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Update modules/studentact/student_activities_v2.py
Browse files
modules/studentact/student_activities_v2.py
CHANGED
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@@ -16,119 +16,169 @@ import base64
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import seaborn as sns
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import logging
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logger = logging.getLogger(__name__)
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###################################################################################
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def
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#
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ax.set_xlabel(t.get("analysis_type", "Tipo de análisis"))
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ax.set_ylabel(t.get("count", "Cantidad"))
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st.pyplot(fig)
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if not morphosyntax_entries:
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st.warning("No se encontraron análisis morfosintácticos.")
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for entry in morphosyntax_entries:
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st.subheader(f"{t.get('analysis_of', 'Análisis del')} {entry['timestamp']}")
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if 'arc_diagrams' in entry and entry['arc_diagrams']:
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try:
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st.write(entry['arc_diagrams'][0], unsafe_allow_html=True)
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except Exception as e:
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logger.error(f"Error al mostrar diagrama de arco: {str(e)}")
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st.error("Error al mostrar el diagrama de arco.")
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else:
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st.write(t.get("no_arc_diagram", "No se encontró diagrama de arco para este análisis."))
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if not semantic_entries:
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st.warning("No se encontraron análisis semánticos.")
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for entry in semantic_entries:
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st.subheader(f"{t.get('analysis_of', 'Análisis del')} {entry['timestamp']}")
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if 'key_concepts' in entry:
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st.write(t.get("key_concepts", "Conceptos clave:"))
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concepts_str = " | ".join([f"{concept} ({frequency:.2f})" for concept, frequency in entry['key_concepts']])
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st.markdown(f"<div style='background-color: #f0f2f6; padding: 10px; border-radius: 5px;'>{concepts_str}</div>", unsafe_allow_html=True)
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if 'graph' in entry:
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try:
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img_bytes = base64.b64decode(entry['graph'])
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st.image(img_bytes, caption=t.get("conceptual_relations_graph", "Gráfico de relaciones conceptuales"))
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except Exception as e:
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logger.error(f"Error al mostrar gráfico semántico: {str(e)}")
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st.error(t.get("graph_display_error", f"No se pudo mostrar el gráfico: {str(e)}"))
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st.write(f"{t.get('key_concepts', 'Conceptos clave')} {t.get('document', 'documento')} {i}:")
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concepts_str = " | ".join([f"{concept} ({frequency:.2f})" for concept, frequency in entry[f'key_concepts{i}']])
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st.markdown(f"<div style='background-color: #f0f2f6; padding: 10px; border-radius: 5px;'>{concepts_str}</div>", unsafe_allow_html=True)
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try:
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if 'combined_graph' in entry and entry['combined_graph']:
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img_bytes = base64.b64decode(entry['combined_graph'])
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st.image(img_bytes, caption=t.get("combined_graph", "Gráfico combinado"))
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elif 'graph1' in entry and 'graph2' in entry:
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col1, col2 = st.columns(2)
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with col1:
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if entry['graph1']:
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img_bytes1 = base64.b64decode(entry['graph1'])
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st.image(img_bytes1, caption=t.get("graph_doc1", "Gráfico documento 1"))
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with col2:
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if entry['graph2']:
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img_bytes2 = base64.b64decode(entry['graph2'])
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st.image(img_bytes2, caption=t.get("graph_doc2", "Gráfico documento 2"))
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except Exception as e:
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st.error(t.get("graph_display_error", f"No se pudieron mostrar los gráficos: {str(e)}"))
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for message in chat['messages']:
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st.
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else:
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st.write(f"{t.get('assistant', 'Asistente')}: {message['content']}")
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st.write("---")
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else:
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st.write(t.get("no_chat_history", "No se encontraron conversaciones con el ChatBot."))
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st.
