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Alex Spinov
Alex Spinov

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Typesense Has a Free API You Should Know About

#typesense #search #api #webdev

Typesense is an open-source search engine built for speed — searches complete in under 10ms with built-in typo tolerance.

Define Collection & Index Data 

import Typesense from 'typesense'

const client = new Typesense.Client({
  nodes: [{ host: 'localhost', port: 8108, protocol: 'http' }],
  apiKey: 'xyz'
})

// Create collection with schema
await client.collections().create({
  name: 'products',
  fields: [
    { name: 'name', type: 'string' },
    { name: 'description', type: 'string' },
    { name: 'price', type: 'float' },
    { name: 'category', type: 'string', facet: true },
    { name: 'brand', type: 'string', facet: true },
    { name: 'rating', type: 'float' }
  ],
  default_sorting_field: 'rating'
})

// Index documents
await client.collections('products').documents().import([
  { id: '1', name: 'MacBook Pro M3', description: 'Pro laptop', price: 1999, category: 'Laptops', brand: 'Apple', rating: 4.8 },
  { id: '2', name: 'ThinkPad X1', description: 'Business laptop', price: 1499, category: 'Laptops', brand: 'Lenovo', rating: 4.5 }
])
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Search 

const results = await client.collections('products').documents().search({
  q: 'macbok', // Typo-tolerant!
  query_by: 'name,description',
  filter_by: 'price:<2000 && category:Laptops',
  sort_by: 'rating:desc',
  facet_by: 'category,brand',
  per_page: 10,
  highlight_full_fields: 'name'
})
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REST API 

curl 'http://localhost:8108/collections/products/documents/search?q=laptop&query_by=name,description&filter_by=price:<2000' \
  -H 'X-TYPESENSE-API-KEY: xyz'
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Geosearch 

await client.collections('stores').create({
  name: 'stores',
  fields: [
    { name: 'name', type: 'string' },
    { name: 'location', type: 'geopoint' }
  ]
})

// Find stores within 10km
const results = await client.collections('stores').documents().search({
  q: '*',
  filter_by: 'location:(48.85, 2.35, 10 km)', // Near Paris
  sort_by: 'location(48.85, 2.35):asc'
})
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Vector Search (Semantic) 

await client.collections().create({
  name: 'docs',
  fields: [
    { name: 'title', type: 'string' },
    { name: 'content', type: 'string' },
    { name: 'embedding', type: 'float[]', num_dim: 384 }
  ]
})

// Hybrid search: keyword + vector
const results = await client.collections('docs').documents().search({
  q: 'how to deploy',
  query_by: 'title,content',
  vector_query: 'embedding:([0.1, 0.2, ...], k:10)',
  exclude_fields: 'embedding'
})
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InstantSearch Integration 

import TypesenseInstantSearchAdapter from 'typesense-instantsearch-adapter'
import { InstantSearch, SearchBox, Hits } from 'react-instantsearch'

const adapter = new TypesenseInstantSearchAdapter({
  server: { apiKey: 'search-only-key', nodes: [{ host: 'localhost', port: 8108, protocol: 'http' }] },
  additionalSearchParameters: { query_by: 'name,description' }
})

function Search() {
  return (
    <InstantSearch searchClient={adapter.searchClient} indexName="products">
      <SearchBox />
      <Hits hitComponent={Hit} />
    </InstantSearch>
  )
}
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Real-World Use Case

An e-commerce platform with 500K products was using Elasticsearch. Infrastructure: 3 nodes, 24GB RAM, $300/month. Search latency: 200-500ms. They migrated to Typesense: single node, 4GB RAM, $20/month. Search latency: 5-15ms. Same features (facets, typo tolerance, sorting), 95% less infrastructure.

Typesense is search without the Elasticsearch tax.

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