Update app.py

app.py

@@ -6,7 +6,7 @@ st.set_page_config(page_icon='🍃', page_title='MRC for Legal Document Dataset
 
 st.markdown("<h2 style='text-align: center;'>Investigation Legal Dataset checker for Machine Reading Comprehension</h2>", unsafe_allow_html=True)
 
-df = pd.read_csv(filepath_or_buffer='./GeneratedLegalData.csv')
+df = pd.read_csv(filepath_or_buffer='./Legal_AbstractiveA.csv')
 
 if 'idx' not in st.session_state:
     st.session_state.idx = 0
@@ -18,12 +18,24 @@ col_1, col_2, col_3, col_4, col_5, col_6, col_7, col_8, col_9, col_10 = st.colum
 btn_previous = col_1.button(label=':arrow_backward: Previous sample', use_container_width=True)
 btn_next = col_2.button(label='Next sample :arrow_forward:', use_container_width=True)
 btn_save = col_3.button(label=':heavy_check_mark: Save change', use_container_width=True)
+txt_goto = col_5.selectbox(label='Sample', label_visibility='collapsed', options=list(range(1, len(df) + 1)))
+btn_goto = col_6.button(label=':fast_forward: Move to', use_container_width=True)
 
 if len(df) != 0:
-    txt_context = st.text_area(height=300, label='Your context:', value=df['context'][st.session_state.idx])
+    col_x1, col_x2 = st.columns([8.5, 1.5])
+    txt_context = col_x1.text_area(height=300, label='Your context:', value=df['context'][st.session_state.idx])
     txt_question = st.text_area(height=100, label='Your question:', value=df['question'][st.session_state.idx])
     txt_answer = st.text_area(height=100, label='Your answer:', value=df['answer'][st.session_state.idx])
 
+    options = ['Never been evaluated', 'Bad', 'Acceptable', 'Good']
+    criteria_1_value = df['criteria_1'][st.session_state.idx] if 'criteria_1' in df.columns else 'Never been evaluated'
+    criteria_2_value = df['criteria_2'][st.session_state.idx] if 'criteria_2' in df.columns else 'Never been evaluated'
+    criteria_3_value = df['criteria_3'][st.session_state.idx] if 'criteria_3' in df.columns else 'Never been evaluated'
+    
+    criteria_1 = col_x2.selectbox(label='Are the questions natural, comprehensive, and appropriate to the content?', options=['Never been evaluated', 'Bad', 'Acceptable', 'Good'], index=options.index(criteria_1_value))
+    criteria_2 = col_x2.selectbox(label='Is the answer correct, clear, and fluent?', options=['Never been evaluated', 'Bad', 'Acceptable', 'Good'], index=options.index(criteria_2_value))
+    criteria_3 = col_x2.selectbox(label='Do the question and answer pairs match each other?', options=['Never been evaluated', 'Bad', 'Acceptable', 'Good'], index=options.index(criteria_3_value))
+
     if txt_answer.strip() and txt_context.strip():
         highlighted_context = re.sub(re.escape(txt_answer), "<mark>" + txt_answer + "</mark>", txt_context, flags=re.IGNORECASE)
         st.markdown(highlighted_context, unsafe_allow_html=True)
@@ -46,5 +58,13 @@ if len(df) != 0:
         df['context'][st.session_state.idx] = txt_context
         df['question'][st.session_state.idx] = txt_question
         df['answer'][st.session_state.idx] = txt_answer
+
+        df['criteria_1'][st.session_state.idx] = criteria_1
+        df['criteria_2'][st.session_state.idx] = criteria_2
+        df['criteria_3'][st.session_state.idx] = criteria_3
         btn_download = col_4.download_button(data=df.to_csv(), label=':arrow_down_small: Download file', use_container_width=True, file_name="checked.csv", mime="text/csv")
-        df.to_csv(path_or_buf='./GeneratedLegalData.csv', index=None)
+        df.to_csv(path_or_buf='./Legal_AbstractiveA.csv', index=None)
+
+    if btn_goto:
+        st.session_state.idx = txt_goto - 1
+        st.rerun()