import gradio as gr
from gramformer import Gramformer
from textblob import TextBlob
from language_tool_python import LanguageTool
from langdetect import detect
import warnings
import difflib
import re

# Disable future warnings
warnings.filterwarnings("ignore", category=FutureWarning)

# Initialize Gramformer for grammar correction
gf = Gramformer(models=1, use_gpu=True)
tool = LanguageTool('en-US')  # Initialize LanguageTool for additional grammar checks

# Function to correct grammar, highlight mistakes, and provide suggestions
def correct_and_suggest(essay):
    corrected_sentences = []
    highlighted_essay = []
    mistakes_count = 0
    suggestions = []  # To store suggestions for spelling, grammar, and tense

    # Split essay into sentences
    #sentences = essay.split('. ')
    sentences = re.split(r'(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)\s', essay)

    for sentence in sentences:
        # Grammar correction using Gramformer
        correction_set = gf.correct(sentence)
        corrected_sentence = list(correction_set)[0] if correction_set else sentence

        # Compare original and corrected sentences using difflib
        diff = difflib.ndiff(sentence.split(), corrected_sentence.split())

        # Initialize the highlighted sentence with corrections
        highlighted_sentence = []
        for word in diff:
            if word.startswith('- '):  # Indicates a removed word
                # Avoid highlighting numbers and capitalized words
                if not word[2:].isdigit() and not word[2:].istitle():
                    highlighted_sentence.append(f"<span style='color:red'>{word[2:]}</span>")
                    mistakes_count += 1
                else:
                    highlighted_sentence.append(word[2:])
            elif word.startswith('+ '):  # Indicates an added word
                highlighted_sentence.append(f"<span style='color:green'>{word[2:]}</span>")
            elif not word.startswith('? '):  # Ignore metadata lines
                highlighted_sentence.append(word[2:])

        # Additional suggestions using TextBlob and LanguageTool
        blob = TextBlob(sentence)
        tool_matches = tool.check(sentence)
        tense_suggestions = []
        grammar_suggestions = []
        spelling_suggestions = []

        if len(tool_matches) > 0:
            grammar_suggestions.append(f"Grammar issues in: '{sentence}'")

        # Detect language using langdetect
        if detect(sentence) != 'en':
            tense_suggestions.append(f"Possible tense issue in: '{sentence}'")

        # Append all suggestions
        suggestions.extend(spelling_suggestions + grammar_suggestions + tense_suggestions)

        # Append the results to the respective lists
        highlighted_essay.append(' '.join(highlighted_sentence))
        corrected_sentences.append(corrected_sentence)

    # Simple score formula based on mistakes
    total_words = len(re.findall(r'\w+', essay))  # Total number of words
    score = max((100-mistakes_count), 0)

    # Video suggestions
    videos = [
        "<a href='https://youtu.be/yle3Wytf_LE?si=xYfPEpvbwHzSyLOF' target='_blank'>Essay Tips Video 1</a>",
        "<a href='https://youtu.be/goqQFP8r4-o?si=vBjy7SdtzqkF1y9z' target='_blank'>Essay Tips Video 2</a>",
        "<a href='https://youtu.be/o9aVjBHEEbU?si=il0Xg4PVk-BMvC1g' target='_blank'>Essay Tips Video 3</a>",
        "<a href='https://youtu.be/GNL1_tNTqpw?si=svssNMZCw5gn1UKN' target='_blank'>Essay Tips Video 4</a>"
    ]

    return ' '.join(highlighted_essay), ' '.join(corrected_sentences), f"Score: {round(score, 2)}", \
           '\n'.join(suggestions), '<br>'.join(videos), f"Word count: {total_words}"

# Define Gradio inputs and outputs
app_inputs = gr.Textbox(lines=10, placeholder="Enter your full essay here...", label="Essay")
app_outputs = [gr.HTML(label="Highlighted Mistakes"), gr.Textbox(label="Corrected Essay"),
               gr.Textbox(label="Score"), gr.Textbox(label="Suggestions"), gr.HTML(label="Helpful Videos"),
               gr.Textbox(label="Word Count", interactive=False)]

# Create Gradio interface
interface = gr.Interface(
    fn=correct_and_suggest,
    inputs=app_inputs,
    outputs=app_outputs,
    title="Essay Checker"
)

# Launch the Gradio app with a public link
interface.launch(share=True)