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Create semantic_interface_BackUp_18-5-2025.py
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modules/semantic/semantic_interface_BackUp_18-5-2025.py
ADDED
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1 |
+
#modules/semantic/semantic_interface.py
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2 |
+
import streamlit as st
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3 |
+
from streamlit_float import *
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4 |
+
from streamlit_antd_components import *
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5 |
+
from streamlit.components.v1 import html
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6 |
+
import spacy_streamlit
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7 |
+
import io
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8 |
+
from io import BytesIO
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9 |
+
import base64
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10 |
+
import matplotlib.pyplot as plt
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11 |
+
import pandas as pd
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12 |
+
import re
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13 |
+
import logging
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14 |
+
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+
# Configuración del logger
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+
logger = logging.getLogger(__name__)
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17 |
+
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+
# Importaciones locales
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+
from .semantic_process import (
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+
process_semantic_input,
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+
format_semantic_results
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)
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+
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+
from ..utils.widget_utils import generate_unique_key
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+
from ..database.semantic_mongo_db import store_student_semantic_result
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+
from ..database.chat_mongo_db import store_chat_history, get_chat_history
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+
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+
# from ..database.semantic_export import export_user_interactions
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+
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+
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###############################
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+
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# En semantic_interface.py
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+
def display_semantic_interface(lang_code, nlp_models, semantic_t):
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35 |
+
try:
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36 |
+
# 1. Inicializar el estado de la sesión
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37 |
+
if 'semantic_state' not in st.session_state:
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+
st.session_state.semantic_state = {
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39 |
+
'analysis_count': 0,
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40 |
+
'last_analysis': None,
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41 |
+
'current_file': None,
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'pending_analysis': False # Nuevo flag para controlar el análisis pendiente
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}
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+
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+
# 2. Área de carga de archivo con mensaje informativo
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+
st.info(semantic_t.get('initial_instruction',
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+
'Para comenzar un nuevo análisis semántico, cargue un archivo de texto (.txt)'))
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48 |
+
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uploaded_file = st.file_uploader(
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semantic_t.get('semantic_file_uploader', 'Upload a text file for semantic analysis'),
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type=['txt'],
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key=f"semantic_file_uploader_{st.session_state.semantic_state['analysis_count']}"
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)
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+
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+
# 2.1 Verificar si hay un archivo cargado y un análisis pendiente
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if uploaded_file is not None and st.session_state.semantic_state.get('pending_analysis', False):
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try:
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+
with st.spinner(semantic_t.get('processing', 'Processing...')):
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+
# Realizar análisis
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+
text_content = uploaded_file.getvalue().decode('utf-8')
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61 |
+
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+
analysis_result = process_semantic_input(
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63 |
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text_content,
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lang_code,
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nlp_models,
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semantic_t
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)
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68 |
+
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69 |
+
if analysis_result['success']:
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+
# Guardar resultado
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+
st.session_state.semantic_result = analysis_result
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+
st.session_state.semantic_state['analysis_count'] += 1
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st.session_state.semantic_state['current_file'] = uploaded_file.name
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+
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# Guardar en base de datos
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storage_success = store_student_semantic_result(
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st.session_state.username,
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78 |
+
text_content,
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79 |
+
analysis_result['analysis']
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+
)
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81 |
+
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82 |
+
if storage_success:
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+
st.success(
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+
semantic_t.get('analysis_complete',
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'Análisis completado y guardado. Para realizar un nuevo análisis, cargue otro archivo.')
