Update app.py

app.py

@@ -4,64 +4,57 @@ import streamlit as st
 # Title
 st.title("Q&A Evaluation Tool")
 
-# Upload the dataset
+# Load the dataset from the repository
 @st.cache_data
-def load_data(file_path):
-    return pd.read_excel(file_path)
-
-# File upload section
-uploaded_file = st.file_uploader("Upload the Q&A Excel File", type=["xlsx"])
-
-if uploaded_file:
-    # Load data
-    data = load_data(uploaded_file)
-
-    # Add columns for evaluation if not present
-    if "Rating" not in data.columns:
-        data["Rating"] = ""
-    if "Comments" not in data.columns:
-        data["Comments"] = ""
-
-    # Initialize session state for tracking progress
-    if "current_index" not in st.session_state:
-        st.session_state.current_index = 0
-
-    # Display current question-answer pair
-    idx = st.session_state.current_index
-    if idx < len(data):
-        st.subheader(f"Question {idx + 1}:")
-        st.write(data.loc[idx, "Question"])
-
-        st.subheader("Generated Answer:")
-        st.write(data.loc[idx, "Generated Answer"])
-
-        # Rating input
-        rating = st.slider("Rate the answer (1 = Poor, 5 = Excellent)", 1, 5, step=1)
-        comment = st.text_area("Add any comments or suggestions")
-
-        # Save feedback
-        if st.button("Submit Feedback"):
-            data.at[idx, "Rating"] = rating
-            data.at[idx, "Comments"] = comment
-            st.session_state.current_index += 1
-
-            # Save the updated dataset
-            data.to_excel("evaluated_data.xlsx", index=False)
-
-            # Confirmation and next question
-            st.success("Feedback submitted!")
-            st.experimental_rerun()
-    else:
-        st.write("You have completed the evaluation. Thank you!")
-
-        # Download the evaluated file
-        with open("evaluated_data.xlsx", "rb") as f:
-            st.download_button(
-                "Download Evaluated Data",
-                f,
-                file_name="evaluated_data.xlsx",
-                mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
-            )
-
+def load_data():
+    return pd.read_csv("dummy_qa_data.csv")
+
+# Load data
+data = load_data()
+
+# Add columns for evaluation if not present
+if "Rating" not in data.columns:
+    data["Rating"] = ""
+if "Comments" not in data.columns:
+    data["Comments"] = ""
+
+# Initialize session state for tracking progress
+if "current_index" not in st.session_state:
+    st.session_state.current_index = 0
+
+# Display current question-answer pair
+idx = st.session_state.current_index
+if idx < len(data):
+    st.subheader(f"Question {idx + 1}:")
+    st.write(data.loc[idx, "Question"])
+
+    st.subheader("Generated Answer:")
+    st.write(data.loc[idx, "Generated Answer"])
+
+    # Rating input
+    rating = st.slider("Rate the answer (1 = Poor, 5 = Excellent)", 1, 5, step=1)
+    comment = st.text_area("Add any comments or suggestions")
+
+    # Save feedback
+    if st.button("Submit Feedback"):
+        data.at[idx, "Rating"] = rating
+        data.at[idx, "Comments"] = comment
+        st.session_state.current_index += 1
+
+        # Save the updated dataset
+        data.to_csv("evaluated_data.csv", index=False)
+
+        # Confirmation and next question
+        st.success("Feedback submitted!")
+        st.experimental_rerun()
 else:
-    st.info("Please upload an Excel file to get started.")
+    st.write("You have completed the evaluation. Thank you!")
+
+    # Download the evaluated file
+    with open("evaluated_data.csv", "rb") as f:
+        st.download_button(
+            "Download Evaluated Data",
+            f,
+            file_name="evaluated_data.csv",
+            mime="text/csv",
+        )