Update modules/ui.py

modules/ui.py

@@ -303,22 +303,22 @@ def display_semantic_analysis_interface(nlp_models, lang_code):
             'title': "AIdeaText - Análisis semántico",
             'file_uploader': "Cargar archivo de texto",
             'analyze_button': "Analizar texto",
-            'entities_list': "Lista de entidades",
-            'network_diagram': "Diagrama de red semántica",
+            'context_analysis': "Análisis de Contexto",
+            'semantic_relations': "Análisis de Relaciones Semánticas",
         },
         'en': {
             'title': "AIdeaText - Semantic Analysis",
             'file_uploader': "Upload text file",
             'analyze_button': "Analyze text",
-            'entities_list': "Entities List",
-            'network_diagram': "Semantic Network Diagram",
+            'context_analysis': "Context Analysis",
+            'semantic_relations': "Semantic Relations Analysis",
         },
         'fr': {
             'title': "AIdeaText - Analyse sémantique",
             'file_uploader': "Télécharger le fichier texte",
             'analyze_button': "Analyser le texte",
-            'entities_list': "Liste des entités",
-            'network_diagram': "Diagramme de réseau sémantique",
+            'context_analysis': "Analyse de Contexte",
+            'semantic_relations': "Analyse des Relations Sémantiques",
         }
     }
 
@@ -332,41 +332,13 @@ def display_semantic_analysis_interface(nlp_models, lang_code):
         text_content = uploaded_file.getvalue().decode('utf-8')
 
         if st.button(t['analyze_button']):
-            col1, col2 = st.columns([1, 3])
-
-            with col1:
-                st.subheader(t['entities_list'])
-                entities = extract_entities(text_content, nlp_models[lang_code])
-                for entity_type, entity_list in entities.items():
-                    st.write(f"**{entity_type}:**")
-                    for entity in entity_list:
-                        st.write(f"- {entity}")
-
-            with col2:
-                st.subheader(t['network_diagram'])
-                fig = visualize_semantic_network(text_content, nlp_models[lang_code], lang_code)
-                st.pyplot(fig)
-
-def extract_entities(text, nlp):
-    doc = nlp(text)
-    entities = {
-        "Personas": [],
-        "Conceptos": [],
-        "Lugares": [],
-        "Fechas": []
-    }
+            context_graph, relations_graph = perform_semantic_analysis(text_content, nlp_models[lang_code], lang_code)
 
-    for ent in doc.ents:
-        if ent.label_ == "PER":
-            entities["Personas"].append(ent.text)
-        elif ent.label_ == "LOC" or ent.label_ == "GPE":
-            entities["Lugares"].append(ent.text)
-        elif ent.label_ == "DATE":
-            entities["Fechas"].append(ent.text)
-        else:
-            entities["Conceptos"].append(ent.text)
+            with st.expander(t['context_analysis'], expanded=True):
+                st.pyplot(context_graph)
 
-    return entities
+            with st.expander(t['semantic_relations'], expanded=True):
+                st.pyplot(relations_graph)
 
 ##################################################################################################
 def get_chatbot_response(input_text):