Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import re | |
| import nltk | |
| from nltk.corpus import stopwords | |
| from nltk import FreqDist | |
| from graphviz import Digraph | |
| nltk.download('punkt') | |
| nltk.download('stopwords') | |
| def remove_timestamps(text): | |
| return re.sub(r'\d{1,2}:\d{2}\n.*\n', '', text) # Updated regex pattern | |
| def process_text(text): | |
| lines = text.split("\n") | |
| processed_lines = [] | |
| for line in lines: | |
| if line: | |
| processed_lines.append(line) | |
| outline = "" | |
| for i, line in enumerate(processed_lines): | |
| if i % 2 == 0: | |
| outline += f"**{line}**\n" | |
| else: | |
| outline += f"- {line} 😄\n" | |
| return outline | |
| def extract_high_information_words(text, top_n=10): | |
| words = nltk.word_tokenize(text) | |
| words = [word.lower() for word in words if word.isalpha()] | |
| stop_words = set(stopwords.words('english')) | |
| filtered_words = [word for word in words if word not in stop_words] | |
| freq_dist = FreqDist(filtered_words) | |
| high_information_words = [word for word, _ in freq_dist.most_common(top_n)] | |
| return high_information_words | |
| def create_relationship_graph(words): | |
| graph = Digraph() | |
| for index, word in enumerate(words): | |
| graph.node(str(index), word) | |
| if index > 0: | |
| graph.edge(str(index - 1), str(index), label=str(index)) | |
| return graph | |
| def display_relationship_graph(words): | |
| graph = create_relationship_graph(words) | |
| st.graphviz_chart(graph) | |
| uploaded_file = st.file_uploader("Choose a .txt file", type=['txt']) | |
| if uploaded_file: | |
| file_text = uploaded_file.read().decode("utf-8") | |
| text_without_timestamps = remove_timestamps(file_text) | |
| top_words = extract_high_information_words(text_without_timestamps, 10) | |
| st.markdown("**Top 10 High Information Words:**") | |
| st.write(top_words) | |
| st.markdown("**Relationship Graph:**") | |
| display_relationship_graph(top_words) |