Spaces:
Sleeping
Sleeping
Update modules/studentact/current_situation_interface.py
Browse files
modules/studentact/current_situation_interface.py
CHANGED
|
@@ -25,6 +25,16 @@ def display_current_situation_interface(lang_code, nlp_models, t):
|
|
| 25 |
"""
|
| 26 |
Interfaz simplificada para el análisis inicial, enfocada en recomendaciones directas.
|
| 27 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 28 |
st.markdown("## Análisis Inicial de Escritura")
|
| 29 |
|
| 30 |
# Container principal con dos columnas
|
|
@@ -33,51 +43,56 @@ def display_current_situation_interface(lang_code, nlp_models, t):
|
|
| 33 |
|
| 34 |
with input_col:
|
| 35 |
st.markdown("### Ingresa tu texto")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 36 |
text_input = st.text_area(
|
| 37 |
t.get('input_prompt', "Escribe o pega tu texto aquí:"),
|
| 38 |
height=400,
|
| 39 |
-
key=
|
|
|
|
|
|
|
| 40 |
help="Este texto será analizado para darte recomendaciones personalizadas"
|
| 41 |
)
|
| 42 |
|
|
|
|
| 43 |
if st.button(
|
| 44 |
t.get('analyze_button', "Analizar mi escritura"),
|
| 45 |
type="primary",
|
| 46 |
-
disabled=not text_input.strip(),
|
| 47 |
use_container_width=True,
|
| 48 |
-
key=f"analyze_button_{st.session_state.get('analysis_count', 0)}" # Key dinámica
|
| 49 |
):
|
| 50 |
try:
|
| 51 |
with st.spinner(t.get('processing', "Analizando...")):
|
| 52 |
-
# Incrementar contador de análisis
|
| 53 |
-
if 'analysis_count' not in st.session_state:
|
| 54 |
-
st.session_state.analysis_count = 0
|
| 55 |
-
st.session_state.analysis_count += 1
|
| 56 |
-
|
| 57 |
# Procesar texto y obtener métricas
|
| 58 |
doc = nlp_models[lang_code](text_input)
|
| 59 |
metrics = analyze_text_dimensions(doc)
|
| 60 |
|
| 61 |
-
#
|
| 62 |
st.session_state.current_doc = doc
|
| 63 |
st.session_state.current_metrics = metrics
|
|
|
|
|
|
|
|
|
|
|
|
|
| 64 |
|
| 65 |
-
# Forzar rerun para actualizar visualización
|
| 66 |
-
st.rerun()
|
| 67 |
-
|
| 68 |
except Exception as e:
|
| 69 |
logger.error(f"Error en análisis: {str(e)}")
|
| 70 |
st.error(t.get('analysis_error', "Error al analizar el texto"))
|
| 71 |
|
| 72 |
-
# Mostrar resultados
|
| 73 |
with results_col:
|
| 74 |
-
if
|
| 75 |
display_recommendations(st.session_state.current_metrics, t)
|
| 76 |
|
| 77 |
# Opción para ver detalles
|
| 78 |
with st.expander("🔍 Ver análisis detallado", expanded=False):
|
| 79 |
display_current_situation_visual(
|
| 80 |
-
st.session_state.current_doc,
|
| 81 |
st.session_state.current_metrics
|
| 82 |
)
|
| 83 |
|
|
|
|
| 25 |
"""
|
| 26 |
Interfaz simplificada para el análisis inicial, enfocada en recomendaciones directas.
|
| 27 |
"""
|
| 28 |
+
# Inicializar estados si no existen
|
| 29 |
+
if 'text_input' not in st.session_state:
|
| 30 |
+
st.session_state.text_input = ""
|
| 31 |
+
if 'show_results' not in st.session_state:
|
| 32 |
+
st.session_state.show_results = False
|
| 33 |
+
if 'current_doc' not in st.session_state:
|
| 34 |
+
st.session_state.current_doc = None
|
| 35 |
+
if 'current_metrics' not in st.session_state:
|
| 36 |
+
st.session_state.current_metrics = None
|
| 37 |
+
|
| 38 |
st.markdown("## Análisis Inicial de Escritura")
|
| 39 |
|
| 40 |
# Container principal con dos columnas
|
|
|
|
| 43 |
|
| 44 |
with input_col:
|
| 45 |
st.markdown("### Ingresa tu texto")
|
| 46 |
+
|
| 47 |
+
# Función para manejar cambios en el texto
|
| 48 |
+
def on_text_change():
|
| 49 |
+
st.session_state.text_input = st.session_state.text_area
|
| 50 |
+
st.session_state.show_results = False # Resetear resultados cuando el texto cambia
|
| 51 |
+
|
| 52 |
+
# Text area con manejo de estado
|
| 53 |
text_input = st.text_area(
|
| 54 |
t.get('input_prompt', "Escribe o pega tu texto aquí:"),
|
| 55 |
height=400,
|
| 56 |
+
key="text_area",
|
| 57 |
+
value=st.session_state.text_input,
|
| 58 |
+
on_change=on_text_change,
|
| 59 |
help="Este texto será analizado para darte recomendaciones personalizadas"
|
| 60 |
)
|
| 61 |
|
| 62 |
+
# Botón de análisis
|
| 63 |
if st.button(
|
| 64 |
t.get('analyze_button', "Analizar mi escritura"),
|
| 65 |
type="primary",
|
| 66 |
+
disabled=not text_input.strip(),
|
| 67 |
use_container_width=True,
|
|
|
|
| 68 |
):
|
| 69 |
try:
|
| 70 |
with st.spinner(t.get('processing', "Analizando...")):
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 71 |
# Procesar texto y obtener métricas
|
| 72 |
doc = nlp_models[lang_code](text_input)
|
| 73 |
metrics = analyze_text_dimensions(doc)
|
| 74 |
|
| 75 |
+
# Actualizar estado con nuevos resultados
|
| 76 |
st.session_state.current_doc = doc
|
| 77 |
st.session_state.current_metrics = metrics
|
| 78 |
+
st.session_state.show_results = True
|
| 79 |
+
|
| 80 |
+
# Mantener el texto en el estado
|
| 81 |
+
st.session_state.text_input = text_input
|
| 82 |
|
|
|
|
|
|
|
|
|
|
| 83 |
except Exception as e:
|
| 84 |
logger.error(f"Error en análisis: {str(e)}")
|
| 85 |
st.error(t.get('analysis_error', "Error al analizar el texto"))
|
| 86 |
|
| 87 |
+
# Mostrar resultados en la columna derecha
|
| 88 |
with results_col:
|
| 89 |
+
if st.session_state.show_results and st.session_state.current_metrics is not None:
|
| 90 |
display_recommendations(st.session_state.current_metrics, t)
|
| 91 |
|
| 92 |
# Opción para ver detalles
|
| 93 |
with st.expander("🔍 Ver análisis detallado", expanded=False):
|
| 94 |
display_current_situation_visual(
|
| 95 |
+
st.session_state.current_doc,
|
| 96 |
st.session_state.current_metrics
|
| 97 |
)
|
| 98 |
|