🎓 Interview Copilot

Your AI-Powered EdTech Assistant for Mastering Interviews

Empowering students, professionals, and learners to confidently navigate technical and behavioral interviews with real-time AI guidance.

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🚀 About The Project

Interview Copilot is a cutting-edge EdTech application designed to bridge the gap between learning and landing your dream job. Running locally as a lightweight desktop application or accessible online, it acts as a real-time mentor during your mock or real interviews.

By leveraging advanced AI, Interview Copilot listens, analyzes, and provides instant, context-aware suggestions—helping you learn how to answer, not just what to answer.

✨ Key Features

• 🎙️ Real-time Audio Transcription: Seamlessly transcribes interview questions on the fly.
• 🧠 AI-Powered Guidance: Instantly generates hints, talking points, and structured answers.
• 💻 Desktop Overlay: A discreet, floating desktop app (powered by Electron) that stays out of your way.
• 🌐 Web Ready: Can also be hosted on the cloud via Vercel for browser-based practice.
• 🔒 Privacy Focused: Your local configurations and private API keys stay on your machine.

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🛠️ Tech Stack

• Frontend Core: React 19, Vite
• Styling: Tailwind CSS 4, Radix UI, shadcn/ui
• Desktop Environment: Electron
• Routing & State: TanStack Router, React Query
• AI Integrations: AI SDK (OpenAI, Google, Groq)

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📥 Getting Started (For Users)

If you just want to use the application, you do not need to build it from source!

1. Head over to the Releases page.
2. Download the latest InterviewCopilot-Public.zip.
3. Extract the folder and run InterviewCopilot-Public.exe.
4. Start practicing!

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💻 Local Development (For Contributors)

Want to contribute, add features, or run the project locally? Follow these steps:

Prerequisites

• Node.js (v18+)
• Bun (Recommended) or npm

Installation

1. Clone the repository:

   git clone https://github.com/sahilparihar-git/interview-whisperer.git
   cd interview-whisperer

2. Install dependencies:

   bun install

   (or use npm install)

3. Set up Environment Variables: Create a .env file in the root directory and add your necessary API keys (e.g., OpenAI, Groq).

4. Run in Development Mode (Web):

   bun run dev

5. Run the Desktop App (Electron): Open a separate terminal and run:

   bun run electron:dev

Building for Production

To package the application into a Windows .exe:

bun run electron:build-public

The compiled build will be available in the electron-release/ directory.

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📜 License

Distributed under the MIT License. See LICENSE for more information.

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Built with ❤️ for learners everywhere.