install FlexSearch

FlexSearch uses Json documents to define and populate its indices. Here is the markdown frontmatter that needs indexed for this project.

---
title: Bump Version
description: This Go program makes it easy to... 
date_created: 2026-02-25
date_updated: 2026-06-04
date_published: false
rank: 0
pinned:
tags:
  - go
  - git
  - cli
---

index = new Document({
    document: {
        id: "id",
        store: [
            "id",
            "title",
            "url",
            "tags",
            "folder",
            "description",
        ],
        index: ["title", "url", "content", "tags", "description"],
        tag: [{ field: "folder" }],
    },
    tokenize: "forward",
    encoder: Charset.Normalize,
});

This article talks about creating a single FlexSearch index. However, if its prudent for your application, FlexSearch supports multiple indexes.

For an elevently site, we'll get the Json with a Nunjucks template.

How you convert your content into Json is up to you. For this example, the content is primary markdown documents, we so need a way to generate Json index data from these markdown documents.

Markdown documents have YAML frontmatter in them at the start of the document, deliimited by three dashes (---).

In markdown-friendly projects, (like Astro, Eleventy, Svelte, and many others)

---
title: Bump Version
description: This Go program makes it easy to increment a package version number and promote that number to GitHub. 
date_created: 2026-02-25
date_updated: 2026-06-04
date_published:
rank: 0
pinned:
tags:
  - go
  - git
  - cli
---

[content here]

Nunjucks template

---
permalink: /data/search-index.json
eleventyExcludeFromCollections: true
---
[
  {%- for post in collections.posts -%}
    {%- if not loop.first -%},{%- endif -%}
    {
        "id": { loop.index0 | dump | safe }},
        "title": { post.data.title | dump | safe }},
        "description": { post.data.description | dump | safe }},
        "url": { post.url | dump | safe }},
        "tags": { post.data.tags | dump | safe }},
        "content": { post.templateContent | striptags | trim | dump | safe }},
        "folder": "post"
    }
  {%- endfor -%}
]

document structure

  {
      "id": 11,
      "title": "Bump Version",
      "description": "This is a Go to increment a package ...",
      "url": "/posts/bump-version/",
      "tags": ["posts", "go", "git", "cli"],
      "content": "This Go program makes it easy...",
      "folder": "post"
  }

/posts/flexsearch-worker/#search-worker-js

To stress-test FlexSearch,

• I created 5000 markdown documents where the content for each was randomly sized between 750 words and 2000 words.
• Eleventy translated these 5000 documents into a 8mb Json file.
• FlexSearch took about 2/3 of a second to index that Json document on each page load.
• Chrome showed the tab using 200-300mb of memory (which was pretty much what my browser showed Amazon using)