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Update modules/discourse/discourse_interface.py
Browse files
modules/discourse/discourse_interface.py
CHANGED
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@@ -125,6 +125,9 @@ def display_discourse_interface(lang_code, nlp_models, discourse_t):
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logger.error(f"Error general en interfaz del discurso: {str(e)}")
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st.error(discourse_t.get('general_error', 'Se produjo un error. Por favor, intente de nuevo.'))
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def display_discourse_results(result, lang_code, discourse_t):
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"""
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Muestra los resultados del análisis del discurso
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@@ -133,6 +136,49 @@ def display_discourse_results(result, lang_code, discourse_t):
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st.warning(discourse_t.get('no_results', 'No hay resultados disponibles'))
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return
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col1, col2 = st.columns(2)
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# Documento 1
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@@ -140,12 +186,43 @@ def display_discourse_results(result, lang_code, discourse_t):
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with st.expander(discourse_t.get('doc1_title', 'Documento 1'), expanded=True):
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st.subheader(discourse_t.get('key_concepts', 'Conceptos Clave'))
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if 'key_concepts1' in result:
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if 'graph1' in result:
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else:
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st.warning(discourse_t.get('graph_not_available', 'Gráfico no disponible'))
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else:
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@@ -156,12 +233,43 @@ def display_discourse_results(result, lang_code, discourse_t):
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with st.expander(discourse_t.get('doc2_title', 'Documento 2'), expanded=True):
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st.subheader(discourse_t.get('key_concepts', 'Conceptos Clave'))
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if 'key_concepts2' in result:
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if 'graph2' in result:
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else:
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st.warning(discourse_t.get('graph_not_available', 'Gráfico no disponible'))
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else:
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logger.error(f"Error general en interfaz del discurso: {str(e)}")
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st.error(discourse_t.get('general_error', 'Se produjo un error. Por favor, intente de nuevo.'))
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+
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#####################################################################################################################
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def display_discourse_results(result, lang_code, discourse_t):
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"""
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Muestra los resultados del análisis del discurso
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st.warning(discourse_t.get('no_results', 'No hay resultados disponibles'))
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return
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# Estilo CSS
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st.markdown("""
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<style>
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.concepts-container {
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display: flex;
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flex-wrap: nowrap;
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gap: 8px;
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padding: 12px;
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background-color: #f8f9fa;
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border-radius: 8px;
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overflow-x: auto;
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margin-bottom: 15px;
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white-space: nowrap;
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}
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.concept-item {
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background-color: white;
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border-radius: 4px;
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padding: 6px 10px;
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display: inline-flex;
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align-items: center;
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gap: 4px;
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box-shadow: 0 1px 2px rgba(0,0,0,0.1);
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flex-shrink: 0;
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}
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.concept-name {
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font-weight: 500;
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color: #1f2937;
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font-size: 0.85em;
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}
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.concept-freq {
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color: #6b7280;
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font-size: 0.75em;
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}
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.graph-container {
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background-color: white;
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padding: 15px;
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border-radius: 8px;
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box-shadow: 0 2px 4px rgba(0,0,0,0.1);
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margin-top: 10px;
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}
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</style>
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""", unsafe_allow_html=True)
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col1, col2 = st.columns(2)
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# Documento 1
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with st.expander(discourse_t.get('doc1_title', 'Documento 1'), expanded=True):
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st.subheader(discourse_t.get('key_concepts', 'Conceptos Clave'))
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if 'key_concepts1' in result:
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concepts_html = f"""
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<div class="concepts-container">
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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 result['key_concepts1']
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])}
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</div>
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"""
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st.markdown(concepts_html, unsafe_allow_html=True)
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if 'graph1' in result:
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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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st.pyplot(result['graph1'])
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# Botones y controles
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button_col1, spacer_col1 = st.columns([1,4])
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with button_col1:
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if 'graph1_bytes' in result:
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st.download_button(
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label="📥 " + discourse_t.get('download_graph', "Download"),
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data=result['graph1_bytes'],
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file_name="discourse_graph1.png",
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mime="image/png",
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use_container_width=True
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)
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with st.expander("📊 " + discourse_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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st.markdown('</div>', unsafe_allow_html=True)
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else:
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st.warning(discourse_t.get('graph_not_available', 'Gráfico no disponible'))
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else:
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with st.expander(discourse_t.get('doc2_title', 'Documento 2'), expanded=True):
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st.subheader(discourse_t.get('key_concepts', 'Conceptos Clave'))
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if 'key_concepts2' in result:
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concepts_html = f"""
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<div class="concepts-container">
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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 result['key_concepts2']
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])}
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</div>
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"""
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st.markdown(concepts_html, unsafe_allow_html=True)
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if 'graph2' in result:
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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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st.pyplot(result['graph2'])
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# Botones y controles
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button_col2, spacer_col2 = st.columns([1,4])
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with button_col2:
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if 'graph2_bytes' in result:
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st.download_button(
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label="📥 " + discourse_t.get('download_graph', "Download"),
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data=result['graph2_bytes'],
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file_name="discourse_graph2.png",
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mime="image/png",
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use_container_width=True
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)
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with st.expander("📊 " + discourse_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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st.markdown('</div>', unsafe_allow_html=True)
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else:
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st.warning(discourse_t.get('graph_not_available', 'Gráfico no disponible'))
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else:
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