modules/studentact/current_situation_interface.py

# modules/studentact/current_situation_interface.py

import streamlit as st
import logging
from ..utils.widget_utils import generate_unique_key
import matplotlib.pyplot as plt
import numpy as np
from ..database.current_situation_mongo_db import store_current_situation_result

from .current_situation_analysis import (
    analyze_text_dimensions, 
    analyze_clarity,
    analyze_vocabulary_diversity, 
    analyze_cohesion,
    analyze_structure,
    get_dependency_depths, 
    normalize_score, 
    generate_sentence_graphs, 
    generate_word_connections, 
    generate_connection_paths,
    create_vocabulary_network, 
    create_syntax_complexity_graph, 
    create_cohesion_heatmap,     
)

# Configuración del estilo de matplotlib para el gráfico de radar
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['axes.grid'] = True
plt.rcParams['axes.spines.top'] = False
plt.rcParams['axes.spines.right'] = False

logger = logging.getLogger(__name__)
####################################

TEXT_TYPES = {
    'academic_article': {
        'name': 'Artículo Académico',
        'thresholds': {
            'vocabulary': {'min': 0.70, 'target': 0.85},
            'structure': {'min': 0.75, 'target': 0.90},
            'cohesion': {'min': 0.65, 'target': 0.80},
            'clarity': {'min': 0.70, 'target': 0.85}
        }
    },
    'student_essay': {
        'name': 'Trabajo Universitario',
        'thresholds': {
            'vocabulary': {'min': 0.60, 'target': 0.75},
            'structure': {'min': 0.65, 'target': 0.80},
            'cohesion': {'min': 0.55, 'target': 0.70},
            'clarity': {'min': 0.60, 'target': 0.75}
        }
    },
    'general_communication': {
        'name': 'Comunicación General',
        'thresholds': {
            'vocabulary': {'min': 0.50, 'target': 0.65},
            'structure': {'min': 0.55, 'target': 0.70},
            'cohesion': {'min': 0.45, 'target': 0.60},
            'clarity': {'min': 0.50, 'target': 0.65}
        }
    }
}
####################################

def display_current_situation_interface(lang_code, nlp_models, current_situation_t):
    """
    Interfaz simplificada con gráfico de radar para visualizar métricas.
    """
    # Inicializar estados si no existen
    if 'text_input' not in st.session_state:
        st.session_state.text_input = ""
    if 'text_area' not in st.session_state:  # Añadir inicialización de text_area
        st.session_state.text_area = ""
    if 'show_results' not in st.session_state:
        st.session_state.show_results = False
    if 'current_doc' not in st.session_state:
        st.session_state.current_doc = None
    if 'current_metrics' not in st.session_state:
        st.session_state.current_metrics = None
        
    try:
        # Container principal con dos columnas
        with st.container():
            input_col, results_col = st.columns([1,2])
            
            with input_col:
                # Text area con manejo de estado
                text_input = st.text_area(
                    current_situation_t['input_prompt'],  # Corregido: usar corchetes
                    height=400,
                    key="text_area",
                    value=st.session_state.text_input,
                    help=current_situation_t.get('help', '')  # Manejar clave faltante
                )
                
                # Función para manejar cambios de texto
                if text_input != st.session_state.text_input:
                    st.session_state.text_input = text_input
                    st.session_state.show_results = False
                
                if st.button(
                    current_situation_t['analyze_button'],  # Corregido: usar corchetes
                    type="primary",
                    disabled=not text_input.strip(),
                    use_container_width=True,
                ):
                    try:
                        with st.spinner(current_situation_t['processing']):  # Corregido: usar corchetes
                            doc = nlp_models[lang_code](text_input)
                            metrics = analyze_text_dimensions(doc)
                            
                            storage_success = store_current_situation_result(
                                username=st.session_state.username,
                                text=text_input,
                                metrics=metrics,
                                feedback=None
                            )
                            
