β”€ txt_parser.py           # Adapter: Plain text processing
β”‚   β”‚   β”‚   └── doc_parser.py           # Adapter: Legacy DOC format
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ analyzers/               # 🎯 STRATEGY + πŸ“‹ TEMPLATE METHOD
β”‚   β”‚   β”‚   β”œβ”€β”€ base_analyzer.py        # Template Method (analysis workflow)
β”‚   β”‚   β”‚   β”œβ”€β”€ ats_analyzer.py         # Strategy: ATS compatibility analysis
β”‚   β”‚   β”‚   β”œβ”€β”€ keyword_analyzer.py     # Strategy: Keyword extraction/matching
β”‚   β”‚   β”‚   β”œβ”€β”€ content_analyzer.py     # Strategy: Content quality analysis
β”‚   β”‚   β”‚   └── scoring_analyzer.py     # Strategy: Match score calculation
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ ai/                      # πŸ”Œ ADAPTER + 🎯 STRATEGY
β”‚   β”‚   β”‚   β”œβ”€β”€ llm_adapter.py          # Adapter Pattern (AI model abstraction)
β”‚   β”‚   β”‚   β”œβ”€β”€ ollama_adapter.py       # Adapter: Local Ollama integration
β”‚   β”‚   β”‚   β”œβ”€β”€ openai_adapter.py       # Adapter: OpenAI API integration
β”‚   β”‚   β”‚   β”œβ”€β”€ anthropic_adapter.py    # Adapter: Anthropic API integration
β”‚   β”‚   β”‚   └── ai_service.py           # Strategy: AI provider selection
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ recommendations/         # πŸ—οΈ BUILDER + πŸ”§ COMMAND
β”‚   β”‚   β”‚   β”œβ”€β”€ recommendation_builder.py # Builder Pattern (flexible rec creation)
β”‚   β”‚   β”‚   β”œβ”€β”€ recommendation_engine.py  # Template Method (rec generation)
β”‚   β”‚   β”‚   β”œβ”€β”€ commands/               # Command Pattern implementation
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ base_command.py     # Abstract command interface
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ keyword_command.py  # Command: Keyword recommendations
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ format_command.py   # Command: Formatting suggestions
β”‚   β”‚   β”‚   β”‚   └── content_command.py  # Command: Content improvements
β”‚   β”‚   β”‚   └── invoker.py              # Command invoker and history
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ observers/               # πŸ‘οΈ OBSERVER PATTERN
β”‚   β”‚   β”‚   β”œβ”€β”€ analysis_observer.py    # Observer interface
β”‚   β”‚   β”‚   β”œβ”€β”€ progress_observer.py    # Observer: Progress tracking
β”‚   β”‚   β”‚   β”œβ”€β”€ ui_observer.py          # Observer: Real-time UI updates
β”‚   β”‚   β”‚   └── logging_observer.py     # Observer: Analysis logging
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ models/                  # πŸ“Š DATA MODELS
β”‚   β”‚   β”‚   β”œβ”€β”€ resume_model.py         # Resume data structure
β”‚   β”‚   β”‚   β”œβ”€β”€ job_description_model.py# Job description data structure
β”‚   β”‚   β”‚   β”œβ”€β”€ analysis_result_model.py# Analysis results structure
β”‚   β”‚   β”‚   └── recommendation_model.py # Recommendation data structure
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ api/                     # 🎭 FACADE + 🌐 REST API
β”‚   β”‚   β”‚   β”œβ”€β”€ routes/                 # API route definitions
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ analysis.py         # Analysis endpoints
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ upload.py           # File upload endpoints
β”‚   β”‚   β”‚   β”‚   └── recommendations.py  # Recommendation endpoints
β”‚   β”‚   β”‚   └── middleware.py           # CORS, auth, logging middleware
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ database/                # πŸ’Ύ DATA PERSISTENCE
β”‚   β”‚   β”‚   β”œβ”€β”€ connection.py           # Database connection management
β”‚   β”‚   β”‚   β”œβ”€β”€ models.py               # SQLAlchemy models
β”‚   β”‚   β”‚   └── repositories/           # Repository pattern
β”‚   β”‚   β”‚       β”œβ”€β”€ resume_repository.py
β”‚   β”‚   β”‚       └── analysis_repository.py
β”‚   β”‚   β”‚
β”‚   β”‚   └── main.py                     # FastAPI application entry point
β”‚   β”‚
β”‚   β”œβ”€β”€ πŸ“ tests/                       # Testing Infrastructure
β”‚   └── requirements.txt                # Python dependencies
β”‚
β”œβ”€β”€ πŸ“ frontend/                        # Next.js Frontend Application
β”‚   β”œβ”€β”€ πŸ“ src/                         # Source Code
β”‚   β”‚   β”œβ”€β”€ πŸ“ app/                     # Next.js App Router
β”‚   β”‚   β”‚   β”œβ”€β”€ upload/                 # File upload page
β”‚   β”‚   β”‚   β”œβ”€β”€ analysis/               # Analysis results page
β”‚   β”‚   β”‚   └── recommendations/        # Recommendations page
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ components/              # React Components
β”‚   β”‚   β”‚   β”œβ”€β”€ upload/                 # πŸ‘οΈ OBSERVER (progress updates)
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ FileUpload.tsx      # Observer: File upload progress
β”‚   β”‚   β”‚   β”‚   └── UploadProgress.tsx  # Observer: Real-time progress
β”‚   β”‚   β”‚   β”‚
β”‚   β”‚   β”‚   β”œβ”€β”€ analysis/               # 🎨 PRESENTATION LAYER
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ AnalysisResults.tsx # Results display component
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ ScoreCard.tsx       # Score visualization
β”‚   β”‚   β”‚   β”‚   └── AnalysisCharts.tsx  # Data visualization
β”‚   β”‚   β”‚   β”‚
β”‚   β”‚   β”‚   └── recommendations/        # πŸ”§ COMMAND PATTERN UI
β”‚   β”‚   β”‚       β”œβ”€β”€ RecommendationList.tsx # Recommendations display
β”‚   β”‚   β”‚       β”œβ”€β”€ ActionableItem.tsx     # Command: Apply recommendation
β”‚   β”‚   β”‚       └── RecommendationCard.tsx # Individual recommendation UI
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ services/                # πŸ”Œ ADAPTER + 🎯 STRATEGY
β”‚   β”‚   β”‚   β”œβ”€β”€ api_client.py           # Adapter: Backend API communication
β”‚   β”‚   β”‚   β”œβ”€β”€ file_service.py         # Strategy: File handling strategies
β”‚   β”‚   β”‚   └── notification_service.py # Observer: User notifications
β”‚   β”‚   β”‚
β”‚   β”‚   β”œβ”€β”€ πŸ“ hooks/                   # React Custom Hooks
β”‚   β”‚   β”‚   β”œβ”€β”€ useAnalysis.ts          # Analysis state management
β”‚   β”‚   β”‚   β”œβ”€β”€ useFileUpload.ts        # File upload state
β”‚   β”‚   β”‚   └── useRecommendations.ts   # Recommendations state
β”‚   β”‚   β”‚
β”‚   β”‚   └── πŸ“ utils/                   # Utility Functions
β”‚   β”‚       β”œβ”€β”€ formatters.ts           # Data formatting utilities
β”‚   β”‚       └── validators.ts           # Input validation
β”‚   β”‚
β”‚   β”œβ”€β”€ πŸ“ public/                      # Static Assets
β”‚   β”œβ”€β”€ next.config.js                  # Next.js configuration
β”‚   β”œβ”€β”€ tailwind.config.js              # Tailwind CSS configuration
β”‚   └── package.json                    # Node.js dependencies
β”‚
β”œβ”€β”€ πŸ“ docs/                            # Documentation
β”‚   β”œβ”€β”€ api.md                          # API documentation
β”‚   β”œβ”€β”€ setup.md                        # Setup instructions
β”‚   └── architecture.md                 # Architecture overview
β”‚
β”œβ”€β”€ πŸ“ scripts/                         # Utility Scripts
β”‚   β”œβ”€β”€ setup.sh                        # Environment setup
β”‚   └── deploy.sh                       # Deployment script
β”‚
β”œβ”€β”€ docker-compose.yml                  # Docker containerization
β”œβ”€β”€ .env.example                        # Environment variables template
└── README.md                          # Project documentation

Design Pattern Interactions & Data Flow

Pattern Synergies & System Properties

πŸ”„ End-to-End Pattern Flow

🎯 Achieved System Capabilities

Pattern Combination
System Property
Real-World Benefit

Factory + Adapter

Multi-Format Support

Seamless PDF, DOCX, TXT, DOC processing

Strategy + Template Method

Flexible Analysis

Custom analysis while maintaining consistency

Facade + Observer

User Experience

Simple API with real-time feedback

Command + Builder

Actionable Results

Flexible, executable recommendations

Adapter + Strategy (AI)

Privacy-First AI

Local processing with cloud fallback

Observer + All Patterns

Transparent Operations

Complete visibility into analysis process

🏒 Enterprise Production Features

Key Architecture Insights

Why This Design Works

  1. 🎭 Facade Layer: Clean API interface hiding document processing complexity

  2. 🏭 Factory Ecosystem: Seamless multi-format document support

  3. 🎯 Strategy Network: Flexible analysis algorithms for different user needs

  4. πŸ”Œ Adapter Integration: Privacy-focused local AI with cloud alternatives

  5. πŸ‘οΈ Observer System: Transparent, real-time user experience

  6. πŸ—οΈ Builder Flexibility: Customizable recommendation generation

Privacy-First Architecture Benefits

  • Local Processing: Ollama integration keeps sensitive data on-device

  • Flexible Deployment: Can run completely offline or with cloud augmentation

  • User Control: Choice between local privacy and cloud performance

  • Transparent Operations: Full visibility into analysis process

  • Data Security: No external dependencies for core functionality

Real-World Production Value

  • HR/Recruiting Industry: Addresses genuine need for ATS-optimized resumes

  • Privacy Compliance: Meets enterprise privacy requirements

  • Scalable Architecture: Can handle high-volume document processing

  • User-Centric Design: Intuitive interface for complex AI functionality

  • Extensible Platform: Easy to add new analysis types and AI providers

This architecture demonstrates how classic design patterns can be combined to create privacy-focused, user-friendly AI applications that solve real-world problems while maintaining professional software engineering standards.

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