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@promptbook/javascript

Promptbook: Turn your company's scattered knowledge into AI ready books

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โœจ Promptbook: AI Agents

Create persistent AI agents that turn your company's scattered knowledge into action โ€” powered by the Agents Server

NPM Version of Promptbook logo Promptbook Quality of package Promptbook logo Promptbook Known Vulnerabilities ๐Ÿงช Test Books ๐Ÿงช Test build ๐Ÿงช Lint ๐Ÿงช Spell check ๐Ÿงช Test types Issues

๐ŸŒŸ New Features

  • Gemini 3 Support
โš  Warning: This is a pre-release version of the library. It is not yet ready for production use. Please look at latest stable release.

๐Ÿ“ฆ Package @promptbook/javascript

To install this package, run:

# Install entire promptbook ecosystem
npm i ptbk

# Install just this package to save space
npm install @promptbook/javascript

JavaScript execution engine for Promptbook, providing secure JavaScript code execution within promptbook pipelines and script tasks.

๐ŸŽฏ Purpose and Motivation

This package provides a secure JavaScript execution environment for Promptbook pipelines. It enables the execution of JavaScript code in SCRIPT tasks, allowing for complex data transformations, calculations, and logic within promptbook workflows while maintaining security and isolation.

๐Ÿ”ง High-Level Functionality

The package provides JavaScript execution capabilities:

  • Script Task Execution: Execute JavaScript code within promptbook SCRIPT tasks
  • Variable Extraction: Analyze JavaScript code to extract variable dependencies
  • Postprocessing Functions: Built-in JavaScript functions for common postprocessing tasks
  • Secure Execution: Safe execution environment with proper isolation
  • Multiple Execution Modes: Support for different JavaScript execution strategies

โœจ Key Features

  • ๐Ÿ”’ Secure Execution - Safe JavaScript execution with proper sandboxing
  • ๐Ÿ“ Script Tasks - Execute JavaScript code within promptbook pipelines
  • ๐Ÿ”ง Variable Analysis - Extract variable dependencies from JavaScript code
  • ๐Ÿ“Š Postprocessing Functions - Built-in functions for common data transformations
  • โšก Multiple Execution Modes - Different execution strategies for various use cases
  • ๐Ÿ›ก๏ธ Error Handling - Comprehensive error handling for script execution
  • ๐ŸŽฏ Pipeline Integration - Seamless integration with promptbook execution flow

๐Ÿ“ฆ Exported Entities

Version Information

  • BOOK_LANGUAGE_VERSION - Current book language version
  • PROMPTBOOK_ENGINE_VERSION - Current engine version

Execution Tools

  • JavascriptEvalExecutionTools - JavaScript execution tools using eval
  • JavascriptExecutionTools - Standard JavaScript execution tools

Postprocessing

  • POSTPROCESSING_FUNCTIONS - Built-in postprocessing functions for JavaScript

Utilities

  • extractVariablesFromJavascript - Extract variable dependencies from JavaScript code

๐Ÿ’ก This package provides JavaScript execution for promptbook applications. For the core functionality, see @promptbook/core or install all packages with npm i ptbk

Rest of the documentation is common for entire promptbook ecosystem:

๐Ÿ“– The Book Whitepaper

Promptbook lets you create persistent AI agents that work on real goals for your company. The Agents Server is the heart of the project โ€” a place where your AI agents live, remember context, collaborate in teams, and get things done.

Nowadays, the biggest challenge for most business applications isn't the raw capabilities of AI models. Large language models such as GPT-5.2 and Claude-4.5 are incredibly capable.

The main challenge lies in managing the context, providing rules and knowledge, and narrowing the personality.

In Promptbook, you define your agents using simple Books โ€” a human-readable language that is explicit, easy to understand and write, reliable, and highly portable. You then deploy them to the Agents Server, where they run persistently and work toward their goals.

