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import gradio as gr | |
import tiktoken | |
encodings = tiktoken.list_encoding_names() | |
encodings.reverse() | |
def function(input, encoding): | |
tokens = tiktoken.get_encoding(encoding).encode(input) | |
return len(tokens) | |
value1 = gr.Textbox(lines=6, label="Input", placeholder="Enter text here...") | |
value2 = gr.Dropdown( | |
label="Encoding", | |
choices=encodings, | |
value="cl100k_base", | |
info="The encoding to use. (GPT-3.5 and GPT-4 use cl100k_base as their encoding.)" | |
) | |
value3 = gr.Number(label="Output") # Don't include lines and placeholder | |
examples = [ | |
["The only way to do great work is to love what you do. - Steve Jobs", "cl100k_base"], | |
["In the end, we will remember not the words of our enemies, but the silence of our friends. - Martin Luther King Jr.", "cl100k_base"], | |
["Success is not final, failure is not fatal: It is the courage to continue that counts. - Winston Churchill", "cl100k_base"], | |
["The greatest glory in living lies not in never falling, but in rising every time we fall. - Nelson Mandela", "cl100k_base"], | |
["The best and most beautiful things in the world cannot be seen or even touched - they must be felt with the heart. - Helen Keller", "cl100k_base"] | |
] | |
demo = gr.Interface( | |
fn=function, | |
inputs=[value1, value2], | |
outputs=value3, | |
title="ChatGPT Token Calculator", | |
examples=examples, | |
description="Calculate the number of tokens in a text string." | |
) | |
demo.launch(debug=True) |