tokengauge 0.2.2

Zero-config AI usage tracking — wrap any OpenAI/Anthropic/Gemini client and log to your TokenGauge dashboard

TokenGauge SDK

Zero-config AI usage tracking. Wrap your existing OpenAI, Anthropic, or Google Gemini client with one line — every call is automatically logged to your TokenGauge dashboard.

Your API keys stay with you. The SDK only reads token counts from API responses and sends them to TokenGauge. Nothing is proxied.

Install

pip install tokengauge

Quick start

1. Sign up at tokengauge.onrender.com and copy your SDK token from Settings.

2. Wrap your client:

from tokengauge import TokenGauge
import openai

tw = TokenGauge(token="your-sdk-token")
client = tw.wrap(openai.OpenAI(api_key="sk-..."))

# Use exactly as before — usage appears on your dashboard automatically
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

Anthropic

from tokengauge import TokenGauge
import anthropic

tw = TokenGauge(token="your-sdk-token")
client = tw.wrap(anthropic.Anthropic(api_key="sk-ant-..."))

response = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=256,
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.content[0].text)

Google Gemini

from tokengauge import TokenGauge
from google import genai

tw = TokenGauge(token="your-sdk-token")
client = tw.wrap(genai.Client(api_key="your-gemini-key"))

response = client.models.generate_content(
    model="gemini-1.5-flash",
    contents="Hello!",
)
print(response.text)

Async clients

from tokengauge import TokenGauge
import openai, asyncio

tw = TokenGauge(token="your-sdk-token")
client = tw.wrap(openai.AsyncOpenAI(api_key="sk-..."))

async def main():
    response = await client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": "Hello!"}],
    )
    print(response.choices[0].message.content)

asyncio.run(main())

Tag calls by feature

summarizer = tw.wrap(openai.OpenAI(api_key="sk-..."), app_tag="summarizer")
chatbot    = tw.wrap(openai.OpenAI(api_key="sk-..."), app_tag="chatbot")

Login instead of pasting a token

tw = TokenGauge.login(email="[e-mail]", password="your-password")

What gets tracked

Field	Description
Provider	openai / anthropic / google
Model	e.g. gpt-4o-mini, claude-3-5-sonnet
Tokens in	Prompt token count
Tokens out	Completion token count
Cost (USD)	Calculated from current model pricing
Latency	End-to-end request time in ms
App tag	Optional label you set per-client