Delete Upload function :))

app.py

@@ -1,67 +1,50 @@
-import streamlit as st
 import pandas as pd
+import streamlit as st
 import re
 
 st.set_page_config(page_icon='🍃', page_title='MRC for Legal Document Dataset checker', layout='wide', initial_sidebar_state="collapsed")
 
-# start processing events
-def load_data(file_uploader):
-    if file_uploader is not None:
-        return pd.read_csv(file_uploader)
-    else:
-        return pd.DataFrame(columns=['context', 'question', 'answer'])
-    
-def convert_df(df):
-    # IMPORTANT: Cache the conversion to prevent computation on every rerun
-    return df.to_csv().encode("utf-8")
-# end processing events
-
-st.markdown("<h1 style='text-align: center;'>Investigation Legal Dataset checker for Machine Reading Comprehension</h1>", unsafe_allow_html=True)
-
-file = st.file_uploader(label='Upload your file here:', type=['csv'], accept_multiple_files=False, label_visibility='hidden')
-df = load_data(file_uploader=file)
+st.markdown("<h2 style='text-align: center;'>Investigation Legal Dataset checker for Machine Reading Comprehension</h2>", unsafe_allow_html=True)
 
-if 'df' not in st.session_state:
-    st.session_state.df = df
+df = pd.read_csv(filepath_or_buffer='D:\KNOWLEDGES FUNDAMENTAL\YEAR 3\[NLP] INVESTIGATION LEGAL DOCUMENTS\Datasets\Legal_AbstractiveA.csv')
 
 if 'idx' not in st.session_state:
     st.session_state.idx = 0
 
-st.markdown(f"<h3 style='text-align: center;'>Sample {st.session_state.idx + 1}/{len(df)}</h3>", unsafe_allow_html=True)
+st.markdown(f"<h4 style='text-align: center;'>Sample {st.session_state.idx + 1}/{len(df)}</h4>", unsafe_allow_html=True)
 
 col_1, col_2, col_3, col_4, col_5, col_6, col_7, col_8, col_9, col_10 = st.columns([1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
 
 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_4.selectbox(label='None', options=[np.array(range(len(df)))], label_visibility='collapsed')
 
 if len(df) != 0:
-    index = st.session_state.idx
-
-    print(f"Length: {len(st.session_state.df)}")
-    txt_context = st.text_area(height=300, label='Your context:', value=st.session_state.df['context'][index])
-    txt_question = st.text_area(height=100, label='Your question:', value=st.session_state.df['question'][index])
-    txt_answer = st.text_area(height=100, label='Your answer:', value=st.session_state.df['answer'][index])
+    txt_context = st.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])
 
     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)
 
+    if btn_previous:
+        if st.session_state.idx > 0:
+            st.session_state.idx -= 1
+            st.rerun()
+        else:
+            pass
 
     if btn_next:
-        if index < len(df) - 1:
+        if st.session_state.idx <= (len(df) - 1):
             st.session_state.idx += 1
-            # st.rerun()
-
+            st.rerun()
+        else:
+            pass
+    
     if btn_save:
-        st.session_state.df['context'][index] = txt_context
-        st.session_state.df['question'][index] = txt_question
-        st.session_state.df['answer'][index] = txt_answer
-        csv_file = convert_df(df=st.session_state.df)
-        btn_download = col_4.download_button(data=csv_file, label=':arrow_down_small: Download file', use_container_width=True, file_name="large_df.csv", mime="text/csv")
+        df['context'][st.session_state.idx] = txt_context
+        df['question'][st.session_state.idx] = txt_question
+        df['answer'][st.session_state.idx] = txt_answer
 
-    if btn_previous:
-        if index > 0:
-            st.session_state.idx -= 1
-            # st.rerun()
+        df.to_csv(path_or_buf='D:\KNOWLEDGES FUNDAMENTAL\YEAR 3\[NLP] INVESTIGATION LEGAL DOCUMENTS\Datasets\Legal_AbstractiveA.csv', index=None)