Update app.py

app.py

@@ -41,6 +41,11 @@ def generate_html_with_textarea(text_to_speak):
     </html>
     '''
 
+# Initialize session state for tracking the last clicked row
+if 'last_clicked_row' not in st.session_state:
+    st.session_state['last_clicked_row'] = None
+
+    
 # Streamlit App 🚀
 st.title("AI Medical Explorer with Speech Synthesis 🎙")
 
@@ -57,7 +62,13 @@ data = large_data if file_option == "usmle_16.2MB.jsonl" else small_data
 # Top 20 healthcare terms for USMLE
 top_20_terms = ['Heart', 'Lung', 'Pain', 'Memory', 'Kidney', 'Diabetes', 'Cancer', 'Infection', 'Virus', 'Bacteria', 'Gastrointestinal', 'Skin', 'Blood', 'Surgery']
 
-# Your existing expander and columns UI
+
+# Initialize session state for tracking the last clicked row
+if 'last_clicked_row' not in st.session_state:
+    st.session_state['last_clicked_row'] = None
+
+
+# Expander UI for common terms
 with st.expander("Search by Common Terms 📚"):
     cols = st.columns(4)
     for term in top_20_terms:
@@ -66,33 +77,30 @@ with st.expander("Search by Common Terms 📚"):
                 filtered_data = filter_by_keyword(data, term)
                 st.write(f"Filter on '{term}' 📊")
                 with st.sidebar:
-                    # Modified part: Display each row with a button
+                    # Display each row with a button
                     for idx, row in filtered_data.iterrows():
                         if st.button(f"Row {idx}", key=f"row_{idx}"):
                             st.session_state['last_clicked_row'] = idx
 
-                # Check if there's a selected row and it's in the filtered data
-                if st.session_state['last_clicked_row'] in filtered_data.index:
-                    row = filtered_data.loc[st.session_state['last_clicked_row']]
-                    question_text = row.get("question", "No question field")
-                    documentHTML5 = generate_html_with_textarea(question_text)
-                    components.html(documentHTML5, width=1280, height=1024)
+                # Check if 'last_clicked_row' is set and in the filtered data
+                if st.session_state['last_clicked_row'] is not None and st.session_state['last_clicked_row'] in filtered_data.index:
+                    selected_row = filtered_data.loc[st.session_state['last_clicked_row']]
+
+                    # Extract only the first three columns of the selected row
+                    first_three_columns = selected_row.iloc[:3]
 
-# Text input for search keyword
-search_keyword = st.text_input("Or, enter a keyword to filter data:")
-if st.button("Search 🕵️‍♀️"):
-    filtered_data = filter_by_keyword(data, search_keyword)
-    st.write(f"Filtered Dataset by '{search_keyword}' 📊")
-    st.dataframe(filtered_data)
-    if not filtered_data.empty:
-        html_blocks = []
-        for idx, row in filtered_data.iterrows():
-            question_text = row.get("question", "No question field")
-            documentHTML5 = generate_html_with_textarea(question_text)
-            html_blocks.append(documentHTML5)
-        all_html = ''.join(html_blocks)
-        components.html(all_html, width=1280, height=1024)
+                    # Display these columns in the sidebar
+                    st.sidebar.write("Selected Row Details:")
+                    for col in first_three_columns.index:
+                        st.sidebar.write(f"{col}: {first_three_columns[col]}")
 
+                    # Concatenate these column values with the question_text
+                    additional_info = ' '.join([f"{col}: {val}" for col, val in first_three_columns.items()])
+                    question_text = selected_row.get("question", "No question field")
+                    full_text = f"{additional_info} Question: {question_text}"
+                    
+                    documentHTML5 = generate_html_with_textarea(full_text)
+                    components.html(documentHTML5, width=1280, height=1024)
 
 
 # Inject HTML5 and JavaScript for styling