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# Mostrar conteo de tipos de análisis
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analysis_types = [entry['analysis_type'] for entry in username['entries']]
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type_counts = {t: analysis_types.count(t) for t in set(analysis_types)}
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st.write("Conteo de tipos de análisis:")
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st.write(type_counts)
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import seaborn as sns
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import logging
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# Importaciones de la base de datos
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from ..database.morphosintax_mongo_db import get_student_morphosyntax_analysis
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from ..database.semantic_mongo_db import get_student_semantic_analysis
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from ..database.discourse_mongo_db import get_student_discourse_analysis
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from ..database.chat_mongo_db import get_chat_history
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logger = logging.getLogger(__name__)
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###################################################################################
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def display_student_activities(username: str, lang_code: str, t: dict):
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"""
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Muestra todas las actividades del estudiante
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Args:
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username: Nombre del estudiante
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lang_code: Código del idioma
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t: Diccionario de traducciones
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"""
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try:
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st.header(t.get('activities_title', 'Mis Actividades'))
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# Tabs para diferentes tipos de análisis
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tabs = st.tabs([
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t.get('morpho_activities', 'Análisis Morfosintáctico'),
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t.get('semantic_activities', 'Análisis Semántico'),
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t.get('discourse_activities', 'Análisis del Discurso'),
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t.get('chat_activities', 'Conversaciones con el Asistente')
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])
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# Tab de Análisis Morfosintáctico
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with tabs[0]:
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display_morphosyntax_activities(username, t)
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# Tab de Análisis Semántico
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with tabs[1]:
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display_semantic_activities(username, t)
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# Tab de Análisis del Discurso
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with tabs[2]:
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display_discourse_activities(username, t)
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# Tab de Conversaciones del Chat
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with tabs[3]:
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display_chat_activities(username, t)
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except Exception as e:
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logger.error(f"Error mostrando actividades: {str(e)}")
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st.error(t.get('error_loading_activities', 'Error al cargar las actividades'))
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def display_morphosyntax_activities(username: str, t: dict):
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"""Muestra actividades de análisis morfosintáctico"""
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try:
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analyses = get_student_morphosyntax_analysis(username)
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if not analyses:
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st.info(t.get('no_morpho_analyses', 'No hay análisis morfosintácticos registrados'))
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return
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for analysis in analyses:
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with st.expander(
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f"{t.get('analysis_date', 'Fecha')}: {analysis['timestamp']}",
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expanded=False
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):
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st.text(f"{t.get('analyzed_text', 'Texto analizado')}:")
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st.write(analysis['text'])
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if 'arc_diagrams' in analysis:
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st.subheader(t.get('syntactic_diagrams', 'Diagramas sintácticos'))
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for diagram in analysis['arc_diagrams']:
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st.write(diagram, unsafe_allow_html=True)
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except Exception as e:
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logger.error(f"Error mostrando análisis morfosintáctico: {str(e)}")
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st.error(t.get('error_morpho', 'Error al mostrar análisis morfosintáctico'))
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def display_semantic_activities(username: str, t: dict):
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"""Muestra actividades de análisis semántico"""
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try:
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analyses = get_student_semantic_analysis(username)
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if not analyses:
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st.info(t.get('no_semantic_analyses', 'No hay análisis semánticos registrados'))
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return
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for analysis in analyses:
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with st.expander(
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f"{t.get('analysis_date', 'Fecha')}: {analysis['timestamp']}",
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expanded=False
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):
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st.text(f"{t.get('analyzed_file', 'Archivo analizado')}:")
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st.write(analysis['text'])
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if 'key_concepts' in analysis:
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st.subheader(t.get('key_concepts', 'Conceptos clave'))
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df = pd.DataFrame(analysis['key_concepts'])
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st.dataframe(df)
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except Exception as e:
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logger.error(f"Error mostrando análisis semántico: {str(e)}")
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st.error(t.get('error_semantic', 'Error al mostrar análisis semántico'))
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def display_discourse_activities(username: str, t: dict):
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"""Muestra actividades de análisis del discurso"""
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try:
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analyses = get_student_discourse_analysis(username)
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if not analyses:
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st.info(t.get('no_discourse_analyses', 'No hay análisis del discurso registrados'))
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return
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for analysis in analyses:
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with st.expander(
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f"{t.get('analysis_date', 'Fecha')}: {analysis['timestamp']}",
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expanded=False
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):
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col1, col2 = st.columns(2)
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with col1:
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st.text(f"{t.get('text_1', 'Texto 1')}:")
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st.write(analysis['text1'])
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with col2:
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st.text(f"{t.get('text_2', 'Texto 2')}:")
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st.write(analysis['text2'])
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if 'key_concepts1' in analysis and 'key_concepts2' in analysis:
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display_discourse_comparison(analysis, t)
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except Exception as e:
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logger.error(f"Error mostrando análisis del discurso: {str(e)}")
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st.error(t.get('error_discourse', 'Error al mostrar análisis del discurso'))
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def display_chat_activities(username: str, t: dict):
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"""Muestra historial de conversaciones del chat"""
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try:
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chat_history = get_chat_history(username, limit=50)
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if not chat_history:
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st.info(t.get('no_chat_history', 'No hay conversaciones registradas'))
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return
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for chat in chat_history:
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with st.expander(
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f"{t.get('chat_date', 'Fecha de conversación')}: {chat['timestamp']}",
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expanded=False
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):
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for message in chat['messages']:
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with st.chat_message(message["role"]):
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st.markdown(message["content"])
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except Exception as e:
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logger.error(f"Error mostrando historial del chat: {str(e)}")
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st.error(t.get('error_chat', 'Error al mostrar historial del chat'))
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def display_discourse_comparison(analysis: dict, t: dict):
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"""Muestra la comparación de análisis del discurso"""
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st.subheader(t.get('comparison_results', 'Resultados de la comparación'))
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col1, col2 = st.columns(2)
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with col1:
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st.markdown(f"**{t.get('concepts_text_1', 'Conceptos Texto 1')}**")
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df1 = pd.DataFrame(analysis['key_concepts1'])
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st.dataframe(df1)
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with col2:
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st.markdown(f"**{t.get('concepts_text_2', 'Conceptos Texto 2')}**")
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df2 = pd.DataFrame(analysis['key_concepts2'])
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st.dataframe(df2)
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