Fumadocs

Algolia Search

Integrate Algolia Search with Fumadocs

Notice

If you're using Algolia's free tier, you have to display their logo on your search dialog.

Introduction

The Algolia Integration automatically configures Algolia Search for document search.

It creates a record for each paragraph in your document, it is also recommended by Algolia.

Each record contains searchable attributes:

AttributeDescription
titlePage Title
sectionHeading ID (nullable)
contentParagraph content

The section field only exists in paragraphs under a heading. Headings and paragraphs are indexed as an individual record, grouped by their page ID.

Notice that it expects the url property of a page to be unique, you shouldn't have two pages with the same url.

Setup

Install dependencies:

npm install algoliasearch
pnpm add algoliasearch
yarn add algoliasearch
bun add algoliasearch

Sign up on Algolia

Sign up and obtain the app id and API keys for your search. Store these credentials in environment variables.

Sync Search Indexes

Export the search indexes from Next.js using a route handler, this way we can access the search indexes after production build:

app/static.json/route.ts
import { NextResponse } from 'next/server';
import { type DocumentRecord } from 'fumadocs-core/search/algolia';
import { source } from '@/lib/source';

export const revalidate = false;

export function GET() {
  const results: DocumentRecord[] = [];

  for (const page of source.getPages()) {
    results.push({
      _id: page.url,
      structured: page.data.structuredData,
      url: page.url,
      title: page.data.title,
      description: page.data.description,
    });
  }

  return NextResponse.json(results);
}

Make a script to sync search indexes:

update-index.mjs
// @ts-check
import { algoliasearch } from 'algoliasearch';
import { sync } from 'fumadocs-core/search/algolia';
import * as fs from 'node:fs';

const content = fs.readFileSync('.next/server/app/static.json.body');

// now you can pass it to `sync`
/** @type {import('fumadocs-core/search/algolia').DocumentRecord[]} **/
const records = JSON.parse(content.toString());

const client = algoliasearch('id', 'key');

void sync(client, {
  indexName: 'document',
  documents: records,
});

The sync function will update the index settings and sync search indexes.

Now run the script after build:

package.json
{
  "scripts": {
    "build": "next build && node ./update-index.mjs"
  }
}

Workflow

You may make it a script and manually sync with node ./update-index.mjs, or integrate it with your CI/CD pipeline.

Typescript Usage

If you are running the script with TSX or other similar Typescript executors, ensure to name it .mts for best ESM compatibility.

Search UI

You can consider different options for implementing the UI:

  • Using Fumadocs UI search dialog.

  • Build your own using the built-in search client hook:

    import {  } from 'algoliasearch/lite';
    import {  } from 'fumadocs-core/search/client';
    
    const  = ('id', 'key');
    
    const { , ,  } = ({
      : 'algolia',
      : 'document',
      ,
    });
  • Use their official clients directly.

Options

Tag Filter

To configure tag filtering, add a tag value to indexes.

import { sync } from 'fumadocs-core/search/algolia';

void sync(client, {
  indexName: 'document',
  documents: records.map((index) => ({
    ...index,
    tag: 'value',
  })),
});

And update your search client:

  • Fumadocs UI: Enable Tag Filter on Search UI.

  • Search Client: You can add the tag filter like:

    import { useDocsSearch } from 'fumadocs-core/search/client';
    
    const { search, setSearch, query } = useDocsSearch({
      tag: '<your tag value>',
      // ...
    });

The tag field is an attribute for faceting. You can also use the filter tag:value on Algolia search clients.

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