update app.py

app.py

@@ -2,12 +2,19 @@ import streamlit as st
 import pandas as pd
 from PIL import Image
 from transformers import pipeline, AutoTokenizer
+import os
+
+DATASET_REPO_URL = "https://huggingface.co/datasets/tiedaar/question_scoring_stresstest"
+DATA_FILENAME = "output.csv"
+DATA_FILE = os.path.join("data", DATA_FILENAME)
+HF_TOKEN = os.environ.get("HF_TOKEN")
+
 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'])
-output = pd.read_csv('output.csv')
+output = pd.read_csv(DATA_FILE)
 
 def reset():
     st.session_state.ind = False
@@ -74,7 +81,7 @@ if st.session_state.ind:
             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.to_csv('output.csv')
+            output.to_csv(DATA_FILE)
         else:
             st.write("Please indicate whether you are providing a correct answer.")
 

requirements.txt

@@ -1,3 +1,4 @@
 transformers
 pandas
-torch
+torch
+google-cloud-bigquery