@promptbook/cli
v0.78.4
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It's time for a paradigm shift. The future of software in plain English, French or Latin
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❄ Promptbook
❄ New Features
- 💙 Working the Book language v1.0.0
- 🖤 Run books from CLI -
npx ptbk run path/to/your/book
- 📚 Support of
.docx
,.doc
and.pdf
documents - ✨ Support of OpenAI o1 model
📦 Package @promptbook/cli
- Promptbooks are divided into several packages, all are published from single monorepo.
- This package
@promptbook/cli
is one part of the promptbook ecosystem.
To install this package, run:
# Install entire promptbook ecosystem
npm i ptbk
# Install as dev dependency
npm install --save-dev @promptbook/cli
# Or install globally
npm install --global @promptbook/cli
CLI utils for Promptbook. After install you can use promptbook
command in terminal:
Make your Promptbook Library
You can prebuild your own Promptbook library with ptbk make
command:
npx ptbk make ./books --format typescript --verbose
This will emit index.ts
with getPipelineCollection
function file in books
directory.
Then just use it:
import { createPipelineExecutor, assertsExecutionSuccessful } from '@promptbook/core';
import { $provideExecutionToolsForNode } from '@promptbook/node';
import { $provideFilesystemForNode } from '@promptbook/node';
import { getPipelineCollection } from './books'; // <- Importing from pre-built library
import { JavascriptExecutionTools } from '@promptbook/execute-javascript';
import { OpenAiExecutionTools } from '@promptbook/openai';
// ▶ Get single Pipeline
const promptbook = await getPipelineCollection().getPipelineByUrl(
`https://promptbook.studio/my-collection/write-article.book.md`,
);
// ▶ Create executor - the function that will execute the Pipeline
const pipelineExecutor = createPipelineExecutor({ pipeline, tools: await $provideExecutionToolsForNode() });
// ▶ Prepare input parameters
const inputParameters = { word: 'cat' };
// 🚀▶ Execute the Pipeline
const result = await pipelineExecutor(inputParameters);
// ▶ Fail if the execution was not successful
assertsExecutionSuccessful(result);
// ▶ Handle the result
const { isSuccessful, errors, outputParameters, executionReport } = result;
console.info(outputParameters);
This is simmilar to compilation process, during the build time the ptbk make
command will check promptbooks for errors, convert them to the more optimized format and build knowledge (RAG) for the pipeline collection.
There is also a javascript and json format available.
Prettify
npx ptbk prettify 'promptbook/**/*.book.md'
This will prettify all promptbooks in promptbook
directory and adds Mermaid graphs to them.
Rest of the documentation is common for entire promptbook ecosystem:
🤍 The Book Abstract
It's time for a paradigm shift! The future of software is in plain English, French or Latin.
During the computer revolution, we have seen multiple generations of computer languages, from the physical rewiring of the vacuum tubes through low-level machine code to the high-level languages like Python or JavaScript. And now, we're on the edge of the next revolution!
It's a revolution of writing software in plain human language that is understandable and executable by both humans and machines – and it's going to change everything!
The incredible growth in power of microprocessors and the Moore's Law have been the driving force behind the ever-more powerful languages, and it's been an amazing journey! Similarly, the large language models (like GPT or Claude) are the next big thing in language technology, and they're set to transform the way we interact with computers.
This shift is going to happen, whether we are ready for it or not. Our mission is to make it excellently, not just good.
Join us in this journey!
🚀 Get started
Take a look at the simple starter kit with books integrated into the Hello World sample applications:
💜 The Promptbook Project
Promptbook project is ecosystem of multiple projects and tools, following is a list of most important pieces of the project:
Also we have a community of developers and users:
💙 Book language (for prompt-engineer)
💙 The blueprint of book language
Following is the documentation and blueprint of the Book language.
Example
# 🌟 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}
Goals and principles of book language
File is designed to be easy to read and write. It is strict subset of markdown. It is designed to be understandable by both humans and machines and without specific knowledge of the language.
It has file with .book.md
or .book
extension with UTF-8
non BOM encoding.
As it is source code, it can leverage all the features of version control systems like git and does not suffer from the problems of binary formats, proprietary formats, or no-code solutions.
But unlike programming languages, it is designed to be understandable by non-programmers and non-technical people.
Structure
Book is divided into sections. Each section starts with heading. The language itself is not sensitive to the type of heading (h1
, h2
, h3
, ...) but it is recommended to use h1
for header section and h2
for other sections.
Header
Header is the first section of the book. It contains metadata about the pipeline. It is recommended to use h1
heading for header section but it is not required.
