Three Prompt Libraries you should know as a AI Engineer
Tags: generativeai, prompting, webdev, beginners
Published: 2024-07-11 09:54:15

As developers we write code to develop logic that eventually helps solve larger problems or automate a workflow that is unproductive for humans. 

When LLMs came into picture, prompting obviously became famous. Prompt Engineering became a art! 

Prompting became one of the key components in Generative AI and so the use of prompt libraries. These libraries provide predefined prompts that can be used to train AI models, making the development process more efficient and effective.

In this Blog, we’ll explore What is a Prompt library, how it boosts our workflow, Is it safe or not? Finally we will take a look at three Prompt Libraries to maximise productivity as an AI Engineer.

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/x7w7odhq26jfmdmap458.png)


## What is a Prompt Library?

A prompt library is not just a repository for prompts; it serves as a powerful solution for collaboration and knowledge sharing within your organisation.

Prompt libraries provide centralised platforms to store, organise, and access AI prompts, enabling teams to collaborate and streamline workflows. Therefore, the overarching purpose of a prompt library is to improve efficiency, performance, and collaboration. 

It enables your teams to discover and reuse prompts rapidly, avoiding duplicate work and accelerating development cycles. By providing access to highly optimised, pre-tested prompts, a prompt library ensures that the output quality of your projects is consistently high.

How Prompt libraries boosts your workflow?

Prompt libraries can significantly streamline AI development by providing ready-to-use prompts that can be easily integrated into your projects. 

Here are some ways prompt libraries can enhance your workflow:

* Simplified Task Execution: Prompt libraries provides a collection of predefined prompts that we can use for various tasks such as text generation, sentiment analysis, and more. With this we don’t have to create prompts from the scratch.

* Increased Productivity: Focus on higher-level tasks rather than spending time on prompt creation. This improves the overall productivity of the Team.

* Consistency and Quality: Prompt libraries ensure consistency in the prompts used across different projects. This consistency helps to produce higher quality AI outputs and reduces the chances of errors.

## Is it Safe to Use AI Prompt Libraries?

While prompt libraries offer numerous benefits, it is important to consider their safety and reliability. Here are some points we should keep in mind:

* Potential Risks: Using pre-defined prompts may introduce biases or inaccuracies if the prompts are not well-designed. It is crucial to review and test the prompts thoroughly before using them in production.

* Best Practices: To ensure safe and ethical use of AI prompt libraries, follow best practices such as regularly updating the libraries, validating the prompts, and monitoring the AI outputs for any anomalies.

* Reliability: Choose prompt libraries from reputable sources and communities. This ensures that the prompts are well-maintained and updated regularly.

## Three Prompt Libraries

### [Priompt](https://github.com/anysphere/priompt )

Priompt is a prompt library designed for creating prompts specifically for large language models (LLMs). It uses JSX syntax, similar to what we use in React development, to structure our prompts.

Here are some Key Features of Prompt: 

* JSX-based syntax: This makes building prompts more intuitive and easier to read, especially for those familiar with React. 
* Priorities: Priompt lets us to define priorities for different parts of your prompt. This helps the LLM determine what information to include in the context window based on its importance. 
* Control flow: Components like <first> enable you to control the flow of information in your prompt. For instance, you can use it to define fallbacks or shorten prompts that become too long.

Priompt aims to streamline the process of designing prompts for LLMs by providing a familiar and structured approach.

### [Promptfoo](https://www.promptfoo.dev/)

Promptfoo is an open-source toolkit designed to help developers improve the performance of large language models (LLMs) through  prompt engineering.

Here are some of the key features of Prompfoo:

* Systematic Evaluation: Prompfoo allows us to establish benchmarks and test cases to systematically evaluate the outputs of LLMs. This eliminates the need for time-consuming trial-and-error approaches. 

* Side-by-Side Comparisons: It enables you to compare the outputs of various prompts and see which ones generate the best results for your specific use case.

* Automatic Scoring: It can automatically score the outputs of LLMs based on the metrics you define. This helps you objectively assess the quality and effectiveness of the LLM's responses.
 
* Multiple LLM Support: Prompfoo works with a wide range of LLM APIs, including OpenAI, Anthropic, Azure, Google, and HuggingFace.

Overall, Prompfoo offers a structured approach to prompt engineering, helping developers build reliable prompts and fine-tune LLMs for their specific applications.


### [PromptHub](https://www.prompthub.us/ )

PromptHub is a platform designed to specifically address prompt testing and evaluation for large language models.

Here are some of the key features of PromptHub:

* Prompt Collection: Provides a library of pre-built prompts for common Natural Language Processing (NLP) tasks like text summarization, question answering, and code generation. 

* Prompt Testing: Allows you to test your own prompts or those from the library with different LLMs. 

* Evaluation Metrics: Offers various metrics to assess prompt performance, such as accuracy, relevance, and coherence of LLM outputs. 
* Hyperparameter Tuning: Enables you to experiment with different hyperparameters within a prompt (e.g., wording, examples) to optimize LLM performance. 

* Collaboration Features: May provide functionalities for sharing prompts and test results with team members (depending on the specific offering).
 
Overall, PromptHub is a valuable tool for those working with LLMs and prompt engineering. It streamlines the process of testing and evaluating prompts, leading to better-performing LLMs for various NLP tasks.


## To Summarise: 

Prompt Libraries play a vital role in enhancing the efficiency and effectiveness of Generative AI App development. By providing ready-to-use prompts, these libraries can simplify tasks, increase productivity, and ensure consistency and quality in AI outputs. 

We at Portkey have been building a [Open-source AI Gateway](https://github.com/Portkey-AI/gateway) that helps you build a resilient LLM-powered application in production. Join our community of AI practitioners to learn together and share more interesting updates.   

Happy Building!