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+
)
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87 |
+
else:
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+
st.error(semantic_t.get('error_message', 'Error saving analysis'))
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+
else:
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+
st.error(analysis_result['message'])
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+
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+
# Restablecer el flag de análisis pendiente
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93 |
+
st.session_state.semantic_state['pending_analysis'] = False
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+
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95 |
+
except Exception as e:
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96 |
+
logger.error(f"Error en análisis semántico: {str(e)}")
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97 |
+
st.error(semantic_t.get('error_processing', f'Error processing text: {str(e)}'))
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98 |
+
# Restablecer el flag de análisis pendiente en caso de error
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99 |
+
st.session_state.semantic_state['pending_analysis'] = False
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100 |
+
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101 |
+
# 3. Columnas para los botones y mensajes
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102 |
+
col1, col2 = st.columns([1,4])
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103 |
+
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104 |
+
# 4. Botón de análisis
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+
with col1:
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+
analyze_button = st.button(
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semantic_t.get('semantic_analyze_button', 'Analyze'),
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108 |
+
key=f"semantic_analyze_button_{st.session_state.semantic_state['analysis_count']}",
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109 |
+
type="primary",
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110 |
+
icon="🔍",
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111 |
+
disabled=uploaded_file is None,
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112 |
+
use_container_width=True
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113 |
+
)
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114 |
+
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115 |
+
# 5. Procesar análisis
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116 |
+
if analyze_button and uploaded_file is not None:
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117 |
+
# En lugar de realizar el análisis inmediatamente, establecer el flag
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118 |
+
st.session_state.semantic_state['pending_analysis'] = True
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119 |
+
# Forzar la recarga de la aplicación
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120 |
+
st.rerun()
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121 |
+
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122 |
+
# 6. Mostrar resultados previos o mensaje inicial
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123 |
+
elif 'semantic_result' in st.session_state and st.session_state.semantic_result is not None:
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124 |
+
# Mostrar mensaje sobre el análisis actual
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125 |
+
st.info(
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126 |
+
semantic_t.get('current_analysis_message',
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127 |
+
'Mostrando análisis del archivo: {}. Para realizar un nuevo análisis, cargue otro archivo.'
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128 |
+
).format(st.session_state.semantic_state["current_file"])
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129 |
+
)
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130 |
+
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131 |
+
display_semantic_results(
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132 |
+
st.session_state.semantic_result,
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133 |
+
lang_code,
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134 |
+
semantic_t
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135 |
+
)
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136 |
+
else:
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137 |
+
st.info(semantic_t.get('upload_prompt', 'Cargue un archivo para comenzar el análisis'))
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138 |
+
|
139 |
+
except Exception as e:
|
140 |
+
logger.error(f"Error general en interfaz semántica: {str(e)}")
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141 |
+
st.error(semantic_t.get('general_error', "Se produjo un error. Por favor, intente de nuevo."))
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142 |
+
|
143 |
+
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144 |
+
#######################################
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145 |
+
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146 |
+
def display_semantic_results(semantic_result, lang_code, semantic_t):
|
147 |
+
"""
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148 |
+
Muestra los resultados del análisis semántico de conceptos clave.
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149 |
+
"""
|
150 |
+
if semantic_result is None or not semantic_result['success']:
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151 |
+
st.warning(semantic_t.get('no_results', 'No results available'))
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152 |
+
return
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153 |
+
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154 |
+
analysis = semantic_result['analysis']
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155 |
+
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156 |
+
# Mostrar conceptos clave en formato horizontal (se mantiene igual)
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157 |
+
st.subheader(semantic_t.get('key_concepts', 'Key Concepts'))
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158 |
+
if 'key_concepts' in analysis and analysis['key_concepts']:
|
159 |
+
df = pd.DataFrame(
|
160 |
+
analysis['key_concepts'],
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161 |
+
columns=[
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162 |
+
semantic_t.get('concept', 'Concept'),
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163 |
+
semantic_t.get('frequency', 'Frequency')
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164 |
+
]
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165 |
+
)
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166 |
+
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167 |
+
st.write(
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168 |
+
"""
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169 |
+
<style>
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170 |
+
.concept-table {
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171 |
+
display: flex;
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172 |
+
flex-wrap: wrap;
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173 |
+
