Update modules/studentact/current_situation_interface.py
Browse files
modules/studentact/current_situation_interface.py
CHANGED
@@ -81,16 +81,7 @@ def display_current_situation_interface(lang_code, nlp_models, t):
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"""
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# Agregar logs para depuración
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logger.info(f"Idioma: {lang_code}")
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logger.info(f"
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logger.info(f"Claves en CURRENT_SITUATION: {list(t.get('CURRENT_SITUATION', {}).keys())}")
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# Obtener traducciones de la situación actual
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current_situation_t = t.get('CURRENT_SITUATION', {})
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# Obtener traducciones para tipos de texto
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#text_types_translations = {}
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#if 'RECOMMENDATIONS' in t and lang_code in t['RECOMMENDATIONS']:
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# text_types_translations = t['RECOMMENDATIONS'][lang_code]['text_types']
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# Inicializar estados si no existen
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if 'text_input' not in st.session_state:
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@@ -105,21 +96,20 @@ def display_current_situation_interface(lang_code, nlp_models, t):
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st.session_state.current_metrics = None
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if 'current_recommendations' not in st.session_state:
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st.session_state.current_recommendations = None
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####################################################################################
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try:
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# Container principal con dos columnas
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with st.container():
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input_col, results_col = st.columns([1,2])
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with input_col:
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# Text area con manejo de estado
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text_input = st.text_area(
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t.get('input_prompt', "Escribe o pega tu texto aquí:"),
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height=400,
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key="
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value=st.session_state.text_input,
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help="Este texto será analizado para darte recomendaciones personalizadas"
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)
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# Función para manejar cambios de texto
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@@ -128,13 +118,13 @@ def display_current_situation_interface(lang_code, nlp_models, t):
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st.session_state.show_results = False
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if st.button(
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t.get('analyze_button', "Analizar mi escritura"),
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type="primary",
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disabled=not text_input.strip(),
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use_container_width=True,
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):
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try:
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with st.spinner(t.get('processing', "Analizando...")):
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doc = nlp_models[lang_code](text_input)
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metrics = analyze_text_dimensions(doc)
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@@ -154,37 +144,33 @@ def display_current_situation_interface(lang_code, nlp_models, t):
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except Exception as e:
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logger.error(f"Error en análisis: {str(e)}")
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st.error(t.get('analysis_error', "Error al analizar el texto"))
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#######################################################################################################
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# Mostrar resultados en la columna derecha
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with results_col:
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if st.session_state.show_results and st.session_state.current_metrics is not None:
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# Primero los radio buttons para tipo de texto
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st.markdown(f"### {
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# Preparar opciones de tipos de texto con nombres traducidos
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text_type_options = {}
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for text_type_key in TEXT_TYPES.keys():
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'general_communication': 'General Communication' if lang_code == 'en' else 'Загальна комунікація' if lang_code == 'uk' else 'Comunicación General'
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}
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text_type_options[text_type_key] = default_names.get(text_type_key, text_type_key)
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text_type = st.radio(
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label=
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options=list(TEXT_TYPES.keys()),
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format_func=lambda x: text_type_options.get(x, x),
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horizontal=True,
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key="text_type_radio",
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label_visibility="collapsed",
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help=
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)
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st.session_state.current_text_type = text_type
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@@ -201,7 +187,7 @@ def display_current_situation_interface(lang_code, nlp_models, t):
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metrics=st.session_state.current_metrics,
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text_type=text_type,
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lang_code=lang_code,
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t=current_situation_t
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)
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# Mostrar recomendaciones en el segundo subtab
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@@ -217,7 +203,7 @@ def display_current_situation_interface(lang_code, nlp_models, t):
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except Exception as e:
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logger.error(f"Error en interfaz principal: {str(e)}")
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st.error(
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#################################################################
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#################################################################
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"""
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# Agregar logs para depuración
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logger.info(f"Idioma: {lang_code}")
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logger.info(f"Claves en t: {list(t.keys())}")
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# Inicializar estados si no existen
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if 'text_input' not in st.session_state:
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st.session_state.current_metrics = None
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if 'current_recommendations' not in st.session_state:
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st.session_state.current_recommendations = None
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+
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try:
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# Container principal con dos columnas
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with st.container():
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input_col, results_col = st.columns([1,2])
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with input_col:
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# Text area con manejo de estado - usando t.get directamente
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text_input = st.text_area(
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t.get('input_prompt', "Escribe o pega tu texto aquí:"),
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height=400,
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key=f"text_area_{lang_code}", # Clave única por idioma
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value=st.session_state.text_input,
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help=t.get('help', "Este texto será analizado para darte recomendaciones personalizadas")
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)
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# Función para manejar cambios de texto
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st.session_state.show_results = False
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if st.button(
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t.get('analyze_button', "Analizar mi escritura"), # Usando t.get directamente
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type="primary",
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disabled=not text_input.strip(),
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use_container_width=True,
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):
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try:
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with st.spinner(t.get('processing', "Analizando...")): # Usando t.get directamente
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doc = nlp_models[lang_code](text_input)
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metrics = analyze_text_dimensions(doc)
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except Exception as e:
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logger.error(f"Error en análisis: {str(e)}")
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st.error(t.get('analysis_error', "Error al analizar el texto")) # Usando t.get directamente
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# Mostrar resultados en la columna derecha
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with results_col:
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if st.session_state.show_results and st.session_state.current_metrics is not None:
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# Primero los radio buttons para tipo de texto - usando t.get directamente
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st.markdown(f"### {t.get('text_type_header', 'Tipo de texto')}")
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# Preparar opciones de tipos de texto con nombres traducidos
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text_type_options = {}
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for text_type_key in TEXT_TYPES.keys():
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# Fallback a nombres genéricos si no hay traducción
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default_names = {
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'academic_article': 'Academic Article' if lang_code == 'en' else 'Артикул академічний' if lang_code == 'uk' else 'Artículo Académico',
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'student_essay': 'Student Essay' if lang_code == 'en' else 'Студентське есе' if lang_code == 'uk' else 'Trabajo Universitario',
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'general_communication': 'General Communication' if lang_code == 'en' else 'Загальна комунікація' if lang_code == 'uk' else 'Comunicación General'
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}
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text_type_options[text_type_key] = default_names.get(text_type_key, text_type_key)
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text_type = st.radio(
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label=t.get('text_type_header', "Tipo de texto"), # Usando t.get directamente
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options=list(TEXT_TYPES.keys()),
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format_func=lambda x: text_type_options.get(x, x),
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horizontal=True,
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key="text_type_radio",
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label_visibility="collapsed",
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help=t.get('text_type_help', "Selecciona el tipo de texto para ajustar los criterios de evaluación") # Usando t.get directamente
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)
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st.session_state.current_text_type = text_type
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metrics=st.session_state.current_metrics,
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text_type=text_type,
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lang_code=lang_code,
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t=t # Pasar t directamente, no current_situation_t
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)
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# Mostrar recomendaciones en el segundo subtab
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except Exception as e:
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logger.error(f"Error en interfaz principal: {str(e)}")
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st.error(t.get('error_interface', "Ocurrió un error al cargar la interfaz")) # Usando t.get directamente
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#################################################################
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#################################################################
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