Update modules/semantic/semantic_interface.py

modules/semantic/semantic_interface.py

@@ -31,7 +31,7 @@ from ..database.semantic_export import export_user_interactions
 
 def display_semantic_interface(lang_code, nlp_models, semantic_t):
     """
-    Interfaz para el análisis semántico con controles fijos y manejo de estado mejorado
+    Interfaz para el análisis semántico con controles alineados horizontalmente
     """
     try:
         # Inicializar estados
@@ -42,26 +42,22 @@ 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 con bordes
+        # Contenedor principal para la fila de controles
         with st.container():
-            st.markdown("### Semantic Analysis Controls")
-            st.markdown("---")
+            # Crear una fila con cuatro columnas de igual ancho
+            col1, col2, col3, col4 = st.columns([3, 1, 1, 1])
 
-            # Sección de carga de archivo
-            col_file, _ = st.columns([6, 4])
-            with col_file:
+            # Columna 1: Carga de archivo
+            with col1:
                 uploaded_file = st.file_uploader(
-                    semantic_t.get('file_uploader', 'Upload a text file for analysis'),
+                    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)
                 )
 
-            # Contenedor fijo para botones
-            st.markdown("---")
-            col1, col2, col3, col4 = st.columns([2, 2, 2, 6])
-            
-            with col1:
+            # Columna 2: Botón de análisis
+            with col2:
                 analyze_button = st.button(
                     semantic_t.get('analyze_button', 'Analyze Text'),
                     disabled=not st.session_state.semantic_file_content,
@@ -69,7 +65,8 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
                     key="analyze_semantic"
                 )
 
-            with col2:
+            # Columna 3: Botón de exportación
+            with col3:
                 export_button = st.button(
                     semantic_t.get('export_button', 'Export Analysis'),
                     disabled=not st.session_state.semantic_analysis_done,
@@ -77,55 +74,46 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
                     key="export_semantic"
                 )
 
-            with col3:
-                clear_button = st.button(
-                    semantic_t.get('clear_button', 'Clear Analysis'),
+            # Columna 4: Botón de nuevo análisis
+            with col4:
+                new_analysis_button = st.button(
+                    semantic_t.get('new_analysis_button', 'New Analysis'),
                     disabled=not st.session_state.semantic_analysis_done,
                     use_container_width=True,
-                    key="clear_semantic"
+                    key="new_semantic"
                 )
 
-            st.markdown("---")
-
-            # Procesar análisis
-            if analyze_button and st.session_state.semantic_file_content:
-                try:
-                    with st.spinner(semantic_t.get('processing', 'Processing...')):
-                        analysis_result = process_semantic_input(
-                            st.session_state.semantic_file_content,
-                            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(
-                                st.session_state.username,
-                                st.session_state.semantic_file_content,
-                                analysis_result['analysis']
-                            ):
-                                st.success(semantic_t.get('success_message', 'Analysis saved successfully'))
-                                # Mostrar resultados
-                                display_semantic_results(
-                                    analysis_result,
-                                    lang_code,
-                                    semantic_t
-                                )
-                            else:
-                                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 an��lisis semántico: {str(e)}")
-                    st.error(semantic_t.get('error_processing', f'Error processing text: {str(e)}'))
-
-            # Manejo de exportación
-            if export_button and st.session_state.semantic_analysis_done:
+        # Separador sutil
+        st.markdown("<hr style='margin: 1em 0; padding: 0; opacity: 0.3'>", unsafe_allow_html=True)
+
+        # Procesar análisis
+        if analyze_button and st.session_state.semantic_file_content:
+            try:
+                with st.spinner(semantic_t.get('processing', 'Processing...')):
+                    doc = nlp_models[lang_code](st.session_state.semantic_file_content)
+                    
+                    # Usar spacy-streamlit para las visualizaciones
+                    st.markdown("### Semantic Analysis Results")
+                    
+                    # Visualizar entidades nombradas
+                    spacy_streamlit.visualize_ner(
+                        doc,
+                        labels=nlp_models[lang_code].get_pipe("ner").labels
+                    )
+                    
+                    # Visualizar dependencias sintácticas
+                    spacy_streamlit.visualize_parser(doc)
+                    
+                    st.session_state.semantic_analysis_done = True
+                    st.session_state.semantic_result = {'doc': doc}
+                    
+            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)}'))
+
+        # Manejo de exportación
+        if export_button and st.session_state.semantic_analysis_done:
+            try:
                 pdf_buffer = export_user_interactions(st.session_state.username, 'semantic')
                 st.download_button(
                     label=semantic_t.get('download_pdf', 'Download PDF'),
@@ -134,41 +122,25 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
                     mime="application/pdf",
                     key=f"semantic_download_{st.session_state.semantic_analysis_counter}"
                 )
+            except Exception as e:
+                st.error(f"Error exporting analysis: {str(e)}")
 
-            # Manejo de limpieza
-            if clear_button:
-                st.session_state.semantic_file_content = None
-                st.session_state.semantic_analysis_done = False
-                st.session_state.semantic_result = None
-                st.rerun()
-
-            # Mostrar resultados previos 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:
-                st.info(semantic_t.get('initial_message', 'Upload a file to begin analysis'))
+        # Manejo de nuevo análisis
+        if new_analysis_button:
+            st.session_state.semantic_file_content = None
+            st.session_state.semantic_analysis_done = False
+            st.session_state.semantic_result = None
+            st.session_state.semantic_analysis_counter += 1
+            st.rerun()
+
+        # Mostrar mensaje inicial si no hay archivo
+        if not st.session_state.semantic_file_content and not st.session_state.semantic_analysis_done:
+            st.info(semantic_t.get('initial_message', 'Upload a TXT file to begin analysis'))
 
     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 handle_file_upload(uploaded_file):
-    """Maneja la carga de archivos y mantiene el estado"""
-    if uploaded_file is not None:
-        try:
-            content = uploaded_file.getvalue().decode('utf-8')
-            st.session_state.semantic_file_content = content
-            st.session_state.page = 'semantic'  # Mantener en la página semántica
-        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
-    else:
-        st.session_state.semantic_file_content = None
 
 # [Resto del código igual...] ###############################################################################################################