Paul Smith

PERSONA You are a company lawyer.
Your job is to provide legal advice and support to the company and its employees.
GOAL Respond to incoming legal inquiries via email and keep the company website updated with the latest legal policies.
RULE You are knowledgeable, professional, and detail-oriented.
KNOWLEDGE https://company.com/company-policies.pdf
KNOWLEDGE https://company.com/internal-documents/employee-handbook.docx
USE EMAIL
USE BROWSER
TEAM You are part of the legal team of Paul Smith & Associรฉs, you discuss with {Emily White}, the head of the compliance department. {George Brown} is expert in corporate law and {Sophia Black} is expert in labor law.

Aspects of great AI agent

We have created a language called Book, which allows you to write AI agents in their native language and create your own AI persona. Book provides a guide to define all the traits and commitments.

You can look at it as "prompting" (or writing a system message), but decorated by commitments.

Commitments are special syntax elements that define contracts between you and the AI agent. They are transformed by Promptbook Engine into low-level parameters like which model to use, its temperature, system message, RAG index, MCP servers, and many other parameters. For some commitments (for example RULE commitment) Promptbook Engine can even create adversary agents and extra checks to enforce the rules.

Persona commitment

Personas define the character of your AI persona, its role, and how it should interact with users. It sets the tone and style of communication.

Paul Smith & Associรฉs

PERSONA You are a company lawyer.
Your job is to provide legal advice and support to the company and its employees.

Goal commitment

Goals define what the agent should actively work toward. Unlike a chatbot that only responds when asked, an agent with goals takes initiative and works on tasks persistently on the Agents Server.

Paul Smith & Associรฉs

PERSONA You are a company lawyer.
Your job is to provide legal advice and support to the company and its employees.
GOAL Respond to incoming legal inquiries via email within 24 hours.
GOAL Keep the company website updated with the latest legal policies and compliance information.

Knowledge commitment

Knowledge Commitment allows you to provide specific information, facts, or context that the AI should be aware of when responding.

This can include domain-specific knowledge, company policies, or any other relevant information.

Promptbook Engine will automatically enforce this knowledge during interactions. When the knowledge is short enough, it will be included in the prompt. When it is too long, it will be stored in vector databases and RAG retrieved when needed. But you don't need to care about it.

Paul Smith & Associรฉs

PERSONA You are a company lawyer.
Your job is to provide legal advice and support to the company and its employees.
GOAL Respond to incoming legal inquiries via email within 24 hours.
GOAL Keep the company website updated with the latest legal policies and compliance information.
KNOWLEDGE https://company.com/company-policies.pdf
KNOWLEDGE https://company.com/internal-documents/employee-handbook.docx

Rule commitment

Rules will enforce specific behaviors or constraints on the AI's responses. This can include ethical guidelines, communication styles, or any other rules you want the AI to follow.

Depending on rule strictness, Promptbook will either propagate it to the prompt or use other techniques, like adversary agent, to enforce it.

Paul Smith & Associรฉs

PERSONA You are a company lawyer.
Your job is to provide legal advice and support to the company and its employees.
GOAL Respond to incoming legal inquiries via email within 24 hours.
GOAL Keep the company website updated with the latest legal policies and compliance information.
RULE Always ensure compliance with local laws and regulations.
RULE Never provide legal advice outside your area of expertise.
RULE Never provide legal advice about criminal law.
KNOWLEDGE https://company.com/company-policies.pdf
KNOWLEDGE https://company.com/internal-documents/employee-handbook.docx

Use commitments

Use commitments grant the agent real capabilities โ€” tools it can use to interact with the outside world. USE EMAIL lets the agent send emails, USE BROWSER lets it access and read web content, USE SEARCH ENGINE lets it search the web, and many more.

These are what turn a chatbot into a persistent agent that actually does work.

