Interview Answer Coaching System

A containerized full-stack platform that lets users practice interview questions through live recording, automatic transcription, and AI-driven feedback.

Code

System Components

• 🧠 ML Client: Captures audio, transcribes with OpenAI, generates structured feedback.
• 🌐 Web App (Flask): Dashboard to record answers, submit sessions, and review results.
• 🗄️ MongoDB: Central store for transcripts, scores, and coaching tips.

Features

• In-browser recording with immediate transcription and rubric-style feedback.
• Session history with stored transcripts and model comments for review.
• Containerized services for reproducible local dev and deployment.

Tech Stack

• Python, Flask
• OpenAI API (speech-to-text & feedback)
• MongoDB
• Docker / Docker Compose
• HTML5 Audio, JavaScript
• Git
• CI/CD