Smart AI Resume Analyzer
An intelligent full-stack application that parses PDF resumes using Gemini AI to extract structured data and provides dynamic document highlighting.
Project Overview
A full-stack application built with FastAPI and Vue.js, utilizing Google's Gemini 2.5 Flash model for high-speed, accurate resume parsing. The system provides a seamless experience for uploading PDF resumes, automatically extracting personal and professional information into a structured format, and dynamically highlighting specific keywords directly within the PDF document.
Key Features
Seamless drag-and-drop PDF resume uploading
Detailed implementation of this feature ensured optimal user experience and performance.
Automated extraction of structured data (skills, experience, contact info) via LLM
Detailed implementation of this feature ensured optimal user experience and performance.
Dynamic in-browser document highlighting based on search queries
Detailed implementation of this feature ensured optimal user experience and performance.
Modern, responsive, and fast frontend built with Vue 3 and Vite
Detailed implementation of this feature ensured optimal user experience and performance.
High-performance asynchronous backend powered by FastAPI
Detailed implementation of this feature ensured optimal user experience and performance.
Project Gallery
Challenges & Solutions
PDF Text Extraction & Manipulation
Reliably extracting raw text from unpredictable PDF layouts and adding visual annotations without corrupting the file geometry.
Integrated PyMuPDF (fitz) for robust text extraction and accurate spatial coordinate mapping, enabling the precise highlighting feature.
Unstructured Data Formatting
Converting highly variable unstructured resume texts into a consistent, strictly validated JSON format.
Leveraged Gemini 2.5 Flash with detailed system prompting and JSON response schema enforcement to guarantee reliable parsing regardless of the resume layout.
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