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import streamlit as st
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from .chat_process import ChatProcessor
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from ..database.chat_mongo_db import store_chat_history
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import logging
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logger = logging.getLogger(__name__)
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def display_sidebar_chat(lang_code: str, chatbot_t: dict):
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"""Chatbot mejorado con manejo completo del contexto semántico"""
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with st.sidebar:
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st.markdown("""
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<style>
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.chat-container {
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max-height: 60vh;
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overflow-y: auto;
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padding: 10px;
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}
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.chat-message { margin-bottom: 15px; }
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</style>
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""", unsafe_allow_html=True)
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try:
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if 'chat_processor' not in st.session_state:
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st.session_state.chat_processor = ChatProcessor()
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logger.info("Nuevo ChatProcessor inicializado")
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if st.session_state.get('semantic_agent_active', False):
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semantic_data = st.session_state.get('semantic_agent_data')
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if semantic_data and all(k in semantic_data for k in ['text', 'metrics']):
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try:
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st.session_state.chat_processor.set_semantic_context(
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text=semantic_data['text'],
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metrics=semantic_data['metrics'],
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graph_data=semantic_data.get('graph_data'),
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lang_code=lang_code
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)
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logger.info("Contexto semántico configurado en el chat")
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except Exception as e:
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logger.error(f"Error configurando contexto: {str(e)}")
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st.error("Error al configurar el análisis. Recargue el documento.")
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return
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with st.expander("💬 Asistente de Análisis", expanded=True):
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if 'sidebar_messages' not in st.session_state:
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initial_msg = {
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'en': "Hello! Ask me about the semantic analysis.",
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'es': "¡Hola! Pregúntame sobre el análisis semántico.",
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'pt': "Olá! Pergunte-me sobre a análise semântica."
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}.get(lang_code, "Hello!")
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st.session_state.sidebar_messages = [
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{"role": "assistant", "content": initial_msg}
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]
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chat_container = st.container()
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with chat_container:
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for msg in st.session_state.sidebar_messages:
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st.chat_message(msg["role"]).write(msg["content"])
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user_input = st.chat_input(
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{
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'en': "Ask about the analysis...",
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'es': "Pregunta sobre el análisis...",
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'pt': "Pergunte sobre a análise..."
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}.get(lang_code, "Message...")
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)
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if user_input:
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try:
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with chat_container:
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st.chat_message("user").write(user_input)
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st.session_state.sidebar_messages.append(
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{"role": "user", "content": user_input}
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)
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with st.chat_message("assistant"):
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response = st.write_stream(
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st.session_state.chat_processor.process_chat_input(
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user_input, lang_code
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)
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)
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st.session_state.sidebar_messages.append(
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{"role": "assistant", "content": response.replace("▌", "")}
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)
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if 'username' in st.session_state:
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store_chat_history(
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username=st.session_state.username,
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messages=st.session_state.sidebar_messages,
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chat_type='semantic_analysis',
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metadata={
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'text_sample': st.session_state.semantic_agent_data['text'][:500],
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'concepts': st.session_state.semantic_agent_data['metrics']['key_concepts'][:5]
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}
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)
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except Exception as e:
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logger.error(f"Error en conversación: {str(e)}", exc_info=True)
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st.error({
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'en': "Error processing request. Try again.",
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'es': "Error al procesar. Intente nuevamente.",
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'pt': "Erro ao processar. Tente novamente."
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}.get(lang_code, "Error"))
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if st.button("🔄 Reiniciar Chat"):
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st.session_state.sidebar_messages = []
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st.rerun()
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except Exception as e:
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logger.error(f"Error fatal en sidebar_chat: {str(e)}", exc_info=True)
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st.error("System error. Please refresh the page.") |
