app.py

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):
    graph = create_context_graph(context_words)
    st.graphviz_chart(graph)

def display_context_table(context_words):
    table = "| Before | High Info Word | After |\n|--------|----------------|-------|\n"
    for before, high, after in context_words:
        table += f"| {before if before else ''} | {high} | {after if after else ''} |\n"
    st.markdown(table)


# ...

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)

    context_words = extract_context_words(text_without_timestamps, top_words)
    st.markdown("**Relationship Graph:**")
    display_relationship_graph(top_words)

    st.markdown("**Context Graph:**")
    display_context_graph(context_words)
    
    st.markdown("**Context Table:**")
    display_context_table(context_words)