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

Getting Started

Dashboard

Gateway

Python SDK

TypeScript SDK

Guides

API Reference

​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