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ade2da4 8567f55 ade2da4 5d4f30e ade2da4 5d4f30e 916c7bb ade2da4 776edea f12bc52 df163bd 776edea ade2da4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 | import streamlit as st
from src.document_processor import process_document
from src.summarizer import TextSummarizer
import logging
from textblob import TextBlob
import http.server
import threading
import json
# Set up logging
logging.basicConfig(level=logging.DEBUG)
def main():
# Streamlit app configuration
st.set_page_config(
page_title="SumItUp | Document Summarizer",
page_icon="✍️", # Or another icon that represents summarization
layout="wide"
)
st.title("✍️ SumItUp")
st.subheader("Intelligent Document Summarization Made Easy")
if health_check():
return
# Sidebar for configuration
st.sidebar.header("Summarization Settings")
summary_length = st.sidebar.slider(
"Summary Length",
min_value=100,
max_value=400,
value=250
)
# Tabs for different input methods
tab1, tab2 = st.tabs(["Paste Text", "Upload Document"])
# Initialize summarizer
summarizer = TextSummarizer()
# Function to classify sentiment
def classify_sentiment(polarity):
if polarity > 0:
return "Positive 😊"
elif polarity < 0:
return "Negative 😟"
else:
return "Neutral 😐"
# Tab 1: Direct Text Input
with tab1:
st.header("Direct Text Input")
text_input = st.text_area(
"Paste your text here:",
height=300,
help="Enter the text you want to summarize"
)
if st.button("Summarize Text", key="text_summarize"):
if text_input:
with st.spinner('Generating summary and sentiment analysis...'):
try:
# Generate summary
summary = summarizer.generate_summary(
text_input,
max_length=summary_length,
min_length=summary_length // 2 # Optional: set min_length proportionally
)
st.subheader("Summary")
st.write(summary)
# Perform sentiment analysis
if text_input.strip():
sentiment = TextBlob(text_input).sentiment
sentiment_class = classify_sentiment(sentiment.polarity)
st.subheader("Sentiment Analysis")
st.write(f"Sentiment: {sentiment_class}")
st.write(f"Polarity: {sentiment.polarity:.2f} (Range: -1 to 1)")
st.write(f"Subjectivity: {sentiment.subjectivity:.2f} (Range: 0 to 1)")
else:
st.warning("No valid text for sentiment analysis.")
except Exception as e:
st.error(f"Summarization failed: {e}")
else:
st.warning("Please enter some text to summarize.")
# Tab 2: Document Upload
with tab2:
st.header("Document Upload")
uploaded_file = st.file_uploader(
"Choose a file",
type=['txt', 'pdf', 'docx'],
help="Upload a text, PDF, or Word document"
)
if uploaded_file is not None:
if st.button("Summarize Document", key="doc_summarize"):
with st.spinner('Processing, summarizing, and analyzing sentiment...'):
try:
# Process document
document_text = process_document(uploaded_file)
# Generate summary
summary = summarizer.generate_summary(
document_text,
max_length=summary_length,
min_length=summary_length // 2 # Optional: set min_length proportionally
)
st.subheader("Summary")
st.write(summary)
# Perform sentiment analysis
if document_text.strip():
sentiment = TextBlob(document_text).sentiment
sentiment_class = classify_sentiment(sentiment.polarity)
st.subheader("Sentiment Analysis")
st.write(f"Sentiment: {sentiment_class}")
st.write(f"Polarity: {sentiment.polarity:.2f} (Range: -1 to 1)")
st.write(f"Subjectivity: {sentiment.subjectivity:.2f} (Range: 0 to 1)")
else:
st.warning("No valid text for sentiment analysis.")
except Exception as e:
st.error(f"Error processing document: {e}")
def health_check():
"""Simple health check endpoint that returns JSON"""
params = params = st.query_params
if 'health' in params and params['health'][0] == 'true':
st.write('{"status": "OK"}')
st.cache_data.clear() # Clear cache to ensure fresh state
return True
return False
if __name__ == "__main__":
main()
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