xAI

xAI provides access to the Grok family of language models designed for reasoning and real-time information processing. Braintrust integrates seamlessly with xAI through direct API access, wrapper functions for automatic tracing, and proxy support.

Setup

To use xAI models, configure your xAI API key in Braintrust.

Get an xAI API key from xAI Console
Add the xAI API key as an organization or project AI provider.
Set the xAI API key and your Braintrust API key as environment variables

.env

XAI_API_KEY=<your-xai-api-key>
BRAINTRUST_API_KEY=<your-braintrust-api-key>

# For organizations on the EU data plane, use https://api-eu.braintrust.dev
# For self-hosted deployments, use your data plane URL
# BRAINTRUST_API_URL=<your-braintrust-api-url>

API keys are stored as one-way cryptographic hashes, never in plaintext.

Use xAI with Braintrust gateway

The Braintrust gateway allows you to access xAI models through a unified interface. Use any supported provider’s SDK to call xAI models. First, install the braintrust and openai packages.

# pnpm
pnpm add braintrust openai
# npm
npm install braintrust openai

pip install braintrust openai

Then, initialize the client and make a request to a xAI model via the Braintrust gateway.

import { OpenAI } from "openai";

const client = new OpenAI({
  baseURL: "https://gateway.braintrust.dev/v1",
  apiKey: process.env.BRAINTRUST_API_KEY,
});

const response = await client.chat.completions.create({
  model: "grok-4",
  messages: [{ role: "user", content: "Hello, world!" }],
});

import os

from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.braintrust.dev/v1",
    api_key=os.environ["BRAINTRUST_API_KEY"],
)

response = client.chat.completions.create(
    model="grok-4",
    messages=[{"role": "user", "content": "Hello, world!"}],
)

Trace logs with xAI

Trace your xAI LLM calls for observability and monitoring. When using the Braintrust gateway, API calls are automatically logged to the specified project.

import { OpenAI } from "openai";
import { initLogger } from "braintrust";

initLogger({
  projectName: "My Project",
  apiKey: process.env.BRAINTRUST_API_KEY,
});

const client = new OpenAI({
  baseURL: "https://gateway.braintrust.dev/v1",
  apiKey: process.env.BRAINTRUST_API_KEY,
});

// All API calls are automatically logged
const result = await client.chat.completions.create({
  model: "grok-4",
  messages: [{ role: "user", content: "What is machine learning?" }],
});

import os

from braintrust import init_logger
from openai import OpenAI

init_logger(project="My Project")

client = OpenAI(
    base_url="https://gateway.braintrust.dev/v1",
    api_key=os.environ["BRAINTRUST_API_KEY"],
)

# All API calls are automatically logged
result = client.chat.completions.create(
    model="grok-4",
    messages=[{"role": "user", "content": "What is machine learning?"}],
)

The Braintrust gateway is not required. For more control, learn how to customize traces.

Evaluate with xAI

Evaluations distill the non-deterministic outputs of xAI models into an effective feedback loop that enables you to ship more reliable, higher quality products. Braintrust Eval is a simple function composed of a dataset of user inputs, a task, and a set of scorers. To learn more about evaluations, check out the Experiments guide.

import { Eval } from "braintrust";
import { OpenAI } from "openai";

const client = new OpenAI({
  baseURL: "https://gateway.braintrust.dev/v1",
  apiKey: process.env.BRAINTRUST_API_KEY,
});

Eval("xAI Evaluation", {
  data: () => [
    { input: "What is 2+2?", expected: "4" },
    { input: "What is the capital of France?", expected: "Paris" },
  ],
  task: async (input) => {
    const response = await client.chat.completions.create({
      model: "grok-4",
      messages: [{ role: "user", content: input }],
    });
    return response.choices[0].message.content;
  },
  scores: [
    {
      name: "accuracy",
      scorer: (args) => (args.output === args.expected ? 1 : 0),
    },
  ],
});

import os

from braintrust import Eval
from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.braintrust.dev/v1",
    api_key=os.environ["BRAINTRUST_API_KEY"],
)


def task(input):
    response = client.chat.completions.create(
        model="grok-4",
        messages=[{"role": "user", "content": input}],
    )
    return response.choices[0].message.content


def accuracy_scorer(output, expected, **kwargs):
    return 1 if output == expected else 0


Eval(
    "xAI Evaluation",
    data=[
        {"input": "What is 2+2?", "expected": "4"},
        {"input": "What is the capital of France?", "expected": "Paris"},
    ],
    task=task,
    scores=[accuracy_scorer],
)

To learn more about tool use, multimodal support, attachments, and masking sensitive data with xAI, visit the customize traces guide.

AI providers

SDKs

Developer tools

Setup

Use xAI with Braintrust gateway

Trace logs with xAI

Evaluate with xAI

​Setup

​Use xAI with Braintrust gateway

​Trace logs with xAI

​Evaluate with xAI

Setup

Use xAI with Braintrust gateway

Trace logs with xAI

Evaluate with xAI