@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;
}


Discord

Blog

Documentation

Examples

Integrations

Changelog

API Dashboard

Exa Search

LangChain Docs

Overview

Welcome to Exa

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

Quickstart

Search the web with an Exa prompt-engineered query.  

`/search` returns a list of links relevant to your query and optionally get their full page contents.

Search

Retrieve contents of documents based on a list of document IDs.

`/contents` is used to _instantly_ get content for documents, given the IDs of the documents.

Also note that “instant” is a little bit of a lie if you are using keyword search, in which case contents might take a few seconds to retrieve.

Get contents

Find similar links to the link provided and optionally get page contents.

Find similar links

Generate an LLM answer using Exa search results

`/answer` performs an Exa search and uses an LLM to generate either:

- A direct answer for specific queries 
- A detailed summary with citations for complex queries

The response includes both the generated answer and the source documents used to create it. Supports streaming responses for real-time answer generation.

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 OpenAI's endpoint to send queries to Exa's `/answer` endpoint`

Chat Completions Endpoint

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.

Exa-powered Hallucination Detector

Exa-powered Writing Assistant

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

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

LlamaIndex Docs

CrewAI Docs

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