requirements.txt

streamlit
nltk

app.py

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+import streamlit as st
+from nltk import ngrams
+import nltk
+nltk.download('punkt')
+
+def extract_ngrams(text, n):
+    tokens = nltk.word_tokenize(text)
+    n_grams = list(ngrams(tokens, n))
+    return n_grams
+
+def main():
+    st.title("N-gram Extractor")
+
+    # User input
+    text_input = st.text_area("Enter a text passage:", "")
+
+    # Choose n for n-grams
+    n = st.slider("Select the value of n for n-grams:", min_value=1, max_value=5, value=2)
+
+    if st.button("Extract N-grams"):
+        if not text_input:
+            st.warning("Please enter a text passage.")
+        else:
+            # 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()