@markprompt/web
A prebuilt version of the Markprompt dialog, based on @markprompt/react
, built with Preact for bundle-size savings. Viable for use from vanilla JavaScript or any framework.
Installation
Install the package from NPM:
npm add @markprompt/web @markprompt/css
Usage
Include the CSS on your page, via a link tag or by importing it in your JavaScript:
<link rel="stylesheet" href="https://esm.sh/@markprompt/css@0.2.0?css" />
import '@markprompt/css';
Call the markprompt
function with your project key:
import { markprompt } from '@markprompt/web';
const markpromptEl = document.querySelector('#markprompt');
markprompt('YOUR-PROJECT-KEY', markpromptEl, {
references: {
transformReferenceId: (referenceId) => ({
text: referenceId.replace('-', ' '),
href: `/docs/${referenceId}`,
}),
},
});
where YOUR-PROJECT-KEY
can be obtained in your project settings on Markprompt.com.
Options are optional and allow you to configure the texts used in the component to some extent. You will most likely want to pass transformReferenceId
to transform your reference ids into links to your corresponding documentation and getResultHref
to transform search result paths into links to your documentation.
import {
type SubmitPromptOptions,
type SubmitSearchQueryOptions,
} from '@markprompt/core';
import type { SearchResultWithMetadata } from '@markprompt/react';
type MarkpromptOptions = {
display?: 'plain' | 'dialog';
close?: {
label?: string;
};
description?: {
hide?: boolean;
text?: string;
};
prompt?: SubmitPromptOptions & {
label?: string;
placeholder?: string;
cta?: string;
};
references?: {
transformReferenceId: (referenceId: string) => {
href: string;
text: string;
};
loadingText?: string;
referencesText?: string;
};
search?: SubmitSearchQueryOptions & {
enabled?: boolean;
getResultHref?: (
path: string,
sectionHeading: SectionHeading | undefined,
source: Source,
) => string;
};
trigger?: {
label?: string;
placeholder?: string;
floating?: boolean;
};
title?: {
hide?: boolean;
text?: string;
};
};
Styles are easily overridable for customization via targeting classes. Additionally, see the styling section in our documentation for a full list of variables.
Usage via <script>
tag
Besides initializing the Markprompt component yourselves from JavaScript, you can load the script from a CDN. You can attach the options for the Markprompt component to the window prior to loading our script:
<link
rel="stylesheet"
href="https://unpkg.com/@markprompt/css@0.2.0/markprompt.css"
/>
<script>
window.markprompt = {
projectKey: `YOUR-PROJECT-KEY`,
container: `#markprompt`,
options: {
references: {
transformReferenceId: (referenceId) => ({
text: referenceId.replace('-', ' '),
href: `/docs/${referenceId}`,
}),
},
},
};
</script>
<script
async
src="https://unpkg.com/@markprompt/web@0.5.0/dist/init.js"
></script>
API
markprompt(projectKey, container, options?)
Render a Markprompt dialog button.
Arguments
projectKey
(string
): Your Markprompt project key.container
(HTMLElement | string
): The element or selector to render Markprompt into.options
(object
): Options for customizing Markprompt.
Options
projectKey
(string
): The project key associated to your project. It can be obtained in the project settings on Markprompt.com under "Project key".close
(object
): Options for the close modal buttonclose.label
(string
): aria-label
for the close modal button (Default: Close Markprompt
)close.visible
(boolean
): Show the close button (Default: true
)description
(object
): Options for the descriptiondescription.hide
(boolean
): Visually hide the description (Default: true
)description.text
(string
): Description textprompt
(object
): Options for the promptprompt.label
(string
): Label for the prompt input (Default: Ask me anything…
)prompt.placeholder
(string
): Placeholder for the prompt input (Default: Ask me anything…
)prompt.cta
(string
): When search is enabled, this label is used for the CTA button that opens the prompt (Default: Ask Docs AI…
)prompt.completionsUrl
(string
): URL at which to fetch completions. (Default: https://api.markprompt.com/v1/completions
)prompt.iDontKnowMessage
(string
): Message returned when the model does not have an answer. (Default: Sorry, I am not sure how to answer that.
)prompt.model
(string
): The OpenAI model to use. (Default: gpt-3.5-turbo
)prompt.promptTemplate
(string
): The prompt template. (Default: You are a very enthusiastic company representative who loves to help people! Given the following sections from the documentation (preceded by a section id), answer the question using only that information, outputted in Markdown format. If you are unsure and the answer is not explicitly written in the documentation, you can say 'I don't know' and the question will be passed to the OpenAI model to answer.\n\n# Sections\n\n{{#each sections}}\n## {{this.id}}\n\n{{this.content}}\n\n{{/each}}\n\n# Question\n\n{{question}}\n\n# Answer\n\n
)prompt.temperature
(number
): The model temperature. (Default: 0.1
)prompt.topP
(number
): The model top P. (Default: 1
)prompt.frequencyPenalty
(number
): The model frequency penalty. (Default: 0
)prompt.presencePenalty
(number
): The model presence penalty. (Default: 0
)prompt.maxTokens
(number
): The max number of tokens to include in the response. (Default: 500
)prompt.sectionsMatchCount
(number
): The number of sections to include in the prompt context. (Default: 10
)prompt.sectionsMatchThreshold
(number
): The similarity threshold between the input question and selected sections. (Default: 0.5
)prompt.signal
(AbortSignal
): AbortController signal.references
(object
): Options for the referencesreferences.transformReferenceId
(function
): Callback to transform a reference id into an href and textreferences.loadingText
(string
): Loading text (Default: Fetching relevant pages…
)references.referencesText
(string
): References title (Default: Answer generated from the following sources:
)search
(object
): Options for searchsearch.enable
(boolean
): Enable search (Default: false
)search.getResultHref
(function
): Callback to transform a search result into an hrefsearch.enable
(boolean
): Whether or not to enable search. (Default: true
)search.limit
(number
): Maximum amount of results to return. (Default: 5
)search.searchUrl
(string
): URL at which to fetch search results. (Default: https://api.markprompt.com/v1/search
)search.signal
(AbortSignal
): AbortController signal.trigger
(object
): Options for the triggertrigger.customElement
(boolean
): Use a custom element as the trigger. Will disable rendering any trigger element. Use openMarkprompt()
to trigger the Markprompt dialog. (Default: false
)trigger.label
(string
): aria-label
for the open button (Default: Open Markprompt
)trigger.placeholder
(string
): Placeholder text for non-floating element (Default: Ask docs
)title
(object
): Options for the titletitle.hide
(boolean
): Visually hide the title (Default: true
)title.text
(string
): Title text (Default: Ask me anything
)
When rendering the Markprompt component, it will render a search input-like button by default. You have two other options:
- set
trigger.floating = true
to render a floating button - set
trigger.customElement = true
, then import { openMarkprompt } from '@markprompt/react'
and call openMarkprompt()
from your code. This gives you the flexibility to render your own trigger element and attach whatever event handlers you would like and/or open the Markprompt dialog programmatically.
Documentation
The full documentation for @markprompt/web
can be found on the Markprompt docs.
Authors
This library is created by the team behind Markprompt
(@markprompt).
License
MIT © Markprompt