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July 10, 2023
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GPT Prompt Engineer

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AI-powered prompt engineering for GitHub
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The 'gpt-prompt-engineer' is an AI tool available on GitHub, created by 'mshumer'. The tool aims to enhance the workload of data engineers working with Generative Pretrained Transformer models (GPT-models).

Its purpose is to automate and streamline the process of generating prompts that work well with GPT models. This is beneficial as it eliminates the manual task of trial-and-error in creating effective prompts, saving valuable time and resources.

The tool contains a number of files and notebooks like 'Instruct_Prompt > Base_Model_Prompt_Converter.ipynb', 'XL_to_XS_conversion.ipynb', 'claude_prompt_engineer.ipynb' and 'gpt_prompt_engineer.ipynb', which facilitate the prompt generation process.

The tool operates under MIT License providing users with the liberty to use, modify, and distribute the software. Through its public repository, it encourages wide community contribution towards its development.

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GPT Prompt Engineer was manually vetted by our editorial team and was first featured on July 10th 2023.

Pros and Cons

Pros

Public GitHub repository
Actively maintained
Automates prompt generation
Eliminates manual task
Saves time and resources
Multiple files and notebooks
Freedom to modify software
Supports community contribution
Prompt Generation
Resource Optimization
Jupyter Notebook support
Contains 'XL to XS conversion'
Automates Claude Prompt Engineering
Released under MIT License
ELO rating system
Handles classification tasks
Working with Anthropic's Claude 3 Opus
Optimizes Opus and Haiku models
Optional logging to Weights & Biases
Optional logging to Portkey
Possible to define multiple input variables
Optional use of Google Colab
Ability to add Anthropic API key
Built-in system for prompt testing and ranking
Generates, tests, and ranks prompts
Supports real-time information input
Handles Claude 3 Opus & Haiku conversion

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Cons

Requires API key setup
Manual test case configuration
Limited to Jupyter notebooks
High running costs possible
Optional logging to third-party platforms
Potential latency for large datasets

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