Every Token Counts: The Art of (Dynamic) OpenAI API Cost Optimization
<p>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:</p>
<ol>
<li><strong><em>Estimating Token Usage</em></strong>: How to determine token usage before making an API call.</li>
<li><strong><em>Predicting Costs</em></strong>: How to forecast the costs based on token count.</li>
<li><strong><em>Dynamically Selecting Models</em></strong>: Choosing the most cost-effective model without compromising performance.</li>
</ol>
<p>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.</p>
<h1>Token Estimation with <em>tiktoken</em></h1>
<p>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.</p>
<p><strong>What is `tiktoken`?</strong></p>
<p>`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.</p>
<p><a href="https://medium.com/@aglaforge/every-token-counts-the-art-of-dynamic-openai-cost-optimization-55a51f62971d">Website</a></p>