OpenAI SDK Compatibility

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Overview

Exa provides OpenAI-compatible endpoints that work seamlessly with the OpenAI SDK:

Endpoint	OpenAI Interface	Models Available	Use Case
`/chat/completions`	Chat Completions API	`exa`	Traditional chat interface
`/responses`	Responses API	`exa-agent`	Agent API (async research, enrichment, list-building)

/chat/completions routes to /answer. /responses routes to the Agent API — see Agent via Responses API below.

Answer

To use Exa’s /answer endpoint via the chat completions interface:

Replace base URL with https://api.exa.ai
Replace API key with your Exa API key
Replace model name with exa.

See the full /answer endpoint reference here.

Need custom behavior when routing through /answer? Contact us at hello@exa.ai and we can help tailor the integration.

import os
from openai import OpenAI

client = OpenAI(
  base_url="https://api.exa.ai", # use exa as the base url
  api_key=os.environ["EXA_API_KEY"],
)

completion = client.chat.completions.create(
  model="exa",
  messages = [
  {"role": "system", "content": "You are a helpful assistant."},
  {"role": "user", "content": "What are the latest developments in quantum computing?"}
],

# use extra_body to pass extra parameters to the /answer endpoint
  extra_body={
    "text": True # include full text from sources
  }
)

print(completion.choices[0].message.content)  # print the response content
print(completion.choices[0].message.citations)  # print the citations

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.exa.ai", // use exa as the base url
  apiKey: process.env.EXA_API_KEY,
});

async function main() {
  const completion = await openai.chat.completions.create({
    model: "exa",
    messages: [
      { role: "system", content: "You are a helpful assistant." },
      {
        role: "user",
        content: "What are the latest developments in quantum computing?",
      },
    ],
    store: true,
    stream: true,
    extra_body: {
      text: true, // include full text from sources
    },
  });

  for await (const chunk of completion) {
    console.log(chunk.choices[0].delta.content);
  }
}

main();

curl https://api.exa.ai/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $EXA_API_KEY" \
  -d '{
    "model": "exa",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "What are the latest developments in quantum computing?"
      }
    ],
    "text": true
  }'

Agent via Responses API

Exa’s /responses endpoint provides OpenAI Responses API compatibility for the Agent API. Runs are asynchronous — set background: true and poll GET /responses/{id} for the result.

The /responses surface maps directly to the Agent API. For the full Agent API reference and examples, see the Agent guide.

import os
import time
from openai import OpenAI

client = OpenAI(
    base_url="https://api.exa.ai",
    api_key=os.environ["EXA_API_KEY"],
)

response = client.responses.create(
    model="exa-agent",
    input="Find the top 5 AI startups founded in 2025 with their funding amounts",
    background=True,
)

# Poll until complete
while response.status in ("queued", "in_progress"):
    time.sleep(5)
    response = client.responses.retrieve(response.id)

print(response.output_text)

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "https://api.exa.ai",
  apiKey: process.env.EXA_API_KEY,
});

async function main() {
  let response = await openai.responses.create({
    model: "exa-agent",
    input: "Find the top 5 AI startups founded in 2025 with their funding amounts",
    background: true,
  });

  // Poll until complete
  while (response.status === "queued" || response.status === "in_progress") {
    await new Promise((r) => setTimeout(r, 5000));
    response = await openai.responses.retrieve(response.id);
  }

  console.log(response.output_text);
}

main();

# Create a background run
curl -X POST 'https://api.exa.ai/responses' \
  -H "x-api-key: $EXA_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "exa-agent",
    "input": "Find the top 5 AI startups founded in 2025 with their funding amounts",
    "background": true
  }'

# Poll with the returned response ID
curl 'https://api.exa.ai/responses/resp_agent_run_...' \
  -H "x-api-key: $EXA_API_KEY"

Chat Wrapper

Exa provides a Python wrapper that automatically enhances any OpenAI chat completion with RAG capabilities. With one line of code, you can turn any OpenAI chat completion into an Exa-powered RAG system that handles search, chunking, and prompting automatically.

from openai import OpenAI
from exa_py import Exa

# Initialize clients
openai = OpenAI(api_key='OPENAI_API_KEY')
exa = Exa(api_key='EXA_API_KEY')

# Wrap the OpenAI client
exa_openai = exa.wrap(openai)

# Use exactly like the normal OpenAI client
completion = exa_openai.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "What is the latest climate tech news?"}]
)

print(completion.choices[0].message.content)

The wrapped client works exactly like the native OpenAI client, except it automatically improves your completions with relevant search results when needed. The wrapper supports any parameters from the exa.search() function.

completion = exa_openai.chat.completions.create(
    model="gpt-4o",
    messages=messages,
    use_exa="auto",              # "auto", "required", or "none"
    num_results=5,               # defaults to 3
    result_max_len=1024,         # defaults to 2048 characters
    include_domains=["arxiv.org"],
    category="research paper",
    start_published_date="2019-01-01"
)

​Overview

​Answer

​Agent via Responses API

​Chat Wrapper

Overview

Answer

Agent via Responses API

Chat Wrapper