GPT Prompt Engineer
An automated tool that generates, tests, and ranks AI prompts using GPT-4, GPT-3.5-Turbo, or Claude 3 to find the most effective ones.
What is GPT Prompt Engineer?
gpt-prompt-engineer is an automated prompt engineering tool that generates, tests, and ranks AI prompts to find the most effective ones for a given task. It uses models like GPT-4 or Claude 3 to create multiple prompt candidates, evaluates them against user-provided test cases, and applies an ELO rating system to rank their performance. This systematic approach replaces manual experimentation with data-driven optimization.
AI developers, researchers, and practitioners who regularly work with large language models and need to optimize prompts for specific tasks like content generation, classification, or email automation.
It automates the tedious and unpredictable process of prompt engineering, providing a reproducible method to identify high-performing prompts through competitive testing and ranking. The tool supports multiple LLM providers and includes specialized versions for classification and cost optimization.
Overview
gpt-prompt-engineer automates the experimental process of prompt engineering for large language models. It systematically generates multiple prompt candidates, evaluates them against user-defined test cases, and ranks them to identify the highest-performing prompts.
Key Features
- Prompt Generation — Creates a variety of possible prompts based on a use-case description using GPT-4, GPT-3.5-Turbo, or Claude 3 Opus.
- Prompt Testing — Tests each generated prompt against all provided test cases to evaluate performance.
- ELO Rating System — Ranks prompts competitively using an ELO system, starting each at 1200 and adjusting based on performance.
- Classification Support — Includes a specialized version for classification tasks that matches outputs to expected true/false labels.
- Claude 3 Integration — Features a version that auto-generates test cases and supports multiple input variables using Anthropic's Claude 3 models.
- Cost Optimization — Offers a Claude 3 Opus to Haiku conversion notebook to maintain quality while reducing latency and cost.
Philosophy
The project treats prompt engineering as an empirical optimization problem, replacing manual trial-and-error with systematic generation, testing, and ranking to discover the most effective prompts.
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