Many students and professionals struggle with:

• Resume Analysis: Understanding what skills to highlight
• Career Guidance: Finding the right career path
• Skill Development: Knowing what to learn next
• Job Search: Getting personalized career advice

An intelligent AI-powered career mentor that:

• Analyzes resumes using advanced PDF parsing
• Provides personalized career guidance through RAG (Retrieval Augmented Generation)
• Identifies skill gaps and suggests learning paths
• Offers career path recommendations based on your background

• PyMuPDF Integration: Superior text extraction (3x better than PyPDF2)
• Smart Section Detection: Handles complex resume formats
• Contact Extraction: Email, phone, LinkedIn, GitHub
• Skill Analysis: 33+ skills with categorization
• Project Recognition: Identifies and analyzes projects

• RAG Pipeline: Retrieval Augmented Generation for contextual responses
• Personalized Advice: Based on your actual resume content
• Skill Gap Analysis: Compare current vs target skills
• Career Path Suggestions: AI-generated recommendations
• Learning Roadmaps: Step-by-step guidance

• Responsive Design: Works on all devices
• Real-time Chat: AI career advisor interface
• File Upload: Drag-and-drop resume upload
• Progress Tracking: Visual feedback and status
• Performance Monitoring: RAG pipeline status

• Django 5.0+: Web framework
• PyMuPDF: Advanced PDF processing
• LangChain: RAG pipeline framework
• HuggingFace: AI models and transformers
• FAISS: Vector database for embeddings

• HTML5/CSS3: Modern web standards
• Bootstrap 5: Responsive UI framework
• JavaScript: Interactive features
• FontAwesome: Icons and visual elements

• DialoGPT-small: Optimized language model
• Sentence Transformers: Text embeddings
• ONNX Runtime: Performance optimization
• CPU Optimization: torch.float32, low_cpu_mem_usage

Sahay-AI/
├── career_mentor_web/          # Django project
├── career_advisor/             # Main Django app
├── src/
│   ├── rag/                   # RAG pipeline
│   └── utils/                 # PDF & resume parsing
├── templates/                 # HTML templates
├── static/                    # CSS, JS, images
├── media/                     # Uploaded files
├── data/                      # Sample resume
└── requirements.txt           # Dependencies

• Python 3.8+
• pip package manager

# Clone the repository
git clone <repository-url>
cd Sahay-AI

# Install dependencies
pip install -r requirements.txt

# Run migrations
python manage.py migrate

# Start the development server
python manage.py runserver

1. Upload Resume: Use the upload interface
2. View Analysis: See parsed skills, projects, education
3. Chat with AI: Ask career-related questions
4. Get Recommendations: Receive personalized guidance

• Upload PDF resume
• Get instant analysis of skills, projects, education
• View completeness score and recommendations

• Ask questions about your career
• Get personalized advice based on your resume
• Receive skill development recommendations

• Compare current skills with target role
• Get specific learning recommendations
• View skill development roadmap

• Discover suitable career trajectories
• Get industry insights and guidance
• Understand role requirements

• Advanced PDF Parsing: PyMuPDF with custom algorithms
• RAG Integration: State-of-the-art AI career guidance
• Performance Optimization: CPU-optimized AI models
• Modern Architecture: Django + AI + Vector Database

• Career Guidance: Personalized AI recommendations
• Skill Development: Gap analysis and learning paths
• Resume Optimization: Quality assessment and suggestions
• Professional Growth: Long-term career planning

• Before: PyPDF2 - 0 characters extracted
• After: PyMuPDF - 3,118 characters extracted

• Model Caching: Global model caching for speed
• CPU Optimization: torch.float32, low_cpu_mem_usage
• ONNX Support: Optional ONNX runtime for faster inference
• Memory Management: Efficient resource usage

Sahay AI - Your intelligent career companion powered by AI.

• Email: [email protected]
• LinkedIn: /linkedin.com/in/sohamtripathy/
• GitHub: github.com/SOHAM-3T