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# modules/chatbot/sidebar_chat.py
import streamlit as st
from .chat_process import ChatProcessor
from ..database.chat_mongo_db import store_chat_history
import logging
logger = logging.getLogger(__name__)
def display_sidebar_chat(lang_code: str, chatbot_t: dict):
"""Chatbot mejorado con manejo completo del contexto semántico"""
with st.sidebar:
# Configuración de estilos
st.markdown("""
<style>
.chat-container {
max-height: 60vh;
overflow-y: auto;
padding: 10px;
}
.chat-message { margin-bottom: 15px; }
</style>
""", unsafe_allow_html=True)
try:
# Inicialización del procesador
if 'chat_processor' not in st.session_state:
st.session_state.chat_processor = ChatProcessor()
logger.info("Nuevo ChatProcessor inicializado")
# Configurar contexto semántico si está activo
if st.session_state.get('semantic_agent_active', False):
semantic_data = st.session_state.get('semantic_agent_data')
if semantic_data and all(k in semantic_data for k in ['text', 'metrics']):
try:
st.session_state.chat_processor.set_semantic_context(
text=semantic_data['text'],
metrics=semantic_data['metrics'],
graph_data=semantic_data.get('graph_data'),
lang_code=lang_code
)
logger.info("Contexto semántico configurado en el chat")
except Exception as e:
logger.error(f"Error configurando contexto: {str(e)}")
st.error("Error al configurar el análisis. Recargue el documento.")
return
# Interfaz del chat
with st.expander("💬 Asistente de Análisis", expanded=True):
# Inicializar historial si no existe
if 'sidebar_messages' not in st.session_state:
initial_msg = {
'en': "Hello! Ask me about the semantic analysis.",
'es': "¡Hola! Pregúntame sobre el análisis semántico.",
'pt': "Olá! Pergunte-me sobre a análise semântica."
}.get(lang_code, "Hello!")
st.session_state.sidebar_messages = [
{"role": "assistant", "content": initial_msg}
]
# Mostrar historial
chat_container = st.container()
with chat_container:
for msg in st.session_state.sidebar_messages:
st.chat_message(msg["role"]).write(msg["content"])
# Manejo de mensajes nuevos
user_input = st.chat_input(
{
'en': "Ask about the analysis...",
'es': "Pregunta sobre el análisis...",
'pt': "Pergunte sobre a análise..."
}.get(lang_code, "Message...")
)
if user_input:
try:
# Mostrar mensaje del usuario
with chat_container:
st.chat_message("user").write(user_input)
st.session_state.sidebar_messages.append(
{"role": "user", "content": user_input}
)
# Obtener y mostrar respuesta
with st.chat_message("assistant"):
response = st.write_stream(
st.session_state.chat_processor.process_chat_input(
user_input, lang_code
)
)
st.session_state.sidebar_messages.append(
{"role": "assistant", "content": response.replace("▌", "")}
)
# Guardar en base de datos
if 'username' in st.session_state:
store_chat_history(
username=st.session_state.username,
messages=st.session_state.sidebar_messages,
chat_type='semantic_analysis',
metadata={
'text_sample': st.session_state.semantic_agent_data['text'][:500],
'concepts': st.session_state.semantic_agent_data['metrics']['key_concepts'][:5]
}
)
except Exception as e:
logger.error(f"Error en conversación: {str(e)}", exc_info=True)
st.error({
'en': "Error processing request. Try again.",
'es': "Error al procesar. Intente nuevamente.",
'pt': "Erro ao processar. Tente novamente."
}.get(lang_code, "Error"))
# Botón para reiniciar
if st.button("🔄 Reiniciar Chat"):
st.session_state.sidebar_messages = []
st.rerun()
except Exception as e:
logger.error(f"Error fatal en sidebar_chat: {str(e)}", exc_info=True)
st.error("System error. Please refresh the page.") |