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import streamlit as st
import os
import sys
# Ensure src/infrastructure is in sys.path to allow imports if running from root
current_dir = os.path.dirname(os.path.abspath(__file__))
sys.path.append(current_dir)
from advanced_broker_vehicular import preparar_rag, clasificar_intencion, manejar_saludo, manejar_emergencia
# Page configuration
st.set_page_config(page_title="Copiloto de Seguros", page_icon="🚗", layout="centered")
# Helper function to cache the RAG chain
@st.cache_resource(show_spinner="Inicializando sistema de seguros...")
def get_cached_rag_chain():
return preparar_rag()
# Initialize session state for chat history
if "messages" not in st.session_state:
st.session_state.messages = []
# Load the RAG chain (cached)
try:
st.session_state.rag_chain = get_cached_rag_chain()
except Exception as e:
st.error(f"Error al cargar el sistema de seguros: {e}")
st.session_state.rag_chain = None
# Sidebar
st.sidebar.title("🚗 Copiloto de Seguros")
st.sidebar.markdown("""
Asistente inteligente para consultas sobre seguros vehiculares.
- **Consultas**: Pregunta por coberturas, precios, etc.
- **Emergencias**: Reporta siniestros.
- **Comparaciones**: Compara aseguradoras.
""")
# Display chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# Chat input
if prompt := st.chat_input("Escribe tu consulta aquí..."):
# Add user message to chat history
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
# Process response
with st.chat_message("assistant"):
message_placeholder = st.empty()
full_response = ""
# 1. Classify intention
intencion = clasificar_intencion(prompt)
response_text = ""
if intencion == "SALUDO":
response_text = manejar_saludo()
elif intencion == "EMERGENCIA":
response_text = manejar_emergencia()
elif intencion == "CONSULTA":
if st.session_state.rag_chain:
message_placeholder.markdown("🔍 Analizando pólizas...")
try:
res = st.session_state.rag_chain.invoke({"query": prompt})
response_text = res['result']
except Exception as e:
response_text = f"Error al consultar la base de conocimiento: {str(e)}"
else:
response_text = "⚠️ El sistema de consultas no está disponible (PDFs no cargados)."
else:
response_text = "No estoy seguro de cómo ayudarte con eso. Intenta preguntar sobre seguros, emergencias o salúdame."
message_placeholder.markdown(response_text)
# Add assistant response to chat history
st.session_state.messages.append({"role": "assistant", "content": response_text})
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