Update modules/semantic/semantic_interface.py
Browse files
modules/semantic/semantic_interface.py
CHANGED
@@ -28,24 +28,22 @@ from ..database.semantic_export import export_user_interactions
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def display_semantic_interface(lang_code, nlp_models, semantic_t):
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"""
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Interfaz para el análisis semántico
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Args:
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lang_code: Código del idioma actual
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nlp_models: Modelos de spaCy cargados
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semantic_t: Diccionario de traducciones
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"""
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# Mantener la página actual
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st.session_state.page = 'semantic'
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#
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st.markdown("""
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<style>
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.stButton button {
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width: 100%;
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}
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.upload-container {
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display: flex;
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align-items: center;
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}
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</style>
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""", unsafe_allow_html=True)
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@@ -54,96 +52,111 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
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with st.container():
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col_upload, col_analyze, col_export, col_new = st.columns([4,2,2,2])
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with col_upload:
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uploaded_file = st.file_uploader(
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semantic_t.get('file_uploader', 'Upload text file'),
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type=['txt'],
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key="semantic_file_uploader"
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)
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with col_analyze:
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analyze_button = st.button(
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semantic_t.get('semantic_analyze_button', 'Analyze
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use_container_width=True
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)
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with col_export:
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export_button = st.button(
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semantic_t.get('semantic_export_button', 'Export
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use_container_width=True
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)
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with col_new:
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new_button = st.button(
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semantic_t.get('semantic_new_button', 'New
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use_container_width=True
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)
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# Línea separadora
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st.markdown("---")
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#
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if uploaded_file is not None
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try:
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# Procesar el archivo
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text_content = uploaded_file.getvalue().decode('utf-8')
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with st.spinner(semantic_t.get('processing', 'Processing...')):
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# Realizar análisis
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analysis_result = perform_semantic_analysis(
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text_content,
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nlp_models[lang_code],
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lang_code
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)
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else:
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st.error(
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# Mostrar resultados
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display_semantic_results(analysis_result, lang_code, semantic_t)
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except Exception as e:
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st.error(f"Error: {str(e)}")
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#
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if export_button and
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try:
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pdf_buffer = export_user_interactions(st.session_state.username, 'semantic')
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st.download_button(
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label=semantic_t.get('download_pdf', 'Download PDF'),
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data=pdf_buffer,
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file_name="semantic_analysis.pdf",
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mime="application/pdf"
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)
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except Exception as e:
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st.error(f"Error exporting: {str(e)}")
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#
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if new_button:
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st.rerun()
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# Mostrar resultados
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if
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display_semantic_results(st.session_state.semantic_result, lang_code, semantic_t)
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elif
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st.info(semantic_t.get('initial_message', 'Upload a file to begin analysis'))
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def display_semantic_interface(lang_code, nlp_models, semantic_t):
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"""
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Interfaz para el análisis semántico
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"""
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# Mantener la página actual
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st.session_state.page = 'semantic'
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# Inicializar estados si no existen
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if 'semantic_has_file' not in st.session_state:
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st.session_state.semantic_has_file = False
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if 'semantic_result' not in st.session_state:
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st.session_state.semantic_result = None
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# Estilos para los botones
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st.markdown("""
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<style>
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.stButton button {
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width: 100%;
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height: 38px;
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}
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</style>
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""", unsafe_allow_html=True)
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with st.container():
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col_upload, col_analyze, col_export, col_new = st.columns([4,2,2,2])
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# Columna para carga de archivo
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with col_upload:
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uploaded_file = st.file_uploader(
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semantic_t.get('file_uploader', 'Upload text file'),
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type=['txt'],
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key="semantic_file_uploader"
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)
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# Actualizar estado cuando se carga un archivo
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if uploaded_file is not None:
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st.session_state.semantic_has_file = True
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if 'file_content' not in st.session_state or st.session_state.file_content != uploaded_file:
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st.session_state.file_content = uploaded_file
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st.session_state.semantic_result = None # Resetear resultado si el archivo cambia
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else:
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st.session_state.semantic_has_file = False
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# Columna para botón de análisis
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with col_analyze:
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analyze_disabled = not st.session_state.semantic_has_file
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analyze_button = st.button(
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semantic_t.get('semantic_analyze_button', 'Analyze'),
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disabled=analyze_disabled,
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key="semantic_analysis_button",
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use_container_width=True
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)
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# Columna para botón de exportación
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with col_export:
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export_disabled = st.session_state.semantic_result is None
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export_button = st.button(
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semantic_t.get('semantic_export_button', 'Export'),
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disabled=export_disabled,
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key="semantic_export_button",
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use_container_width=True
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)
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# Columna para botón de nuevo análisis
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with col_new:
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new_disabled = not st.session_state.semantic_has_file
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new_button = st.button(
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semantic_t.get('semantic_new_button', 'New'),
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disabled=new_disabled,
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key="semantic_new_button",
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use_container_width=True
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)
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st.markdown("---")
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# Procesar análisis
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if analyze_button and uploaded_file is not None:
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try:
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text_content = uploaded_file.getvalue().decode('utf-8')
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with st.spinner(semantic_t.get('processing', 'Processing...')):
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analysis_result = perform_semantic_analysis(
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text_content,
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nlp_models[lang_code],
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lang_code
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)
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if analysis_result['success']:
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st.session_state.semantic_result = analysis_result
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# Guardar en base de datos
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if store_student_semantic_result(
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st.session_state.username,
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text_content,
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analysis_result
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):
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st.success(semantic_t.get('success_message', 'Analysis saved successfully'))
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# Mostrar resultados
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display_semantic_results(analysis_result, lang_code, semantic_t)
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else:
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st.error(semantic_t.get('error_message', 'Error saving analysis'))
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else:
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st.error(analysis_result['message'])
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except Exception as e:
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st.error(f"Error: {str(e)}")
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# Manejar exportación
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if export_button and st.session_state.semantic_result is not None:
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try:
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pdf_buffer = export_user_interactions(st.session_state.username, 'semantic')
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st.download_button(
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label=semantic_t.get('download_pdf', 'Download PDF'),
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data=pdf_buffer,
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file_name="semantic_analysis.pdf",
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mime="application/pdf",
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key="semantic_download_button"
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)
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except Exception as e:
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st.error(f"Error exporting: {str(e)}")
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# Manejar nuevo análisis
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if new_button:
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st.session_state.semantic_result = None
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st.session_state.semantic_has_file = False
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st.session_state.file_content = None
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st.rerun()
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# Mostrar resultados o mensaje inicial
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if st.session_state.semantic_result is not None:
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display_semantic_results(st.session_state.semantic_result, lang_code, semantic_t)
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elif not st.session_state.semantic_has_file:
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st.info(semantic_t.get('initial_message', 'Upload a file to begin analysis'))
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