gap: 10px;
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174 |
+
margin-bottom: 20px;
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175 |
+
}
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176 |
+
.concept-item {
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177 |
+
background-color: #f0f2f6;
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178 |
+
border-radius: 5px;
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179 |
+
padding: 8px 12px;
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180 |
+
display: flex;
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181 |
+
align-items: center;
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182 |
+
gap: 8px;
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183 |
+
}
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184 |
+
.concept-name {
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185 |
+
font-weight: bold;
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186 |
+
}
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187 |
+
.concept-freq {
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188 |
+
color: #666;
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189 |
+
font-size: 0.9em;
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190 |
+
}
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191 |
+
</style>
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192 |
+
<div class="concept-table">
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193 |
+
""" +
|
194 |
+
''.join([
|
195 |
+
f'<div class="concept-item"><span class="concept-name">{concept}</span>'
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196 |
+
f'<span class="concept-freq">({freq:.2f})</span></div>'
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197 |
+
for concept, freq in df.values
|
198 |
+
]) +
|
199 |
+
"</div>",
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200 |
+
unsafe_allow_html=True
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201 |
+
)
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202 |
+
else:
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203 |
+
st.info(semantic_t.get('no_concepts', 'No key concepts found'))
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204 |
+
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205 |
+
# Gráfico de conceptos (versión modificada)
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206 |
+
if 'concept_graph' in analysis and analysis['concept_graph'] is not None:
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207 |
+
try:
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208 |
+
# Sección del gráfico (sin div contenedor)
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209 |
+
st.image(
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210 |
+
analysis['concept_graph'],
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211 |
+
use_container_width=True
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212 |
+
)
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213 |
+
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214 |
+
# --- SOLO ESTE BLOQUE ES NUEVO ---
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215 |
+
st.markdown("""
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216 |
+
<style>
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217 |
+
div[data-testid="stExpander"] div[role="button"] p {
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218 |
+
text-align: center;
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219 |
+
font-weight: bold;
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220 |
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}
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221 |
+
</style>
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222 |
+
""", unsafe_allow_html=True)
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223 |
+
# ---------------------------------
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224 |
+
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225 |
+
# Expandible con la interpretación (se mantiene igual)
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226 |
+
with st.expander("📊 " + semantic_t.get('semantic_graph_interpretation', "Interpretación del gráfico semántico")):
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+
st.markdown(f"""
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228 |
+
- 🔀 {semantic_t.get('semantic_arrow_meaning', 'Las flechas indican la dirección de la relación entre conceptos')}
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229 |
+
- 🎨 {semantic_t.get('semantic_color_meaning', 'Los colores más intensos indican conceptos más centrales en el texto')}
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230 |
+
- ⭕ {semantic_t.get('semantic_size_meaning', 'El tamaño de los nodos representa la frecuencia del concepto')}
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231 |
+
- ↔️ {semantic_t.get('semantic_thickness_meaning', 'El grosor de las líneas indica la fuerza de la conexión')}
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232 |
+
""")
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233 |
+
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234 |
+
# Contenedor para botones (se mantiene igual pero centrado)
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235 |
+
st.markdown("""
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236 |
+
<style>
|
237 |
+
.download-btn-container {
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238 |
+
display: flex;
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239 |
+
justify-content: center;
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240 |
+
margin-top: 10px;
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241 |
+
}
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242 |
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</style>
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+
<div class="download-btn-container">
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244 |
+
""", unsafe_allow_html=True)
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245 |
+
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246 |
+
st.download_button(
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247 |
+
label="📥 " + semantic_t.get('download_semantic_network_graph', "Descargar gráfico de red semántica"),
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248 |
+
data=analysis['concept_graph'],
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249 |
+
file_name="semantic_graph.png",
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250 |
+
mime="image/png",
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251 |
+
use_container_width=True
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252 |
+
)
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253 |
+
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254 |
+
st.markdown("</div>", unsafe_allow_html=True)
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255 |
+
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256 |
+
except Exception as e:
|
257 |
+
logger.error(f"Error displaying graph: {str(e)}")
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258 |
+
st.error(semantic_t.get('graph_error', 'Error displaying the graph'))
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259 |
+
else:
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260 |
+
st.info(semantic_t.get('no_graph', 'No concept graph available'))
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261 |
+
|