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@promptbook/azure-openai
Advanced tools
It's time for a paradigm shift. The future of software in plain English, French or Latin
npx ptbk run path/to/your/book
.docx
, .doc
and .pdf
documents@promptbook/azure-openai
@promptbook/azure-openai
is one part of the promptbook ecosystem.To install this package, run:
# Install entire promptbook ecosystem
npm i ptbk
# Install just this package to save space
npm install @promptbook/azure-openai
@promptbook/azure-openai
integrates Azure OpenAI API with Promptbook. It allows to execute Promptbooks with Azure OpenAI GPT models.
Note: This is similar to @promptbook/openai but more useful for Enterprise customers who use Azure OpenAI to ensure strict data privacy and compliance.
import { createPipelineExecutor, assertsExecutionSuccessful } from '@promptbook/core';
import {
createCollectionFromDirectory,
$provideExecutionToolsForNode,
$provideFilesystemForNode,
} from '@promptbook/node';
import { JavascriptExecutionTools } from '@promptbook/execute-javascript';
import { AzureOpenAiExecutionTools } from '@promptbook/azure-openai';
// โถ Prepare tools
const fs = $provideFilesystemForNode();
const llm = new AzureOpenAiExecutionTools(
// <- TODO: [๐งฑ] Implement in a functional (not new Class) way
{
isVerbose: true,
resourceName: process.env.AZUREOPENAI_RESOURCE_NAME,
deploymentName: process.env.AZUREOPENAI_DEPLOYMENT_NAME,
apiKey: process.env.AZUREOPENAI_API_KEY,
},
);
const executables = await $provideExecutablesForNode();
const tools = {
llm,
fs,
scrapers: await $provideScrapersForNode({ fs, llm, executables }),
script: [new JavascriptExecutionTools()],
};
// โถ Create whole pipeline collection
const collection = await createCollectionFromDirectory('./books', tools);
// โถ Get single Pipeline
const pipeline = await collection.getPipelineByUrl(`https://promptbook.studio/my-collection/write-article.book.md`);
// โถ Create executor - the function that will execute the Pipeline
const pipelineExecutor = createPipelineExecutor({ pipeline, tools });
// โถ Prepare input parameters
const inputParameters = { word: 'crocodile' };
// ๐โถ Execute the Pipeline
const result = await pipelineExecutor(inputParameters);
// โถ Fail if the execution was not successful
assertsExecutionSuccessful(result);
// โถ Handle the result
const { isSuccessful, errors, outputParameters, executionReport } = result;
console.info(outputParameters);
You can use multiple LLM providers in one Promptbook execution. The best model will be chosen automatically according to the prompt and the model's capabilities.
import { createPipelineExecutor, assertsExecutionSuccessful } from '@promptbook/core';
import {
createCollectionFromDirectory,
$provideExecutionToolsForNode,
$provideFilesystemForNode,
} from '@promptbook/node';
import { JavascriptExecutionTools } from '@promptbook/execute-javascript';
import { AzureOpenAiExecutionTools } from '@promptbook/azure-openai';
import { OpenAiExecutionTools } from '@promptbook/openai';
import { AnthropicClaudeExecutionTools } from '@promptbook/anthropic-claude';
// โถ Prepare multiple tools
const fs = $provideFilesystemForNode();
const llm = [
// Note: You can use multiple LLM providers in one Promptbook execution.
// The best model will be chosen automatically according to the prompt and the model's capabilities.
new AzureOpenAiExecutionTools(
// <- TODO: [๐งฑ] Implement in a functional (not new Class) way
{
resourceName: process.env.AZUREOPENAI_RESOURCE_NAME,
deploymentName: process.env.AZUREOPENAI_DEPLOYMENT_NAME,
apiKey: process.env.AZUREOPENAI_API_KEY,
},
),
new OpenAiExecutionTools(
// <- TODO: [๐งฑ] Implement in a functional (not new Class) way
{
apiKey: process.env.OPENAI_API_KEY,
},
),
new AnthropicClaudeExecutionTools(
// <- TODO: [๐งฑ] Implement in a functional (not new Class) way
{
apiKey: process.env.ANTHROPIC_CLAUDE_API_KEY,
},
),
];
const executables = await $provideExecutablesForNode();
const tools = {
llm,
fs,
scrapers: await $provideScrapersForNode({ fs, llm, executables }),
script: [new JavascriptExecutionTools()],
};
// โถ Create whole pipeline collection
const collection = await createCollectionFromDirectory('./books', tools);
// โถ Get single Pipeline
const pipeline = await collection.getPipelineByUrl(`https://promptbook.studio/my-collection/write-article.book.md`);
// โถ Create executor - the function that will execute the Pipeline
const pipelineExecutor = createPipelineExecutor({ pipeline, tools });
// โถ Prepare input parameters
const inputParameters = { word: 'snake' };
// ๐โถ Execute the Pipeline
const result = await pipelineExecutor(inputParameters);
// โถ Fail if the execution was not successful
assertsExecutionSuccessful(result);
// โถ Handle the result
const { isSuccessful, errors, outputParameters, executionReport } = result;
console.info(outputParameters);
See the other models available in the Promptbook package:
Rest of the documentation is common for entire promptbook ecosystem:
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 โ 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!
Take a look at the simple starter kit with books integrated into the Hello World sample applications:
Promptbook project is ecosystem of multiple projects and tools, following is a list of most important pieces of the project:
Project | Description | Link |
---|---|---|
Core | Promptbook Core is a description and documentation of the basic concepts, ideas and inner workings of how Promptbook should be implemented, and defines what features must be describable by book language. | https://github.com/webgptorg/book |
Book language | Book is a markdown-like language to define core entities like projects, pipelines, knowledge,.... It is designed to be understandable by non-programmers and non-technical people | |
Promptbook typescript project | Promptbook implementation in TypeScript released as multiple NPM packages | https://github.com/webgptorg/promptbook + Multiple packages published on NPM |
Promptbook studio | Studio to write Books and instantly publish them as miniapps |
https://promptbook.studio https://github.com/hejny/promptbook-studio |
Hello World | Simple starter kit with Books integrated into the sample applications |
https://github.com/webgptorg/hello-world https://github.com/webgptorg/hello-world-node-js https://github.com/webgptorg/hello-world-next-js |
Also we have a community of developers and users:
Following is the documentation and blueprint of the Book language.
# ๐ 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}
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.
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 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.
Foo bar
Reserved words:
PERSONA
, EXPECT
, KNOWLEDGE
, etc.content
context
knowledge
examples
modelName
currentDate
Todo todo
Todo todo
Todo todo
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
ptbk
.pdf
documents.docx
, .odt
,โฆ.doc
, .rtf
,โฆThe following glossary is used to clarify certain concepts:
Note: Thos section is not complete dictionary, more list of general AI / LLM terms that has connection with Promptbook
If you have a question start a discussion, open an issue or write me an email.
See CHANGELOG.md
Promptbook by Pavol Hejnรฝ 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 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.
FAQs
It's time for a paradigm shift. The future of software in plain English, French or Latin
The npm package @promptbook/azure-openai receives a total of 583 weekly downloads. As such, @promptbook/azure-openai popularity was classified as not popular.
We found that @promptbook/azure-openai demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago.ย It has 0 open source maintainers collaborating on the project.
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