Have you started developing with OpenAI and found yourself wondering about the costs? If so, you’re in good company. In this guide, we’ll explore:
- Estimating Token Usage: How to determine token usage before making an API call.
- Predicting Costs: How to forecast the costs based on token count.
- Dynamically Selecting Models: Choosing the most cost-effective model without compromising performance.
Understanding token usage and its costs is essential, especially for frequent or large-scale API users. It helps you extract the maximum value from the OpenAI API.
Token Estimation with tiktoken
Tokens are at the heart of cost management when working with OpenAI. But how do we count them accurately? That’s where `tiktoken` comes in — a Python library from OpenAI.
What is `tiktoken`?
`tiktoken` lets you determine the number of tokens in a text string without an API call. Think of it as a token counter in your toolkit, helping you gauge and predict costs more effectively.
Setting Up `tiktoken`
Getting started is simple:
pip install tiktoken
How Does It Work?
Unlike basic word counters, `tiktoken` evaluates the text and counts tokens, ranging from a single character to an entire word. For instance, “ChatGPT is great!” translates into five tokens: [“Chat”, “G”, “PT”, “ is”, “ great!”].
Here’s a basic usage example: