Update app.py

app.py

@@ -1,11 +1,63 @@
+import streamlit as st
+import requests
+from transformers import pipeline
+import plotly.express as px
+import pandas as pd
+from collections import Counter
+import re
 
-from diagrams import Diagram
-from diagrams.k8s.clusterconfig import HPA
-from diagrams.k8s.compute import Deployment, Pod, ReplicaSet
-from diagrams.k8s.network import Ingress, Service
+def get_markdown_from_github(url):
+    response = requests.get(url)
+    markdown = response.text
+    return markdown
 
-with Diagram("Exposed Pod with 3 Replicas", show=False):
-    net = Ingress("domain.com") >> Service("svc")
-    net >> [Pod("pod1"),
-            Pod("pod2"),
-            Pod("pod3")] << ReplicaSet("rs") << Deployment("dp") << HPA("hpa")
+def preprocess_text(text):
+    text = text.lower()
+    text = re.sub('[^A-Za-z0-9]+', ' ', text)
+    return text
+    
+def get_most_frequent_words(text, n):
+    words = re.findall(r'\b\w{5,}\b', text)
+    word_count = Counter(words)
+    most_common_words = word_count.most_common(n)
+    return most_common_words
+
+def get_sentences_with_common_words(text, common_words):
+    sentences = re.split('[.?!]', text)
+    selected_sentences = []
+    for sentence in sentences:
+        for word in common_words:
+            if word in sentence:
+                selected_sentences.append(sentence.strip())
+                break
+    return selected_sentences
+
+def render_heatmap(words, sentences):
+    df = pd.DataFrame(words, columns=['word', 'frequency'])
+    fig = px.treemap(df, path=['word'], values='frequency', color='frequency', hover_data=['frequency'], color_continuous_scale='reds')
+    st.plotly_chart(fig, use_container_width=True)
+
+def main():
+    st.title('Markdown Analyzer')
+
+    # Get markdown from GitHub
+    default_markdown_url = 'https://github.com/AaronCWacker/Yggdrasil/blob/main/README.md'
+    markdown_url = st.sidebar.text_input("Enter a URL to analyze (default is provided):", default_markdown_url)
+    markdown = get_markdown_from_github(markdown_url)
+
+    # Preprocess text
+    text = preprocess_text(markdown)
+
+    # Get most frequent words
+    n_most_frequent_words = st.sidebar.slider('Number of most frequent words to display', 1, 20, 10)
+    most_frequent_words = get_most_frequent_words(text, n_most_frequent_words)
+
+    # Get sentences containing common words
+    common_words = [word for word, _ in most_frequent_words]
+    sentences = get_sentences_with_common_words(text, common_words)
+
+    # Render heatmap
+    render_heatmap(most_frequent_words, sentences)
+
+if __name__ == '__main__':
+    main()