Update modules/semantic/semantic_interface.py

modules/semantic/semantic_interface.py

@@ -25,32 +25,15 @@ 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 handle_file_upload(uploaded_file):
-    """
-    Maneja la carga de archivos y mantiene el estado
-    Args:
-        uploaded_file: Archivo subido a través del file_uploader
-    """
-    try:
-        if uploaded_file is not None:
-            content = uploaded_file.getvalue().decode('utf-8')
-            st.session_state.semantic_file_content = content
-            st.session_state.page = 'semantic'  # Mantener en la página semántica
-            logger.info(f"Archivo cargado exitosamente: {uploaded_file.name}")
-        else:
-            st.session_state.semantic_file_content = None
-            logger.info("No se ha cargado ningún archivo")
-    except Exception as e:
-        logger.error(f"Error al cargar archivo: {str(e)}")
-        st.error("Error al cargar el archivo. Asegúrese de que es un archivo de texto válido.")
-        st.session_state.semantic_file_content = None
-
 def display_semantic_interface(lang_code, nlp_models, semantic_t):
     """
     Interfaz para el análisis semántico con controles alineados horizontalmente
     """
+    # Mantener la página en semántico
+    st.session_state.page = 'semantic'
+
     try:
-        # Inicializar estados
+        # Inicializar estados si no existen
         if 'semantic_analysis_counter' not in st.session_state:
             st.session_state.semantic_analysis_counter = 0
         if 'semantic_file_content' not in st.session_state:
@@ -58,52 +41,72 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
         if 'semantic_analysis_done' not in st.session_state:
             st.session_state.semantic_analysis_done = False
 
-        # Contenedor principal para la fila de controles
+        # Estilos CSS para alinear los botones
+        st.markdown("""
+            <style>
+            .stButton > button {
+                width: 100%;
+                margin: 0;
+                height: 38px;
+                display: inline-flex;
+                align-items: center;
+                justify-content: center;
+            }
+            .upload-container {
+                margin-bottom: 0 !important;
+                padding-bottom: 0 !important;
+            }
+            </style>
+        """, unsafe_allow_html=True)
+
+        # Contenedor principal con layout fijo
         with st.container():
-            # Crear una fila con cuatro columnas de igual ancho
-            col1, col2, col3, col4 = st.columns([3, 1, 1, 1])
+            # Una sola fila para todos los controles
+            cols = st.columns([4, 2, 2, 2])
 
             # Columna 1: Carga de archivo
-            with col1:
+            with cols[0]:
                 uploaded_file = st.file_uploader(
                     semantic_t.get('file_uploader', 'Upload TXT file'),
                     type=['txt'],
-                    key=f"semantic_file_uploader_{st.session_state.semantic_analysis_counter}",
-                    on_change=lambda: handle_file_upload(uploaded_file)
+                    key=f"semantic_file_uploader_{st.session_state.semantic_analysis_counter}"
                 )
+                
+                # Actualizar el estado cuando se sube un archivo
+                if uploaded_file is not None:
+                    content = uploaded_file.getvalue().decode('utf-8')
+                    st.session_state.semantic_file_content = content
+                    st.session_state.page = 'semantic'
 
             # Columna 2: Botón de análisis
-            with col2:
+            with cols[1]:
                 analyze_button = st.button(
                     semantic_t.get('analyze_button', 'Analyze Text'),
-                    disabled=not st.session_state.semantic_file_content,
-                    use_container_width=True,
-                    key="analyze_semantic"
+                    disabled=(uploaded_file is None),
+                    key=f"analyze_semantic_{st.session_state.semantic_analysis_counter}"
                 )
 
             # Columna 3: Botón de exportación
-            with col3:
+            with cols[2]:
                 export_button = st.button(
-                    semantic_t.get('export_button', 'Export Analysis'),
+                    semantic_t.get('export_button', 'Export'),
                     disabled=not st.session_state.semantic_analysis_done,
-                    use_container_width=True,
-                    key="export_semantic"
+                    key=f"export_semantic_{st.session_state.semantic_analysis_counter}"
                 )
 
             # Columna 4: Botón de nuevo análisis
-            with col4:
+            with cols[3]:
                 new_analysis_button = st.button(
-                    semantic_t.get('new_analysis_button', 'New Analysis'),
+                    semantic_t.get('new_analysis', 'New'),
                     disabled=not st.session_state.semantic_analysis_done,
-                    use_container_width=True,
-                    key="new_semantic"
+                    key=f"new_semantic_{st.session_state.semantic_analysis_counter}"
                 )
 
-        # Separador sutil
-        st.markdown("<hr style='margin: 1em 0; padding: 0; opacity: 0.3'>", unsafe_allow_html=True)
+        # Separador
+        st.markdown("<hr style='margin: 1em 0; opacity: 0.3'>", unsafe_allow_html=True)
 
         # Procesar análisis
-        if analyze_button and st.session_state.semantic_file_content:
+        if analyze_button and uploaded_file is not None:
             try:
                 with st.spinner(semantic_t.get('processing', 'Processing...')):
                     analysis_result = process_semantic_input(
@@ -116,7 +119,6 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
                     if analysis_result['success']:
                         st.session_state.semantic_result = analysis_result
                         st.session_state.semantic_analysis_done = True
-                        st.session_state.semantic_analysis_counter += 1
                         
                         # Guardar en la base de datos
                         if store_student_semantic_result(
@@ -135,7 +137,7 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
                             st.error(semantic_t.get('error_message', 'Error saving analysis'))
                     else:
                         st.error(analysis_result['message'])
-                        
+
             except Exception as e:
                 logger.error(f"Error en análisis semántico: {str(e)}")
                 st.error(semantic_t.get('error_processing', f'Error processing text: {str(e)}'))
@@ -160,16 +162,16 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
             st.session_state.semantic_analysis_done = False
             st.session_state.semantic_result = None
             st.session_state.semantic_analysis_counter += 1
-            st.rerun()
+            st.experimental_rerun()
 
-        # Mostrar resultados previos o mensaje inicial
-        elif st.session_state.semantic_analysis_done and 'semantic_result' in st.session_state:
+        # Mostrar resultados o mensaje inicial
+        if st.session_state.semantic_analysis_done and 'semantic_result' in st.session_state:
             display_semantic_results(
                 st.session_state.semantic_result,
                 lang_code,
                 semantic_t
             )
-        elif not st.session_state.semantic_file_content:
+        elif not uploaded_file:
             st.info(semantic_t.get('initial_message', 'Upload a TXT file to begin analysis'))
 
     except Exception as e: