Update app.py

app.py

@@ -46,26 +46,46 @@
 #     main()
 
 import streamlit as st
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
 
-# Function to categorize input sentences
-def categorize_sentence(sentence):
-    # Replace this function with your own logic to categorize sentences
-    categories = ['Restaurants', 'Food', 'Travel', 'New York City']
-    return categories
+# Load pre-trained Sentence Transformer model
+model = SentenceTransformer('bert-base-nli-mean-tokens')
 
-# Configure Streamlit layout
-st.set_page_config(page_title='Sentence Categorizer', layout='wide')
+# Define your dataset here (example categories)
+categories = {
+    'sports': ['football', 'basketball', 'tennis'],
+    'politics': ['election', 'government', 'policy'],
+    'technology': ['AI', 'machine learning', 'data science']
+}
 
-# Add title and description
-st.title('Welcome to Sentence Categorizer')
-st.write('Enter a sentence and discover relevant categories!')
+# Function to get relevant categories based on user query
+def get_relevant_categories(query):
+    query_embedding = model.encode([query])
+    category_scores = {}
 
-# Create input box
-sentence = st.text_input('Enter a sentence')
+    for category, keywords in categories.items():
+        keyword_embeddings = model.encode(keywords)
+        similarity_scores = cosine_similarity(query_embedding, keyword_embeddings)
+        category_scores[category] = sum(similarity_scores)[0]
 
-# Create button to trigger categorization
-if st.button('Categorize'):
-    st.write('Categories:')
-    categories = categorize_sentence(sentence)
-    for category in categories:
-        st.success(category)
+    relevant_categories = [category for category, score in sorted(category_scores.items(), key=lambda x: x[1], reverse=True) if score > 0]
+    return relevant_categories
+
+# Streamlit app layout and UI
+def main():
+    st.title("Sentence Categorization App")
+    st.write("Enter a sentence to categorize:")
+    user_input = st.text_input('', value='', max_chars=None, key=None, type='default')
+
+    if st.button('Categorize'):
+        if user_input:
+            relevant_categories = get_relevant_categories(user_input)
+            st.write("Relevant Categories:")
+            for category in relevant_categories:
+                st.write(f"- {category}")
+        else:
+            st.write("Please enter a sentence for categorization.")
+
+if __name__ == "__main__":
+    main()