Update app.py

app.py

@@ -232,7 +232,7 @@ def display_home_info():
     )
     
     # Title with emoji
-    st.title("🏠 Welcome to TraffiTrack ")
+    st.title("🏠 Welcome to the Drug-Related Content Detector")
 
     # Section for description
     st.markdown(
@@ -303,7 +303,7 @@ elif selected == "Chat":
 
             if st.button("Analyze 🚨"):
                 # Initialize count and list for drug-related messages
-                drug_count = 0  # Initialize drug_count here
+                drug_count = 0
                 drug_messages = []
                 user_data = {}  # Initialize user data dictionary
 
@@ -311,7 +311,7 @@ elif selected == "Chat":
                 for idx, row in messages_df.iterrows():
                     message_text = row['message_text']
                     sender_name = row['sender_name']
-                    sender_id = row['sender_id']
+                    sender_id = row['sender_id']  # This will change with each message
                     phone_number = row['phone_number']
 
                     # Get response from the chat model
@@ -332,6 +332,7 @@ elif selected == "Chat":
                         if sender_name not in user_data:
                             user_data[sender_name] = {
                                 "phone_number": phone_number,
+                                "sender_id": sender_id,  # Store the sender_id here
                                 "message_count": 0,
                                 "drug_words": []
                             }
@@ -343,24 +344,18 @@ elif selected == "Chat":
                 st.write(f"Total drug-related messages detected: {drug_count}")
 
                 if drug_count > 0:
-                    # st.write("Details of detected messages:")
-                    # for message in drug_messages:
-                    #     st.markdown(f"**Phone Number**: {message['phone_number']}  \
-                    #                 **Sender ID**: {message['sender_id']}  \
-                    #                 **Message**: {message['message_text']}  \
-                    #                 **Drug Detected**: {message['drug_word']}")
-                    
                     # Prepare data for visualization
                     user_names = list(user_data.keys())
                     message_counts = [data["message_count"] for data in user_data.values()]
                     phone_numbers = [data["phone_number"] for data in user_data.values()]
+                    sender_ids = [data["sender_id"] for data in user_data.values()]  # Use stored sender_id
 
                     # 1. Bar chart: Messages per user
                     st.markdown("### Number of Messages per User 📊")
                     fig = px.bar(
-                        x=user_names, 
-                        y=message_counts, 
-                        labels={'x': 'User Name', 'y': 'Message Count'}, 
+                        x=user_names,
+                        y=message_counts,
+                        labels={'x': 'User Name', 'y': 'Message Count'},
                         title="Messages Detected per User"
                     )
                     st.plotly_chart(fig)
@@ -369,28 +364,17 @@ elif selected == "Chat":
                     st.markdown("### Drug Distribution Among Users 🍰")
                     drugs_detected = [drug for user in user_data.values() for drug in user["drug_words"]]
                     fig = px.pie(
-                        names=drugs_detected, 
+                        names=drugs_detected,
                         title="Distribution of Detected Drugs"
                     )
                     st.plotly_chart(fig)
 
-                    # 3. Horizontal bar chart: Number of drug-related messages per user
-                    st.markdown("### Drug-related Messages per User 📊")
-                    fig = px.bar(
-                        y=user_names, 
-                        x=message_counts, 
-                        orientation='h', 
-                        labels={'y': 'User Name', 'x': 'Drug-related Messages Count'}, 
-                        title="Drug-related Messages per User"
-                    )
-                    st.plotly_chart(fig)
-
-                    # 4. Display user details in a table
+                    # 3. Display user details in a table
                     st.markdown("### User Details Table 📋")
                     user_df = pd.DataFrame({
                         "User Name": user_names,
                         "Phone Number": phone_numbers,
-                        "Group_id" : sender_id,
+                        "Sender ID": sender_ids,  # Display the correct sender ID
                         "Messages Detected": message_counts
                     })
                     st.dataframe(user_df)
@@ -400,6 +384,7 @@ elif selected == "Chat":
                 else:
                     st.write("No drug-related messages detected.")
 
+
         else:
             # Display chat messages for other platforms with unique keys
             for idx, msg in enumerate(st.session_state.messages):
@@ -420,7 +405,7 @@ elif selected == "Chat":
                     st.session_state.messages.append({"message": response, "is_user": False})
 
                     # Rerun to refresh the UI with new messages
-                    st.rerun()
+                    st.experimental_rerun()
                 else:
                     st.warning("Please enter a message.")