Update app.py

app.py

@@ -4,91 +4,89 @@ import copy
 
 N = 10
 state = st.session_state
-# generated_path = 'generated_predictions.txt'
-
-# ORI_RES = f'DUC/results/{generated_path}'
-# # CONTEXT_SENT_0_h_0_RES = f'/home/nlp/wolhanr/mds_faithfull/data/DUC/output_dir/sent_window_0_h_0_clusters/{generated_path}'
-# CONTEXT_SENT_0_h_1_RES = f'DUC/output_dir/sent_window_0_clusters/{generated_path}'
-# CONTEXT_SENT_1_h_1_RES = f'DUC/output_dir/sent_window_1_h_1_clusters/{generated_path}'
-
-# source_path = 'DUC/sent_window_1_h_1_clusters/test.source'
-
-# OPTIONS = ["faithfull", "Not faithfull"]
-
-# if "number_button_fill" not in state:
-#     state.number_button_fill = 0
-
-# if "annotations" not in state:
-#     state.annotations = {}
-#     state.annotations['data_id', 'index', 'output', 'model', 'is_faithfull'] = ''
-#     f_0 = open(source_path)
-#     source = f_0.read().split('\n')[:N]
-#     f_1 = open(ORI_RES)
-#     ori_res = f_1.read().split('\n')[:N]
-#     # f_2 = open(CONTEXT_SENT_0_h_0_RES)
-#     f_3 = open(CONTEXT_SENT_0_h_1_RES)
-#     sent_0_h_1 = f_3.read().split('\n')[:N]
-#     f_4 = open(CONTEXT_SENT_1_h_1_RES)
-#     sent_1_h_1 = f_4.read().split('\n')[:N]
-#     state.files = list(zip(source, ori_res, sent_0_h_1, sent_1_h_1))
-#     state.current_file = state.files[0]
-#     state.counter = 0
-#     state.submit = 0
-
-
-# def submit(index_0, index_1, index_2):
-#     x = [(index_0, state.a),(index_1, state.b), (index_2, state.c)]
-#     x = sorted(x, key=lambda x: x[0])
-#     if state.submit == 0:
-#         state.annotations[state.counter, x[0][0], state.current_file[1], 'ori_res', x[0][1]] = ''
-#         state.annotations[state.counter, x[1][0], state.current_file[2], 'sent_0_h_1', x[1][1]] = ''
-#         state.annotations[state.counter, x[2][0], state.current_file[3], 'sent_1_h_1', x[2][1]] = ''
-#         state.submit = 1
-#     if state.submit == 1:
-#         state.files.remove(state.current_file)
-#         random.shuffle(state.indexes)
-#         state.current_file = state.files[0]
-#         state.counter += 1
-#         state.submit = 0
+generated_path = 'generated_predictions.txt'
+
+ORI_RES = f'DUC/results/{generated_path}'
+# CONTEXT_SENT_0_h_0_RES = f'/home/nlp/wolhanr/mds_faithfull/data/DUC/output_dir/sent_window_0_h_0_clusters/{generated_path}'
+CONTEXT_SENT_0_h_1_RES = f'DUC/output_dir/sent_window_0_clusters/{generated_path}'
+CONTEXT_SENT_1_h_1_RES = f'DUC/output_dir/sent_window_1_h_1_clusters/{generated_path}'
+
+source_path = 'DUC/sent_window_1_h_1_clusters/test.source'
+
+OPTIONS = ["faithfull", "Not faithfull"]
+
+if "number_button_fill" not in state:
+    state.number_button_fill = 0
+
+if "annotations" not in state:
+    state.annotations = {}
+    state.annotations['data_id', 'index', 'output', 'model', 'is_faithfull'] = ''
+    f_0 = open(source_path)
+    source = f_0.read().split('\n')[:N]
+    f_1 = open(ORI_RES)
+    ori_res = f_1.read().split('\n')[:N]
+    # f_2 = open(CONTEXT_SENT_0_h_0_RES)
+    f_3 = open(CONTEXT_SENT_0_h_1_RES)
+    sent_0_h_1 = f_3.read().split('\n')[:N]
+    f_4 = open(CONTEXT_SENT_1_h_1_RES)
+    sent_1_h_1 = f_4.read().split('\n')[:N]
+    state.files = list(zip(source, ori_res, sent_0_h_1, sent_1_h_1))
+    state.current_file = state.files[0]
+    state.counter = 0
+    state.submit = 0
+
+
+def submit(index_0, index_1, index_2):
+    x = [(index_0, state.a),(index_1, state.b), (index_2, state.c)]
+    x = sorted(x, key=lambda x: x[0])
+    if state.submit == 0:
+        state.annotations[state.counter, x[0][0], state.current_file[1], 'ori_res', x[0][1]] = ''
+        state.annotations[state.counter, x[1][0], state.current_file[2], 'sent_0_h_1', x[1][1]] = ''
+        state.annotations[state.counter, x[2][0], state.current_file[3], 'sent_1_h_1', x[2][1]] = ''
+        state.submit = 1
+    if state.submit == 1:
+        state.files.remove(state.current_file)
+        random.shuffle(state.indexes)
+        state.current_file = state.files[0]
+        state.counter += 1
+        state.submit = 0
 
