Algolia Search

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:

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

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

Pre-render a static route /static.json to export search indexes into production build:

import { source } from '@/lib/source';
import type { DocumentRecord } from 'fumadocs-core/search/algolia';

export async function exportSearchIndexes() {
  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 results;
}

import { exportSearchIndexes } from '@/lib/export-search-indexes';

export const revalidate = false;

export async function GET() {
  return Response.json(await exportSearchIndexes());
}

Make a script to sync search indexes:

import { algoliasearch } from 'algoliasearch';
import { sync, DocumentRecord } from 'fumadocs-core/search/algolia';
import * as fs from 'node:fs';

// the path of pre-rendered `static.json`, choose one according to your React framework
const filePath = {
  next: '.next/server/app/static.json.body',
  'tanstack-start': '.output/public/static.json',
  'react-router': 'build/client/static.json',
  waku: 'dist/public/static.json',
}['next'];

const content = fs.readFileSync(filePath);

const records = JSON.parse(content.toString()) as DocumentRecord[];

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

// update the index settings and sync search indexes
void sync(client, {
  indexName: 'document',
  documents: records,
});

Now run the script after build:

{
  "scripts": {
    "build": "... && bun ./scripts/sync-content.ts"
  }
}

Workflow

You may manually upload search indexes with the script, or integrate it with your CI/CD pipeline.

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 { liteClient } from 'algoliasearch/lite';
  import { useDocsSearch } from 'fumadocs-core/search/client';
  
  const client = liteClient('id', 'key');
  
  const { search, setSearch, query } = useDocsSearch({
    type: 'algolia',
    indexName: 'document',
    client,
  });

• Use their official clients directly.

Options

Tag Filter

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

import { source } from '@/lib/source';
import type { DocumentRecord } from 'fumadocs-core/search/algolia';

export async function exportSearchIndexes() {
  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,
      tag: '<your value>',
    });
  }

  return results;
}

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.