import streamlit as st from ..text_analysis.morpho_analysis import perform_advanced_morphosyntactic_analysis from ..text_analysis.semantic_analysis import perform_semantic_analysis from ..text_analysis.discourse_analysis import perform_discourse_analysis class AIdeaTextChatbot: def __init__(self): self.conversation_history = [] def handle_morphosyntactic_input(self, user_input, lang_code, nlp_models, t): if user_input.startswith('/analisis_morfosintactico'): text_to_analyze = user_input.split('[', 1)[1].rsplit(']', 1)[0] result = perform_advanced_morphosyntactic_analysis(text_to_analyze, nlp_models[lang_code]) if result is None or 'arc_diagrams' not in result: return t.get('morphosyntactic_analysis_error', 'Error en el análisis morfosintáctico'), None, None return t.get('morphosyntactic_analysis_completed', 'Análisis morfosintáctico completado'), result['arc_diagrams'], result else: # Aquí puedes manejar otras interacciones relacionadas con el análisis morfosintáctico return self.generate_response(user_input, lang_code), None, None def handle_semantic_input(self, user_input, lang_code, nlp_models, t): # Implementar lógica para análisis semántico pass def handle_discourse_input(self, user_input, lang_code, nlp_models, t): # Implementar lógica para análisis de discurso pass def handle_generate_response(self, prompt, lang_code): # Aquí iría la lógica para generar respuestas generales del chatbot # Puedes usar la API de Claude aquí si lo deseas pass def initialize_chatbot(): return AIdeaTextChatbot() def process_chat_input(user_input, lang_code, nlp_models, analysis_type, t, file_contents=None): chatbot = st.session_state.get('aideatext_chatbot') if not chatbot: chatbot = initialize_chatbot() st.session_state.aideatext_chatbot = chatbot if analysis_type == 'morphosyntactic': return chatbot.handle_morphosyntactic_input(user_input, lang_code, nlp_models, t) # ... manejar otros tipos de análisis ...