from ..text_analysis.discourse_analysis import perform_discourse_analysis, compare_semantic_analysis
import streamlit as st

def process_discourse_input(user_input, lang_code, nlp_model, file_contents, t):
    if user_input.startswith('/analisis_discurso'):
        if file_contents is None or len(file_contents) != 2:
            return t['no_files_uploaded'], None
        text1, text2 = file_contents
        result = perform_discourse_analysis(text1, text2, nlp_model, lang_code)
        return t['discourse_analysis_completed'], (result['graph1'], result['graph2'])
    elif user_input.startswith('/comparar'):
        if file_contents is None or len(file_contents) != 2:
            return t['no_files_uploaded'], None
        text1, text2 = file_contents
        comparison_result = compare_semantic_analysis(text1, text2, nlp_model, lang_code)
        return t['comparison_completed'], comparison_result
    else:
        # Procesar otros tipos de inputs del usuario
        chatbot = st.session_state.discourse_chatbot
        response = chatbot.generate_response(user_input, lang_code, context=str(file_contents))
        return response, None