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#modules/morphosyntax/morphosyntax_interface.py
import streamlit as st
from streamlit_float import *
from streamlit_antd_components import *
from streamlit.components.v1 import html
import spacy
from spacy import displacy
import spacy_streamlit
import pandas as pd
import base64
import re
from .morphosyntax_process import (
process_morphosyntactic_input,
format_analysis_results,
perform_advanced_morphosyntactic_analysis,
get_repeated_words_colors,
highlight_repeated_words,
POS_COLORS,
POS_TRANSLATIONS
)
from ..utils.widget_utils import generate_unique_key
from ..database.morphosintax_mongo_db import store_student_morphosyntax_result
from ..database.chat_mongo_db import store_chat_history, get_chat_history
import logging
logger = logging.getLogger(__name__)
def display_morphosyntax_interface(lang_code, nlp_models, morpho_t):
try:
# Inicializar el estado si no existe
if 'morphosyntax_state' not in st.session_state:
st.session_state.morphosyntax_state = {
'analysis_count': 0,
'current_text': '', # Almacenar el texto actual
'last_analysis': None,
'needs_update': False # Flag para actualización
}
# Campo de entrada de texto que mantiene su valor
text_key = "morpho_text_input"
# Función para manejar cambios en el texto
def on_text_change():
st.session_state.morphosyntax_state['current_text'] = st.session_state[text_key]
st.session_state.morphosyntax_state['needs_update'] = True
# Recuperar el texto anterior si existe
default_text = st.session_state.morphosyntax_state.get('current_text', '')
sentence_input = st.text_area(
morpho_t.get('morpho_input_label', 'Enter text to analyze'),
value=default_text, # Usar el texto guardado
height=150,
key=text_key,
on_change=on_text_change,
placeholder=morpho_t.get('morpho_input_placeholder', 'Enter your text here...')
)
# Botón de análisis
col1, col2, col3 = st.columns([2,1,2])
with col1:
analyze_button = st.button(
morpho_t.get('morpho_analyze_button', 'Analyze Morphosyntax'),
key=f"morpho_button_{st.session_state.morphosyntax_state['analysis_count']}",
type="primary",
icon="🔍",
disabled=not bool(sentence_input.strip()),
use_container_width=True
)
# Procesar análisis solo cuando sea necesario
if (analyze_button or st.session_state.morphosyntax_state['needs_update']) and sentence_input.strip():
try:
with st.spinner(morpho_t.get('processing', 'Processing...')):
doc = nlp_models[lang_code](sentence_input)
advanced_analysis = perform_advanced_morphosyntactic_analysis(
sentence_input,
nlp_models[lang_code]
)
st.session_state.morphosyntax_result = {
'doc': doc,
'advanced_analysis': advanced_analysis
}
# Solo guardar en DB si fue un click en el botón
if analyze_button:
if store_student_morphosyntax_result(
username=st.session_state.username,
text=sentence_input,
arc_diagrams=advanced_analysis['arc_diagrams']
):
st.success(morpho_t.get('success_message', 'Analysis saved successfully'))
st.session_state.morphosyntax_state['analysis_count'] += 1
st.session_state.morphosyntax_state['needs_update'] = False
# Mostrar resultados en un contenedor específico
with st.container():
display_morphosyntax_results(
st.session_state.morphosyntax_result,
lang_code,
morpho_t
)
except Exception as e:
logger.error(f"Error en análisis morfosintáctico: {str(e)}")
st.error(morpho_t.get('error_processing', f'Error processing text: {str(e)}'))
# Mostrar resultados previos si existen
elif 'morphosyntax_result' in st.session_state and st.session_state.morphosyntax_result:
with st.container():
display_morphosyntax_results(
st.session_state.morphosyntax_result,
lang_code,
morpho_t
)
except Exception as e:
logger.error(f"Error general en display_morphosyntax_interface: {str(e)}")
st.error("Se produjo un error. Por favor, intente de nuevo.")
def display_morphosyntax_results(result, lang_code, morpho_t):
"""
Muestra solo el análisis sintáctico con diagramas de arco.
"""
if result is None:
st.warning(morpho_t.get('no_results', 'No results available'))
return
doc = result['doc']
# Análisis sintáctico (diagramas de arco)
st.markdown(f"### {morpho_t.get('arc_diagram', 'Syntactic analysis: Arc diagram')}")
with st.container():
sentences = list(doc.sents)
for i, sent in enumerate(sentences):
with st.container():
st.subheader(f"{morpho_t.get('sentence', 'Sentence')} {i+1}")
try:
html = displacy.render(sent, style="dep", options={
"distance": 100,
"arrow_spacing": 20,
"word_spacing": 30
})
# Ajustar dimensiones del SVG
html = html.replace('height="375"', 'height="200"')
html = re.sub(r'<svg[^>]*>', lambda m: m.group(0).replace('height="450"', 'height="300"'), html)
html = re.sub(r'<g [^>]*transform="translate\((\d+),(\d+)\)"',
lambda m: f'<g transform="translate({m.group(1)},50)"', html)
# Envolver en un div con clase para estilos
html = f'<div class="arc-diagram-container">{html}</div>'
st.write(html, unsafe_allow_html=True)
except Exception as e:
logger.error(f"Error rendering sentence {i}: {str(e)}")
st.error(f"Error displaying diagram for sentence {i+1}")
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