Paul Smith & Associรฉs

PERSONA You are a company lawyer.
Your job is to provide legal advice and support to the company and its employees.
GOAL Respond to incoming legal inquiries via email within 24 hours.
GOAL Keep the company website updated with the latest legal policies and compliance information.
RULE Always ensure compliance with local laws and regulations.
RULE Never provide legal advice outside your area of expertise.
RULE Never provide legal advice about criminal law.
KNOWLEDGE https://company.com/company-policies.pdf
KNOWLEDGE https://company.com/internal-documents/employee-handbook.docx
USE EMAIL
USE BROWSER
USE SEARCH ENGINE

Team commitment

Team commitment allows you to define the team structure and advisory fellow members the AI can consult with. This allows the AI to simulate collaboration and consultation with other experts, enhancing the quality of its responses.

Paul Smith & Associรฉs

PERSONA You are a company lawyer.
Your job is to provide legal advice and support to the company and its employees.
GOAL Respond to incoming legal inquiries via email within 24 hours.
GOAL Keep the company website updated with the latest legal policies and compliance information.
RULE Always ensure compliance with local laws and regulations.
RULE Never provide legal advice outside your area of expertise.
RULE Never provide legal advice about criminal law.
KNOWLEDGE https://company.com/company-policies.pdf
KNOWLEDGE https://company.com/internal-documents/employee-handbook.docx
USE EMAIL
USE BROWSER
USE SEARCH ENGINE
TEAM You are part of the legal team of Paul Smith & Associรฉs, you discuss with {Emily White}, the head of the compliance department. {George Brown} is expert in corporate law and {Sophia Black} is expert in labor law.

Promptbook Ecosystem

Promptbook is an ecosystem of tools centered around the Agents Server โ€” a production-ready platform for running persistent AI agents.

Agents Server

The Agents Server is the primary way to use Promptbook. It is a web application where your AI agents live and work. You can create agents, give them knowledge and rules using the Book language, organize them into teams, and let them work on goals persistently. The Agents Server provides a UI for managing agents, an API for integrating them into your applications, and can be self-hosted via Docker or deployed on Vercel.

Promptbook Engine

The Promptbook Engine is the open-source core that powers everything. It parses the Book language, applies commitments, manages LLM provider integrations, and executes agents. The Agents Server is built on top of the Engine. If you need to embed agent capabilities directly into your own application, you can use the Engine as a standalone TypeScript/JavaScript library via NPM packages.

๐Ÿ’œ The Promptbook Project

Promptbook project is an ecosystem centered around the Agents Server โ€” a platform for creating, deploying, and running persistent AI agents. Following is a list of the most important pieces of the project:

ProjectAbout
โญ Agents Server The primary way to use Promptbook. A production-ready platform where your AI agents live โ€” create, manage, deploy, and interact with persistent agents that work on goals. Available as a hosted service or self-hosted via Docker.
Book language Human-friendly, high-level language that abstracts away low-level details of AI. It allows to focus on personality, behavior, knowledge, and rules of AI agents rather than on models, parameters, and prompt engineering. There is also a plugin for VSCode to support .book file extension
Promptbook Engine The open-source core that powers the Agents Server. Can also be used as a standalone TypeScript/JavaScript library to embed agent capabilities into your own applications. Released as multiple NPM packages.

๐ŸŒ Community & Social Media

Join our growing community of developers and users:

PlatformDescription
๐Ÿ’ฌ DiscordJoin our active developer community for discussions and support
๐Ÿ—ฃ๏ธ GitHub DiscussionsTechnical discussions, feature requests, and community Q&A
๐Ÿ‘” LinkedInProfessional updates and industry insights
๐Ÿ“ฑ FacebookGeneral announcements and community engagement
๐Ÿ”— ptbk.ioOfficial landing page with project information

๐Ÿ–ผ๏ธ Product & Brand Channels

Promptbook.studio

๐Ÿ“ธ Instagram @promptbook.studioVisual updates, UI showcases, and design inspiration

๐Ÿ“š Documentation

See detailed guides and API reference in the docs or online.

๐Ÿ”’ Security

For information on reporting security vulnerabilities, see our Security Policy.

