TikToken (ah...Not TikTok, ok?) Thought might be of interest? For most of us on a budget?

If you want to make sure you're not spending tons of $$$ with GPT4.

Below is a conversation I had with Peplexity AI regarding monitoring how much you will be

spending @ OpenAI.

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To implement OpenAI's tiktoken library directly to count tokens in Python, you can follow a simple example based on the information provided in the OpenAI Cookbook

. The tiktoken library is a fast, open-source tokenizer designed by OpenAI for efficiently counting tokens, which is crucial for managing usage and costs when working with OpenAI's API.

Installation

First, ensure you have tiktoken installed. If not, you can install it using pip:

bash

pip install tiktoken

Counting Tokens with tiktoken

Here's a basic example of how to use tiktoken to count the number of tokens in a given text string:

python

from tiktoken import Tokenizer # Initialize the tokenizer tokenizer = Tokenizer() # Your text input text = "This is a sample text to tokenize." # Tokenize the text and count the tokens tokens = tokenizer.tokenize(text) token_count = len(tokens) print(f"Token count: {token_count}")

This code snippet initializes the tiktoken tokenizer, tokenizes a given text string, and then counts the number of tokens by measuring the length of the resulting list of tokens.

Important Notes

The tiktoken library supports various encodings used by OpenAI models. Make sure to choose the appropriate encoding for the model you are working with. The default tokenizer should work well for general purposes.

Token counts are crucial for understanding how much text you can send to OpenAI's API in a single request and for estimating costs, as OpenAI's pricing is based on the number of tokens processed.

By following this simple example, you can integrate token counting into your applications, helping you to monitor and manage your usage of OpenAI's API more effectively.

Hope this helps out...

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