Update app.py

app.py

@@ -4,6 +4,7 @@ from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.schema import Document
 from transformers import pipeline
 import pickle
+import time
 
 def load_faiss_index(index_file="faiss_course_index.pkl"):
     with open(index_file, "rb") as f:
@@ -46,34 +47,37 @@ def search_and_answer(query, index_file="faiss_course_index.pkl"):
     return response
 
 def main():
-    st.title("Course Search WebApp")
-    query = st.text_input("Enter your query:")
-    
+    st.title("📚 Course Search WebApp")
+    st.markdown("Find the best courses tailored to your needs.")
+    query = st.text_input("🔍 Enter your query:")  
     if st.button("Search"):
-        response = search_and_answer(query, index_file = "faiss_course_index.pkl")
-        if response == "No relevant courses found.":
-            st.write(response)
-        else :
-            st.write(response)
-            '''
-            retriever = get_faiss_retriever("faiss_course_index.pkl")
-            retrieved_docs = retriever.invoke(query)
-            count = len(retrieved_docs)
-            st.write(f"Related Courses:{count}")
+        with st.spinner("Fetching results..."):
+            start_time = time.time()
+            response = search_and_answer(query, index_file="faiss_course_index.pkl")
+            if response == "No relevant courses found.":
+                st.warning(response)
+            else:
+                st.success("Results fetched successfully!")
+                
+                # Display the formatted response
+                sections = response.split("\n\n")
+                st.markdown("### **Related Courses:**")
+                for section in sections[:-1]:  # Exclude summary section
+                    if section.strip():
+                        st.markdown(section)
+                        st.write("---")
+                
+                # Display summary
+                summary = sections[-1].replace("Summary:", "").strip()
+                st.subheader("📝 Summary:")
+                st.info(summary)
             
-            for doc in retrieved_docs:
-                title = doc.metadata.get('title', 'No Title')
-                lessons = doc.metadata.get('lessons', 'No lessons listed')
-                st.write(f"**Course Title:** {title}")
-                st.write(f"**Course Lessons:** {lessons}")
-                st.write("---")
+            # Log time taken
+            end_time = time.time()
+            st.markdown(f"⏱ **Time Taken:** {end_time - start_time:.2f} seconds")
 
-            # Generate summary
-            context = retrieved_docs[0].page_content
-            summary = get_answer_from_t5(query, context)
-            st.write("**Summary:**")
-            st.write(summary)
-            '''
+    st.markdown("---")
+    st.markdown("Developed with ❤️ by [Your Name](https://your-link.com)")
 
 if __name__ == "__main__":
     main()