app.py

import streamlit as st
from bs4 import BeautifulSoup
from nltk.tokenize import word_tokenize
from nltk.corpus import wordnet
import random
import nltk
nltk.download('punkt')
nltk.download('wordnet')

import streamlit as st
from bs4 import BeautifulSoup
from nltk.tokenize import word_tokenize
from nltk.corpus import wordnet
from transformers import pipeline

# Text analytics
from textblob import TextBlob
from textatistic import Textatistic

# Integration with other tools
from grammarbot import GrammarBotClient

# Error handling and logging
import logging


def paraphrase_text(text, synonyms_num=5, random_synonym=True):
    # Tokenize the text
    tokens = word_tokenize(text)
    # Create a list to hold the paraphrased words
    paraphrased_tokens = []
    for token in tokens:
        # Check if the token is a word
        if token.isalpha():
            # Get the synonyms of the word
            synonyms = []
            for syn in wordnet.synsets(token):
                for lemma in syn.lemmas():
                    if lemma.name() != token:
                        synonyms.append(lemma.name())
            # If there are synonyms available, choose a random one
            if synonyms:
                if random_synonym:
                    paraphrased_word = random.choice(synonyms)
                else:
                    paraphrased_word = ", ".join(synonyms[:synonyms_num])
            # If no synonyms are available, use the original word
            else:
                paraphrased_word = token
        # If the token is not a word, use it as-is
        else:
            paraphrased_word = token
        # Add the paraphrased word to the list
        paraphrased_tokens.append(paraphrased_word)
    # Join the paraphrased tokens back into a string
    paraphrased_text = ' '.join(paraphrased_tokens)
    return paraphrased_text


def paraphrase_html(html_text, synonyms_num, random_synonym):
    # Parse the HTML using BeautifulSoup
    soup = BeautifulSoup(html_text, 'html.parser')
    # Find all the text nodes in the HTML
    text_nodes = soup.find_all(text=True)
    # Paraphrase the text nodes
    for node in text_nodes:
        node.replace_with(paraphrase_text(node.string, synonyms_num, random_synonym))
    # Return the paraphrased HTML
    paraphrased_html = str(soup)
    return paraphrased_html


def analyze_text(text):
    # Text analytics using textblob and textatistic
    blob = TextBlob(text)
    sentiment = blob.sentiment.polarity
    subjectivity = blob.sentiment.subjectivity
    text_stats = Textatistic(text)
    readability_score = text_stats.flesch_score

    return sentiment, subjectivity, readability_score


def grammar_check(text):
    # Integration with grammarbot tool
    client = GrammarBotClient()
    response = client.check(text)

    matches = response['matches']
    if not matches:
        return "No grammar errors found."
    else:
        message = "Grammar errors found:\n"
        for match in matches:
            message += f"{match['message']} at line {match['replacements'][0]['startLine']}\n"
        return message


def paraphrase_with_model(text, model):
    # Advanced paraphrasing using pre-trained models
    paraphrase_pipeline = pipeline("text2text-generation", model=model, tokenizer=model, device=0 if st.config.experimental.get_query_params()['device'] == 'cpu' else -1)
    paraphrased_text = paraphrase_pipeline(text, max_length=50, do_sample=True, temperature=0.9)[0]['generated_text']
    return paraphrased_text


st.set_page_config(page_title="HTML Paraphraser and Analyzer", page_icon=":pencil2:")

st.sidebar.title("HTML Paraphraser and Analyzer")

st.title("HTML Paraphraser and Analyzer")
html_input = st.text_area("Enter HTML to paraphrase", height=250)

synonyms_num = st.slider("Number of synonyms per word", min_value=1, max_value=10, value=5, step=1)

random_synonym = st.checkbox("Use random synonym", value=True)

#Add a button to paraphrase the HTML
if st.button("Paraphrase HTML"):
    try:
        paraphrased_html = paraphrase_html(html_input, synonyms_num, random_synonym)
        st.write(paraphrased_html, unsafe_allow_html=True)
    except Exception as e:
        logging.exception("Error occurred while paraphrasing HTML")
        st.error("An error occurred while paraphrasing the HTML. Please try again.")

#Add a text area for the user to input the text to analyze
text_input = st.text_area("Enter text to analyze")

#Add a button to analyze the text
if st.button("Analyze Text"):
    try:
        sentiment, subjectivity, readability_score = analyze_text(text_input)
        st.write(f"Sentiment: {sentiment:.2f}")
        st.write(f"Subjectivity: {subjectivity:.2f}")
        st.write(f"Readability Score: {readability_score:.2f}")
    except Exception as e:
        logging.exception("Error occurred while analyzing text")
        st.error("An error occurred while analyzing the text. Please try again.")

#Add a button to check grammar using GrammarBot
if st.button("Check Grammar"):
    try:
        grammar_check_result = grammar_check(text_input)
        st.write(grammar_check_result)
    except Exception as e:
        logging.exception("Error occurred while checking grammar")
        st.error("An error occurred while checking grammar. Please try again.")

#Add a selectbox for choosing the pre-trained model for advanced paraphrasing
models = {
"GPT-2": "gpt2",
"GPT-Neo": "EleutherAI/gpt-neo-1.3B",
"T5": "t5-base",
"Pegasus": "google/pegasus-large",
}
model_name = st.selectbox("Choose a pre-trained model for advanced paraphrasing", options=list(models.keys()))

#Add a button to paraphrase the text using the selected model
if st.button("Advanced Paraphrasing"):
    try:
        model = models[model_name]
        paraphrased_text = paraphrase_with_model(text_input, model)
        st.write(paraphrased_text)
    except Exception as e:
        logging.exception("Error occurred while performing advanced paraphrasing")
        st.error("An error occurred while performing advanced paraphrasing. Please try again.")

#Set up logging to capture any errors
logging.basicConfig(filename='error.log', level=logging.ERROR, format='%(asctime)s %(message)s')