@font-face {
  font-family: 'Reckless';
  src: url('https://exa.ai/search/fonts/RecklessTRIAL-Medium.woff2');
  font-weight: normal;
  font-style: normal;
  font-display: swap;
}

@font-face {
    font-family: 'ABCDiatype';
    src: url("https://exa.ai/search/fonts/ABCDiatype-Regular.otf") format("opentype");
}

@font-face {
  font-family: 'SuisseIntlMono';
  src: url("https://exa.ai/search/fonts/SuisseIntlMono-Regular-WebTrial.woff2") format('woff2');
}

h1, h2, h3 {
  font-family: 'Reckless';
  letter-spacing: normal !important;
  margin-bottom: 1rem !important;
}

p {
    font-family: 'ABCDiatype';
}

.card {
  border-radius: 15px;
  overflow: hidden;
  margin-bottom: 1rem !important;
}

pre {
  margin-top: 0.5rem !important;
  margin-bottom: 0.5rem !important;
}

section,
.section,
.content section {
  margin-bottom: 1rem !important;
}

h1, h2, h3, h4 {
  margin-top: 0.5rem !important;
  margin-bottom: 0.5rem !important;
}

hr {
  margin-bottom: 1.5rem !important;
  margin-top: 1.5rem !important;;
}

.anchor-icon-wrapper {
  border-radius: 50% !important;
}

.anchors-icon {
  border-radius: 50% !important;
}

.py-6 {
  padding-top: 0.5rem;
  padding-bottom: 0.5rem;
}

.mt-4 {
  margin-top: 0.5rem;
}

.text-primary-light {
  color: #FFFFFF !important;
}

.border-primary-light {
  border-color: #FFFFFF !important;
}

.border-primary {
  border-color: #FFFFFF !important;
}

.card-title {
  font-family: 'ABCDiatype' !important;
  font-size: 1.2rem !important;
  padding-top: 0.5rem !important;
}

.mt-2 {
  margin-top: .5rem;
  margin-bottom: .5rem;
}

/* Reduces spacing between title and text in steps */
.w-full.overflow-hidden.pl-12.pr-px p {
  margin-top: 0 !important;
  margin-bottom: 0rem !important;
  padding-top: 0.5rem !important;
}

/* Reduces spacing after code blocks */
.not-prose.rounded-xl {
  margin-bottom: 1rem !important;
} 

hr {
  margin-bottom: 1rem !important;
  margin-top: 1rem !important;
}

.mt-8 {
  margin-top: 1rem !important;
}

.mt-10 {
  margin-top: 1rem !important;
}

.max-h-\[300px\] {
  max-height: 500px !important;  
}

.api-button {
  align-items: center;
  background: rgb(var(--primary));
  color: var(--white, #fff);
  display: flex;
  font-family: var(SuisseIntlMono);
  text-transform: uppercase;
  font-size: 16px;
  font-style: normal;
  font-weight: 400;
  gap: 10px;
  height: 40px;
  justify-content: center;
  line-height: 27px;
  padding: 14px 32px;
  text-decoration: none;
  transition: 0.1s ease-in-out;
  border: 2px solid var(--primary);
  word-spacing: 8px;
  letter-spacing: 1px;
}

.api-button:hover {
  background-color: #000000;
}


Sales

Recruiting

Market Research/Investing

Sourcing

Research Papers

Here are some examples for things to search for, to get you started!

Example queries for Websets

Overview

Welcome to Exa

Make your first request to one of Exa's API endpoints

Quickstart

The search endpoint lets you intelligently search the web and extract contents from the results. 

By default, it automatically chooses between traditional keyword search and Exa's embeddings-based model, to find the most relevant results for your query.

Search

Get the full page contents, summaries, and metadata for a list of URLs.

Returns instant results from our cache, with automatic live crawling as fallback for uncached pages.

Get contents

Find similar links to the link provided and optionally return the contents of the pages.

Find similar links

Get an LLM answer to a question informed by Exa search results. Fully compatable with OpenAI's chat completions endpoint - docs [here](https://docs.exa.ai/reference/chat-completions).

`/answer` performs an Exa search and uses an LLM (GPT-4o-mini) to generate either:
1. A direct answer for specific queries. (i.e. "What is the capital of France?" would return "Paris")
2. A detailed summary with citations for open-ended queries (i.e. "What is the state of ai in healthcare?" would return a summary with citations to relevant sources)

The response includes both the generated answer and the sources used to create it. The endpoint also supports streaming (as `stream=True`), which will returns tokens as they are generated.


Answer

OpenAPI Specification

Learn how to build your first Retrieval Augmented Generation (RAG) system with Exa and OpenAI. 

RAG with Exa and OpenAI

How to use Exa's integration with LangChain to perform RAG.

RAG with LangChain

Enhance your OpenAI chat completetions with a simple Exa wrapper that handles search, chunking and prompting.

OpenAI Exa Wrapper

Learn how to add Exa retrieval capabilities to your CrewAI agents.

CrewAI agents with Exa

A quick-start guide on how to add Exa retrieval to a LlamaIndex Agent Application.

RAG with LlamaIndex

Learn to use OpenAI's tool call feature with Exa's Search Integration

Tool calling with GPT

Using Claude's "Tool Use" Feature with Exa Search Integration.

Tool calling with Claude

Use Exa's /chat/completions endpoint as a drop-in replacement for your OpenAI chat completions code. This will send queries to Exa's `/answer` endpoint

OpenAI Chat Completions

Exa is a novel search engine that utilizes the latest advancements in AI language processing to return the best possible results.

How Exa Search Works

We spend a lot of time and energy creating a high quality, curated index.

The Exa Index

Prompting Guide

Contents retrieval with Exa API

This page explains some of the available feature functionalities of Exa and some unique ways you might use Exa for your use-case

Exa's Capabilities Explained

FAQs

Crawling Subpages with Exa

Exa LiveCrawl

Details on Team structure and account management for the Exa platform

Setting Up and Managing Your Team

Rate Limits

Enterprise Documentation & Security 

A live demo that detects hallucinations in content using Exa's search.

Hallucination Detector

Writing Assistant

Chat app

Company researcher

Twitter Wrapped

Twitter/X post Retrieval

Make your very own Hacker News powered by Exa

Hacker News Clone

Learn how to build an AI-powered news summarizer that searches and summarizes recent articles using Exa and GPT.

Building a News Summarizer

Learn how to build an AI-powered system that identifies and verifies claims using Exa and LangGraph.

Building a Hallucination Checker

Using Exa to enable retrieval-augmented generation.

RAG Q&A

Example project using the Exa Python SDK.

Company Analyst

Exa Researcher - JavaScript

Exa Researcher - Python

Recruiting Agent

Phrase Filters: Niche Company Finder

Tutorial for simple Exa searches on our front-end.

Job Search with Exa

Build a Retrieval Agent with LangGraph

Using Exa with instructor to generate structured outputs from web content.

Structured Outputs with Instructor

LangChain Docs

LlamaIndex Docs

CrewAI Docs

Enumeration of methods and types in the Exa Python SDK (exa_py).

Python SDK Specification

TypeScript SDK Specification

Some common code you might want to use - don't miss the TypeScript tab below!

Python and TS Cheat Sheets

Welcome to Websets! Our goal is to help you find anything you want on the web, no matter how complex.

Get started

Websets FAQ

Auto search, which intelligently combines Exa's proprietary neural search with traditional keyword search, is now the default search type for all queries.

Websets

​Sales

​Recruiting

​Market Research/Investing

​Sourcing

​Research Papers

Sales

Recruiting

Market Research/Investing

Sourcing

Research Papers