Two research models are available: exa-research and exa-ultra.

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Example: JavaScript (Node.js)

import { OpenAI } from "openai";

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

  const stream = await openai.chat.completions.create({
    model: "exa-research",
    messages: [
      {
        role: "user",
        content: "What are ants",
      },
    ],
    stream: true,
  });

  for await (const chunk of stream) {
    const content = chunk.choices?.[0]?.delta?.content;
    if (content) {
      process.stdout.write(content);
    }
  }
}

main().catch((err) => {
  console.error("Chat completion example failed:", err);
  process.exit(1);
});

​
Example: Python

import os
from openai import OpenAI

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

completion = client.chat.completions.create(
    model="exa-research",
    messages=[
        {"role": "user", "content": "What makes some LLMs so much better than others?"}
    ],
    stream=True,
)

for chunk in completion:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)