Update modules/semantic/semantic_interface.py

modules/semantic/semantic_interface.py

@@ -27,97 +27,119 @@ 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 alineados horizontalmente
+    Interfaz para el análisis semántico
+    Args:
+        lang_code: Código del idioma actual
+        nlp_models: Modelos de spaCy cargados
+        semantic_t: Diccionario de traducciones
     """
-    # Forzar la página a semántico
+    # Mantener la página actual
     st.session_state.page = 'semantic'
-    
-    # Inicializar estados básicos
-    if 'semantic_content' not in st.session_state:
-        st.session_state.semantic_content = None
-    if 'semantic_analyzed' not in st.session_state:
-        st.session_state.semantic_analyzed = False
 
-    # Contenedor principal
+    # Estilos para los botones y controles
+    st.markdown("""
+        <style>
+        .stButton button {
+            width: 100%;
+            padding: 0.5rem;
+        }
+        .upload-container {
+            display: flex;
+            align-items: center;
+        }
+        </style>
+    """, unsafe_allow_html=True)
+
+    # Contenedor principal para controles
     with st.container():
-        # Una sola fila para todos los controles
-        cols = st.columns([4, 2, 2, 2])
+        # Área de carga de archivo y botones
+        col_upload, col_analyze, col_export, col_new = st.columns([4,2,2,2])
         
-        # Columna 1: Carga de archivo
-        with cols[0]:
+        with col_upload:
             uploaded_file = st.file_uploader(
-                "Upload text file",  # Simplificamos el mensaje
-                type=['txt'],
-                key="semantic_file_upload"
+                semantic_t.get('file_uploader', 'Upload text file'), 
+                type=['txt']
+            )
+
+        with col_analyze:
+            analyze_button = st.button(
+                semantic_t.get('analyze_button', 'Analyze'),
+                disabled=(uploaded_file is None)
+            )
+
+        with col_export:
+            export_button = st.button(
+                semantic_t.get('export_button', 'Export'),
+                disabled=not ('semantic_result' in st.session_state)
+            )
+
+        with col_new:
+            new_button = st.button(
+                semantic_t.get('new_analysis', 'New'),
+                disabled=not ('semantic_result' in st.session_state)
             )
 
-        # Columna 2: Botón de análisis
-        with cols[1]:
-            can_analyze = uploaded_file is not None and not st.session_state.semantic_analyzed
-            if st.button('Analyze', 
-                        disabled=not can_analyze,
-                        key="semantic_analyze"):
-                if uploaded_file:
-                    text_content = uploaded_file.getvalue().decode('utf-8')
-                    # Realizar el análisis
-                    with st.spinner("Analyzing..."):
-                        analysis_result = process_semantic_input(
-                            text_content,
-                            lang_code,
-                            nlp_models,
-                            semantic_t
-                        )
-                        if analysis_result['success']:
-                            st.session_state.semantic_result = analysis_result
-                            st.session_state.semantic_analyzed = True
-                            st.success("Analysis completed!")
-                            
-                            # Mostrar resultados
-                            display_semantic_results(
-                                analysis_result,
-                                lang_code,
-                                semantic_t
-                            )
-
-        # Columna 3: Botón de exportación
-        with cols[2]:
-            if st.button('Export', 
-                        disabled=not st.session_state.semantic_analyzed,
-                        key="semantic_export"):
-                if st.session_state.semantic_analyzed:
-                    try:
-                        pdf_buffer = export_user_interactions(
-                            st.session_state.username, 
-                            'semantic'
-                        )
-                        st.download_button(
-                            "Download PDF",
-                            data=pdf_buffer,
-                            file_name="semantic_analysis.pdf",
-                            mime="application/pdf"
-                        )
-                    except Exception as e:
-                        st.error(f"Error exporting: {str(e)}")
-
-        # Columna 4: Botón de nuevo análisis
-        with cols[3]:
-            if st.button('New Analysis', 
-                        disabled=not st.session_state.semantic_analyzed,
-                        key="semantic_new"):
-                st.session_state.semantic_content = None
-                st.session_state.semantic_analyzed = False
-                st.session_state.semantic_result = None
-                st.rerun()
-
-    # Mostrar resultados si existen
-    if st.session_state.semantic_analyzed and 'semantic_result' in st.session_state:
-        display_semantic_results(
-            st.session_state.semantic_result,
-            lang_code,
-            semantic_t
-        )
-    elif not uploaded_file:
-        st.info("Please upload a text file to begin analysis")
+    # Línea separadora
+    st.markdown("---")
+
+    # Lógica de análisis
+    if uploaded_file is not None and analyze_button:
+        try:
+            # Procesar el archivo
+            text_content = uploaded_file.getvalue().decode('utf-8')
+            
+            with st.spinner(semantic_t.get('processing', 'Processing...')):
+                # Realizar análisis
+                analysis_result = perform_semantic_analysis(
+                    text_content,
+                    nlp_models[lang_code],
+                    lang_code
+                )
+                
+                # Guardar resultado
+                st.session_state.semantic_result = analysis_result
+                
+                # Guardar en base de datos
+                if store_student_semantic_result(
+                    st.session_state.username,
+                    text_content,
+                    analysis_result
+                ):
+                    st.success(semantic_t.get('success_message', 'Analysis saved successfully'))
+                else:
+                    st.error(semantic_t.get('error_message', 'Error saving analysis'))
+                
+                # Mostrar resultados
+                display_semantic_results(analysis_result, lang_code, semantic_t)
+                
+        except Exception as e:
+            st.error(f"Error: {str(e)}")
+
+    # Manejo de exportación
+    if export_button and 'semantic_result' in st.session_state:
+        try:
+            pdf_buffer = export_user_interactions(st.session_state.username, 'semantic')
+            st.download_button(
+                label=semantic_t.get('download_pdf', 'Download PDF'),
+                data=pdf_buffer,
+                file_name="semantic_analysis.pdf",
+                mime="application/pdf"
+            )
+        except Exception as e:
+            st.error(f"Error exporting: {str(e)}")
+
+    # Nuevo análisis
+    if new_button:
+        if 'semantic_result' in st.session_state:
+            del st.session_state.semantic_result
+        st.rerun()
+
+    # Mostrar resultados previos o mensaje inicial
+    if 'semantic_result' in st.session_state:
+        display_semantic_results(st.session_state.semantic_result, lang_code, semantic_t)
+    elif uploaded_file is None:
+        st.info(semantic_t.get('initial_message', 'Upload a file to begin analysis'))
+
 
 def display_semantic_results(result, lang_code, semantic_t):
     """