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# modules/discourse/discourse/discourse_live_interface.py
import streamlit as st
from streamlit_float import *
from streamlit_antd_components import *
import pandas as pd
import logging
import io
import matplotlib.pyplot as plt
# Configuraci贸n del logger
logger = logging.getLogger(__name__)
# Importaciones locales
from .discourse_process import perform_discourse_analysis
from .discourse_interface import display_discourse_results # A帽adida esta importaci贸n
from ..utils.widget_utils import generate_unique_key
from ..database.discourse_mongo_db import store_student_discourse_result
from ..database.chat_mongo_db import store_chat_history, get_chat_history
def fig_to_bytes(fig):
"""Convierte una figura de matplotlib a bytes."""
try:
buf = io.BytesIO()
fig.savefig(buf, format='png', dpi=300, bbox_inches='tight')
buf.seek(0)
return buf.getvalue()
except Exception as e:
logger.error(f"Error en fig_to_bytes: {str(e)}")
return None
def display_discourse_live_interface(lang_code, nlp_models, discourse_t):
"""
Interfaz para el an谩lisis del discurso en vivo
"""
try:
# 1. Inicializar el estado de la sesi贸n
if 'discourse_live_state' not in st.session_state:
st.session_state.discourse_live_state = {
'analysis_count': 0,
'current_text1': '',
'current_text2': '',
'last_result': None,
'text_changed': False
}
# 2. Funci贸n para manejar cambios en los textos
def on_text1_change():
current_text = st.session_state.discourse_live_text1
st.session_state.discourse_live_state['current_text1'] = current_text
st.session_state.discourse_live_state['text_changed'] = True
def on_text2_change():
current_text = st.session_state.discourse_live_text2
st.session_state.discourse_live_state['current_text2'] = current_text
st.session_state.discourse_live_state['text_changed'] = True
# 3. Crear columnas con proporci贸n 1:3
input_col, result_col = st.columns([1, 3])
# Columna izquierda: Entrada de textos
with input_col:
st.subheader(discourse_t.get('enter_text', 'Ingrese sus textos'))
# Primer 谩rea de texto
st.markdown("**Texto 1 (Patr贸n)**")
text_input1 = st.text_area(
"Texto 1",
height=250,
key="discourse_live_text1",
value=st.session_state.discourse_live_state.get('current_text1', ''),
on_change=on_text1_change,
label_visibility="collapsed"
)
# Segundo 谩rea de texto
st.markdown("**Texto 2 (Comparaci贸n)**")
text_input2 = st.text_area(
"Texto 2",
height=250,
key="discourse_live_text2",
value=st.session_state.discourse_live_state.get('current_text2', ''),
on_change=on_text2_change,
label_visibility="collapsed"
)
# Bot贸n de an谩lisis
analyze_button = st.button(
discourse_t.get('analyze_button', 'Analizar'),
key="discourse_live_analyze",
type="primary",
icon="馃攳",
disabled=not (text_input1 and text_input2),
use_container_width=True
)
if analyze_button and text_input1 and text_input2:
try:
with st.spinner(discourse_t.get('processing', 'Procesando...')):
# Realizar an谩lisis
result = perform_discourse_analysis(
text_input1,
text_input2,
nlp_models[lang_code],
lang_code
)
if result['success']:
# Convertir gr谩ficos a bytes antes de guardar
if 'graph1' in result:
result['graph1_bytes'] = fig_to_bytes(result['graph1'])
if 'graph2' in result:
result['graph2_bytes'] = fig_to_bytes(result['graph2'])
st.session_state.discourse_live_state['last_result'] = result
st.session_state.discourse_live_state['analysis_count'] += 1
st.session_state.discourse_live_state['text_changed'] = False
# Guardar en base de datos
store_student_discourse_result(
st.session_state.username,
text_input1,
text_input2,
result
)
else:
st.error(result.get('message', 'Error en el an谩lisis'))
except Exception as e:
logger.error(f"Error en an谩lisis: {str(e)}")
st.error(discourse_t.get('error_processing', 'Error al procesar el texto'))
# Columna derecha: Visualizaci贸n de resultados
with result_col:
st.subheader(discourse_t.get('live_results', 'Resultados en vivo'))
if 'last_result' in st.session_state.discourse_live_state and \
st.session_state.discourse_live_state['last_result'] is not None:
# Mostrar resultados usando la misma funci贸n que el an谩lisis normal
display_discourse_results(
st.session_state.discourse_live_state['last_result'],
lang_code,
discourse_t
)
elif st.session_state.discourse_live_state.get('text_changed', False):
st.info(discourse_t.get('changes_pending',
'Los textos han cambiado. Presione Analizar para ver los nuevos resultados.'))
else:
st.info(discourse_t.get('initial_message',
'Ingrese los textos y presione Analizar para ver los resultados.'))
except Exception as e:
logger.error(f"Error general en interfaz del discurso en vivo: {str(e)}")
st.error(discourse_t.get('general_error', "Se produjo un error. Por favor, intente de nuevo.")) |