text_generator.py

from transformers import AutoTokenizer
 

def tokenize(input_text):
    tokens = tokenizer(input_text)["input_ids"]
    return f"Number of tokens: {len(tokens)}"

tokenize_tool = gr.Interface(
    fn=tokenize,
    inputs=gr.Textbox(lines=7, label="Input Text"),
    outputs=gr.Textbox(label="Tokenization Result"),
    live=True,
    title="GPT-2 Tokenizer",
    description="This tool tokenizes input text using the lgaalves/gpt2-dolly model.",
)

tokenize_tool.launch()

import os
from transformers import pipeline
from transformers import Tool

class TokenCounterTool(Tool):
    name = "text_generator"
    description = "This is a tool for counting token used by a prompt. It takes a prompt as input and returns the generated text."
    inputs = ["text"]
    outputs = ["text"]

    def __call__(self, prompt: str):
        token = os.environ['hf']
        tokenizer = AutoTokenizer.from_pretrained("lgaalves/gpt2-dolly")
        tokens = tokenizer(input_text)["input_ids"]
        return f"Number of tokens: {len(tokens)}"