Terminal.skills
Skills/typesense
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typesense

Typesense is an open-source, typo-tolerant search engine optimized for instant search experiences. Learn to deploy with Docker, define collections, index documents, and build search UIs as a modern alternative to Algolia.

#typesense#search-engine#full-text-search#docker#typo-tolerant
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed typesense v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Analyze the sales data in revenue.csv and identify trends"
  • "Create a visualization comparing Q1 vs Q2 performance metrics"

Information

Version
1.0.0
Author
terminal-skills
Category
Data & AI
License
Apache-2.0

Documentation

Typesense is a fast, typo-tolerant search engine you can self-host. It offers sub-50ms search, built-in typo correction, faceting, filtering, and geo-search.

Installation

bash
# Docker deployment
docker run -d --name typesense -p 8108:8108 \
  -v typesense-data:/data \
  typesense/typesense:27.1 \
  --data-dir /data \
  --api-key=xyz123 \
  --enable-cors

# Node.js client
npm install typesense

# Python client
pip install typesense

Create a Collection

javascript
// create-collection.js: Define a collection schema
const Typesense = require('typesense');

const client = new Typesense.Client({
  nodes: [{ host: 'localhost', port: 8108, protocol: 'http' }],
  apiKey: 'xyz123',
  connectionTimeoutSeconds: 5,
});

async function createCollection() {
  await client.collections().create({
    name: 'products',
    fields: [
      { name: 'name', type: 'string' },
      { name: 'description', type: 'string' },
      { name: 'price', type: 'float', facet: true },
      { name: 'category', type: 'string', facet: true },
      { name: 'rating', type: 'float', facet: true },
      { name: 'in_stock', type: 'bool', facet: true },
      { name: 'tags', type: 'string[]', facet: true },
    ],
    default_sorting_field: 'rating',
  });
}

createCollection().catch(console.error);

Index Documents

javascript
// index-documents.js: Import documents into Typesense
const documents = [
  { id: '1', name: 'MacBook Pro', description: 'Apple laptop with M3 chip', price: 1999, category: 'Laptops', rating: 4.8, in_stock: true, tags: ['apple', 'laptop'] },
  { id: '2', name: 'ThinkPad X1', description: 'Lenovo business laptop', price: 1499, category: 'Laptops', rating: 4.5, in_stock: true, tags: ['lenovo', 'laptop'] },
];

// Single document
await client.collections('products').documents().create(documents[0]);

// Bulk import (JSONL)
const results = await client.collections('products').documents().import(documents, { action: 'upsert' });
console.log(results);

Search

javascript
// search.js: Search with typo tolerance, filters, and facets
const results = await client.collections('products').documents().search({
  q: 'laptp',  // typo-tolerant — matches "laptop"
  query_by: 'name,description,tags',
  filter_by: 'price:<2000 && in_stock:true',
  sort_by: 'rating:desc',
  facet_by: 'category,tags',
  per_page: 10,
  page: 1,
  highlight_full_fields: 'name,description',
});

console.log(`Found ${results.found} results`);
results.hits.forEach(hit => {
  console.log(hit.document.name, hit.highlights);
});

Python Client

python
# search.py: Typesense with Python client
import typesense

client = typesense.Client({
    'nodes': [{'host': 'localhost', 'port': '8108', 'protocol': 'http'}],
    'api_key': 'xyz123',
    'connection_timeout_seconds': 5,
})

# Search
results = client.collections['products'].documents.search({
    'q': 'laptop',
    'query_by': 'name,description',
    'filter_by': 'price:<2000',
    'sort_by': 'rating:desc',
})

for hit in results['hits']:
    print(hit['document']['name'], hit['document']['price'])

Geo Search

javascript
// geo-search.js: Location-based search with Typesense
// Collection must have a geopoint field: { name: 'location', type: 'geopoint' }
const results = await client.collections('stores').documents().search({
  q: '*',
  query_by: 'name',
  filter_by: 'location:(48.8566, 2.3522, 10 km)',
  sort_by: 'location(48.8566, 2.3522):asc',
});

Synonyms and Curation

javascript
// synonyms.js: Configure search synonyms and curations
// Synonyms
await client.collections('products').synonyms().upsert('laptop-synonyms', {
  synonyms: ['laptop', 'notebook', 'portable computer'],
});

// Curate results — pin or hide specific documents for a query
await client.collections('products').overrides().upsert('featured-laptop', {
  rule: { query: 'best laptop', match: 'exact' },
  includes: [{ id: '1', position: 1 }],
  excludes: [{ id: '99' }],
});

Docker Compose for Production

yaml
# docker-compose.yml: Typesense cluster with 3 nodes
services:
  typesense-1:
    image: typesense/typesense:27.1
    ports:
      - "8108:8108"
    volumes:
      - ts1-data:/data
    command: >
      --data-dir /data
      --api-key=xyz123
      --nodes=/config/nodes.txt
      --peering-address=typesense-1
      --peering-port=8107

volumes:
  ts1-data: