Gateway Setup

This guide shows you how to route your LLM requests through the Muxx Gateway.

Prerequisites

A Muxx account with a project created
Your Muxx API key (muxx_sk_live_...)
Provider API keys configured in your project settings

Configuration

OpenAI

Python
TypeScript
cURL

from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.muxx.dev/v1",
    default_headers={
        "X-Muxx-Api-Key": "muxx_sk_live_xxxxxxxxxxxx"
    }
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
)
print(response.choices[0].message.content)

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://gateway.muxx.dev/v1',
  defaultHeaders: {
    'X-Muxx-Api-Key': 'muxx_sk_live_xxxxxxxxxxxx',
  },
});

const response = await client.chat.completions.create({
  model: 'gpt-4o',
  messages: [
    { role: 'user', content: 'Explain quantum computing in simple terms' },
  ],
});
console.log(response.choices[0].message.content);

curl https://gateway.muxx.dev/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "X-Muxx-Api-Key: muxx_sk_live_xxxxxxxxxxxx" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Anthropic

Python
TypeScript

from anthropic import Anthropic

client = Anthropic(
    base_url="https://gateway.muxx.dev/v1",
    default_headers={
        "X-Muxx-Api-Key": "muxx_sk_live_xxxxxxxxxxxx"
    }
)

response = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
)
print(response.content[0].text)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  baseURL: 'https://gateway.muxx.dev/v1',
  defaultHeaders: {
    'X-Muxx-Api-Key': 'muxx_sk_live_xxxxxxxxxxxx',
  },
});

const response = await client.messages.create({
  model: 'claude-3-5-sonnet-20241022',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Explain quantum computing in simple terms' },
  ],
});
console.log(response.content[0].text);

Environment Variables

We recommend storing your Muxx API key in environment variables:

export MUXX_API_KEY="muxx_sk_live_xxxxxxxxxxxx"

Then reference it in your code:

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.muxx.dev/v1",
    default_headers={
        "X-Muxx-Api-Key": os.environ["MUXX_API_KEY"]
    }
)

Adding Metadata

You can attach custom metadata to requests for filtering in the dashboard:

client = OpenAI(
    base_url="https://gateway.muxx.dev/v1",
    default_headers={
        "X-Muxx-Api-Key": "muxx_sk_live_xxxxxxxxxxxx",
        "X-Muxx-Metadata": '{"user_id": "user_123", "feature": "chat"}'
    }
)

This metadata appears in the dashboard and can be used for filtering and analytics.

Streaming

The gateway fully supports streaming responses:

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Write a haiku"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Getting Started

Dashboard

Gateway

Python SDK

TypeScript SDK

Guides

API Reference

Gateway Setup

Prerequisites

Configuration

OpenAI

Anthropic

Environment Variables

Adding Metadata

Streaming

Next Steps

Caching

Rate Limiting

​Prerequisites

​Configuration

​OpenAI

​Anthropic

​Environment Variables

​Adding Metadata

​Streaming

​Next Steps

Caching

Rate Limiting

Prerequisites

Configuration

OpenAI

Anthropic

Environment Variables

Adding Metadata

Streaming

Next Steps