 st.header("Dataset annotation")
 
-# if state.files:
-#     selected_file = state.current_file
-#     # source_file = selected_file[0] 
-#     # ori_file = selected_file[1] 
-#     # sent_0_h_1_file = selected_file[2]
-#     # sent_1_h_1_file = selected_file[3]
+if state.files:
+    selected_file = state.current_file
+    # source_file = selected_file[0] 
+    # ori_file = selected_file[1] 
+    # sent_0_h_1_file = selected_file[2]
+    # sent_1_h_1_file = selected_file[3]
 
-#     st.write(f"Source file: {selected_file[0]}")
+    st.write(f"Source file: {selected_file[0]}")
 
-#     if 'indexes' not in state:
-#         state.indexes = [1, 2, 3]
-#         random.shuffle(state.indexes)
+    if 'indexes' not in state:
+        state.indexes = [1, 2, 3]
+        random.shuffle(state.indexes)
 
-#     st.write(f"Output: {selected_file[state.indexes[0]]}")
-#     # c = st.columns(len(OPTIONS))
-#     state.a = st.radio('a', OPTIONS, key=f'{0}')
-#     st.write(f"Output: {selected_file[state.indexes[1]]}")
-#     state.b = st.radio('b', OPTIONS, key=f'{1}')
-#     st.write(f"Output: {selected_file[state.indexes[2]]}")
-#     state.c = st.radio('c', OPTIONS, key=f'{2}')
+    st.write(f"Output: {selected_file[state.indexes[0]]}")
+    # c = st.columns(len(OPTIONS))
+    state.a = st.radio('a', OPTIONS, key=f'{0}')
+    st.write(f"Output: {selected_file[state.indexes[1]]}")
+    state.b = st.radio('b', OPTIONS, key=f'{1}')
+    st.write(f"Output: {selected_file[state.indexes[2]]}")
+    state.c = st.radio('c', OPTIONS, key=f'{2}')
 
 
-#     st.button('Submit', on_click=submit, args=(copy.deepcopy(state.indexes)))
+    st.button('Submit', on_click=submit, args=(copy.deepcopy(state.indexes)))
 
 
-st.button('Submit')
 
 
+else:
+    st.info("Everything annotated.")
 
-# else:
-#     st.info("Everything annotated.")
+st.info(f"Annotated: {len(state.annotations)}, Remaining: {len(state.files)}")
 
-# st.info(f"Annotated: {len(state.annotations)}, Remaining: {len(state.files)}")
-
-# st.download_button(
-#     "Download annotations as CSV",
-#     "\n".join([f"{k}\t{v}" for k, v in state.annotations.items()]),
-#     file_name="annotations_faithfull.csv",
-# )
+st.download_button(
+    "Download annotations as CSV",
+    "\n".join([f"{k}\t{v}" for k, v in state.annotations.items()]),
+    file_name="annotations_faithfull.csv",
+)