Parameter
Foo bar
Parameter names
Reserved words:
- each command like
PERSONA
,EXPECT
,KNOWLEDGE
, etc. content
context
knowledge
examples
modelName
currentDate
Parameter notation
Task
Task type
Todo todo
Command
Todo todo
Block
Todo todo
Return parameter
Examples
📦 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:
⭐ Marked packages are worth to try first
- ⭐ ptbk - Bundle of all packages, when you want to install everything and you don't care about the size
- promptbook - Same as
ptbk
- @promptbook/core - Core of the library, it contains the main logic for promptbooks
- @promptbook/node - Core of the library for Node.js environment
- @promptbook/browser - Core of the library for browser environment
- ⭐ @promptbook/utils - Utility functions used in the library but also useful for individual use in preprocessing and postprocessing LLM inputs and outputs
- @promptbook/markdown-utils - Utility functions used for processing markdown
- (Not finished) @promptbook/wizzard - Wizard for creating+running promptbooks in single line
- @promptbook/execute-javascript - Execution tools for javascript inside promptbooks
- @promptbook/openai - Execution tools for OpenAI API, wrapper around OpenAI SDK
- @promptbook/anthropic-claude - Execution tools for Anthropic Claude API, wrapper around Anthropic Claude SDK
- @promptbook/vercel - Adapter for Vercel functionalities
- @promptbook/google - Integration with Google's Gemini API
- @promptbook/azure-openai - Execution tools for Azure OpenAI API
- @promptbook/langtail - Execution tools for Langtail API, wrapper around Langtail SDK
- @promptbook/fake-llm - Mocked execution tools for testing the library and saving the tokens
- @promptbook/remote-client - Remote client for remote execution of promptbooks
- @promptbook/remote-server - Remote server for remote execution of promptbooks
- @promptbook/pdf - Read knowledge from
.pdf
documents - @promptbook/documents - Read knowledge from documents like
.docx
,.odt
,… - @promptbook/legacy-documents - Read knowledge from legacy documents like
.doc
,.rtf
,… - @promptbook/website-crawler - Crawl knowledge from the web
- @promptbook/types - Just typescript types used in the library
- @promptbook/cli - Command line interface utilities for promptbooks
📚 Dictionary
📚 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 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: Thos section is not complete dictionary, more list of general AI / LLM terms that has connection with Promptbook
Promptbook core
- Organization (legacy name collection) group jobs, workforce, knowledge, instruments, and actions into one package. Entities in one organization can share resources (= import resources from each other).
- Jobs
- Task
- Subtask
- Workforce
- Persona
- Team
- Role
- Knowledge
- Public
- Private
- Protected
- Instruments
- Actions
- Jobs
Book language
- Book file
- Section
- Heading
- Description
- Command
- Block
- Return statement
- Comment
- Import
- Scope
- Section
💯 Core concepts
- 📚 Collection of pipelines
- 📯 Pipeline
- 🙇♂️ Tasks and pipeline sections
- 🤼 Personas
- ⭕ Parameters
- 🚀 Pipeline execution
- 🧪 Expectations
- ✂️ Postprocessing
- 🔣 Words not tokens
- ☯ Separation of concerns
Advanced concepts
- 📚 Knowledge (Retrieval-augmented generation)
- 🌏 Remote server
- 🃏 Jokers (conditions)
- 🔳 Metaprompting
- 🌏 Linguistically typed languages
- 🌍 Auto-Translations
- 📽 Images, audio, video, spreadsheets
- 🔙 Expectation-aware generation
- ⏳ Just-in-time fine-tuning
- 🔴 Anomaly detection
- 👮 Agent adversary expectations
- view more
Terms specific to Promptbook TypeScript implementation
- Anonymous mode
- Application mode
🔌 Usage in Typescript / Javascript
➕➖ When to use Promptbook?
➕ 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
➖ 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)
🐜 Known issues
🧼 Intentionally not implemented features
❔ FAQ
If you have a question start a discussion, open an issue or write me an email.
- ❔ Why not just use the OpenAI SDK / Anthropic Claude SDK / ...?
- ❔ How is it different from the OpenAI`s GPTs?
- ❔ How is it different from the Langchain?
- ❔ How is it different from the DSPy?
- ❔ How is it different from anything?
- ❔ Is Promptbook using RAG (Retrieval-Augmented Generation)?
- ❔ Is Promptbook using function calling?
⌚ Changelog
See CHANGELOG.md
📜 License
🎯 Todos
See TODO.md
🖋️ Contributing
I am open to pull requests, feedback, and suggestions. Or if you like this utility, you can ☕ buy me a coffee or donate via cryptocurrencies.
You can also ⭐ star the promptbook package, follow me on GitHub or various other social networks.