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import streamlit as st
import pandas as pd
import datetime
import io
import nltk
from nltk.tokenize import sent_tokenize
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.decomposition import LatentDirichletAllocation
nltk.download('punkt')
def save_text_as_file(text, file_type):
current_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
file_name = f"text_file_{current_time}.{file_type}"
with open(file_name, "w") as file:
file.write(text)
st.success(f"Text saved as {file_name}")
def save_csv_as_excel(text):
try:
df = pd.read_csv(io.StringIO(text), header=None)
if df.iloc[0].dtype == object:
header = 0
file_name = f"csv_with_header_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.xlsx"
else:
header = None
file_name = f"csv_without_header_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.xlsx"
df.to_excel(file_name, index=False, header=header)
st.success(f"CSV data saved as {file_name}")
st.dataframe(df)
except pd.errors.EmptyDataError:
st.error("The pasted text does not contain valid CSV data.")
except pd.errors.ParserError as e:
st.error(f"Error parsing CSV data: {str(e)}")
st.info("Please ensure that the pasted text is in a valid CSV format.")
def split_sentences(text):
sentences = sent_tokenize(text)
return "\n".join(sentences)
def perform_nlp(text):
sentences = sent_tokenize(text)
# Topic Modeling
vectorizer = CountVectorizer(stop_words='english')
X = vectorizer.fit_transform(sentences)
lda = LatentDirichletAllocation(n_components=3, random_state=42)
lda.fit(X)
topics = lda.transform(X)
# Display topics
st.subheader("Topic Modeling")
for i, topic in enumerate(topics):
st.write(f"Topic {i+1}:")
topic_words = ", ".join([vectorizer.get_feature_names_out()[i] for i in topic.argsort()[:-6:-1]])
st.write(topic_words)
# Word Frequency
word_freq = pd.Series(" ".join(sentences).split()).value_counts()[:10]
st.subheader("Word Frequency")
st.bar_chart(word_freq)
def main():
st.title("AI UI for Text Processing")
text_input = st.text_area("Paste your text here")
if st.button("Process Text"):
if text_input.strip() == "":
st.warning("Please paste some text.")
else:
if "," in text_input or "\t" in text_input:
save_csv_as_excel(text_input)
elif "." in text_input or "!" in text_input or "?" in text_input:
sentences = split_sentences(text_input)
st.subheader("Sentences")
st.write(sentences)
perform_nlp(text_input)
else:
save_text_as_file(text_input, "txt")
if __name__ == "__main__":
main() |