AI Interview Simulator: Prep Faster, Ace the Interview, and Go Touch Grass published: true

A developer built AI Interview Simulator, an open-source interview practice tool that uses open-weight LLMs served through the Groq API to generate questions and structured JSON evaluations. The app extracts text from uploaded resumes in memory via multer and pdf-parse, runs five-minute mock interview drills, and returns instant answer coaching and a performance report, with a Vercel frontend and Render backend.

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass https://dev.to/challenges/hacktoberfest-week1-2026-10-05 Preparing for interviews is notoriously draining. Developers and professionals spend hundreds of hours glued to screens grinding through static question banks and repetitive mock sessions. AI Interview Simulator was built to solve this: a high-efficiency pair interviewer powered by open-source AI that delivers hyper-focused practice. Upload your resume or choose your field, run a realistic 5-minute drill, get instant answer coaching and model solutions, and close your laptop to go touch grass. The entire codebase is open-source: Practice job interviews with an AI powered by open-source LLMs via Groq. Get real questions, instant feedback, and a full performance report — free. Built for Hacktoberfest 2026 Open-Source AI Challenge . 🌐 Live Demo Frontend : https://ai-interview-simulator-nu-weld.vercel.app/ https://ai-interview-simulator-nu-weld.vercel.app/ ⚡ Live API Backend : https://ai-interview-simulator-9v89.onrender.com/ https://ai-interview-simulator-9v89.onrender.com/ multer and pdf-parse for in-memory resume extraction, deployed on Render. qwen/qwen3.8-27b via high-speed Groq API for zero-latency question generation and structured JSON evaluations. Open-source AI and open-weight models democratize career preparation: Built with ❤️ for hf26challenge