v3 / modules /semantic /semantic_interface.py
AIdeaText's picture
Update modules/semantic/semantic_interface.py
df3c320 verified
raw
history blame
6.15 kB
#modules/semantic/semantic_interface.py
# Importaciones necesarias
import streamlit as st
from streamlit_float import *
from streamlit_antd_components import *
from streamlit.components.v1 import html
import io
from io import BytesIO
import base64
import matplotlib.pyplot as plt
import pandas as pd
import re
import logging
# Configuración del logger
logger = logging.getLogger(__name__)
# Importaciones locales
from .semantic_process import (
process_semantic_input,
format_semantic_results
)
from ..utils.widget_utils import generate_unique_key
from ..database.semantic_mongo_db import store_student_semantic_result
from ..database.semantic_export import export_user_interactions
#modules/semantic/semantic_interface.py
# [Mantener las importaciones igual...]
def display_semantic_interface(lang_code, nlp_models, semantic_t):
"""
Interfaz para el análisis semántico
Args:
lang_code: Código del idioma actual
nlp_models: Modelos de spaCy cargados
semantic_t: Diccionario de traducciones semánticas
"""
try:
# Inicializar estados si no existen
if 'semantic_analysis_counter' not in st.session_state:
st.session_state.semantic_analysis_counter = 0
if 'semantic_current_file' not in st.session_state:
st.session_state.semantic_current_file = None
if 'semantic_page' not in st.session_state:
st.session_state.semantic_page = 'semantic'
# Contenedor fijo para los controles
with st.container():
st.markdown("### Controls")
# Opción para cargar archivo con key única
uploaded_file = st.file_uploader(
semantic_t.get('file_uploader', 'Upload a text file for analysis'),
type=['txt'],
key=f"semantic_file_uploader_{st.session_state.semantic_analysis_counter}",
on_change=lambda: setattr(st.session_state, 'semantic_current_file', uploaded_file)
)
# Botón de análisis deshabilitado si no hay archivo
col1, col2, col3 = st.columns([1,2,1])
with col1:
analyze_button = st.button(
semantic_t.get('analyze_button', 'Analyze text'),
key=f"semantic_analyze_button_{st.session_state.semantic_analysis_counter}",
disabled=not uploaded_file,
use_container_width=True
)
# Botón de exportación solo visible si hay resultados
if 'semantic_result' in st.session_state and st.session_state.semantic_result is not None:
export_button = st.button(
semantic_t.get('export_button', 'Export Analysis'),
key=f"semantic_export_{st.session_state.semantic_analysis_counter}",
use_container_width=True
)
if export_button:
pdf_buffer = export_user_interactions(st.session_state.username, 'semantic')
st.download_button(
label=semantic_t.get('download_pdf', 'Download PDF'),
data=pdf_buffer,
file_name="semantic_analysis.pdf",
mime="application/pdf",
key=f"semantic_download_{st.session_state.semantic_analysis_counter}"
)
st.markdown("---") # Separador
# Procesar el análisis cuando se presiona el botón
if analyze_button and uploaded_file is not None:
try:
with st.spinner(semantic_t.get('processing', 'Processing...')):
text_content = uploaded_file.getvalue().decode('utf-8')
analysis_result = process_semantic_input(
text_content,
lang_code,
nlp_models,
semantic_t
)
if analysis_result['success']:
st.session_state.semantic_result = analysis_result
st.session_state.semantic_analysis_counter += 1
# Guardar en la base de datos
if store_student_semantic_result(
st.session_state.username,
text_content,
analysis_result['analysis']
):
st.success(semantic_t.get('success_message', 'Analysis saved successfully'))
# Asegurar que nos mantenemos en la página semántica
st.session_state.page = 'semantic'
# Mostrar resultados
display_semantic_results(
analysis_result,
lang_code,
semantic_t
)
else:
st.error(semantic_t.get('error_message', 'Error saving analysis'))
else:
st.error(analysis_result['message'])
except Exception as e:
logger.error(f"Error en análisis semántico: {str(e)}")
st.error(semantic_t.get('error_processing', f'Error processing text: {str(e)}'))
# Mostrar resultados previos
elif 'semantic_result' in st.session_state and st.session_state.semantic_result is not None:
display_semantic_results(
st.session_state.semantic_result,
lang_code,
semantic_t
)
else:
st.info(semantic_t.get('initial_message', 'Upload a file to begin analysis'))
except Exception as e:
logger.error(f"Error general en interfaz semántica: {str(e)}")
st.error("Se produjo un error. Por favor, intente de nuevo.")
# [Resto del código igual...]