Collaborate on rich text documents which follow the rich text schema using ProseMirror.
This plugin is beta quality software. The API will probably change a bit before a stable release and there are bugs, but it also works reasonably well.
There is a fully functional editor in this repository, you can play with that by running npm run playground and then visiting http://localhost:5173.
This library provides a plugin which maps between Automerge documents and ProseMirror documents. This plugin relies on two things: firstly that the schema you use be a very specific subset of the ProseMirror schema which is mapped to the Automerge rich text schema (more on this later), and secondly that you initialize the ProseMirror document from the Automerge document. Thus, we provide a simple entrypoint which does all these things for you:
import { init } from "@automerge/prosemirror"
// Obtain a DocHandle somehow
const handle = repo.find("some-doc-url")
// wait for the handle to be ready before continuing
await handle.whenReady()
// This is the important part, we initialize the plugin with the handle and the path to the text field in the document
// and we get back a schema, a ProseMirror document, and a plugin
const { schema, pmDoc, plugin } = init(handle, ["text"])
// Create your prosemirror state with the schema, plugin, and document
let editorConfig = {
schema,
plugins: [
keymap({
...baseKeymap,
"Mod-b": toggleBold,
"Mod-i": toggleItalic,
"Mod-z": undo,
"Mod-y": redo,
"Mod-Shift-z": redo,
}),
plugin,
],
doc: pmDoc
}
let state = EditorState.create(editorConfig)
const view = new EditorView(<whatever DOM element you are rendering to>, {
state
})See the playground/src/Editor.tsx file for a fully featured example.
ProseMirror documents have a schema, which determines the kinds of nodes and marks which are allowed in the document. In order to map between the block markers and marks in the Automerge document and the ProseMirror document you must create a SchemaAdapter. The argument to the SchemaAdapter is the same as the {nodes, marks} object you would use to create a ProseMirror schema, but the nodes and marks objects have an additional optional key called automerge, which configures how the automerge document is mapped to the ProseMirror document.
For example, here's a snippet which maps the paragraph node to the paragraph block type:
import {SchemaAdapter} from "@automerge/prosemirror"
const adapter = new SchemaAdapter({
nodes: {
... // other nodes
/// A plain paragraph textblock. Represented in the DOM
/// as a `<p>` element.
paragraph: {
// ---------------------------------------
// This is the automerge configuration
// ---------------------------------------
automerge: {
block: "paragraph",
},
// ---------------------------------------
content: "inline*",
group: "block",
parseDOM: [{ tag: "p" }],
toDOM() {
return pDOM
},
} as NodeSpec,
}
})This schema adapter can then be passed to init as an option:
const { pmDoc, schema, plugin } = init(handle, ["text"], { schemaAdapter: adapter })There are a number of keys available in the automerge mapping. To understand what they all mean you need to understand the goals of schema mapping:
- Converting between automerge blocks and ProseMirror nodes
- Converting between automerge marks and ProseMirror marks
- Representing unknown blocks and marks in the ProseMirror document so that editing a document with unknown marks or blocks does not cause them to be lost
The simple case of converting blocks to nodes is when there is a one-to-one mapping from the block type to the node type and the node doesn't have any extra attributes. As in the case of the paragraph marker above, this typically looks like:
nodes: {
<node name>: {
// rest of the node spec
automerge: {
block: <block name>
}
}
}A more complex case is when the type of the block depends on surrounding content. For example, a <li> node in ProseMirror can be either an ordered-list-item or an unordered-list-item in the rich text schema. In this case you can use the within key:
nodes: {
list_item: {
// rest of the node spec
automerge: {
// Here the keys of the map are other nodes in the schema
within: {
ordered_list: "ordered-list-item",
bullet_list: "unordered-list-item"
}
}
}
}Many nodes and block markers are more complex than just a type name. They also carry attributes. In this case you use the attrParsers of the automerge key. For example, the heading block marker has a level attribute which is used to determine the level of the heading. This is how you would map that to a ProseMirror node:
nodes: {
heading {
// rest of the node spec
automerge: {
block: "heading",
attrParsers: {
fromAutomerge: block => ({ level: block.attrs.level }),
fromProsemirror: node => ({ level: node.attrs.level }),
},
},
}
}The fromAutomerge function will be passed the block marker and should return a set of node attributes whilst the fromProsemirror function will be passed a node and should return map of block attributes.
Some block types do not represent hierarchical content but instead represent embedded content which does not change the structural role of text following them. For example, an image block tag just indicates that an image should appear at the location of the block marker. For these kinds of blocks you can set the isEmbed key to true:
nodes: {
image: {
// the rest of the node spec
automerge: {
block: "image",
isEmbed: true,
attrParsers: { .. },
}
}
}Marks are a bit simpler than blocks. The automerge key on a mark spec can contain a markName key which specifies what mark in the automerge document corresponds to this mark in the ProseMirror document.
For example, a strong mark might be mapped like this:
marks: {
strong: {
// rest of the mark spec
automerge: {
markName: "strong",
},
},
}As with blocks some marks also have attributes which need to be converted. This is done with the attrParsers key. Unlike blocks marks cannot store complex content on the mark value in automerge, so in the parsers we typically convert to and from a JSON encoded string, like so:
marks: {
link: {
automerge: {
markName: "link",
parsers: {
fromAutomerge: (mark: am.MarkValue) => {
if (typeof mark === "string") {
try {
const value = JSON.parse(mark)
return {
href: value.href || "",
title: value.title || "",
}
} catch (e) {
console.warn("failed to parse link mark as JSON")
}
}
return {
href: "",
title: "",
}
},
fromProsemirror: (mark: Mark) =>
JSON.stringify({
href: mark.attrs.href,
title: mark.attrs.title,
}),
},
},
}
}Every schema adapter must provide some way to represent unknown blocks. This allows applications using different schema to collaborate on the same text document. Unknown blocks will be represented my the node which has the automerge.unknownBlock key set to true and which can contain any other node in the schema.
An easy way to do this is:
nodes: {
unknownBlock: {
automerge: {
unknownBlock: true,
},
group: "block",
content: "block+", // Allow any block content
parseDOM: [{ tag: "div", attrs: { "data-unknown-block": "true" } }],
toDOM() {
return ["div", { "data-unknown-block": "true" }, 0]
},
},
}A SchemaAdapter provides the mapping between a ProseMirror Schema and the block markers you are using in the automerge document. The part of this API to understand is the specification which you pass to the SchemaAdapter constructor.
A schema adapter specification is an extension of a ProseMirror schema. It constists of an object with a nodes key and a marks key, each of which are like their equivalents in a ProseMirror schema but with a few additional keys.
The nodes values must be ProseMirror NodeSpec objects with an additional automerge key with the following type:
type AutomergeNodeSpec = {
unknownBlock?: boolean
block?: BlockMappingSpec
isEmbed?: boolean
attrParsers?: {
fromProsemirror: (node: Node) => { [key: string]: am.MaterializeValue }
fromAutomerge: (block: BlockMarker) => Attrs
}
}
type BlockMappingSpec = string | { within: { [key: string]: string } }
type BlockMarker = {
type: automerge.RawString
parents: automerge.RawString[]
attrs: { [key: string]: any }
isEmbed?: boolean
}The marks values must be ProseMirror MarkSpec objects with an additional automerge key with the following type:
automerge?: {
markName: string
parsers?: {
fromAutomerge: (value: automerge.MarkValue) => Attrs
fromProsemirror: (mark: Mark) => automerge.MarkValue
}
}
