import gradio as gr
from transformers import pipeline
from parrot import Parrot
import torch
import language_tool_python
import nltk

nltk.download('punkt')
nltk.download('averaged_perceptron_tagger')

tool = language_tool_python.LanguageTool('en-US')
parrot = Parrot(model_tag="prithivida/parrot_paraphraser_on_T5", use_gpu=False)

def paraphrase_text(input_text, mode="Standard"):
    if not input_text.strip():
        return "", ""

    corrected = tool.correct(input_text)
    para_phrases = parrot.augment(
        input_phrase=corrected,
        diversity_ranker="levenshtein",
        do_diverse=True,
        max_return_phrases=5,
        adequacy_threshold=0.90,
        fluency_threshold=0.90
    )

    if not para_phrases:
        return corrected, "No paraphrase found."

    best = para_phrases[0][0]

    if mode == "Formal":
        best = best.replace("gonna", "going to").replace("wanna", "want to")
    elif mode == "Creative":
        best = best.capitalize() + " 🌟"
    elif mode == "Concise":
        best = " ".join(best.split()[:12]) + "..."

    return corrected, best

with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("## 🚀 AI Paraphraser — Better Than QuillBot")
    gr.Markdown("### Enter your text and select a paraphrasing mode")

    input_text = gr.Textbox(label="Original Text", placeholder="Type your sentence here...", lines=5)
    mode = gr.Dropdown(["Standard", "Formal", "Creative", "Concise"], label="Paraphrasing Mode", value="Standard")

    with gr.Row():
        btn = gr.Button("🔁 Paraphrase Now")
        clear = gr.Button("🧹 Clear")

    output_corrected = gr.Textbox(label="🧹 Corrected Input (Grammar fixed)", lines=3)
    output_paraphrased = gr.Textbox(label="✨ Paraphrased Output", lines=3)

    btn.click(fn=paraphrase_text, inputs=[input_text, mode], outputs=[output_corrected, output_paraphrased])
    clear.click(lambda: ("", "", ""), None, [input_text, output_corrected, output_paraphrased])

demo.launch()