Update app.py

app.py

@@ -71,77 +71,45 @@ def chatbot_response(user_input):
     response = qa.run(user_input)
     return response
 
-# Function to save user feedback
+import gspread
+from oauth2client.service_account import ServiceAccountCredentials
+import json
+
+# Load Google service account credentials from Hugging Face secrets
+GOOGLE_SERVICE_ACCOUNT_JSON = st.secrets["GOOGLE_SERVICE_ACCOUNT_JSON"]
+
+# Google Sheets setup
+scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
+service_account_info = json.loads(GOOGLE_SERVICE_ACCOUNT_JSON)
+creds = ServiceAccountCredentials.from_json_keyfile_dict(service_account_info, scope)
+client = gspread.authorize(creds)
+sheet = client.open("Streamlit Feedback").sheet1  # Replace with your Google Sheet name
+
+# Function to save user feedback to Google Sheets
 def save_feedback(user_input, bot_response, rating, comment):
-    feedback = {
-        "user_input": user_input,
-        "bot_response": bot_response,
-        "rating": rating,
-        "comment": comment
-    }
-    
-    # Check if the feedback file exists
-    feedback_file = "feedback.csv"
-    if os.path.exists(feedback_file):
-        # Load existing feedback and append new feedback
-        feedback_df = pd.read_csv(feedback_file)
-        feedback_df = feedback_df.append(feedback, ignore_index=True)
-    else:
-        # Create a new dataframe for the feedback
-        feedback_df = pd.DataFrame([feedback])
-    
-    # Save feedback to CSV
-    feedback_df.to_csv(feedback_file, index=False)
-
-# Create columns for logos
-col1, col2, col3 = st.columns([2, 3, 2])
-
-with col1:
-    st.image("Design 3_22.png", width=150, use_column_width=True)
-
-with col3:
-    st.image("Altereo logo 2023 original - eau et territoires durables.png", width=150, use_column_width=True)
-
-# Adding centered header and subtitle
-st.markdown("""
-    <style>
-    .centered-text { text-align: center; }
-    .centered-orange-text { text-align: center; color: darkorange; }
-    </style>
-""", unsafe_allow_html=True)
-st.markdown('<h3 class="centered-text">🤖 AlteriaChat 🤖 </h3>', unsafe_allow_html=True)
-st.markdown('<p class="centered-orange-text">"Votre Réponse à Chaque Défi Méthodologique "</p>', unsafe_allow_html=True)
-
-# Input and button for user interaction
-user_input = st.text_input("You:", "")
-submit_button = st.button("Ask 📨")
-
-# Handle user input and display response
-if submit_button and user_input.strip():
-    bot_response = chatbot_response(user_input)
-    st.markdown("### Bot:")
-    st.text_area("", value=bot_response, height=300)
-    
-    # Star rating system
-    st.markdown("### How would you rate the response?")
-    rating = st.slider("Rate from 1 star to 5 stars", min_value=1, max_value=5, value=3)
-    
-    # Comment section
-    comment = st.text_area("Any comments or suggestions for improvement?", "")
-    
-    # Save feedback when the user submits a rating and comment
-    if st.button("Submit Feedback"):
+    feedback = [user_input, bot_response, rating, comment]
+    sheet.append_row(feedback)
+
+# Streamlit app layout
+st.set_page_config(page_title="Feedback App", page_icon="🤖")
+
+st.markdown("<h3 style='text-align: center;'>🤖 Chatbot Feedback 🤖</h3>", unsafe_allow_html=True)
+
+user_input = st.text_input("You:")
+bot_response = "This is a bot response."  # Replace this with your chatbot's response logic
+
+st.markdown("### Rate the response:")
+rating = st.selectbox("", [1, 2, 3, 4, 5])
+
+st.markdown("### Leave a comment:")
+comment = st.text_area("")
+
+if st.button("Submit"):
+    if user_input.strip() and comment.strip():
         save_feedback(user_input, bot_response, rating, comment)
         st.success("Thank you for your feedback!")
+    else:
+        st.warning("Please provide both input and comment.")
 
-# Motivational quote at the bottom
 st.markdown("---")
-st.markdown("La collaboration est la clé du succès. Chaque question trouve sa réponse, chaque défi devient une opportunité.")
-
-# Section for the developer to review feedback
-if st.checkbox("Show Feedback (Developer Only)"):
-    if os.path.exists("feedback.csv"):
-        feedback_df = pd.read_csv("feedback.csv")
-        st.dataframe(feedback_df)
-    else:
-        st.warning("No feedback available yet.")
+st.markdown("Collaboration is the key to success. Each question finds its answer, each challenge becomes an opportunity.")