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# modules/semantic/semantic_process.py
import streamlit as st
import matplotlib.pyplot as plt
import io
import base64
import logging
from ..text_analysis.semantic_analysis import (
perform_semantic_analysis,
identify_key_concepts,
create_concept_graph,
visualize_concept_graph
)
from ..database.semantic_mongo_db import store_student_semantic_result
logger = logging.getLogger(__name__)
#############################################################################
def process_semantic_input(text_content, lang_code, nlp_models, semantic_t):
"""
Procesa el texto ingresado para realizar el análisis semántico.
"""
try:
logger.info(f"Iniciando análisis semántico para texto de {len(text_content)} caracteres")
# Realizar el análisis semántico
nlp = nlp_models[lang_code]
analysis_result = perform_semantic_analysis(
text_content,
nlp,
lang_code,
semantic_t
)
if not analysis_result['success']:
return {
'success': False,
'message': analysis_result['error'],
'analysis': None
}
logger.info("Análisis semántico completado. Guardando resultados...")
# Intentar guardar en la base de datos
try:
store_result = store_student_semantic_result(
st.session_state.username,
text_content, # Cambiado de text a text_content
analysis_result
)
if not store_result:
logger.warning("No se pudo guardar el análisis en la base de datos")
except Exception as db_error:
logger.error(f"Error al guardar en base de datos: {str(db_error)}")
# Devolver el resultado incluso si falla el guardado
return {
'success': True,
'message': semantic_t.get('success_message', 'Analysis completed successfully'), # Cambiado de t a semantic_t
'analysis': {
'key_concepts': analysis_result['key_concepts'],
'concept_graph': analysis_result['concept_graph']
}
}
except Exception as e:
logger.error(f"Error en process_semantic_input: {str(e)}")
return {
'success': False,
'message': str(e),
'analysis': None
}
########################################################################################
def format_semantic_results(analysis_result, t):
"""
Formatea los resultados del análisis para su visualización.
"""
try:
if not analysis_result['success']:
return {
'formatted_text': analysis_result['message'],
'visualizations': None
}
formatted_sections = []
analysis = analysis_result['analysis']
# Formatear conceptos clave
if 'key_concepts' in analysis:
concepts_section = [f"### {t.get('key_concepts', 'Key Concepts')}"]
concepts_section.extend([
f"- {concept}: {frequency:.2f}"
for concept, frequency in analysis['key_concepts']
])
formatted_sections.append('\n'.join(concepts_section))
return {
'formatted_text': '\n\n'.join(formatted_sections),
'visualizations': {
'concept_graph': analysis.get('concept_graph')
}
}
except Exception as e:
logger.error(f"Error en format_semantic_results: {str(e)}")
return {
'formatted_text': str(e),
'visualizations': None
}
__all__ = [
'process_semantic_input',
'format_semantic_results'
] |