Update modules/ui/ui.py

modules/ui/ui.py

@@ -763,7 +763,7 @@ def display_semantic_analysis_interface(nlp_models, lang_code):
             'text_input_placeholder': "El objetivo de esta aplicación es que mejore sus habilidades de redacción...",
             'file_uploader': "O cargue un archivo de texto",
             'analyze_button': "Analizar texto",
-            'semantic_relations': "Relaciones Semánticas Relevantes",
+            'conceptual_relations': "Relaciones Conceptuales",
             'identified_entities': "Entidades Identificadas",
             'key_concepts': "Conceptos Clave",
             'success_message': "Análisis semántico guardado correctamente.",
@@ -776,7 +776,7 @@ def display_semantic_analysis_interface(nlp_models, lang_code):
             'text_input_placeholder': "The goal of this application is to improve your writing skills...",
             'file_uploader': "Or upload a text file",
             'analyze_button': "Analyze text",
-            'semantic_relations': "Relevant Semantic Relations",
+            'conceptual_relations': "Conceptual Relations",
             'identified_entities': "Identified Entities",
             'key_concepts': "Key Concepts",
             'success_message': "Semantic analysis saved successfully.",
@@ -789,7 +789,7 @@ def display_semantic_analysis_interface(nlp_models, lang_code):
             'text_input_placeholder': "L'objectif de cette application est d'améliorer vos compétences en rédaction...",
             'file_uploader': "Ou téléchargez un fichier texte",
             'analyze_button': "Analyser le texte",
-            'semantic_relations': "Relations Sémantiques Pertinentes",
+            'conceptual_relations': "Relations Conceptuelles",
             'identified_entities': "Entités Identifiées",
             'key_concepts': "Concepts Clés",
             'success_message': "Analyse sémantique enregistrée avec succès.",
@@ -824,18 +824,18 @@ def display_semantic_analysis_interface(nlp_models, lang_code):
 
             # Mostrar conceptos clave
             with st.expander(t['key_concepts'], expanded=True):
-                key_concepts_text = " ".join([f"[[{concept}]]" for concept, _ in analysis_result['key_concepts']])
-                st.markdown(key_concepts_text)
+                for concept, score in analysis_result['key_concepts']:
+                    st.write(f"{concept}: {score:.2f}")
 
             # Mostrar entidades identificadas
             with st.expander(t['identified_entities'], expanded=True):
-                entities_text = ""
                 for entity in analysis_result['entities']:
-                    entities_text += f"[[{entity['text']} ({entity['label']}) - Contexto: {entity['context']}]] "
-                st.markdown(entities_text)
+                    st.write(f"{entity['text']} ({entity['label']}):")
+                    st.write(f"Contexto: {entity['context']}")
+                    st.write("---")
 
-            # Mostrar el gráfico de relaciones semánticas
-            with st.expander(t['semantic_relations'], expanded=True):
+            # Mostrar el gráfico de relaciones conceptuales
+            with st.expander(t['conceptual_relations'], expanded=True):
                 st.pyplot(analysis_result['relations_graph'])
 
             # Guardar el resultado del análisis