tokengauge 0.1.5

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

TokenWatch SDK

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

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

Install

pip install tokenwatch-sdk

Quick start

1. Sign up at tokenwatch.ai and copy your API token from the dashboard.

2. Wrap your client:

from tokenwatch import TokenWatch
import openai

tw = TokenWatch(token="your-token-here", base_url="https://your-server.com")

# One-line wrap — use the client exactly as before
client = tw.wrap(openai.OpenAI(api_key="sk-..."))

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}],
)
# Token usage now appears on your dashboard automatically

Anthropic

import anthropic

client = tw.wrap(anthropic.Anthropic(api_key="sk-ant-..."))

response = client.messages.create(
    model="claude-3-haiku-20240307",
    max_tokens=256,
    messages=[{"role": "user", "content": "Hello!"}],
)

Async clients

import openai, asyncio

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!"}],
    )

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 = TokenWatch.login(
    email="[e-mail]",
    password="your-password",
    base_url="https://your-server.com",
)

Google Colab example

!pip install tokenwatch-sdk openai

from tokenwatch import TokenWatch
import openai

tw = TokenWatch(token="paste-your-token-here", base_url="https://your-server.com")
client = tw.wrap(openai.OpenAI(api_key="sk-..."))

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Summarize the theory of relativity in one paragraph."}],
)
print(response.choices[0].message.content)