Create app.py

app.py

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+import streamlit as st
+import subprocess
+
+# Install NLTK directly within the script
+subprocess.run(["pip", "install", "nltk"])
+
+import nltk
+nltk.download('punkt')
+
+from nltk import ngrams
+from nltk.tokenize import word_tokenize
+
+# Function to generate n-grams from a given text
+def generate_ngrams(text, n):
+    tokens = word_tokenize(text)
+    n_grams = ngrams(tokens, n)
+    return [' '.join(gram) for gram in n_grams]
+
+# Streamlit web application
+def main():
+    st.title("N-gram Generator")
+
+    # User input for text passage
+    text_input = st.text_area("Enter text passage:")
+
+    # User input for selecting n-gram type
+    n_gram_type = st.selectbox("Select n-gram type:", ["Bigram", "Trigram", "Custom N-gram"])
+
+    # Set n value based on user selection
+    if n_gram_type == "Bigram":
+        n_value = 2
+    elif n_gram_type == "Trigram":
+        n_value = 3
+    else:
+        n_value = st.number_input("Enter the value of N:", min_value=1, value=2, step=1)
+
+    # Generate n-grams and display the result
+    if st.button("Generate N-grams"):
+        if text_input:
+            ngrams_result = generate_ngrams(text_input, n_value)
+            st.write(f"{n_gram_type}s:")
+            for gram in ngrams_result:
+                st.write(gram)
+        else:
+            st.warning("Please enter a text passage.")
+
+if __name__ == "__main__":
+    main()