modules/morphosyntax/morphosyntax_interface.py

#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__)

###########################################################################

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

############################################################################

def display_morphosyntax_interface(lang_code, nlp_models, morpho_t):
    try:
        # CSS mejorado para estabilidad y layout
        st.markdown("""
            <style>
            .stTextArea textarea {
                font-size: 1rem;
                line-height: 1.5;
                padding: 0.5rem;
                border-radius: 0.375rem;
                border: 1px solid #e2e8f0;
                background-color: white;
                min-height: 100px !important;
                height: 100px !important;
            }
            .arc-diagram-container {
                width: 100%;
                overflow-x: auto;
                background-color: white;
                padding: 0.5rem;
                border-radius: 0.375rem;
                box-shadow: 0 2px 4px rgba(0,0,0,0.1);
                margin-top: 10px;
                margin-bottom: 20px;
            }
            </style>
        """, unsafe_allow_html=True)

        # Inicialización del estado
        if 'morphosyntax_state' not in st.session_state:
            st.session_state.morphosyntax_state = {
                'original_text': '',
                'original_analysis': None,
                'current_text': '',
                'current_analysis': None,
                'analysis_count': 0
            }

        # Sección del texto original
        st.markdown("### Texto Original")
        original_text = st.text_area(
            "Ingrese una oración",
            value=st.session_state.morphosyntax_state['original_text'],
            key="original_text_input",
            placeholder="Ingresar solo una oración hasta el punto y aparte. Si es punto seguido, dejar así.",
            height=100
        )

        col1, col2, col3 = st.columns([2,1,2])
        with col1:
            analyze_original = st.button(
                "Analizar Texto Original",
                type="primary",
                use_container_width=True,
                disabled=not bool(original_text.strip())
            )

        # Procesar texto original
        if analyze_original and original_text.strip():
            try:
                with st.spinner("Analizando texto original..."):
                    doc = nlp_models[lang_code](original_text)
                    analysis = perform_advanced_morphosyntactic_analysis(
                        original_text,
                        nlp_models[lang_code]
                    )
                    
                    # Guardar análisis original en el estado
                    st.session_state.morphosyntax_state.update({
                        'original_text': original_text,
                        'original_analysis': {'doc': doc, 'analysis': analysis},
                        'current_text': original_text,
                        'analysis_count': st.session_state.morphosyntax_state['analysis_count'] + 1
                    })
                    
                    # Guardar en base de datos
                    store_student_morphosyntax_result(
                        username=st.session_state.username,
                        text=original_text,
                        arc_diagrams=analysis['arc_diagrams']
                    )

            except Exception as e:
                logger.error(f"Error en análisis original: {str(e)}")
                st.error("Error al procesar el texto original")

        # Mostrar diagrama original si existe
        if st.session_state.morphosyntax_state['original_analysis']:
            st.markdown("### Diagrama Original")
            display_morphosyntax_results(
                st.session_state.morphosyntax_state['original_analysis'],
                lang_code,
                morpho_t
            )

            # Sección de iteración
            st.markdown("---")
            st.markdown("### Iteración")
            
            iteration_text = st.text_area(
                "Modifique la oración",
                value=st.session_state.morphosyntax_state['current_text'],
                key=f"iteration_input_{st.session_state.morphosyntax_state['analysis_count']}",
                placeholder="Modifique el texto para mejorar la estructura",
                height=100
            )

            col1, col2, col3 = st.columns([2,1,2])
            with col1:
                analyze_iteration = st.button(
                    "Analizar Cambios",
                    type="primary",
                    use_container_width=True,
                    disabled=not bool(iteration_text.strip())
                )

            # Procesar iteración
            if analyze_iteration and iteration_text.strip():
                try:
                    with st.spinner("Analizando cambios..."):
                        doc = nlp_models[lang_code](iteration_text)
                        analysis = perform_advanced_morphosyntactic_analysis(
                            iteration_text,
                            nlp_models[lang_code]
                        )
                        
                        # Actualizar análisis actual
                        st.session_state.morphosyntax_state.update({
                            'current_text': iteration_text,
                            'current_analysis': {'doc': doc, 'analysis': analysis},
                            'analysis_count': st.session_state.morphosyntax_state['analysis_count'] + 1
                        })
                        
                        # Guardar en base de datos
                        store_student_morphosyntax_result(
                            username=st.session_state.username,
                            text=iteration_text,
                            arc_diagrams=analysis['arc_diagrams']
                        )

                except Exception as e:
                    logger.error(f"Error en iteración: {str(e)}")
                    st.error("Error al procesar los cambios")

            # Mostrar diagrama de iteración si existe
            if st.session_state.morphosyntax_state['current_analysis']:
                st.markdown("### Diagrama de Iteración")
                display_morphosyntax_results(
                    st.session_state.morphosyntax_state['current_analysis'],
                    lang_code,
                    morpho_t
                )

    except Exception as e:
        logger.error(f"Error general: {str(e)}")
        st.error("Se produjo un error. Por favor, intente de nuevo.")


#########################################################################3
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}")