Building an Open-Source AI Mock Interviewer with Resume Personalization & Answer Coaching published: true

A developer built AI Interview Simulator, an open-source mock-interview tool that uses open-source LLMs via the Groq API to generate resume-personalized interview questions and coach candidates on their answers. The app parses uploaded resumes (PDF/TXT) with pdf-parse, supports pre-configured career paths across tech, data science, product, design, marketing, finance and healthcare, and returns STAR-method coaching, model answers, scores and hiring recommendations, with sessions stored in MongoDB Atlas. It runs on a React 18/Vite/Tailwind frontend deployed to Vercel and a Node.js/Express backend on Render.

🎃 Hacktoberfest 2026: The Open-Source AI Challenge Preparing for high-stakes interviews is often stressful. Static question lists don't recreate the pressure of dynamic conversations, nor do they probe into a candidate's actual resume claims. For Week 1 of the Hacktoberfest Open-Source AI Challenge, I built AI Interview Simulator — an intelligent pair interviewer powered entirely by open-source LLMs. 🚀 Live Demo & Links 💡 Key Features 1. 📄 Resume-Driven Question Generation: Upload your resume PDF/TXT or paste your experience. The AI analyzes your projects, tech stack, and career timeline to generate customized questions targeting your background. 2. 🎯 Multi-Industry Support: Pre-configured paths across Tech, AI & Data Science, Product, Design, Marketing & Sales, Finance, and Healthcare plus custom career write-in support . 3. 💡 "How to Improve Your Answer" Coaching: Instead of just a numerical score, candidates receive concrete coaching on how to elevate their response structure with STAR method, cite trade-offs, metrics, edge cases . 4. ✨ Ideal / Model Answers: An interactive reveal toggle showing the exact industry-standard response a senior hiring manager looks for. 5. 📈 Comprehensive Evaluation: Circular score meter, hiring decision recommendations Strongly Recommend, Recommend, Needs Work , top strengths, and areas to improve. 6. 💾 MongoDB Session History: Stores previous sessions to track performance over time. 🛠️ Tech Stack - Frontend: React 18, Vite, Tailwind CSS, Lucide Icons deployed on Vercel - Backend: Node.js, Express, Multer, pdf-parse deployed on Render - Database: MongoDB Atlas - AI Core: Open-Source LLMs via high-speed Groq API 🧠 Architecture Flow