update app.py

app.py

@@ -11,87 +11,78 @@ key: str = os.environ.get("SUPABASE_KEY")
 supabase: Client = create_client(url, key)
 
 
-# pipe = pipeline('text-classification', model='tiedaar/short-answer-classification')
-# bleurt_pipe = pipeline('text-classification', model="vaiibhavgupta/finetuned-bleurt-large")
-# tokenizer = AutoTokenizer.from_pretrained("vaiibhavgupta/finetuned-bleurt-large")
-
-# subsections = pd.read_csv('tp-subsections.csv').dropna(axis=0, how='any', subset=['question'])
-
-text = st.text_input("Write your answer here")
-if text:
-    data, count = supabase.table('automatic-short-answer-scoring') \
-        .insert({"subsection": 1, "question": "Denmark", "answer":text}).execute()
-
-
-
-
-# def reset():
-#     st.session_state.ind = False
-#     st.session_state.student_answer = False
-
-# def get_mpnet(candidate, reference):
-#     text = candidate + '</s>' + reference
-#     res = pipe(text)[0]['label']
-#     return res
-
-# def get_bleurt(candidate, reference):
-#     text = candidate + tokenizer.sep_token + reference
-#     score = bleurt_pipe(text)[0]['score']
-#     if score > 0.7:
-#         return 'correct_answer'
-#     else:
-#         return 'incorrect_answer'
-
-# st.title('iTELL Short Answer Scoring Demo')
-# st.image(Image.open('learlabaialoe.JPG'))
-# st.subheader('This is a demonstration of the iTELL short answer scoring model. You will be provided with a passage from the textbook Think Python and a question. Please provide a short answer to the question.')
-# st.slider('Use this slider to choose your subsection.', min_value=0, max_value=len(subsections), key='ind')
-
-# if st.session_state.ind:
-#     student_answer = False
-#     passage = subsections.iloc[st.session_state.ind]['clean_text']
-#     question = subsections.iloc[st.session_state.ind]['question']
-#     answer = subsections.iloc[st.session_state.ind]['answer']
-#     st.markdown('---')
-#     st.header('Passage')
-#     st.write(passage)
-#     st.markdown('---')
-#     st.header('Question')
-#     st.write(question)
-#     is_correct = st.radio("Are you writing a correct answer?", ["Yes", "No"])
-#     st.text_input("Write your answer here", key='student_answer')
-
-#     if st.session_state.student_answer:
-#         if is_correct:
-#             mpnet_res = get_mpnet(st.session_state.student_answer, answer)
-#             bleurt_res = get_bleurt(st.session_state.student_answer, answer)
-#             col1, col2 = st.columns(2)
-#             with col1:
-#                 if mpnet_res == 'correct_answer':
-#                     st.subheader('MPnet says yes!')
-#                     st.image(Image.open('congratulations-meme.jpeg'))
-#                     st.write('Yay, you got it right!')
-#                 elif mpnet_res == 'incorrect_answer':
-#                     st.subheader('MPnet says no!')
-#                     st.write('Nope, you said', st.session_state.student_answer) 
-#                     st.write('A better answer would have been: ', answer)
-#             with col2:
-#                 if bleurt_res == 'correct_answer':
-#                     st.subheader('Bleurt says yes!')
-#                     st.image(Image.open('congratulations-meme.jpeg'))
-#                     st.write('Yay, you got it right!')
-#                 elif bleurt_res == 'incorrect_answer':
-#                     st.subheader('Bleurt says no!')
-#                     st.write('Nope, you said', st.session_state.student_answer) 
-#                     st.write('A better answer would have been: ', answer)
-#             st.button('Reset', on_click=reset)
-#             entry = {"subsection":st.session_state.ind, "source":passage, "question":question, "answer":answer, "mpnet_response":mpnet_res, "bleurt_response":bleurt_res, "correct_response":is_correct}
-#             output.loc[len(output)] = (entry)
-#             output_ds = Dataset.from_pandas(output)
-#             output_ds.push_to_hub(DATASET_REPO)
-
-#         else:
-#             st.write("Please indicate whether you are providing a correct answer.")
+pipe = pipeline('text-classification', model='tiedaar/short-answer-classification')
+bleurt_pipe = pipeline('text-classification', model="vaiibhavgupta/finetuned-bleurt-large")
+tokenizer = AutoTokenizer.from_pretrained("vaiibhavgupta/finetuned-bleurt-large")
+
+subsections = pd.read_csv('tp-subsections.csv').dropna(axis=0, how='any', subset=['question'])
+
+def reset():
+    st.session_state.ind = False
+    st.session_state.student_answer = False
+
+def get_mpnet(candidate, reference):
+    text = candidate + '</s>' + reference
+    res = pipe(text)[0]['label']
+    return res
+
+def get_bleurt(candidate, reference):
+    text = candidate + tokenizer.sep_token + reference
+    score = bleurt_pipe(text)[0]['score']
+    if score > 0.7:
+        return 'correct_answer'
+    else:
+        return 'incorrect_answer'
+
+st.title('iTELL Short Answer Scoring Demo')
+st.image(Image.open('learlabaialoe.JPG'))
+st.subheader('This is a demonstration of the iTELL short answer scoring model. You will be provided with a passage from the textbook Think Python and a question. Please provide a short answer to the question.')
+st.slider('Use this slider to choose your subsection.', min_value=0, max_value=len(subsections), key='ind')
+
+if st.session_state.ind:
+    student_answer = False
+    passage = subsections.iloc[st.session_state.ind]['clean_text']
+    question = subsections.iloc[st.session_state.ind]['question']
+    answer = subsections.iloc[st.session_state.ind]['answer']
+    st.markdown('---')
+    st.header('Passage')
+    st.write(passage)
+    st.markdown('---')
+    st.header('Question')
+    st.write(question)
+    is_correct = st.radio("Are you writing a correct answer?", ["Yes", "No"])
+    st.text_input("Write your answer here", key='student_answer')
+
+    if st.session_state.student_answer:
+        if is_correct:
+            mpnet_res = get_mpnet(st.session_state.student_answer, answer)
+            bleurt_res = get_bleurt(st.session_state.student_answer, answer)
+            col1, col2 = st.columns(2)
+            with col1:
+                if mpnet_res == 'correct_answer':
+                    st.subheader('MPnet says yes!')
+                    st.image(Image.open('congratulations-meme.jpeg'))
+                    st.write('Yay, you got it right!')
+                elif mpnet_res == 'incorrect_answer':
+                    st.subheader('MPnet says no!')
+                    st.write('Nope, you said', st.session_state.student_answer) 
+                    st.write('A better answer would have been: ', answer)
+            with col2:
+                if bleurt_res == 'correct_answer':
+                    st.subheader('Bleurt says yes!')
+                    st.image(Image.open('congratulations-meme.jpeg'))
+                    st.write('Yay, you got it right!')
+                elif bleurt_res == 'incorrect_answer':
+                    st.subheader('Bleurt says no!')
+                    st.write('Nope, you said', st.session_state.student_answer) 
+                    st.write('A better answer would have been: ', answer)
+            st.button('Reset', on_click=reset)
+            entry = {"subsection":st.session_state.ind, "source":passage, "question":question, "answer":answer, "mpnet_response":mpnet_res, "bleurt_response":bleurt_res, "correct_response":is_correct}
+            data, count = supabase.table('automatic-short-answer-scoring') \
+                .insert(entry).execute()
+
+        else:
+            st.write("Please indicate whether you are providing a correct answer.")