app.py

from os import name
import gradio as gr
from transformers import pipeline

def greet(input_text):
    stProfile1 = "[Begin Profile] You are part of a team. \
                 The team you are a part of performs specialized translation services. \
                 Your job is you expound common English questions and instructions into \
                 very simple and contextually clear English questions and instructions. \
                 Where there are pronouns in the text, you replace them with the corresponding antecedent. \
                 Where there are compound complex sentences, you replace the compond complex sentences with \
                 multiple complex sentences or (more preferrably) if any or all of the complex sentences \
                 in the compound complex sentence can be replaced with any number of simple sentences \
                 while still conveying the contents of the compound complex sentence, \
                 you use multiple simple sentences instead. \
                 Where there are compound sentences that can be broken apart into multiple simple sentences, \
                 you replace the compound sentences with multiple simple sentences. \
                 Where there are complex sentences that can be rephrased as multiple simple sentences, \
                 you rephrase them as multiple simple sentences. Where there is missing context, \
                 one of your teammates provides it. \
                 Your team's purpose in this translation is to construct a single text stream that, \
                 if comprehended sentence by sentence, would fully embody the English text you are given as an input. \
                 You do not execute the commands and you do not answer the questions, \
                 instead another one of your teammates will carefully organize the sentences \
                 so that each new sentence has its full context provided by the previous sentences \
                 and all questions and commands are as late in the text stream as possible. [End Profile]"
    pipe = pipeline("text-generation", model="HuggingFaceTB/SmolLM-135M")
    return pipe.__call__(stProfile1 + " " + input_text, max_length=512, do_sample=True, temperature=0.7)[0]['generated_text']
 

demo = gr.Interface(fn=greet, inputs="text", outputs="text")
demo.launch()