Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import streamlit as st
 import torch
 import torch.nn as nn
@@ -5,7 +6,6 @@ import nltk
 from nltk.corpus import stopwords
 import pandas as pd
 import base64
-import random
 
 # Ensure NLTK resources are downloaded
 nltk.download('punkt')
@@ -21,19 +21,6 @@ def text_convolution(input_text, kernel_size=3):
     output = conv_layer(tensor_input)
     return output, words
 
-    
-# Function to color the bars based on whether they appear together or not
-def color_bars(words):
-    color_map = {}
-    color_index = 0
-    for word in words:
-        if word not in color_map:
-            color_map[word] = color_index
-            color_index += 1
-    colors = [f"#{random.randint(0, 0xFFFFFF):06x}" for _ in range(len(color_map))]
-    return [colors[color_map[word]] for word in words]
-
-    
 # Streamlit UI
 def main():
     st.title("Text Convolution Demonstration")
@@ -49,9 +36,7 @@ def main():
 
         # Visualization
         word_counts = pd.Series(words).value_counts()
-        word_counts = word_counts.sort_values(ascending=False)
-        colors = color_bars(word_counts.index)
-        st.bar_chart(word_counts.head(20), color=colors)
+        st.bar_chart(word_counts.head(20))
 
         # Saving user prompts
         user_file_name = f"{user_email}_prompts.txt"
@@ -67,4 +52,3 @@ def main():
 
 if __name__ == "__main__":
     main()
-