Supercharge your use of large language models
- ✨ Support of OpenAI o1 model
If you have a simple, single prompt for ChatGPT, GPT-4, Anthropic Claude, Google Gemini, Llama 2, 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 drift, word repetition repetition repetition repetition or misuse, lack of context, or just plain w𝒆𝐢rd responses. When this happens, you generally have three options:
- Fine-tune the model to your specifications or even train your own.
- Prompt-engineer the prompt to the best shape you can achieve.
- Orchestrate multiple prompts in a pipeline to get the best result.
In all of these situations, but especially in 3., the Promptbook library can make your life easier.
- Separates concerns between prompt-engineer and programmer, between code files and prompt files, and between prompts and their execution logic.
- Establishes a common format
.ptbk.md
that can be used to describe your prompt 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.
- Has 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. - Promptbook has built in versioning. You can test multiple A/B versions of pipelines and see which one works best.
- Promptbook is designed to do RAG (Retrieval-Augmented Generation) and other advanced techniques. You can use knowledge to improve the quality of the output.
Prompt book markdown file (or .ptbk.md
file) is document that describes a pipeline - a series of prompts that are chained together to form somewhat reciepe for transforming natural language input.
- Multiple pipelines forms a collection which will handle core know-how of your LLM application.
- Theese pipelines are designed such as they can be written by non-programmers.
File write-website-content.ptbk.md
:
Instructions for creating web page content.
- PIPELINE URL https://promptbook.studio/webgpt/write-website-content.ptbk.md
- INPUT PARAM
{rawTitle}
Automatically suggested a site name or empty text- INPUT PARAM
{rawAssigment}
Automatically generated site entry from image recognition- OUTPUT PARAM
{websiteContent}
Web content- OUTPUT PARAM
{keywords}
KeywordsWhat is your web about?
- DIALOG TEMPLATE
{rawAssigment}
-> {assigment}
Website assignment and specification
- PERSONA Jane, Copywriter and Marketing Specialist.
As an experienced marketing specialist, you have been entrusted with improving the name of your client's business. A suggested name from a client: "{rawTitle}" Assignment from customer: > {assigment} ## Instructions: - Write only one name suggestion - The name will be used on the website, business cards, visuals, etc.
-> {enhancedTitle}
Enhanced titleIs the title for your website okay?
- DIALOG TEMPLATE
{enhancedTitle}
-> {title}
Title for the website
- PERSONA Josh, a copywriter, tasked with creating a claim for the website.
As an experienced copywriter, you have been entrusted with creating a claim for the "{title}" web page. A website assignment from a customer: > {assigment} ## Instructions: - Write only one name suggestion - Claim will be used on website, business cards, visuals, etc. - Claim should be punchy, funny, original
-> {claim}
Claim for the web
- PERSONA Paul, extremely creative SEO specialist.
As an experienced SEO specialist, you have been entrusted with creating keywords for the website "{title}". Website assignment from the customer: > {assigment} ## Instructions: - Write a list of keywords - Keywords are in basic form ## Example: - Ice cream - Olomouc - Quality - Family - Tradition - Italy - Craft
-> {keywords}
Keywords
- SIMPLE TEMPLATE
# {title} > {claim}
-> {contentBeginning}
Beginning of web content
- PERSONA Jane
As an experienced copywriter and web designer, you have been entrusted with creating text for a new website {title}. A website assignment from a customer: > {assigment} ## Instructions: - Text formatting is in Markdown - Be concise and to the point - Use keywords, but they should be naturally in the text - This is the complete content of the page, so don't forget all the important information and elements the page should contain - Use headings, bullets, text formatting ## Keywords: {keywords} ## Web Content: {contentBeginning}
-> {contentBody}
Middle of the web content
- SIMPLE TEMPLATE
{contentBeginning} {contentBody}
-> {websiteContent}
Following is the scheme how the promptbook above is executed:
%% 🔮 Tip: Open this on GitHub or in the VSCode website to see the Mermaid graph visually
flowchart LR
subgraph "🌍 Create website content"
direction TB
input((Input)):::input
templateSpecifyingTheAssigment(👤 Specifying the assigment)
input--"{rawAssigment}"-->templateSpecifyingTheAssigment
templateImprovingTheTitle(✨ Improving the title)
input--"{rawTitle}"-->templateImprovingTheTitle
templateSpecifyingTheAssigment--"{assigment}"-->templateImprovingTheTitle
templateWebsiteTitleApproval(👤 Website title approval)
templateImprovingTheTitle--"{enhancedTitle}"-->templateWebsiteTitleApproval
templateCunningSubtitle(🐰 Cunning subtitle)
templateWebsiteTitleApproval--"{title}"-->templateCunningSubtitle
templateSpecifyingTheAssigment--"{assigment}"-->templateCunningSubtitle
templateKeywordAnalysis(🚦 Keyword analysis)
templateWebsiteTitleApproval--"{title}"-->templateKeywordAnalysis
templateSpecifyingTheAssigment--"{assigment}"-->templateKeywordAnalysis
templateCombineTheBeginning(🔗 Combine the beginning)
templateWebsiteTitleApproval--"{title}"-->templateCombineTheBeginning
templateCunningSubtitle--"{claim}"-->templateCombineTheBeginning
templateWriteTheContent(🖋 Write the content)
templateWebsiteTitleApproval--"{title}"-->templateWriteTheContent
templateSpecifyingTheAssigment--"{assigment}"-->templateWriteTheContent
templateKeywordAnalysis--"{keywords}"-->templateWriteTheContent
templateCombineTheBeginning--"{contentBeginning}"-->templateWriteTheContent
templateCombineTheContent(🔗 Combine the content)
templateCombineTheBeginning--"{contentBeginning}"-->templateCombineTheContent
templateWriteTheContent--"{contentBody}"-->templateCombineTheContent
templateCombineTheContent--"{websiteContent}"-->output
output((Output)):::output
classDef input color: grey;
classDef output color: grey;
end;
Note: We are using postprocessing functions like unwrapResult
that can be used to postprocess the result.
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/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/types - Just typescript types used in the library
- @promptbook/cli - Command line interface utilities for promptbooks
The following glossary is used to clarify certain concepts:
- 📚 Collection of pipelines
- 📯 Pipeline
- 🎺 Pipeline templates
- 🤼 Personas
- ⭕ Parameters
- 🚀 Pipeline execution
- 🧪 Expectations
- ✂️ Postprocessing
- 🔣 Words not tokens
- ☯ Separation of concerns
- 📚 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
- 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 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)
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?
See CHANGELOG.md
Promptbook by Pavol Hejný is licensed under CC BY 4.0
See TODO.md
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.