Introduction

TopK is a hybrid retrieval engine built on object storage for 10x lower cost and massive scale. It supports dense/sparse vector search, multi-vector retrieval, powerful filtering, custom ranking, and managed inference in one API.

Get Started

Prerequisites

TopK account (Sign up here)
TopK API key (Get an API key here)

Hybrid Search

Simple example to get you started with TopK. Check out our guides for more complex examples.

Python SDK
JavaScript SDK
SQL

Install Python SDK

pip install topk-sdk

uv add topk-sdk

Initialize the client

Setup the TopK client with your API key and region.

import os
from topk_sdk import Client

client = Client(
    api_key=os.environ["TOPK_API_KEY"],
    region=os.environ.get("TOPK_REGION", "aws-us-east-1-elastica"),
)

import os
from topk_sdk import AsyncClient

client = AsyncClient(
    api_key=os.environ["TOPK_API_KEY"],
    region=os.environ.get("TOPK_REGION", "aws-us-east-1-elastica"),
)

See available regions for a full list of supported regions.

Create a collection

client.collections().create(
  "quickstart",
  schema={
    "title": text().required().index(keyword_index()),
    "content": text().index(semantic_index()),
  }
)

await client.collections().create(
  "quickstart",
  schema={
    "title": text().required().index(keyword_index()),
    "content": text().index(semantic_index()),
  }
)

Upsert documents

client.collection("quickstart").upsert([
  {
      "_id": "1",
      "title": "Catcher in the Rye",
      "content": "IF YOU REALLY WANT TO HEAR about it, the first thing you'll probably want to know is ...",
      "author": "J.D. Salinger",
      "year": 1951,
  },
  {
      "_id": "2",
      "title": "1984",
      "content": "It was a bright cold day in April, and the clocks were striking thirteen. Winston Smith, ...",
      "author": "George Orwell",
      "year": 1949,
  },
  ...
])

await client.collection("quickstart").upsert([
  {
      "_id": "1",
      "title": "Catcher in the Rye",
      "content": "IF YOU REALLY WANT TO HEAR about it, the first thing you'll probably want to know is ...",
      "author": "J.D. Salinger",
      "rating": 3.8
  },
  {
      "_id": "2",
      "title": "1984",
      "content": "It was a bright cold day in April, and the clocks were striking thirteen. Winston Smith, ...",
      "author": "George Orwell",
      "rating": 4.7
  },
  ...
])

Query indexed data

from topk_sdk.query import select, field, fn

client.collection("quickstart").query(
  select(
    # Select document fields to return
    "_id", "title", "author",
    # Compute semantic similarity of content field with the query
    similarity_score = fn.semantic_similarity(
      "content",
      "What is the meaning of life?",
    )
  )
  # Filter documents by metadata
  .filter(field("rating") >= 3.0)
  # Rank using the computed similarity score and rating
  .sort(field("rating") * field("similarity_score"), asc=False)
  # Get top 10 highest ranked documents
  .limit(10)
)

from topk_sdk.query import select, field, fn

await client.collection("quickstart").query(
  select(
    # Select document fields to return
    "_id", "title", "author",
    # Compute semantic similarity of content field with the query
    similarity_score = fn.semantic_similarity(
      "content",
      "What is the meaning of life?",
    )
  )
  # Filter documents by metadata
  .filter(field("rating") >= 3.0)
  # Rank using the computed similarity score and rating
  .sort(field("rating") * field("similarity_score"), asc=False)
  # Get top 10 highest ranked documents
  .limit(10)
)

To learn more about how to use the Python SDK, see the Python SDK documentation.

Install JavaScript SDK

npm install topk-js

yarn add topk-js

pnpm add topk-js

Initialize the client

Setup the TopK client with your API key and region.

import { Client } from "topk-js";

const client = new Client({
  apiKey: process.env.TOPK_API_KEY!,
  region: process.env.TOPK_REGION ?? "aws-us-east-1-elastica",
});

See available regions for a full list of supported regions.

Create a collection

import { text, keywordIndex, semanticIndex } from "topk-js/schema";

await client.collections().create("quickstart", {
  title: text().required().index(keywordIndex()),
  content: text().index(semanticIndex()),
});

Upsert documents

await client.collection("quickstart").upsert([
  {
    _id: "1",
    title: "Catcher in the Rye",
    content: "IF YOU REALLY WANT TO HEAR about it, the first thing you'll probably want to know is ...",
    author: "J.D. Salinger",
    rating: 3.8,
  },
  {
    _id: "2",
    title: "1984",
    content: "It was a bright cold day in April, and the clocks were striking thirteen. Winston Smith, ...",
    author: "George Orwell",
    rating: 4.7,
  },
  // ...
]);

Query indexed data

import { select, field, fn } from "topk-js/query";

await client.collection("quickstart").query(
  select({
    title: field("title"),
    author: field("author"),
    // Compute semantic similarity of content field with the query
    similarity_score: fn.semanticSimilarity(
      "content",
      "What is the meaning of life?",
    ),
  })
  // Filter documents by metadata
  .filter(field("rating").gte(3.0))
  // Rank using the computed similarity score and rating
  .sort(field("rating").mul(field("similarity_score")), false)
  // Get top 10 highest ranked documents
  .limit(10)
);

To learn more about how to use the JavaScript SDK, see the JavaScript SDK documentation.

Connect

Connect using any PostgreSQL client. Use your API key as the password.

psql "host=<region>.sql.topk.io port=5432 user=topk password=$TOPK_API_KEY dbname=topk"

Create a collection

CREATE TABLE quickstart (
  title   TEXT NOT NULL INDEX keyword_index(),
  content TEXT          INDEX semantic_index(),
  rating  FLOAT
);

Upsert documents

INSERT INTO quickstart (_id, title, content, author, rating)
VALUES
  ('1', 'Catcher in the Rye',
   'IF YOU REALLY WANT TO HEAR about it, the first thing you''ll probably want to know is ...',
   'J.D. Salinger', 3.8),
  ('2', '1984',
   'It was a bright cold day in April, and the clocks were striking thirteen. Winston Smith, ...',
   'George Orwell', 4.7);

Query indexed data

SELECT
  _id,
  title,
  semantic_similarity(content, 'What is the meaning of life?') AS similarity_score
FROM quickstart
WHERE rating >= 3.0
ORDER BY similarity_score * rating DESC
LIMIT 10;

Integrations

Python SDK

Full Python SDK reference.

JavaScript SDK

Full TypeScript/JavaScript SDK reference.

CLI

The command-line interface for TopK.

Security & Compliance

TopK is SOC 2 Type I certified. Visit the trust center for full details.

Data encryption

All data is encrypted in transit and at rest.

Access control

Role-based access control with full auditability.

Private Deployment

Deploy inside your own VPC for complete isolation and data residency. Contact us for more details.

Overview

Collection API

Management API

Introduction

Get Started

Hybrid Search

Integrations

Python SDK

JavaScript SDK

CLI

Security & Compliance

Data encryption

Access control

Private Deployment

Learn More

Architecture

Concepts

​Get Started

​Hybrid Search

​Integrations

Python SDK

JavaScript SDK

CLI

​Security & Compliance

Data encryption

Access control

Private Deployment

​Learn More

Architecture

Concepts

Get Started

Hybrid Search

Integrations

Security & Compliance

Learn More