🤖 AI Resume - Interactive Chat Interface

Chat with Michael Wybraniec's AI-powered resume using open-source LLMs - Deploy for FREE!

✨ Now built with a clean, modular architecture for maximum maintainability and scalability.

🚀 Features

• 📄 Interactive Resume Chat - Ask any question about Michael's background and experience
• 🆓 Free Deployment - Deploy on Streamlit Cloud for free
• 🤖 Multiple LLM Providers - OpenRouter (free models), OpenAI, Ollama (local)
• 💬 Modern Chat UI - Beautiful Streamlit interface with quick action buttons
• 📱 Mobile Responsive - Works perfectly on all devices
• ⚡ Real-time - Instant responses with intelligent context retrieval
• 📄 PDF Download - Generate and download professional CV
• 🎯 Smart Matching - Job description analysis for recruiter insights
• ✅ System Status - Real-time status indicator shows when all systems are ready
• 🔧 Auto-Configuration - Smart setup flow with contextual help
• 🏗️ Purpose-Based Architecture - Professional project organization with logical file grouping

🎯 Quick Start (Local)

# 1. Clone the repository
git clone <your-repo-url>
cd mcp-resume

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

# 3. Run the application
streamlit run app.py

# 4. Open http://localhost:8501
# 5. Get a free API key from OpenRouter.ai
# 6. Add your API key in the sidebar and start chatting!

🌟 Deploy to Streamlit Cloud (FREE!)

1. Push to GitHub

git add .
git commit -m "Deploy AI Resume to Streamlit Cloud"
git push origin main

2. Deploy on Streamlit Cloud

1. Go to share.streamlit.io
2. Connect your GitHub account
3. Select your repository
4. Set main file path: app.py
5. Click "Deploy"!

3. Configure Secrets (Optional)

For enhanced LLM providers, add secrets in Streamlit Cloud dashboard:

[secrets]
OPENROUTER_API_KEY = "your_openrouter_api_key_here"
OPENAI_API_KEY = "your_openai_api_key_here"

4. Your app is live! 🎉

You'll get a URL like: https://your-username-mcp-resume-app-xyz.streamlit.app

🤖 LLM Provider Setup

Option 1: OpenRouter (Recommended)

• Free models available!
• Sign up at OpenRouter
• Get API key and add via the sidebar or Streamlit secrets
• Use free models like meta-llama/llama-3.1-8b-instruct:free

Option 2: Ollama (Local Development)

# Install Ollama
brew install ollama  # macOS
# or visit https://ollama.ai for other platforms

# Start Ollama
ollama serve

# Install models
ollama pull llama3.2
ollama pull llama3.1

Option 3: OpenAI (Paid)

• Get API key from OpenAI
• Add to Streamlit secrets or enter in the app

🏗️ Architecture

Purpose-Based Organization:

mcp-resume/
├── 🏠 app.py                     # Main entry point (Streamlit-ready)
├── 📋 requirements.txt           # Dependencies
│
├── 🔧 core/                      # Foundation & Configuration
│   ├── config.py                # Settings & constants
│   └── models.py                # Data models & types
│
├── ⚙️ services/                  # Business Logic & Integrations
│   ├── resume_service.py        # Resume data handling
│   ├── llm_providers.py         # AI/LLM integrations
│   ├── document_generator.py    # PDF generation
│   └── fallback_resume.py       # Data fallback service
│
├── 🎨 ui/                        # User Interface Layer
│   ├── ui_components.py         # UI components & styling
│   └── session_manager.py       # Session state management
│
├── 📊 data/                      # Data Files
│   ├── resume.json
│   ├── michael_wybraniec_resume.json
│   └── CV_Michael_Wybraniec_15_Jun_2025.pdf
│
└── 🔨 utils/                     # Utility Scripts
    └── create_gist.py           # GitHub Gist utilities

Data Flow:

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│ UI Components   │◄──►│ Resume Service   │◄──►│ JSON Resume     │
│ (Chat Interface)│    │ (Data Processing)│    │ Data            │
└─────────────────┘    └──────────────────┘    └─────────────────┘
         │
         ▼
┌─────────────────┐
│ LLM Providers   │
│ • OpenRouter    │
│ • Ollama        │
│ • OpenAI        │
└─────────────────┘

Module Responsibilities:

🔧 Core Layer

• core/config.py - Configuration, constants, and settings
• core/models.py - Data models and type definitions

🎨 UI Layer

• ui/ui_components.py - UI components, styling, and modals
• ui/session_manager.py - Session state management and initialization

⚙️ Services Layer

• services/resume_service.py - Resume data retrieval and context generation
• services/llm_providers.py - LLM provider implementations and unified chat interface
• services/document_generator.py - PDF generation and export functionality
• services/fallback_resume.py - Resume data service and context management

📊 Data Layer

• data/ - Resume JSON files and PDF assets
• utils/ - Utility scripts and helper functions

💡 Usage Examples

💬 Chat Examples:

• "Tell me about Michael's work experience"
• "What are his technical skills?"
• "Summarize his background for a recruiter"
• "Find projects involving JavaScript"
• "What's his experience with AI and machine learning?"
• "How many years of Python experience does he have?"
• "Has he worked with AI/ML technologies?"
• "What industries has he worked in?"

⚡ Quick Actions:

• 👤 Summarize Profile - Get comprehensive candidate overview
• 📅 Years Experience - View career progression timeline
• 🛠️ Technical Skills - Analyze technical competencies
• 🎯 Smart Match - Job fit analysis with match scores
• 📄 Download CV - Professional PDF resume

🎯 For Recruiters & HR:

• "Is this candidate suitable for a senior developer role?"
• "What's their leadership experience?"
• "Do they have experience with cloud platforms?"
• "Rate their frontend vs backend skills"
• "Analyze fit for this job description..." (paste job description)

🔧 Features & Functionality

📱 Modern Chat Interface

• Clean, professional design with expanded sidebar
• Quick action buttons for instant insights
• Real-time system status indicator
• Message timestamps and processing indicators
• Mobile-responsive design

🎯 Smart Context Retrieval

• Intelligent context selection based on user questions
• Focused responses with relevant resume sections
• Experience, skills, projects, and achievements matching
• Job description analysis capabilities

📄 Professional CV Generation

• Generate PDF CV on demand
• Clean, professional formatting
• Download directly from the interface

🔧 Enhanced User Experience

• System Status: Real-time indicator showing "All Systems Ready!" when configured
• Help & Tips: Comprehensive setup guide and sample questions
• Quick Actions: Organized, expandable panel for common tasks
• Auto-Setup: Smart configuration flow with contextual guidance

🌐 Deployment Options

1. Streamlit Cloud (Recommended - Free) ⭐

• Free hosting for public repositories
• Automatic deployments from GitHub
• Built-in secrets management
• Perfect for demos and portfolios

2. Local Development

pip install -r requirements.txt
streamlit run app.py

3. Other Cloud Platforms

• Railway, Render, Heroku
• Use provided requirements.txt and runtime.txt
• Set startup command: streamlit run app.py --server.port $PORT

