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

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Prerequisites

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

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Configuration

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OpenAI

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)

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Anthropic

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)

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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"]
    }
)

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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.

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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="")

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Next Steps

Caching

Enable response caching to reduce costs

Rate Limiting

Configure request limits