Spaces:
Running
Running
# chatbot/chatbot.py | |
import streamlit as st | |
from typing import Dict, List, Tuple | |
import logging | |
logger = logging.getLogger(__name__) | |
class AIdeaTextChatbot: | |
def __init__(self, lang_code: str): | |
self.lang_code = lang_code | |
self.conversation_history = [] | |
self.context = { | |
'current_analysis': None, | |
'last_question': None, | |
'user_profile': None | |
} | |
def process_message(self, message: str, context: Dict = None) -> str: | |
""" | |
Procesa el mensaje del usuario y genera una respuesta | |
""" | |
try: | |
# Actualizar contexto | |
if context: | |
self.context.update(context) | |
# Analizar intenci贸n del mensaje | |
intent = self._analyze_intent(message) | |
# Generar respuesta basada en la intenci贸n | |
response = self._generate_response(intent, message) | |
# Actualizar historial | |
self._update_history(message, response) | |
return response | |
except Exception as e: | |
logger.error(f"Error procesando mensaje: {str(e)}") | |
return self._get_fallback_response() | |
def _analyze_intent(self, message: str) -> str: | |
""" | |
Analiza la intenci贸n del mensaje del usuario | |
""" | |
# Implementar an谩lisis de intenci贸n | |
pass | |
def _generate_response(self, intent: str, message: str) -> str: | |
""" | |
Genera una respuesta basada en la intenci贸n | |
""" | |
# Implementar generaci贸n de respuesta | |
pass | |
def get_conversation_history(self) -> List[Tuple[str, str]]: | |
""" | |
Retorna el historial de conversaci贸n | |
""" | |
return self.conversation_history |