Update app.py

app.py

@@ -24,6 +24,9 @@ warnings.filterwarnings("ignore", category=DeprecationWarning)
 
 load_dotenv()
 
+if "selected_menu" not in st.session_state:
+    st.session_state.selected_menu = "Home"
+    
 # Auth0 credentials
 clientId = os.getenv('client_id')
 domain = os.getenv('auth_domain')
@@ -51,6 +54,55 @@ if 'banned_users' not in st.session_state:
 if 'flowmessages' not in st.session_state:
     st.session_state.flowmessages = []
 
+def display_twitter_analysis():
+    st.title('Twitter Analysis 🐦')
+    username = st.text_input("Enter Twitter username")
+    num_tweets = st.number_input("Number of tweets to analyze", min_value=1, max_value=100, value=10)
+
+    if st.button("Fetch Tweets"):
+        if username:
+            try:
+                scraper = Nitter(0)
+                tweets = scraper.get_tweets(username, mode='user', number=num_tweets)
+                tweet_texts = [tweet['text'] for tweet in tweets['tweets']]
+                
+                st.subheader("Tweets")
+                drug_count = 0
+                drug_tweets = []
+                user_data = {"username": username, "tweet_count": 0, "drug_words": []}
+
+                for i, tweet_text in enumerate(tweet_texts):
+                    st.write(f"{i+1}. {tweet_text}")
+                    response_content = get_chatmodel_response(tweet_text)
+                    if "drug word detected" in response_content and "none" not in response_content:
+                        drug_word = response_content.split("drug word detected: ")[1].strip()
+                        drug_count += 1
+                        drug_tweets.append({"tweet": tweet_text, "drug_word": drug_word})
+                        user_data["tweet_count"] += 1
+                        user_data["drug_words"].append(drug_word)
+
+                st.subheader("Analysis Results 📊")
+                st.write(f"Total drug-related tweets detected: {drug_count}")
+
+                if drug_count > 0:
+                    st.markdown("### Drug Words Distribution 🍰")
+                    fig = px.pie(
+                        names=user_data["drug_words"],
+                        title="Distribution of Detected Drugs in Tweets"
+                    )
+                    st.plotly_chart(fig)
+
+                    st.markdown("### Tweets with Drug-related Content 📋")
+                    drug_df = pd.DataFrame(drug_tweets)
+                    st.dataframe(drug_df)
+
+                else:
+                    st.write("No drug-related content detected in tweets.")
+
+            except Exception as e:
+                st.error(f"Failed to fetch tweets: {e}")
+        else:
+            st.warning("Please enter a Twitter username.")
 
 # Function to handle registration
 def registration():
@@ -102,9 +154,6 @@ password = st.text_input("Enter your password...",type='password')
 
 
 
-
-
-
 # Function to get a response from the chat model
 def get_chatmodel_response(user_message):
     # Ensure user_message is a string
@@ -265,8 +314,9 @@ if user_info:
 else:
     st.write("Please log in to continue.")
 
-if st.button("Login / SignUp"):
-    selected = option_menu(
+#if st.button("Login / SignUp"):
+    st.session_state.selected_menu = "Registration"
+    st.session_state.selected_menu = option_menu(
         "Main Menu", 
         ["Home","Registration","Chat"], 
         
@@ -285,14 +335,16 @@ if st.button("Login / SignUp"):
             },
             "nav-link-selected": {"background-color": "#50B498"},
         }
+        
     )
-    if selected == "Registration":
+    #st.session_state.selected_menu = selected
+    if st.session_state.selected_menu == "Registration":
         registration()
 
-    elif selected == "Home":
+    elif st.session_state.selected_menu == "Home":
         display_home_info()
 
-    elif selected == "Chat":
+    elif st.session_state.selected_menu == "Chat":
         
         def traffitrack_chatbot():
             st.title('TraffiTrack 💬')
@@ -300,11 +352,13 @@ if st.button("Login / SignUp"):
             # Dropdown to select platform
             platform = st.selectbox(
                 "Choose a platform", 
-                ["Live 💁‍♀️", "WhatsApp 📱", "Instagram 📸", "Telegram ✉️"], 
+                ["Live 💁‍♀️", "Twitter 📱", "Instagram 📸", "Telegram ✉️"], 
                 index=0
             )
+            if platform == "Twitter 📱":
+                display_twitter_analysis()
 
-            if platform == "Telegram ✉️":
+            elif platform == "Telegram ✉️":
                 # Hardcoded CSV content
                 csv_content = """sender_name,sender_id,phone_number,message_text
         Shruti,1580593004,917304814120,But I would prefer blowing a bag of Charlie