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Update modules/semantic/semantic_interface.py
Browse files
modules/semantic/semantic_interface.py
CHANGED
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@@ -140,4 +140,72 @@ def display_semantic_interface(lang_code, nlp_models, semantic_t):
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logger.error(f"Error general en interfaz semántica: {str(e)}")
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st.error("Se produjo un error. Por favor, intente de nuevo.")
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# [Resto del código igual...]
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logger.error(f"Error general en interfaz semántica: {str(e)}")
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st.error("Se produjo un error. Por favor, intente de nuevo.")
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# [Resto del código igual...]
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def display_semantic_results(result, lang_code, semantic_t):
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"""
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Muestra los resultados del análisis semántico en tabs
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"""
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if result is None or not result['success']:
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st.warning(semantic_t.get('no_results', 'No results available'))
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return
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analysis = result['analysis']
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# Crear tabs para los resultados
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tab1, tab2 = st.tabs([
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semantic_t.get('concepts_tab', 'Key Concepts Analysis'),
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semantic_t.get('entities_tab', 'Entities Analysis')
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])
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# Tab 1: Conceptos Clave
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with tab1:
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col1, col2 = st.columns(2)
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# Columna 1: Lista de conceptos
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with col1:
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st.subheader(semantic_t.get('key_concepts', 'Key Concepts'))
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concept_text = "\n".join([
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f"• {concept} ({frequency:.2f})"
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for concept, frequency in analysis['key_concepts']
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])
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st.markdown(concept_text)
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# Columna 2: Gráfico de conceptos
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with col2:
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st.subheader(semantic_t.get('concept_graph', 'Concepts Graph'))
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st.image(analysis['concept_graph'])
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# Tab 2: Entidades
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with tab2:
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col1, col2 = st.columns(2)
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# Columna 1: Lista de entidades
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with col1:
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st.subheader(semantic_t.get('identified_entities', 'Identified Entities'))
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if 'entities' in analysis:
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for entity_type, entities in analysis['entities'].items():
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st.markdown(f"**{entity_type}**")
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st.markdown("• " + "\n• ".join(entities))
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# Columna 2: Gráfico de entidades
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with col2:
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st.subheader(semantic_t.get('entity_graph', 'Entities Graph'))
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st.image(analysis['entity_graph'])
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# Botón de exportación al final
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col1, col2, col3 = st.columns([2,1,2])
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with col2:
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if st.button(
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semantic_t.get('export_button', 'Export Analysis'),
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key=f"semantic_export_{st.session_state.semantic_analysis_counter}",
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use_container_width=True
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):
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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=f"semantic_download_{st.session_state.semantic_analysis_counter}"
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)
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