Update app.py

app.py

@@ -15,10 +15,10 @@ html_content = f"""
 </style>
 <div style='display: flex; flex-direction: column; align-items: flex-start;'>
     <div style='display: flex; align-items: center;'>
-        <div style='width: 20px; height: 4px; background-color: green; margin-right: 0px;'></div>
-        <div style='width: 20px; height: 4px; background-color: red; margin-right: 0px;'></div>
-        <div style='width: 20px; height: 4px; background-color: yellow; margin-right: 20px;'></div>
-        <span style='font-size: 40px; font-weight: normal; font-family: "Kanit", sans-serif;'>NOSTRADAMUS</span>
+        <div style='width: 20px; height: 5px; background-color: green; margin-right: 0px;'></div>
+        <div style='width: 20px; height: 5px; background-color: red; margin-right: 0px;'></div>
+        <div style='width: 20px; height: 5px; background-color: yellow; margin-right: 18px;'></div>
+        <span style='font-size: 38px; font-weight: normal; font-family: "Kanit", sans-serif;'>NOSTRADAMUS</span>
     </div>
     <div style='text-align: left; width: 100%;'>
         <span style='font-size: 24px; font-weight: normal; color: #333; font-family: "Kanit", sans-serif'>
@@ -147,35 +147,40 @@ def apply_prophet(df_clean):
     # Renomear colunas e aplicar filtros
     return all_anomalies
 
+tab1, tab2 = st.tabs(["Meta Prophet", "Microsoft TAPEX"])
+
 # Interface para carregar arquivo
 uploaded_file = st.file_uploader("Carregue um arquivo CSV ou XLSX", type=['csv', 'xlsx'])
-if uploaded_file:
-    df = load_data(uploaded_file)
-    df_clean = preprocess_data(df)
-    if df_clean.empty:
-        st.warning("Não há dados válidos para processar.")
-    else:
-        with st.spinner('Aplicando modelo de série temporal...'):
-            all_anomalies = apply_prophet(df_clean)
-            st.session_state['all_anomalies'] = all_anomalies
-
-# Interface para perguntas do usuário
-user_question = st.text_input("Escreva sua questão aqui:", "")
-if user_question:
-    if 'all_anomalies' in st.session_state and not st.session_state['all_anomalies'].empty:
-        bot_response = response(user_question, st.session_state['all_anomalies'])
-        st.session_state['history'].append(('👤', user_question))
-        st.session_state['history'].append(('🤖', bot_response))
-    else:
-        st.warning("Ainda não há dados de anomalias para responder a pergunta.")
-
-# Mostrar histórico de conversa
-for sender, message in st.session_state['history']:
-    if sender == '👤':
-        st.markdown(f"**👤 {message}**")
-    elif sender == '🤖':
-        st.markdown(f"**🤖 {message}**", unsafe_allow_html=True)
-
-# Botão para limpar histórico
-if st.button("Limpar histórico"):
-    st.session_state['history'] = []
+
+with tab1:
+    if uploaded_file:
+        df = load_data(uploaded_file)
+        df_clean = preprocess_data(df)
+        if df_clean.empty:
+            st.warning("Não há dados válidos para processar.")
+        else:
+            with st.spinner('Aplicando modelo de série temporal...'):
+                all_anomalies = apply_prophet(df_clean)
+                st.session_state['all_anomalies'] = all_anomalies
+
+with tab2:
+    # Interface para perguntas do usuário
+    user_question = st.text_input("Escreva sua questão aqui:", "")
+    if user_question:
+        if 'all_anomalies' in st.session_state and not st.session_state['all_anomalies'].empty:
+            bot_response = response(user_question, st.session_state['all_anomalies'])
+            st.session_state['history'].append(('👤', user_question))
+            st.session_state['history'].append(('🤖', bot_response))
+        else:
+            st.warning("Ainda não há dados de anomalias para responder a pergunta.")
+    
+    # Mostrar histórico de conversa
+    for sender, message in st.session_state['history']:
+        if sender == '👤':
+            st.markdown(f"**👤 {message}**")
+        elif sender == '🤖':
+            st.markdown(f"**🤖 {message}**", unsafe_allow_html=True)
+    
+    # Botão para limpar histórico
+    if st.button("Limpar histórico"):
+        st.session_state['history'] = []