Cheetah AI
The GitHub repository "leetcode-mafia/cheetah" is described as a Whisper and GPT-based app that helps users to "crush remote SWE interviews...
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What is Cheetah AI?
Cheetah is an AI-powered macOS application designed specifically to help users practice and excel in software engineering interviews. It offers real-time coaching by transcribing interview audio conversations and generating intelligent responses, hints, and code solutions using advanced AI models. Targeted at aspiring software engineers preparing for remote technical interviews, it simulates real-world scenarios with live coding integration, allowing users to receive discreet assistance during mock sessions.
The app utilizes OpenAI's Whisper via whisper.cpp for local, real-time audio transcription on Apple Silicon Macs, ensuring low latency and privacy by running models on-device. Users input their own OpenAI API key to power GPT-4 (or GPT-3.5-turbo) for creating tailored answers to interviewer questions, refining them based on follow-ups, and analyzing code from browser-based coding platforms. Key features include simple UI buttons for Answer, Refine, and Analyze functions, plus support for capturing both sides of audio via loopback drivers like BlackHole.
Ideal for candidates tired of rote LeetCode grinding, Cheetah provides on-the-fly guidance to build confidence and problem-solving skills. As an open-source tool under CC0-1.0 license, it's buildable from GitHub source, requiring macOS 13.1+, SDL2, and whisper.cpp dependencies. While powerful for practice, it emphasizes mock interview use only, with users bearing responsibility for AI-generated outputs which may occasionally be inaccurate.
Its browser extension enables code log analysis from live coding environments, though limited to Firefox with manual temporary loading. This makes Cheetah a niche, high-performance coach for Mac users aiming to 'crush' tech interviews through AI augmentation rather than traditional study methods.
Cheetah AI pricing
Pricing model: Free
Free open-source tool; no paid plans or free tier restrictions. Requires users to supply their own OpenAI API key for GPT-4/GPT-3.5-turbo usage, incurring separate costs based on OpenAI pricing.
Cheetah AI pros
- Real-time Whisper transcription on Apple Silicon
- GPT-4 powered answer generation for questions
- Refine button for iterative answer updates
- Analyze code and logs from browser extension
- Captures both interviewer and candidate audio
- Local processing for privacy and speed
- Simple three-button UI for quick actions
- Supports highlighting text for detailed refinement
- Integrates with Zoom/Google Meet via BlackHole
- Open-source with 4.2k GitHub stars
- Optimized for M1/M2 Macs low latency
- Compatible with GPT-3.5-turbo fallback
- Simulates remote interview environments
- No subscription, uses own OpenAI key
- Free to build and use indefinitely
- Live transcription snippet preview
- Temporary Firefox extension for platforms
Cheetah AI cons
- Mac-only, requires Apple Silicon
- Needs macOS 13.1 or later
- Requires own OpenAI API key costs
- Browser extension only for Firefox
- Manual temporary extension loading
- Complex audio loopback setup needed
- Slow in debug mode transcription
- Build requires whisper.cpp and SDL2
- Intended for mocks only, risky otherwise
- May generate incorrect solutions
- No pre-built app binaries provided
Frequently asked questions about Cheetah AI
What macOS version is required for Cheetah?
Cheetah requires macOS 13.1 or later, with optimal performance on recent Apple Silicon Macs like M1 or M2 for local Whisper transcription.
How does Cheetah handle audio transcription?
It uses Whisper via Georgi Gerganov's whisper.cpp running locally on your Mac, capturing real-time audio from selected inputs; for full conversations in Zoom or Meet, set up BlackHole loopback driver as a Multi-Output Device without using it as video app input.
What AI model does Cheetah use for responses?
Cheetah leverages GPT-4 (preferred) or GPT-3.5-turbo via your own OpenAI API key to generate hints, answers, refinements, and code analysis; enter the key in the app to start using these features.
How do I install the browser extension for code analysis?
Firefox only: Edit ./extension/manifest.json to add your coding platform's domain to 'matches', then go to about:debugging > This Firefox > Load Temporary Add-on > select manifest.json; reload for each session.
What are the main buttons in the Cheetah UI?
Answer generates responses to interviewer questions; Refine updates answers for new constraints or highlights for details; Analyze reviews code/logs from your browser's live coding environment via the extension.
Is Cheetah suitable for real interviews or only practice?
Strictly intended for mock interviews only, as per disclaimer; it may produce incorrect or inappropriate solutions, and users take full responsibility for all generated information.
How do I build and run Cheetah from source?
Prerequisites: macOS 13.1+, checkout whisper.cpp in ../whisper.cpp, brew install sdl2; then build the Swift app following repo instructions for optimal non-debug performance.
Does Cheetah provide pre-built app downloads?
No pre-built binaries; it's a source code repo where users compile the macOS app themselves using Xcode or similar, with releases like v1.3 available but focused on source.
Can Cheetah run on Intel Macs or Windows?
Designed for Apple Silicon Macs only due to whisper.cpp optimization; no Windows version, and Intel may underperform; recent Mac required for real-time capabilities.
What if transcription is slow in Cheetah?
Avoid debug mode which slows transcription significantly; ensure Apple Silicon Mac, proper audio input selection, and non-loopback for video apps; preview snippet confirms live operation.