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from ..text_analysis.discourse_analysis import perform_discourse_analysis, compare_semantic_analysis
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import streamlit as st
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def process_discourse_input(user_input, lang_code, nlp_model, file_contents, t):
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if user_input.startswith('/analisis_discurso'):
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if file_contents is None or len(file_contents) != 2:
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return t['no_files_uploaded'], None
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text1, text2 = file_contents
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result = perform_discourse_analysis(text1, text2, nlp_model, lang_code)
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return t['discourse_analysis_completed'], (result['graph1'], result['graph2'])
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elif user_input.startswith('/comparar'):
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if file_contents is None or len(file_contents) != 2:
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return t['no_files_uploaded'], None
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text1, text2 = file_contents
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comparison_result = compare_semantic_analysis(text1, text2, nlp_model, lang_code)
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return t['comparison_completed'], comparison_result
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else:
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chatbot = st.session_state.discourse_chatbot
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response = chatbot.generate_response(user_input, lang_code, context=str(file_contents))
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return response, None |