📁 Project Structure

mcp-resume/
├── 🏠 app.py                           # Main entry point (Streamlit-ready)
├── 📋 requirements.txt                 # Python dependencies
├── 🐍 runtime.txt                      # Python version for deployment
├── 📖 README.md                        # Documentation
├── 🚀 DEPLOYMENT.md                    # Deployment guide
├── 🔧 secrets.toml.example             # Example secrets configuration
│
├── 🔧 core/                            # Foundation & Configuration
│   ├── __init__.py
│   ├── config.py                       # Settings & constants
│   └── models.py                       # Data models & types
│
├── ⚙️ services/                        # Business Logic & Integrations
│   ├── __init__.py
│   ├── resume_service.py               # Resume data handling
│   ├── llm_providers.py                # AI/LLM integrations
│   ├── document_generator.py           # PDF generation
│   └── fallback_resume.py              # Data fallback service
│
├── 🎨 ui/                              # User Interface Layer
│   ├── __init__.py
│   ├── ui_components.py                # UI components & styling
│   └── session_manager.py              # Session state management
│
├── 📊 data/                            # Data Files
│   ├── resume.json                     # Primary resume data
│   ├── michael_wybraniec_resume.json   # Backup resume data
│   └── CV_Michael_Wybraniec_15_Jun_2025.pdf # Professional CV
│
├── 🔨 utils/                           # Utility Scripts
│   ├── __init__.py
│   └── create_gist.py                  # GitHub Gist utilities
│
└── 🐍 venv/                            # Virtual environment

🏗️ Purpose-Based Architecture Benefits

🔧 For Developers:

• Easy Navigation: Find files by purpose (UI, services, data, etc.)
• Maintainable: Clear separation of concerns across directories
• Scalable: Add new features without touching existing modules
• Testable: Each layer can be tested independently
• Professional: Industry-standard project organization

🚀 For Features:

• New LLM Providers: Extend services/llm_providers.py
• UI Changes: Modify ui/ui_components.py
• Export Formats: Add to services/document_generator.py
• Data Sources: Extend services/resume_service.py
• Configuration: Update core/config.py

📁 Organization Highlights:

• Streamlit Compatible: app.py stays in root for deployment
• Logical Grouping: Files organized by functionality, not arbitrarily
• Clean Root: No clutter - only essential files visible
• Python Packages: Proper __init__.py files for clean imports

Architecture Highlights:

• 88% reduction in main file complexity (1,500 → 180 lines)
• 8 focused modules instead of monolithic structure
• Clear dependencies and import relationships
• Single responsibility principle throughout

🚀 Getting Started

1. Clone and Install

   git clone <your-repo>
   cd mcp-resume
   pip install -r requirements.txt
   

2. Run Locally

   streamlit run app.py
   

3. Configure & Chat

   • Navigate to http://localhost:8501
   • Get a free API key from OpenRouter.ai
   • Add your API key in the sidebar
   • When you see "✅ All Systems Ready!" you're good to go!
   • Start chatting with the AI resume!

🎨 Customization

Adding Your Own Resume

1. Replace michael_wybraniec_resume.json with your resume data
2. Update the resume_service.py if needed
3. Modify branding in ui_components.py header section
4. Replace the CV PDF file with your own

LLM Configuration

• Add your preferred LLM providers in llm_providers.py
• Configure API keys via sidebar or Streamlit secrets
• Customize system prompts in the provider implementations

UI Customization

• Modify the header branding and colors in ui_components.py
• Update Quick Action buttons and modal content
• Customize the Help & Tips content in the sidebar
• Adjust the responsive CSS styling

Adding New Features

• New Export Format: Extend document_generator.py
• Additional Data Sources: Modify resume_service.py
• New UI Components: Add to ui_components.py
• Custom Session Logic: Extend session_manager.py

📞 Contact & Support

• Developer: Michael Wybraniec
• Website: One-Front.com
• LinkedIn: Connect with Michael
• Custom AI Solutions: Contact through One-Front for enterprise implementations

🛠️ Recent Updates

• ✅ Modular Architecture: Refactored into 8 focused modules for better maintainability
• 🎯 88% Code Reduction: Main app now just 180 lines vs original 1,500
• 📚 Improved Documentation: Clear module responsibilities and architecture overview
• 🔧 Enhanced Testability: Each module can be tested independently
• 🚀 Better Scalability: Easy to add features without touching existing code
• 📱 Maintained All Features: Full functionality preserved in cleaner structure

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Ready to revolutionize resume interactions with a maintainable, scalable architecture? 🚀

Deploy your AI-powered resume today - now with professional-grade code organization!