Commonly used Prompt Engineering Tools

Prompt engineering is the process of designing accurate and contextually appropriate prompts to interact with generative AI models. Prompt engineering tools provide various features and functionalities to optimize the creation of prompts for desired outcomes.

Common functionalities of prompt engineering tools include suggestions for prompts based on input or desired output, structuring prompts for better contextual communication, iterative refinement of prompts, bias mitigation in AI model responses, domain-specific aid with libraries of predefined prompts, and reducing the likelihood of biased or inappropriate outputs.

• IBM Watsonx.ai, which offers a platform with integrated tools for prompt experimentation and prompt building based on different foundation models.

  
  

• Spellbook is an integrated development environment (IDE) by Scale AI that allows users to build applications based on language models (LLMs) and experiment with prompts for various use cases - To draft and review legal contracts

  
  

• Dust provides a web user interface for writing and chaining prompts together, with support for custom coding language and API integration. - Link to Github Repository

  
  

• PromptPerfect is a tool used to optimize prompts for different LLMs or text-to-image models, supporting common text and image models and providing features for autocomplete, optimization, and refinement of prompts.

  
  

• Other tools and interfaces mentioned include GitHub, OpenAI Playground, LangChain, and PromptBase, which provide resources for prompt engineering and experimentation.

  
  

• PromptBase is a marketplace for prompts, allowing users to buy prompts specific to their requirements or sell their own crafted prompts for popular generative AI tools and models.

Note: This is summary from the course Generative AI: Prompt Engineering Basics.

A more detailed course on prompt engineering is available here