app.py

# Importing required libraries
import streamlit as st
import nltk
import os
import random

# Set NLTK data path
nltk_data_path = os.path.join(os.getcwd(), 'nltk_data')
nltk.data.path.append(nltk_data_path)

# Download NLTK data
nltk.download('stopwords', download_dir=nltk_data_path)
nltk.download('punkt', download_dir=nltk_data_path)
nltk.download('wordnet', download_dir=nltk_data_path)

from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize, sent_tokenize
import language_tool_python
from nltk.corpus import wordnet

# Ensure WordNet is loaded
try:
    wordnet.ensure_loaded()
except LookupError:
    nltk.download('wordnet', download_dir=nltk_data_path)

# Function to correct grammatical mistakes
def correct_grammar(text, my_tool):
    matches = my_tool.check(text)
    corrected_text = my_tool.correct(text)
    return corrected_text

# Function to summarize the text
def summarize_text(text, threshold):
    # Tokenizing the text
    stopWords = set(stopwords.words("english"))
    words = word_tokenize(text.lower())

    # Creating a frequency table
    freqTable = {}
    for word in words:
        if word in stopWords:
            continue
        if word in freqTable:
            freqTable[word] += 1
        else:
            freqTable[word] = 1

    # Creating a sentence value dictionary
    sentences = sent_tokenize(text)
    sentenceValue = {}

    for sentence in sentences:
        for word, freq in freqTable.items():
            if word in sentence.lower():
                if sentence in sentenceValue:
                    sentenceValue[sentence] += freq
                else:
                    sentenceValue[sentence] = freq

    # Calculate average sentence value
    sumValues = sum(sentenceValue.values())
    average = int(sumValues / len(sentenceValue))

    # Generate summary
    summary = ""
    for sentence in sentences:
        if (sentence in sentenceValue) and (sentenceValue[sentence] > (threshold * average)):
            summary += " " + sentence

    return summary

# Function to find a random synonym of a word from WordNet
def find_random_synonym(word):
    synonyms = []
    for synset in wordnet.synsets(word):
        for lemma in synset.lemmas():
            synonyms.append(lemma.name())
    
    # Remove duplicates and select a random synonym
    unique_synonyms = list(set(synonyms))
    if unique_synonyms:
        return random.choice(unique_synonyms)
    else:
        return "No synonyms found"

# Streamlit app
def main():
    st.markdown("<h1>Text Analyzer App</h1>", unsafe_allow_html=True)
    # Linking CSS file
    st.markdown("""
    <style>
        %s
    </style>
""" % open("style.css").read(), unsafe_allow_html=True)
    
    # Setting up the grammar tool
    my_tool = language_tool_python.LanguageToolPublicAPI('en-US')

    # Input text for analysis
    text = st.text_area("Enter the text:", "")

    # Sidebar for controlling summary length
    st.sidebar.title("Summary Length")
    threshold = st.sidebar.slider("Select threshold for summary length:", min_value=1.0, max_value=2.0, value=1.2, step=0.1)

    if st.button("Analyze"):
        # Correct grammatical mistakes
        corrected_text = correct_grammar(text, my_tool)
        st.subheader("Grammatically Corrected Text:")
        st.write(corrected_text)

        # Summarize the text
        summary_text = summarize_text(corrected_text, threshold)
        st.subheader("Summary:")
        st.write(summary_text)
    st.write("Made by Rounak Paul(21bce1566) & Tushar Panwar(21bce1074)")
    st.write("NLP PROJECT, VIT CHENNAI")

    # Sidebar for Synonym Finder
    st.sidebar.title("Synonym Finder")
    input_word = st.sidebar.text_input("Enter a word to find its synonym:", "")

    if st.sidebar.button("Find Synonym"):
        if input_word:
            synonym = find_random_synonym(input_word)
            st.sidebar.subheader(f"A random synonym of '{input_word}' is:")
            st.sidebar.write(synonym if synonym != "No synonyms found" else "No synonyms found")
        else:
            st.sidebar.warning("Please enter a word.")

if __name__ == "__main__":
    main()