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@promptbook/remote-client

Supercharge your use of large language models

  • 0.73.0
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Promptbook logo - cube with letters P and B Promptbook

Build responsible, controlled and transparent applications on top of LLM models!

NPM Version of Promptbook logo - cube with letters P and B Promptbook Quality of package Promptbook logo - cube with letters P and B Promptbook Known Vulnerabilities Issues

โœจ New Features

  • ๐Ÿ’™ Working on the Book language v1
  • ๐Ÿ“š Support of .docx, .doc and .pdf documents
  • โœจ Support of OpenAI o1 model

๐Ÿ“ฆ Package @promptbook/remote-client

To install this package, run:

# Install entire promptbook ecosystem
npm i ptbk

# Install just this package to save space
npm install @promptbook/remote-client

Rest of the documentation is common for entire promptbook ecosystem:

๐Ÿค The Promptbook Whitepaper

If you have a simple, single prompt for ChatGPT, GPT-4, Anthropic Claude, Google Gemini, Llama 3, or whatever, it doesn't matter how you integrate it. Whether it's calling a REST API directly, using the SDK, hardcoding the prompt into the source code, or importing a text file, the process remains the same.

But often you will struggle with the limitations of LLMs, such as hallucinations, off-topic responses, poor quality output, language and prompt drift, word repetition repetition repetition repetition or misuse, lack of context, or just plain w๐’†๐ขrd resp0nses. When this happens, you generally have three options:

  1. Fine-tune the model to your specifications or even train your own.
  2. Prompt-engineer the prompt to the best shape you can achieve.
  3. Orchestrate multiple prompts in a pipeline to get the best result.

In all of these situations, but especially in 3., the โœจ Promptbook can make your life waaaaaaaaaay easier.

  • Separates concerns between prompt-engineer and programmer, between code files and prompt files, and between prompts and their execution logic. For this purpose, it introduces a new language called the ๐Ÿ’™ Book.
  • Book allows you to focus on the business logic without having to write code or deal with the technicalities of LLMs.
  • Forget about low-level details like choosing the right model, tokens, context size, temperature, top-k, top-p, or kernel sampling. Just write your intent and persona who should be responsible for the task and let the library do the rest.
  • We have built-in orchestration of pipeline execution and many tools to make the process easier, more reliable, and more efficient, such as caching, compilation+preparation, just-in-time fine-tuning, expectation-aware generation, agent adversary expectations, and more.
  • Sometimes even the best prompts with the best framework like Promptbook :) can't avoid the problems. In this case, the library has built-in anomaly detection and logging to help you find and fix the problems.
  • Versioning is build in. You can test multiple A/B versions of pipelines and see which one works best.
  • Promptbook is designed to use RAG (Retrieval-Augmented Generation) and other advanced techniques to bring the context of your business to generic LLM. You can use knowledge to improve the quality of the output.

๐Ÿ’™ Book language (for prompt-engineer)

Promptbook pipelines are written in markdown-like language called Book. It is designed to be understandable by non-programmers and non-technical people.

# ๐ŸŒŸ My first Book

-   PERSONA Jane, marketing specialist with prior experience in writing articles about technology and artificial intelligence
-   KNOWLEDGE https://ptbk.io
-   KNOWLEDGE ./promptbook.pdf
-   EXPECT MIN 1 Sentence
-   EXPECT MAX 1 Paragraph

> Write an article about the future of artificial intelligence in the next 10 years and how metalanguages will change the way AI is used in the world.
> Look specifically at the impact of Promptbook on the AI industry.

-> {article}

๐Ÿ“ฆ Packages (for developers)

This library is divided into several packages, all are published from single monorepo. You can install all of them at once:

npm i ptbk

Or you can install them separately:

โญ Marked packages are worth to try first

๐Ÿ“š Dictionary

The following glossary is used to clarify certain concepts:

Core concepts

Advanced concepts

๐Ÿ”Œ Usage in Typescript / Javascript

โž•โž– When to use Promptbook?

โž• When to use

  • When you are writing app that generates complex things via LLM - like websites, articles, presentations, code, stories, songs,...
  • When you want to separate code from text prompts
  • When you want to describe complex prompt pipelines and don't want to do it in the code
  • When you want to orchestrate multiple prompts together
  • When you want to reuse parts of prompts in multiple places
  • When you want to version your prompts and test multiple versions
  • When you want to log the execution of prompts and backtrace the issues

See more

โž– When not to use

  • When you have already implemented single simple prompt and it works fine for your job
  • When OpenAI Assistant (GPTs) is enough for you
  • When you need streaming (this may be implemented in the future, see discussion).
  • When you need to use something other than JavaScript or TypeScript (other languages are on the way, see the discussion)
  • When your main focus is on something other than text - like images, audio, video, spreadsheets (other media types may be added in the future, see discussion)
  • When you need to use recursion (see the discussion)

See more

๐Ÿœ Known issues

๐Ÿงผ Intentionally not implemented features

โ” FAQ

If you have a question start a discussion, open an issue or write me an email.

โŒš Changelog

See CHANGELOG.md

๐Ÿ“œ License

Promptbook by Pavol Hejnรฝ is licensed under CC BY 4.0

๐ŸŽฏ Todos

See TODO.md

๐Ÿ–‹๏ธ Contributing

I am open to pull requests, feedback, and suggestions. Or if you like this utility, you can โ˜• buy me a coffee or donate via cryptocurrencies.

You can also โญ star the promptbook package, follow me on GitHub or various other social networks.

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Package last updated on 07 Nov 2024

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