OpenAI Integration

from muxx import Muxx
from openai import OpenAI

muxx = Muxx()
client = muxx.wrap(OpenAI())

# All calls are now automatically traced
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}]
)

from muxx import Muxx
from openai import AsyncOpenAI

muxx = Muxx()
client = muxx.wrap(AsyncOpenAI())

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

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

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

# The complete response is logged when streaming finishes

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get weather for a location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {"type": "string"}
                }
            }
        }
    }
]

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "What's the weather in Paris?"}],
    tools=tools
)

# Tool calls are logged with the response

from muxx import Muxx, trace
from openai import OpenAI

muxx = Muxx()
client = muxx.wrap(OpenAI())

@trace("customer-support")
def handle_support_request(user_message: str):
    # Classify intent
    intent = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "system", "content": "Classify the intent: billing, technical, general"},
            {"role": "user", "content": user_message}
        ]
    )

    # Generate response
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "system", "content": f"You are a {intent.choices[0].message.content} support agent"},
            {"role": "user", "content": user_message}
        ]
    )

    return response.choices[0].message.content

embeddings = client.embeddings.create(
    model="text-embedding-3-small",
    input=["Hello world", "Goodbye world"]
)

# Token usage and latency are logged

from muxx import Muxx
from openai import OpenAI

muxx = Muxx()

# Point to gateway for caching/rate limiting
# SDK still adds tracing
client = muxx.wrap(OpenAI(
    base_url="https://gateway.muxx.dev/v1",
    default_headers={"X-Muxx-Api-Key": muxx.api_key}
))