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# import dependencies | |
import gradio as gr | |
from openai import OpenAI | |
import os | |
import random | |
import string | |
# define the openai key | |
api_key = os.getenv("OPENAI_API_KEY") | |
# make an instance of the openai client | |
client = OpenAI(api_key = api_key) | |
# finetuned model instance | |
finetuned_model = "ft:gpt-3.5-turbo-0125:noaigpt::9yy0fWeK" | |
# text processing functions | |
def random_capitalize(word): | |
if word.isalpha() and random.random() < 0.1: | |
return word.capitalize() | |
return word | |
def random_remove_punctuation(text): | |
if random.random() < 0.2: | |
text = list(text) | |
indices = [i for i, c in enumerate(text) if c in string.punctuation] | |
if indices: | |
remove_indices = random.sample(indices, min(3, len(indices))) | |
for idx in sorted(remove_indices, reverse=True): | |
text.pop(idx) | |
return ''.join(text) | |
return text | |
def random_double_period(text): | |
if random.random() < 0.2: | |
text = text.replace('.', '..', 3) | |
return text | |
def random_double_space(text): | |
if random.random() < 0.2: | |
words = text.split() | |
for _ in range(min(3, len(words) - 1)): | |
idx = random.randint(0, len(words) - 2) | |
words[idx] += ' ' | |
return ' '.join(words) | |
return text | |
def random_replace_comma_space(text, period_replace_percentage=0.33): | |
# Count occurrences | |
comma_occurrences = text.count(", ") | |
period_occurrences = text.count(". ") | |
# Replacements | |
replace_count_comma = max(1, comma_occurrences // 3) | |
replace_count_period = max(1, period_occurrences // 3) | |
# Find indices | |
comma_indices = [i for i in range(len(text)) if text.startswith(", ", i)] | |
period_indices = [i for i in range(len(text)) if text.startswith(". ", i)] | |
# Sample indices | |
replace_indices_comma = random.sample(comma_indices, min(replace_count_comma, len(comma_indices))) | |
replace_indices_period = random.sample(period_indices, min(replace_count_period, len(period_indices))) | |
# Apply replacements | |
for idx in sorted(replace_indices_comma + replace_indices_period, reverse=True): | |
if text.startswith(", ", idx): | |
text = text[:idx] + " ," + text[idx + 2:] | |
if text.startswith(". ", idx): | |
text = text[:idx] + " ." + text[idx + 2:] | |
return text | |
def transform_paragraph(paragraph): | |
words = paragraph.split() | |
if len(words) > 12: | |
words = [random_capitalize(word) for word in words] | |
transformed_paragraph = ' '.join(words) | |
transformed_paragraph = random_remove_punctuation(transformed_paragraph) | |
transformed_paragraph = random_double_period(transformed_paragraph) | |
transformed_paragraph = random_double_space(transformed_paragraph) | |
transformed_paragraph = random_replace_comma_space(transformed_paragraph) | |
else: | |
transformed_paragraph = paragraph | |
transformed_paragraph = transformed_paragraph.replace("#", "*") | |
transformed_paragraph = transformed_paragraph.replace("*", "") | |
# transformed_paragraph = transformed_paragraph.replace(", ", " ,") | |
return transformed_paragraph | |
def transform_text(text): | |
paragraphs = text.split('\n') | |
transformed_paragraphs = [transform_paragraph(paragraph) for paragraph in paragraphs] | |
return '\n'.join(transformed_paragraphs) | |
# function to humanize text | |
def humanize_text(AI_text): | |
"""Humanizes the provided AI text using the fine-tuned model.""" | |
response = client.chat.completions.create( | |
model=finetuned_model, | |
temperature = 0.87, | |
messages=[ | |
{"role": "system", "content": """ | |
You are a text humanizer. | |
You humanize AI generated text. | |
The text must appear like humanly written. | |
THE INPUT AND THE OUTPUT HEADINGS MUST BE SAME. NO HEADING SHOULD BE MISSED. | |
NAMES LIKE NOVEL NAME SHOULD REMAIN INTACT WITHOUT ANY CHANGE. | |
THE INPUT AND THE OUTPUT SHOULD HAVE SAME WORD COUNT. | |
THE OUTPUT SENTENCES MUST NOT BE SIMPLE. THEY SHOULD BE COMPOUND, COMPLEX, OR COMPOUND COMPLEX. | |
ABOVE ALL, THE GRAMMAR AND THE SENSE OF THE SENTENCES MUST BE TOP NOTCH - DO NOT COMPROMISE ON THAT."""}, | |
{"role": "system", "content": "YOU ARE TEXT HUMANIZER BUT YOU DO NOT REDUCE THE LENGTH OF THE SENTENCES. YOUR OUTPUT SENTENCES ARE OF EXACTLY THE SAME LENGTH AS THE INPUT"}, | |
{"role": "user", "content": f"THE LANGUAGE OF THE INPUT AND THE OUTPUT MUST BE SAME. THE SENTENCES SHOULD NOT BE SHORT LENGTH - THEY SHOULD BE SAME AS IN THE INPUT. ALSO THE PARAGRAPHS SHOULD NOT BE SHORT EITHER - PARAGRAPHS MUST HAVE THE SAME LENGTH"}, | |
{"role": "user", "content": f"THE GRAMMAR AND THE QUALITY OF THE SENTENCES MUST BE TOP NOTCH - EASY TO UNDERSTAND AND NO GRAMMATICAL ERRORS."}, | |
{"role": "user", "content": "Use as many conjunctions and punctuations to make the sentence long. COMPOUND, COMPLEX, OR COMPOUND COMPLEX sentences are required"}, | |
{"role": "user", "content": f"Humanize the text. Keep the output format i.e. the bullets and the headings as it is. THE GRAMMAR MUST BE TOP NOTCH WITH NO ERRORS AND EASY TO UNDERSTAND!!!!. \nTEXT: {AI_text}"} | |
] | |
) | |
return response.choices[0].message.content.strip() | |
def main_function(AI_text): | |
humanized_text = humanize_text(AI_text) | |
# humanized_text= transform_text(humanized_text) | |
return humanized_text | |
# Gradio interface definition | |
interface = gr.Interface( | |
fn=main_function, | |
inputs="textbox", | |
outputs="textbox", | |
title="AI Text Humanizer", | |
description="Enter AI-generated text and get a human-written version. This space is availabe for limited time only so contact [email protected] to put this application in production.", | |
) | |
# Launch the Gradio app | |
interface.launch(debug = True) | |
# import gradio as gr | |
# # Function to handle text submission | |
# def contact_info(text): | |
# return "Contact [email protected] for Humanizer Application service" | |
# # Gradio interface definition | |
# interface = gr.Interface( | |
# fn=contact_info, | |
# inputs="textbox", | |
# outputs="text", | |
# title="AI TEXT HUMANIZER", | |
# description="Enter AI text and get its humanizer equivalent" | |
# ) | |
# # Launch the Gradio app | |
# if __name__ == "__main__": | |
# interface.launch() | |