mshumer/gpt-prompt-engineer - GitHub vs Versy.ai

mshumer/gpt-prompt-engineer is an open source prompt engineering toolkit that generates, tests, and ranks candidate prompts for a task you define. You describe the use case, supply test cases, and the notebooks create multiple prompt variants, run them against every test case, and sort results with an ELO rating system starting at 1200. It ships as Jupyter notebooks you can run in Google Colab or locally.

Most prompt tools help you write one prompt at a time. gpt-prompt-engineer treats prompt selection like a tournament: dozens of candidates compete on your test cases, and the highest ELO scores surface the winners. Separate notebooks cover classification tasks, Claude 3 Opus with auto-generated test cases, and Opus-to-Haiku conversion for cheaper inference. Optional Weights & Biases and Portkey logging trace each run.

ML engineers, prompt engineers, and AI developers use it when they need reproducible prompt tuning instead of manual trial and error. The repo has 9.7k GitHub stars and runs on your own OpenAI or Anthropic API keys. It is free under the MIT license.

Versy.ai turns floor plans, moodboards, and design briefs into explorable spatial experiences you share through a browser link. Architects and interior teams upload references, build scenes in the cloud, and let clients walk a project before approvals instead of decoding static boards.

Render farms and video tours show space but rarely keep layout, materials, and light in one live conversation. Versy.ai combines navigable interiors, AI-generated 3D assets, cloud material libraries, and lighting edits so stakeholders evaluate scale and atmosphere in real time without VR headsets.

Interior studios, architecture firms, and brand experience teams in beta use it for client presentations, studio reviews, and spatial marketing landings where one shareable link replaces scattered PDFs and render decks.