app.py

import gradio as gr
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
import random

#model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base")
#tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-base")

    
def generate(text,ver):
    if ver == "Hidden Identity 1":
        guess = "Michael Jackson"
    else:
        guess = "Brad Pitt"
    return random.choice(["Yes","No"])
    #inputs =  tokenizer(f"Answer with yes or no the following question about {guess}: {text}?", return_tensors="pt")
    #return tokenizer.batch_decode(model.generate(**inputs), skip_special_tokens=True)[0]

examples = [
    ["Is he/she dead?"],
    ["Is he/she a female?"],
]

title = "Who is who chatgpt"
description = "Guess who is the person that chatgpt is thinking of today with the minimum number of questions!!"


demo = gr.Interface(
    fn=generate,
    inputs=[gr.inputs.Textbox(lines=5, label="Input Text"),
    		gr.inputs.Radio(["Hidden Identity 1","Hidden Identity 2"], type="value", default='Hidden Identity 1', label='Hidden identity')],
    outputs=gr.outputs.Textbox(label="Generated Text"),
    title=title,
    description=description,
    examples=examples
)

demo.launch()