app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the AuthorMist model and tokenizer
model_name = "authormist/authormist-originality"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Function to humanize input text
def humanize_text(text):
    prompt = f"Please paraphrase the following text to make it human-like:\n\n{text}\n\nParaphrased text:"
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(inputs.input_ids, max_new_tokens=512, temperature=0.7, top_p=0.9)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)

    # Extract only the paraphrased part
    if "Paraphrased text:" in response:
        return response.split("Paraphrased text:")[1].strip()
    return response.strip()

# Launch Gradio UI
gr.Interface(
    fn=humanize_text,
    inputs=gr.Textbox(lines=10, placeholder="Paste AI-written text here..."),
    outputs="text",
    title="AuthorMist AI Humanizer",
    description="Turns AI-generated text into human-like writing to reduce detection by tools like GPTZero."
).launch()