๐Ÿ“ฆ Deployment & Packages

The fastest way to get started is with the Agents Server:

  • ๐Ÿ‹ Docker image โ€” Self-host the Agents Server with full control over your data
  • โ˜๏ธ Hosted Agents Server โ€” Start creating agents immediately, no setup required

NPM Packages (for developers embedding the Engine)

If you want to embed the Promptbook Engine directly into your application, the library is divided into several packages published from a 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:

General LLM / AI terms

  • Prompt drift is a phenomenon where the AI model starts to generate outputs that are not aligned with the original prompt. This can happen due to the model's training data, the prompt's wording, or the model's architecture.
  • Pipeline, workflow scenario or chain is a sequence of tasks that are executed in a specific order. In the context of AI, a pipeline can refer to a sequence of AI models that are used to process data.
  • Fine-tuning is a process where a pre-trained AI model is further trained on a specific dataset to improve its performance on a specific task.
  • Zero-shot learning is a machine learning paradigm where a model is trained to perform a task without any labeled examples. Instead, the model is provided with a description of the task and is expected to generate the correct output.
  • Few-shot learning is a machine learning paradigm where a model is trained to perform a task with only a few labeled examples. This is in contrast to traditional machine learning, where models are trained on large datasets.
  • Meta-learning is a machine learning paradigm where a model is trained on a variety of tasks and is able to learn new tasks with minimal additional training. This is achieved by learning a set of meta-parameters that can be quickly adapted to new tasks.
  • Retrieval-augmented generation is a machine learning paradigm where a model generates text by retrieving relevant information from a large database of text. This approach combines the benefits of generative models and retrieval models.
  • Longtail refers to non-common or rare events, items, or entities that are not well-represented in the training data of machine learning models. Longtail items are often challenging for models to predict accurately.

Note: This section is not a complete dictionary, more list of general AI / LLM terms that has connection with Promptbook

๐Ÿ’ฏ Core concepts

Advanced concepts

Data & Knowledge ManagementPipeline Control
Language & Output ControlAdvanced Generation

๐Ÿ” View more concepts

๏ฟฝ Agents Server

The Agents Server is the primary way to use Promptbook. It is a production-ready platform where you create, deploy, and manage persistent AI agents that work toward goals. Agents remember context across conversations, collaborate in teams, and follow the rules and knowledge you define in the Book language.

  • Hosted at gallery.ptbk.io โ€” start creating agents immediately
  • Self-hosted via Docker โ€” full control over your data and infrastructure
  • API for integrating agents into your own applications

๐Ÿš‚ Promptbook Engine

The Engine is the open-source core that powers the Agents Server. If you need to embed agent capabilities directly into your TypeScript/JavaScript application, you can use it as a standalone library.

Schema of Promptbook Engine

โž•โž– When to use Promptbook?

โž• When to use

  • When you want to deploy persistent AI agents that work on goals for your company
  • When you need agents with specific personalities, knowledge, and rules tailored to your business
  • When you want agents that collaborate in teams and consult each other
  • When you need to integrate AI agents into your existing applications via API
  • When you want to self-host your AI agents with full control over data and infrastructure
  • When you are writing an app that generates complex things via LLM โ€” like websites, articles, presentations, code, stories, songs,...
  • When you want to version your agent definitions and test multiple versions
  • When you want to log agent execution and backtrace issues

See more

โž– When not to use

  • When a single simple prompt already 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 โ€” 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.

๐Ÿ“… Changelog

See CHANGELOG.md

๐Ÿ“œ License

This project is licensed under BUSL 1.1.

๐Ÿค Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

You can also โญ star the project, follow us on GitHub or various other social networks.We are open to pull requests, feedback, and suggestions.

๐Ÿ†˜ Support & Community

Need help with Book language? We're here for you!

We welcome contributions and feedback to make Book language better for everyone!

Keywords

ai

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Package last updated on 24 Mar 2026

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