diff --git a/streamlit_app.py b/streamlit_app.py
index 516f68b..df86e3b 100644
--- a/streamlit_app.py
+++ b/streamlit_app.py
@@ -1,39 +1,62 @@
-# Code refactored from https://docs.streamlit.io/knowledge-base/tutorials/build-conversational-apps
-
 import openai
 import streamlit as st
 
+# Configuração da barra lateral
 with st.sidebar:
     st.title('🤖💬 OpenAI Chatbot')
+
+    # Verifica se a chave da API está nos segredos
     if 'OPENAI_API_KEY' in st.secrets:
         st.success('API key already provided!', icon='✅')
         openai.api_key = st.secrets['OPENAI_API_KEY']
     else:
+        # Solicita ao usuário a chave da API
         openai.api_key = st.text_input('Enter OpenAI API token:', type='password')
-        if not (openai.api_key.startswith('sk-') and len(openai.api_key)==51):
+        if not (openai.api_key.startswith('sk-') and len(openai.api_key) == 51):
             st.warning('Please enter your credentials!', icon='⚠️')
         else:
             st.success('Proceed to entering your prompt message!', icon='👉')
 
+# Inicializa o histórico de mensagens
 if "messages" not in st.session_state:
     st.session_state.messages = []
 
+# Exibe o histórico de mensagens
 for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
+# Coleta o prompt do usuário
 if prompt := st.chat_input("What is up?"):
     st.session_state.messages.append({"role": "user", "content": prompt})
+    
+    # Exibe a mensagem do usuário no chat
     with st.chat_message("user"):
         st.markdown(prompt)
+    
+    # Prepara a mensagem de resposta
     with st.chat_message("assistant"):
         message_placeholder = st.empty()
         full_response = ""
-        for response in openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=[{"role": m["role"], "content": m["content"]}
-                      for m in st.session_state.messages], stream=True):
-            full_response += response.choices[0].delta.get("content", "")
-            message_placeholder.markdown(full_response + "▌")
+
+        # Chama a API da OpenAI para obter a resposta
+        try:
+            response = openai.ChatCompletion.create(
+                model="gpt-3.5-turbo",
+                messages=[{"role": m["role"], "content": m["content"]} for m in st.session_state.messages],
+                stream=True  # Habilita o streaming de respostas
+            )
+
+            # Processa as respostas no modo streaming
+            for chunk in response:
+                delta_content = chunk.choices[0].delta.get("content", "")
+                full_response += delta_content
+                message_placeholder.markdown(full_response + "▌")  # Exibe a resposta parcial
+        except Exception as e:
+            st.error(f"An error occurred: {str(e)}")
+
+        # Exibe a resposta final
         message_placeholder.markdown(full_response)
+
+    # Armazena a resposta do assistente no histórico
     st.session_state.messages.append({"role": "assistant", "content": full_response})