Update modules/ui/ui.py
Browse files- modules/ui/ui.py +19 -7
modules/ui/ui.py
CHANGED
@@ -825,6 +825,25 @@ def display_semantic_analysis_interface(nlp_models, lang_code):
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# Realizar el análisis
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analysis_result = perform_semantic_analysis(text_content, nlp_models[lang_code], lang_code)
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def display_semantic_results(result, lang_code, t):
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# Mostrar conceptos clave
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with st.expander(t['key_concepts'], expanded=True):
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@@ -835,13 +854,6 @@ def display_semantic_results(result, lang_code, t):
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with st.expander(t['conceptual_relations'], expanded=True):
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st.pyplot(analysis_result['relations_graph'])
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# Guardar el resultado del análisis
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if store_semantic_result(st.session_state.username, text_content, analysis_result):
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st.success(t['success_message'])
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else:
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st.error(t['error_message'])
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else:
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st.warning(t['warning_message'])
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##################################################################################################
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def display_discourse_analysis_interface(nlp_models, lang_code):
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translations = {
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# Realizar el análisis
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analysis_result = perform_semantic_analysis(text_content, nlp_models[lang_code], lang_code)
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# Guardar el resultado en el estado de la sesión
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st.session_state.semantic_result = analysis_result
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# Mostrar resultados
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display_semantic_results(st.session_state.semantic_result, lang_code, t)
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# Guardar el resultado del análisis
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if store_semantic_result(st.session_state.username, text_content, analysis_result):
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st.success(t['success_message'])
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else:
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st.error(t['error_message'])
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else:
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st.warning(t['warning_message'])
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elif 'semantic_result' in st.session_state:
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# Si hay un resultado guardado, mostrarlo
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display_semantic_results(st.session_state.semantic_result, lang_code, t)
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def display_semantic_results(result, lang_code, t):
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# Mostrar conceptos clave
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with st.expander(t['key_concepts'], expanded=True):
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with st.expander(t['conceptual_relations'], expanded=True):
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st.pyplot(analysis_result['relations_graph'])
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##################################################################################################
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def display_discourse_analysis_interface(nlp_models, lang_code):
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translations = {
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