Update modules/semantic/semantic_process.py

modules/semantic/semantic_process.py

@@ -21,16 +21,12 @@ def process_semantic_input(text_content, lang_code, nlp_models, semantic_t):
     Procesa el texto ingresado para realizar el análisis semántico.
     """
     try:
-        logger.info(f"Iniciando análisis semántico para texto de {len(text_content)} caracteres")
+        logger.info(f"Iniciando análisis semántico para texto de {len(text)} caracteres")
         
         # Realizar el análisis semántico
         nlp = nlp_models[lang_code]
-        analysis_result = perform_semantic_analysis(
-            text_content,
-            nlp,
-            lang_code,
-            semantic_t
-        )
+        analysis_result = (text_content, nlp_models[lang_code], lang_code, semantic_t)
+        return format_semantic_results(result, lang_code, semantic_t)
         
         if not analysis_result['success']:
             return {
@@ -40,7 +36,7 @@ def process_semantic_input(text_content, lang_code, nlp_models, semantic_t):
             }
             
         logger.info("Análisis semántico completado. Guardando resultados...")
-       
+        
         # Intentar guardar en la base de datos
         try:
             store_result = store_student_semantic_result(
@@ -56,7 +52,7 @@ def process_semantic_input(text_content, lang_code, nlp_models, semantic_t):
         # Devolver el resultado incluso si falla el guardado
         return {
             'success': True,
-            'message': semantic_t.get('success_message', 'Analysis completed successfully'),  # Cambiado de t a semantic_t
+            'message': t.get('success_message', 'Analysis completed successfully'),
             'analysis': {
                 'key_concepts': analysis_result['key_concepts'],
                 'concept_graph': analysis_result['concept_graph']