Liftoff is an AI-powered mock interview simulator designed for individuals seeking to improve their interview skills. It offers automated feedback on recorded interviews, leveraging advanced AI models for transcription and analysis.

How It Works

The application utilizes FFmpeg.wasm to transcode raw video recordings into a standardized MP3 audio format, accommodating various browser codecs. This audio is then processed by OpenAI's Whisper API for transcription. Subsequently, the transcribed text is fed into OpenAI's gpt-3.5-turbo model to generate real-time, edge-streamed feedback on the interview performance.

Quick Start & Requirements

• Install via npx create-next-app liftoff --example "https://github.com/Tameyer41/liftoff"
• Requires Node.js.
• Deployment to Vercel is supported via a one-click deploy button.
• Official documentation and demo links are not explicitly provided in the README.

Highlighted Details

• Built with Next.js, leveraging React for a performant user experience.
• Utilizes Tailwind CSS and Framer Motion for UI development and animations.
• Integrates HeadlessUI for accessible, unstyled components.
• Employs TypeScript for end-to-end type safety and Prettier/ESLint for code quality.
• Features dynamic Open Graph image generation at the edge.

Maintenance & Community

• The project is authored by Tyler Meyer (@tmeyer_me).
• No specific community channels (Discord, Slack) or roadmap are mentioned.

Licensing & Compatibility

• The README does not specify a license.
• Compatibility for commercial use or closed-source linking is not detailed.

Limitations & Caveats

The project's reliance on external APIs (OpenAI, Upstash) implies potential costs and rate limits. Specific details regarding data privacy, error handling for API failures, and comprehensive testing across different browsers and interview scenarios are not elaborated upon in the README.