Update modules/ui.py

modules/ui.py

@@ -5,10 +5,10 @@ import io
 import base64
 import matplotlib.pyplot as plt
 import pandas as pd
+import time
 from streamlit_player import st_player  # Necesitarás instalar esta librería: pip install streamlit-player
 from spacy import displacy
 
-
 #Importaciones locales
 #Importaciones locales de autenticación y base de datos 
 from .auth import authenticate_user, register_user, get_user_role
@@ -396,28 +396,25 @@ def display_discourse_analysis_interface(nlp_models, lang_code):
 def display_chatbot_interface(lang_code):
     translations = {
         'es': {
-            'title': "AIdeaText - Chatbot Multilingüe",
+            'title': "Expertos en Vacaciones",
             'input_placeholder': "Escribe tu mensaje aquí...",
-            'send_button': "Enviar",
-            'initial_message': "¡Hola! ¿En qué puedo ayudarte hoy?"
+            'initial_message': "¡Hola! ¿Cómo podemos ayudarte?"
         },
         'en': {
-            'title': "AIdeaText - Multilingual Chatbot",
+            'title': "Vacation Experts",
             'input_placeholder': "Type your message here...",
-            'send_button': "Send",
-            'initial_message': "Hello! How can I assist you today?"
+            'initial_message': "Hi! How can we help you?"
         },
         'fr': {
-            'title': "AIdeaText - Chatbot Multilingue",
+            'title': "Experts en Vacances",
             'input_placeholder': "Écrivez votre message ici...",
-            'send_button': "Envoyer",
-            'initial_message': "Bonjour! Comment puis-je vous aider aujourd'hui?"
+            'initial_message': "Bonjour! Comment pouvons-nous vous aider?"
         }
     }
 
     t = translations[lang_code]
 
-    st.header(t['title'])
+    st.title(t['title'])
 
     if 'chatbot' not in st.session_state:
         st.session_state.chatbot = initialize_chatbot()
@@ -425,31 +422,41 @@ def display_chatbot_interface(lang_code):
     if 'messages' not in st.session_state:
         st.session_state.messages = [{"role": "assistant", "content": t['initial_message']}]
 
-    # Mostrar mensajes previos
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
-
-    # Input del usuario
-    if prompt := st.chat_input(t['input_placeholder']):
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        with st.chat_message("user"):
-            st.markdown(prompt)
+    chat_container = st.container()
 
-        with st.chat_message("assistant"):
-            message_placeholder = st.empty()
-            full_response = get_chatbot_response(st.session_state.chatbot, prompt, lang_code)
-            
-            # Simular escritura gradual
-            for i in range(len(full_response)):
-                message_placeholder.markdown(full_response[:i+1] + "▌")
-                time.sleep(0.01)
-            message_placeholder.markdown(full_response)
-        
-        st.session_state.messages.append({"role": "assistant", "content": full_response})
+    # Área de entrada del usuario
+    user_input = st.text_input(t['input_placeholder'], key="user_input")
 
-        # Guardar la conversación en la base de datos
-        store_chat_history(st.session_state.username, st.session_state.messages)
+    # Botón de envío (oculto, se activa con Enter)
+    if st.button("Send", key="send_button", style="display: none;") or user_input:
+        if user_input:
+            st.session_state.messages.append({"role": "user", "content": user_input})
+            with chat_container:
+                for message in st.session_state.messages:
+                    if message["role"] == "user":
+                        st.text_area("You:", value=message["content"], height=50, key=f"user_msg_{len(st.session_state.messages)}", disabled=True)
+                    else:
+                        st.text_area("Assistant:", value=message["content"], height=50, key=f"assistant_msg_{len(st.session_state.messages)}", disabled=True)
+
+            # Generar respuesta del chatbot
+            response = get_chatbot_response(st.session_state.chatbot, user_input, lang_code)
+            st.session_state.messages.append({"role": "assistant", "content": response})
+
+            # Mostrar la respuesta del chatbot con efecto de escritura
+            with chat_container:
+                assistant_message = st.empty()
+                full_response = ""
+                for char in response:
+                    full_response += char
+                    assistant_message.text_area("Assistant:", value=full_response + "▌", height=50, key=f"assistant_msg_{len(st.session_state.messages)+1}", disabled=True)
+                    time.sleep(0.01)
+                assistant_message.text_area("Assistant:", value=full_response, height=50, key=f"assistant_msg_{len(st.session_state.messages)+1}", disabled=True)
+
+            # Guardar la conversación en la base de datos
+            store_chat_history(st.session_state.username, st.session_state.messages)
+
+            # Limpiar el input del usuario
+            st.session_state.user_input = ""
 
     # Mostrar el número de llamadas a la API restantes
     remaining_calls = 50 - st.session_state.get('api_calls', 0)