File size: 3,778 Bytes
c58df45 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 |
# database_export.py
import pandas as pd
import matplotlib.pyplot as plt
from io import BytesIO
#importaciones locales
from .morphosintax_mongo_db import get_student_morphosyntax_analysis
from .chat_db import get_chat_history
def export_user_interactions(username, analysis_type):
# Obtener historial de chat (que ahora incluye los análisis morfosintácticos)
chat_history = get_chat_history(username, analysis_type)
# Crear un PDF
buffer = BytesIO()
doc = SimpleDocTemplate(
buffer,
pagesize=letter,
rightMargin=2*cm,
leftMargin=2*cm,
topMargin=2*cm,
bottomMargin=2*cm
)
story = []
styles = getSampleStyleSheet()
# Título
story.append(Paragraph(f"Interacciones de {username} - Análisis {analysis_type}", styles['Title']))
story.append(Spacer(1, 0.5*cm))
# Historial del chat y análisis
for entry in chat_history:
for message in entry['messages']:
role = message['role']
content = message['content']
story.append(Paragraph(f"<b>{role.capitalize()}:</b> {content}", styles['BodyText']))
story.append(Spacer(1, 0.25*cm))
# Si hay visualizaciones (diagramas SVG), convertirlas a imagen y añadirlas
if 'visualizations' in message and message['visualizations']:
for svg in message['visualizations']:
drawing = svg2rlg(BytesIO(svg.encode('utf-8')))
img_data = BytesIO()
renderPM.drawToFile(drawing, img_data, fmt="PNG")
img_data.seek(0)
img = Image(img_data, width=15*cm, height=7.5*cm)
story.append(img)
story.append(Spacer(1, 0.5*cm))
story.append(PageBreak())
# Construir el PDF
doc.build(story)
buffer.seek(0)
return buffer
#def export_user_interactions(username, analysis_type):
# Obtener análisis morfosintáctico
#morphosyntax_data = get_student_morphosyntax_analysis(username)
# Obtener historial de chat
#chat_history = get_chat_history(username, analysis_type)
# Crear un DataFrame con los datos
#df = pd.DataFrame({
# 'Timestamp': [entry['timestamp'] for entry in chat_history],
# 'Role': [msg['role'] for entry in chat_history for msg in entry['messages']],
# 'Content': [msg['content'] for entry in chat_history for msg in entry['messages']]
#})
# Crear un PDF
#buffer = BytesIO()
#plt.figure(figsize=(12, 6))
#plt.axis('off')
#plt.text(0.5, 0.98, f"Interacciones de {username} - Análisis {analysis_type}", ha='center', va='top', fontsize=16)
#plt.text(0.5, 0.95, f"Total de interacciones: {len(df)}", ha='center', va='top', fontsize=12)
# Añadir tabla con las interacciones
#plt.table(cellText=df.values, colLabels=df.columns, cellLoc='center', loc='center')
# Añadir diagramas de arco si es análisis morfosintáctico
#if analysis_type == 'morphosyntax' and morphosyntax_data:
# for i, analysis in enumerate(morphosyntax_data):
# plt.figure(figsize=(12, 6))
# plt.axis('off')
# plt.text(0.5, 0.98, f"Diagrama de Arco {i+1}", ha='center', va='top', fontsize=16)
# plt.imshow(analysis['arc_diagrams'][0]) # Asumiendo que arc_diagrams es una lista de imágenes
#plt.savefig(buffer, format='pdf', bbox_inches='tight')
#buffer.seek(0)
#return buffer
# Uso:
# pdf_buffer = export_user_interactions(username, 'morphosyntax')
# st.download_button(label="Descargar PDF", data=pdf_buffer, file_name="interacciones.pdf", mime="application/pdf") |