Update modules/semantic/semantic_interface.py

modules/semantic/semantic_interface.py

@@ -25,49 +25,39 @@ from ..utils.widget_utils import generate_unique_key
 from ..database.semantic_mongo_db import store_student_semantic_result
 from ..database.semantic_export import export_user_interactions
 
-
 def display_semantic_interface(lang_code, nlp_models, semantic_t):
     """
     Interfaz para el análisis semántico
+    Args:
+        lang_code: Código del idioma actual
+        nlp_models: Modelos de spaCy cargados
+        semantic_t: Diccionario de traducciones semánticas
     """
     try:
-        # Mantener página en semántico
-        st.session_state.page = 'semantic'
+        # Inicializar el estado si no existe
+        if 'semantic_analysis_counter' not in st.session_state:
+            st.session_state.semantic_analysis_counter = 0
 
-        # Inicializar estados específicos para semántico
-        if 'semantic_state' not in st.session_state:
-            st.session_state.semantic_state = {
-                'counter': 0,
-                'has_file': False,
-                'file_content': None,
-                'result': None
-            }
+        # Opción para cargar archivo con key única
+        uploaded_file = st.file_uploader(
+            semantic_t.get('file_uploader', 'Upload a text file for analysis'),
+            type=['txt'],
+            key=f"semantic_file_uploader_{st.session_state.semantic_analysis_counter}"
+        )
 
-        # Contenedor principal
-        with st.container():
-            # Área de carga de archivo
-            uploaded_file = st.file_uploader(
-                semantic_t.get('file_uploader', 'Upload a text file for analysis'),
-                type=['txt'],
-                key=f"semantic_uploader_{st.session_state.semantic_state['counter']}"
+        # Botón de análisis con key única
+        col1, col2, col3 = st.columns([2,1,2])
+        with col2:
+            analyze_button = st.button(
+                semantic_t.get('analyze_button', 'Analyze text'),
+                key=f"semantic_analyze_button_{st.session_state.semantic_analysis_counter}",
+                use_container_width=True
             )
 
-            # Botones en una fila
-            col1, col2, col3 = st.columns([2,1,2])
-            with col2:
-                analyze_button = st.button(
-                    semantic_t.get('analyze_button', 'Analyze text'),
-                    key=f"semantic_analyze_{st.session_state.semantic_state['counter']}",
-                    use_container_width=True,
-                    disabled=not uploaded_file
-                )
-
-        # Procesamiento
         if analyze_button and uploaded_file is not None:
             try:
                 with st.spinner(semantic_t.get('processing', 'Processing...')):
                     text_content = uploaded_file.getvalue().decode('utf-8')
-                    st.session_state.semantic_state['file_content'] = text_content
                     
                     analysis_result = process_semantic_input(
                         text_content, 
@@ -77,15 +67,17 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
                     )
                     
                     if analysis_result['success']:
-                        st.session_state.semantic_state['result'] = analysis_result
-                        st.session_state.semantic_state['counter'] += 1
+                        st.session_state.semantic_result = analysis_result
+                        st.session_state.semantic_analysis_counter += 1
                         
+                        # Guardar en la base de datos
                         if store_student_semantic_result(
                             st.session_state.username,
                             text_content,
                             analysis_result['analysis']
                         ):
                             st.success(semantic_t.get('success_message', 'Analysis saved successfully'))
+                            # Mostrar resultados
                             display_semantic_results(
                                 analysis_result,
                                 lang_code,
@@ -102,9 +94,9 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
             st.warning(semantic_t.get('warning_message', 'Please upload a file first'))
         
         # Mostrar resultados previos
-        elif st.session_state.semantic_state['result'] is not None:
+        elif 'semantic_result' in st.session_state and st.session_state.semantic_result is not None:
             display_semantic_results(
-                st.session_state.semantic_state['result'],
+                st.session_state.semantic_result,
                 lang_code,
                 semantic_t
             )
@@ -114,7 +106,6 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
     except Exception as e:
         logger.error(f"Error general en interfaz semántica: {str(e)}")
         st.error("Se produjo un error. Por favor, intente de nuevo.")
-        
 
 def display_semantic_results(result, lang_code, semantic_t):
     """