Update app.py

app.py

@@ -1,31 +1,68 @@
 import streamlit as st
 from nltk import ngrams
-from nltk.tokenize import word_tokenize
+import nltk
 
+# Download NLTK data
+nltk.download('punkt')
 
-def generate_ngrams(text, n):
-    tokens = word_tokenize(text)
+# Function to extract n-grams from the input text
+def extract_ngrams(text, n):
+    tokens = nltk.word_tokenize(text)
     n_grams = list(ngrams(tokens, n))
-    return [' '.join(gram) for gram in n_grams]
+    return n_grams
 
+# Main function for Streamlit app
 def main():
-    st.title("N-gram Input Text")
+    # Set page title and favicon
+    st.set_page_config(
+        page_title="N-gram Extractor",
+        page_icon=":memo:",
+        layout="wide"
+    )
 
-   
-    text_input = st.text_area("Enter text:", "Type your text here.")
+    # Set overall page style
+    st.markdown(
+        """
+        <style>
+            body {
+                color: #333;
+                background-color: #f8f9fa;
+            }
+            .main {
+                border: 2px solid #28a745;
+                border-radius: 10px;
+                padding: 20px;
+                margin: 20px;
+            }
+            h1 {
+                color: #007bff;
+            }
+            p, label, .stMarkdown, .stTextInput, .stSlider, .stButton {
+                font-weight: bold;
+            }
+        </style>
+        """,
+        unsafe_allow_html=True
+    )
 
-  
-    n_value = st.slider("Choose N for N-grams:", min_value=2, max_value=5, value=2)
+    # Page layout
+    st.title("N-gram Extractor")
 
-   
-    if st.button("Generate N-grams"):
-        if text_input:
-            ngrams_result = generate_ngrams(text_input, n_value)
-            st.write(f"{n_value}-grams:")
-            for ngram in ngrams_result:
-                st.write(ngram)
+    # User input for text passage
+    text_input = st.text_area("Enter a text passage:", "")
+
+    # Slider to choose the value of n for n-grams
+    n = st.slider("Select the value of n for n-grams:", min_value=1, max_value=5, value=2)
+
+    # Button to trigger n-gram extraction
+    if st.button("Extract N-grams"):
+        if not text_input:
+            st.warning("Please enter a text passage.")
         else:
-            st.warning("Please Write some text.")
+            # Extract and display n-grams
+            n_grams_result = extract_ngrams(text_input, n)
+            st.subheader(f"{n}-grams:")
+            st.write(n_grams_result)
 
 if __name__ == "__main__":
     main()