update

pages/2_batch_evaluation.py

@@ -3,6 +3,7 @@ import streamlit as st
 from util.evaluator import evaluator, write_evaluation_commentary
 import os
 
+
 def check_password():
     with st.sidebar:
         password_input = st.text_input("Enter Password:", type="password")
@@ -14,16 +15,19 @@ def check_password():
             else:
                 st.error("Incorrect Password, please try again.")
 
+
 def batch_evaluate(uploaded_file):
-    # Read the uploaded CSV file into DataFrame
     df = pd.read_csv(uploaded_file)
-    eval_instance = evaluator('gpt4-1106')  # Using fixed model name for simplicity
+    eval_instance = evaluator('gpt4-1106')  # Assuming fixed model name for simplicity
+    total_rows = len(df)
     results = []
 
-    # Process each row in the DataFrame
-    for _, row in df.iterrows():
-        question = row['question']
-        explanation = row['explanation']
+    # Add a progress bar
+    progress_bar = st.progress(0)
+
+    for index, row in enumerate(df.itertuples(), start=1):
+        question = row.question
+        explanation = row.explanation
         scores = eval_instance(question, explanation)  # Evaluate using the evaluator
         commentary_details = write_evaluation_commentary(scores)  # Generate commentary based on scores
         results.append({
@@ -32,8 +36,12 @@ def batch_evaluate(uploaded_file):
             **{detail['Principle']: detail['Score'] for detail in commentary_details}
         })
 
+        # Update progress bar
+        progress_bar.progress(index / total_rows)
+
     return pd.DataFrame(results)
 
+
 st.title('Natural Language Explanation Demo')
 
 if 'password_verified' not in st.session_state or not st.session_state['password_verified']: