Update app.py

app.py

@@ -1,28 +1,56 @@
+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)
+
+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)
+    return [word for word, _ in freq_dist.most_common(top_n)]
+
+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)
+
 def extract_context_words(text, high_information_words):
     words = nltk.word_tokenize(text)
     context_words = []
-
     for index, word in enumerate(words):
         if word.lower() in high_information_words:
             before_word = words[index - 1] if index > 0 else None
             after_word = words[index + 1] if index < len(words) - 1 else None
             context_words.append((before_word, word, after_word))
-
     return context_words
 
 def create_context_graph(context_words):
     graph = Digraph()
-
     for index, (before_word, high_info_word, after_word) in enumerate(context_words):
         graph.node(f'before{index}', before_word, shape='box') if before_word else None
         graph.node(f'high{index}', high_info_word, shape='ellipse')
         graph.node(f'after{index}', after_word, shape='diamond') if after_word else None
-
         if before_word:
             graph.edge(f'before{index}', f'high{index}')
         if after_word:
             graph.edge(f'high{index}', f'after{index}')
-
     return graph
 
 def display_context_graph(context_words):
@@ -35,8 +63,7 @@ def display_context_table(context_words):
         table += f"| {before if before else ''} | {high} | {after if after else ''} |\n"
     st.markdown(table)
 
-
-# ...
+uploaded_file = st.file_uploader("Choose a .txt file", type=['txt'])
 
 if uploaded_file:
     file_text = uploaded_file.read().decode("utf-8")
@@ -46,10 +73,10 @@ if uploaded_file:
     st.markdown("**Top 10 High Information Words:**")
     st.write(top_words)
 
-    context_words = extract_context_words(text_without_timestamps, top_words)
     st.markdown("**Relationship Graph:**")
     display_relationship_graph(top_words)
 
+    context_words = extract_context_words(text_without_timestamps, top_words)
     st.markdown("**Context Graph:**")
     display_context_graph(context_words)