tokenator 0.1.1

Token usage tracking wrapper for LLMs

Tokenator : Easiest way to track and analyze LLM token usage and cost

Have you ever wondered about :

• How many tokens does your AI agent consume?
• How much does it cost to do run a complex AI workflow with multiple LLM providers?
• How much money did I spent today on development?

Afraid not, tokenator is here! With tokenator's easy to use API, you can start tracking LLM usage in a matter of minutes and track your LLM usage.

Get started with just 3 lines of code!

Installation

pip install tokenator

Usage

OpenAI

from openai import OpenAI
from tokenator import tokenator_openai

openai_client = OpenAI(api_key="your-api-key")

# Wrap it with Tokenator
client = tokenator_openai(openai_client)

# Use it exactly like the OpenAI client
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}]
)

Cost Analysis

from tokenator import cost

# Get usage for different time periods
cost.last_hour()
cost.last_day()
cost.last_week()
cost.last_month()

# Custom date range
cost.between("2024-03-01", "2024-03-15")

# Get usage for different LLM providers
cost.last_day("openai")
cost.last_day("anthropic")
cost.last_day("google")

Example cost object

Features

• Drop-in replacement for OpenAI, Anthropic client
• Automatic token usage tracking
• Cost analysis for different time periods
• SQLite storage with zero configuration
• Thread-safe operations
• Minimal memory footprint
• Minimal latency footprint

Most importantly, none of your data is ever sent to any server.

License

MIT