What I Built

A fully offline-capable Windows desktop app that simulates a real guided interview
session — from topic selection to a generated PDF performance report at the end.

You pick your topic (Programming, CS Fundamentals, SQL, Behavioral, etc.), set
the difficulty, and the AI interviewer starts asking questions. You can answer
verbally or type code in the built-in editor. When the session ends, you get a
structured PDF with your scores, feedback, and recommended next steps.

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Tech Stack

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Features I'm Proud Of

• Live speech transcription — answer questions out loud, Whisper handles the rest
• Adaptive follow-up questions — the AI reads your answer and digs deeper
• Built-in code editor — for programming/DSA rounds
• Behavioural monitoring — tracks focus loss, face presence via camera, and filler words
• PDF report — per-question scores, structured feedback, next steps

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Why Desktop + Local-First?

Most AI interview tools are web apps that store your data on their servers.
I wanted something that runs entirely on your machine. You bring your own
Groq API key — no accounts, no backend, no data leaving your PC.

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Architecture: Electron + Python over IPC

The trickiest part was getting Electron and Python to talk reliably.
I went with stdin/stdout IPC — Electron spawns the Python process and
they communicate via structured messages. It's simple, cross-process,
and works well with PyInstaller packaging.

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Research Background

This started as a final-year college project and was presented as a
research paper at ICRTSET-2026 (April 2026).

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GitHub

🔗 https://github.com/VortexV7/AI-Mock-Interview-Assistant

The source is proprietary, but the README has architecture diagrams,
screenshots, and a full breakdown of the app flow.

Happy to answer questions about any of the design decisions in the comments!