Search with Supabase + Algolia's Autocomplete

Search with Supabase + Algolia's Autocomplete

This post is a sneak peek on Algolia's Autocomplete library as the frontend of Supabase's search funcitonality.

I've implemented Full Text Search feature on my side project Quill. Although I have a bit of experience(as in I work there) in Algolia, I didn't use Algolia at this time. Algolia is the most powerful Search-as-a-service out there, but for this small side project, I don't need that power yet. Also, I already have all the data stored in Supabase, and could just simply start using the search funcitonalities of PostgreSQL.

For the UI part, I could've used a simple <form> and <input> but instead went with Algolia's Autocomplete library, which provides a great accessibility including keyboard navigation out-of-the-box.

Full Text Search | Supabase

GitHub - algolia/autocomplete: ๐Ÿ”ฎ Fast and full-featured autocomplete library

I have a table posts with attributes including title and body. For now, I've decided to call two separate search calls, one for title and another one for body. I do not want to mix results, so that I can prioritize posts matched with title to be listed first.


The image above shows you the flow from the frontend to the backend. I don't have much to explain, so here are some snippets for you.

The frontend component โ†“

<div id="autocomplete" />
import { autocomplete } from "@algolia/autocomplete-js";
import "@algolia/autocomplete-theme-classic";

// To learn more about debouncing with Autocomplete,
// Read
function debouncePromise(fn, time) {
  let timerId = undefined;

  return function debounced(...args) {
    if (timerId) {

    return new Promise((resolve) => {
      timerId = setTimeout(() => resolve(fn(...args)), time);
const debounced = debouncePromise((items) => Promise.resolve(items), 300);

// I use two sources, one for search results on `title`, and another one on `body`.
// The code is almost the same, so I extracted it as a function.
const getSource = ({ sourceId, mode }: { sourceId: string, mode: string }) => ({
  onSelect({ item }) {
    window.location.href = `/${item.slug}`;
  async getItems({ query }) {
    const response = await fetch(
    const json = await response.json();
    json.result.forEach(({ slug }) => prefetch(`/${slug}`));
    return json.result;
  templates: {
    ...(mode === "title"
      ? {
          noResults() {
            return "No result for this query.";
      : {}),
    item({ item, createElement }) {
      return createElement("div", {
        dangerouslySetInnerHTML: {
          __html: `
              <div class="aa-ItemWrapper">
                <div class="aa-ItemContent">
                  <div class="aa-ItemContentBody">
                    <div class="aa-ItemContentTitle">
                    <div class="aa-ItemContentSubtitle">

// The real Autocomplete part.
  container: "#autocomplete",
  placeholder: "Search",
  autoFocus: true,
  getSources() {
    return debounced([
      getSource({ sourceId: "postsByTitle", mode: "title" }),
      getSource({ sourceId: "postsByBody", mode: "body" }),

/search.json โ†“

// The way to write serverless function varies according to platform.
// So this is the minimum business logic, excluding all the platform-related code.

function quote(s: string) {
  return "'" + s.replace(/'/g, `\\'`) + "'";

const searchQuery = query.get("query");
const mode = query.get("mode"); // 'title' | 'body'

const quotedQuery = searchQuery
  .split(" ")
  .map((word) => quote(word))
  .join(" & ");

const targetAttribute =
  mode === "title"
    ? "searchable_title"
    : mode === "body"
    ? "searchable_body"
    : null;

const { data } =
  (await supabase.from) <
  Page >
    .textSearch(targetAttribute, quotedQuery)
    .eq("project_id", projectId);

return {
  body: { result: data },