How to use Grok (X) API

curl https://api.x.ai/v1/chat/completions -H "Content-Type: application/json" -H "Authorization: Bearer xai-somecoolapikey" -d '{
  "messages": [
    {
      "role": "system",
      "content": "You are a test assistant."
    },
    {
      "role": "user",
      "content": "Testing. Just say hi and hello world and nothing else."
    }
  ],
  "model": "grok-2-latest",
  "stream": false,
  "temperature": 0
}'

But a little bit cleaner:

#source .env
export XAI_API_KEY="xai-somecoolapikey"

Then just execute the query to Grok via web request:

curl https://api.x.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $XAI_API_KEY" \
-d '{
  "messages": [
    {
      "role": "system",
      "content": "You are a test assistant."
    },
    {
      "role": "user",
      "content": "Testing. Which model are you?."
    }
  ],
  "model": "grok-2-latest",
  "stream": false,
  "temperature": 0
}'

Ways to Call Grok

Via curl CLI, as done previously.
But also you can call Grok with python

ℹ️

From Europe, I could not use the image generation APIs, but it seems available via https://x.com/i/grok

Grok via OpenAI API

from openai import OpenAI

client = OpenAI(
api_key=XAI_API_KEY,
base_url="https://api.x.ai/v1",
)

# ...

completion = client.chat.completions.create(
    model="grok-2-latest",
        messages=[
        {
            "role": "system",
            "content": f"""You are an expert assistant""",
        },
        {"role": "user", "content": "What have been the top 5 news in 2025?"}
    ],
    temperature=0.7)

# ...

Grok via Anthropic

from anthropic import Anthropic
    
client = Anthropic(
  api_key=XAI_API_KEY,
  base_url="https://api.x.ai",
)

# ...

message = client.messages.create(
    model="grok-2-latest",
    max_tokens=689,
    temperature=0,
    messages=[
        {"role": "user", "content": f"What are the latest trends in tech?"}
    ]
)

Grok via LiteLLM

https://jalcocert.github.io/JAlcocerT/how-to-use-lite-llm/

Conclusions

This is it.

Now you have one more LLM to play with via API queries!

ℹ️

See Streamlit-Multichat Source Code 💻

[AI] Using LiteLLM to unify LLMs calls.Audio with AI. TTS and Voice Cloning