Update modules/semantic/semantic_interface.py

modules/semantic/semantic_interface.py

@@ -38,26 +38,55 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
         semantic_t: Diccionario de traducciones semánticas
     """
     try:
-        # Inicializar el estado si no existe
+        # Inicializar estados si no existen
         if 'semantic_analysis_counter' not in st.session_state:
             st.session_state.semantic_analysis_counter = 0
+        if 'semantic_current_file' not in st.session_state:
+            st.session_state.semantic_current_file = None
+        if 'semantic_page' not in st.session_state:
+            st.session_state.semantic_page = 'semantic'
 
-        # 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}"
-        )
-
-        # 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
+        # Contenedor fijo para los controles
+        with st.container():
+            st.markdown("### Controls")
+            # 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}",
+                on_change=lambda: setattr(st.session_state, 'semantic_current_file', uploaded_file)
             )
 
+            # Botón de análisis deshabilitado si no hay archivo
+            col1, col2, col3 = st.columns([1,2,1])
+            with col1:
+                analyze_button = st.button(
+                    semantic_t.get('analyze_button', 'Analyze text'),
+                    key=f"semantic_analyze_button_{st.session_state.semantic_analysis_counter}",
+                    disabled=not uploaded_file,
+                    use_container_width=True
+                )
+
+                # Botón de exportación solo visible si hay resultados
+                if 'semantic_result' in st.session_state and st.session_state.semantic_result is not None:
+                    export_button = st.button(
+                        semantic_t.get('export_button', 'Export Analysis'),
+                        key=f"semantic_export_{st.session_state.semantic_analysis_counter}",
+                        use_container_width=True
+                    )
+                    if export_button:
+                        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",
+                            key=f"semantic_download_{st.session_state.semantic_analysis_counter}"
+                        )
+
+        st.markdown("---")  # Separador
+
+        # Procesar el análisis cuando se presiona el botón
         if analyze_button and uploaded_file is not None:
             try:
                 with st.spinner(semantic_t.get('processing', 'Processing...')):
@@ -81,6 +110,8 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
                             analysis_result['analysis']
                         ):
                             st.success(semantic_t.get('success_message', 'Analysis saved successfully'))
+                            # Asegurar que nos mantenemos en la página semántica
+                            st.session_state.page = 'semantic'
                             # Mostrar resultados
                             display_semantic_results(
                                 analysis_result,
@@ -94,8 +125,6 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
             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)}'))
-        elif analyze_button:
-            st.warning(semantic_t.get('warning_message', 'Please upload a file first'))
         
         # Mostrar resultados previos
         elif 'semantic_result' in st.session_state and st.session_state.semantic_result is not None:
@@ -111,70 +140,4 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
         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):
-    """
-    Muestra los resultados del análisis semántico en tabs
-    """
-    if result is None or not result['success']:
-        st.warning(semantic_t.get('no_results', 'No results available'))
-        return
-
-    analysis = result['analysis']
-    
-    # Crear tabs para los resultados
-    tab1, tab2 = st.tabs([
-        semantic_t.get('concepts_tab', 'Key Concepts Analysis'),
-        semantic_t.get('entities_tab', 'Entities Analysis')
-    ])
-    
-    # Tab 1: Conceptos Clave
-    with tab1:
-        col1, col2 = st.columns(2)
-        
-        # Columna 1: Lista de conceptos
-        with col1:
-            st.subheader(semantic_t.get('key_concepts', 'Key Concepts'))
-            concept_text = "\n".join([
-                f"• {concept} ({frequency:.2f})" 
-                for concept, frequency in analysis['key_concepts']
-            ])
-            st.markdown(concept_text)
-        
-        # Columna 2: Gráfico de conceptos
-        with col2:
-            st.subheader(semantic_t.get('concept_graph', 'Concepts Graph'))
-            st.image(analysis['concept_graph'])
-    
-    # Tab 2: Entidades
-    with tab2:
-        col1, col2 = st.columns(2)
-        
-        # Columna 1: Lista de entidades
-        with col1:
-            st.subheader(semantic_t.get('identified_entities', 'Identified Entities'))
-            if 'entities' in analysis:
-                for entity_type, entities in analysis['entities'].items():
-                    st.markdown(f"**{entity_type}**")
-                    st.markdown("• " + "\n• ".join(entities))
-        
-        # Columna 2: Gráfico de entidades
-        with col2:
-            st.subheader(semantic_t.get('entity_graph', 'Entities Graph'))
-            st.image(analysis['entity_graph'])
-
-    # Botón de exportación al final
-    col1, col2, col3 = st.columns([2,1,2])
-    with col2:
-        if st.button(
-            semantic_t.get('export_button', 'Export Analysis'), 
-            key=f"semantic_export_{st.session_state.semantic_analysis_counter}",
-            use_container_width=True
-        ):
-            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",
-                key=f"semantic_download_{st.session_state.semantic_analysis_counter}"
-            )
+# [Resto del código igual...]