Update modules/semantic/semantic_interface.py
Browse files
modules/semantic/semantic_interface.py
CHANGED
@@ -143,117 +143,133 @@ def display_semantic_results(semantic_result, lang_code, semantic_t):
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"""
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Muestra los resultados del análisis semántico de conceptos clave.
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"""
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# Verificar resultado
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if semantic_result is None or not semantic_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 = semantic_result['analysis']
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}
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)
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else:
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st.info(semantic_t.get('no_concepts', 'No key concepts found'))
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st.markdown(
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"""
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<style>
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.semantic-graph-container {
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background-color: white;
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border-radius: 10px;
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padding: 20px;
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box-shadow: 0 2px 4px rgba(0,0,0,0.1);
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margin: 10px 0;
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}
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.stImage {
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display: flex;
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justify-content: center;
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align-items: center;
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}
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.stImage > img {
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max-width: 100%;
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height: auto;
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object-fit: contain;
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}
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</style>
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""",
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unsafe_allow_html=True
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)
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graph_bytes
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f'<img src="data:image/png;base64,{graph_base64}" alt="Concept Graph" style="width:100%;"/>',
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unsafe_allow_html=True
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)
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# Agregar leyenda o descripción si es necesario
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st.caption(semantic_t.get(
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'graph_description',
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'El grosor de las líneas indica la fuerza de la relación. '
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'Los colores indican la centralidad del concepto.'
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))
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st.markdown('</div>', unsafe_allow_html=True)
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# Agregar botón de descarga
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st.download_button(
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label=semantic_t.get('download_graph', "Download Graph"),
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data=graph_bytes,
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file_name="semantic_graph.png",
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mime="image/png",
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)
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st.
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# Añadir información adicional sobre la interpretación del grafo
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with st.expander(semantic_t.get('graph_help', "How to interpret this graph")):
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st.markdown("""
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- Las flechas indican la dirección de la relación entre conceptos
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- Los colores más intensos indican conceptos más centrales en el texto
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- El tamaño de los nodos representa la frecuencia del concepto
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- El grosor de las líneas indica la fuerza de la conexión
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""")
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########################################################################################
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'''
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"""
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Muestra los resultados del análisis semántico de conceptos clave.
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"""
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if semantic_result is None or not semantic_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 = semantic_result['analysis']
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# Mostrar conceptos clave en formato horizontal
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st.subheader(semantic_t.get('key_concepts', 'Key Concepts'))
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if 'key_concepts' in analysis and analysis['key_concepts']:
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# Crear tabla de conceptos
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df = pd.DataFrame(
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analysis['key_concepts'],
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columns=[
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semantic_t.get('concept', 'Concept'),
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semantic_t.get('frequency', 'Frequency')
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]
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)
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# Convertir DataFrame a formato horizontal
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st.write(
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"""
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<style>
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.concept-table {
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display: flex;
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flex-wrap: wrap;
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gap: 10px;
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margin-bottom: 20px;
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}
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.concept-item {
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background-color: #f0f2f6;
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border-radius: 5px;
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padding: 8px 12px;
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display: flex;
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align-items: center;
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gap: 8px;
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}
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.concept-name {
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font-weight: bold;
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}
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.concept-freq {
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color: #666;
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font-size: 0.9em;
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}
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</style>
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<div class="concept-table">
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""" +
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''.join([
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f'<div class="concept-item"><span class="concept-name">{concept}</span>'
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f'<span class="concept-freq">({freq:.2f})</span></div>'
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for concept, freq in df.values
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]) +
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"</div>",
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unsafe_allow_html=True
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)
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else:
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st.info(semantic_t.get('no_concepts', 'No key concepts found'))
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# Gráfico de conceptos
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st.subheader(semantic_t.get('concept_graph', 'Concepts Graph'))
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if 'concept_graph' in analysis and analysis['concept_graph'] is not None:
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try:
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# Container para el grafo con estilos mejorados
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st.markdown(
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"""
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<style>
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.graph-container {
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background-color: white;
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border-radius: 10px;
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padding: 20px;
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box-shadow: 0 2px 4px rgba(0,0,0,0.1);
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margin: 10px 0;
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}
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.button-container {
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display: flex;
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gap: 10px;
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margin: 10px 0;
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}
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</style>
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""",
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unsafe_allow_html=True
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)
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with st.container():
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st.markdown('<div class="graph-container">', unsafe_allow_html=True)
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# Mostrar grafo
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graph_bytes = analysis['concept_graph']
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graph_base64 = base64.b64encode(graph_bytes).decode()
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st.markdown(
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f'<img src="data:image/png;base64,{graph_base64}" alt="Concept Graph" style="width:100%;"/>',
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unsafe_allow_html=True
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)
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# Leyenda del grafo
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st.caption(semantic_t.get(
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'graph_description',
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'Visualización de relaciones entre conceptos clave identificados en el texto.'
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))
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st.markdown('</div>', unsafe_allow_html=True)
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# Contenedor para botones
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col1, col2 = st.columns([1,4])
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with col1:
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st.download_button(
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label="📥 " + semantic_t.get('download_graph', "Download"),
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data=graph_bytes,
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file_name="semantic_graph.png",
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mime="image/png",
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use_container_width=True
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)
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# Expandible con la interpretación
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with st.expander("📊 " + semantic_t.get('graph_help', "Graph Interpretation")):
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st.markdown("""
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- 🔀 Las flechas indican la dirección de la relación entre conceptos
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- 🎨 Los colores más intensos indican conceptos más centrales en el texto
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- ⭕ El tamaño de los nodos representa la frecuencia del concepto
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- ↔️ El grosor de las líneas indica la fuerza de la conexión
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""")
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except Exception as e:
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logger.error(f"Error displaying graph: {str(e)}")
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st.error(semantic_t.get('graph_error', 'Error displaying the graph'))
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else:
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st.info(semantic_t.get('no_graph', 'No concept graph available'))
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########################################################################################
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'''
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