                            if not storage_success:
                                logger.warning("No se pudo guardar el análisis en la base de datos")
                            
                            st.session_state.current_doc = doc
                            st.session_state.current_metrics = metrics
                            st.session_state.show_results = True
                            
                    except Exception as e:
                        logger.error(f"Error en análisis: {str(e)}")
                        st.error(current_situation_t.get('analysis_error', 'Error analyzing text'))  # Manejar clave faltante
            
            # Mostrar resultados en la columna derecha
            with results_col:
                if st.session_state.show_results and st.session_state.current_metrics is not None:
                    # Primero los radio buttons para tipo de texto
                    st.markdown(f"### {current_situation_t['text_type_header']}")  # Corregido: usar corchetes
                    text_type = st.radio(
                        "",
                        options=list(TEXT_TYPES.keys()),
                        format_func=lambda x: TEXT_TYPES[x]['name'],
                        horizontal=True,
                        key="text_type_radio",
                        help=current_situation_t.get('text_type_help', '')  # Manejar clave faltante
                    )
                    
                    st.session_state.current_text_type = text_type
                    
                    # Luego mostrar los resultados
                    display_results(
                        metrics=st.session_state.current_metrics,
                        text_type=text_type,
                        current_situation_t=current_situation_t
                    )

    except Exception as e:
        logger.error(f"Error en interfaz principal: {str(e)}")
        st.error(current_situation_t.get('error_interface', 'Interface error'))  # Manejar clave faltante

# ... (El resto del archivo mantiene las mismas correcciones con corchetes y get())

######################################
def display_radar_chart(metrics_config, thresholds, current_situation_t):
    """
    Muestra el gráfico radar con los resultados.
    """
    try:
        # Preparar datos para el gráfico
        categories = [m['label'] for m in metrics_config]
        values_user = [m['value'] for m in metrics_config]
        min_values = [m['thresholds']['min'] for m in metrics_config]
        target_values = [m['thresholds']['target'] for m in metrics_config]

        # Crear y configurar gráfico
        fig = plt.figure(figsize=(8, 8))
        ax = fig.add_subplot(111, projection='polar')

        # Configurar radar
        angles = [n / float(len(categories)) * 2 * np.pi for n in range(len(categories))]
        angles += angles[:1]
        values_user += values_user[:1]
        min_values += min_values[:1]
        target_values += target_values[:1]

        # Configurar ejes
        ax.set_xticks(angles[:-1])
        ax.set_xticklabels(categories, fontsize=10)
        circle_ticks = np.arange(0, 1.1, 0.2)
        ax.set_yticks(circle_ticks)
        ax.set_yticklabels([f'{tick:.1f}' for tick in circle_ticks], fontsize=8)
        ax.set_ylim(0, 1)

        # Dibujar áreas de umbrales
        ax.plot(angles, min_values, '#e74c3c', linestyle='--', linewidth=1, label='Mínimo', alpha=0.5)
        ax.plot(angles, target_values, '#2ecc71', linestyle='--', linewidth=1, label='Meta', alpha=0.5)
        ax.fill_between(angles, target_values, [1]*len(angles), color='#2ecc71', alpha=0.1)
        ax.fill_between(angles, [0]*len(angles), min_values, color='#e74c3c', alpha=0.1)

        # Dibujar valores del usuario
        ax.plot(angles, values_user, '#3498db', linewidth=2, label='Tu escritura')
        ax.fill(angles, values_user, '#3498db', alpha=0.2)

        # Ajustar leyenda
        ax.legend(
            loc='upper right',
            bbox_to_anchor=(1.3, 1.1),
            fontsize=10,
            frameon=True,
            facecolor='white',
            edgecolor='none',
            shadow=True
        )

        plt.tight_layout()
        st.pyplot(fig)
        plt.close()

    except Exception as e:
        logger.error(f"Error mostrando gráfico radar: {str(e)}")
        st.error(current_situation_t['error_chart'])
#######################################