v3 / modules /database /backUp /database_oldFromV2.py
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# database.py
# database.py de la versi贸n 3 al 26-9-2024
import streamlit as st
import logging
import os
import pandas as pd
from azure.cosmos import CosmosClient
from azure.cosmos.exceptions import CosmosHttpResponseError
from pymongo import MongoClient
import certifi
from datetime import datetime, timezone
from io import BytesIO
import base64
import matplotlib.pyplot as plt
from matplotlib.figure import Figure
import bcrypt
print(f"Bcrypt version: {bcrypt.__version__}")
import uuid
import plotly.graph_objects as go # Para manejar el diagrama de Sankey
import numpy as np # Puede ser necesario para algunas operaciones
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)
# Variables globales para Cosmos DB SQL API
application_requests_container = None
cosmos_client = None
user_database = None
user_container = None
user_feedback_container = None
# Variables globales para Cosmos DB MongoDB API
mongo_client = None
mongo_db = None
analysis_collection = None
chat_collection = None # Nueva variable global
##############################################################################--- INICIO DE LAS BASES DE DATOS --- ###############################
def initialize_database_connections():
try:
print("Iniciando conexi贸n a MongoDB")
mongodb_success = initialize_mongodb_connection()
print(f"Conexi贸n a MongoDB: {'exitosa' if mongodb_success else 'fallida'}")
except Exception as e:
print(f"Error al conectar con MongoDB: {str(e)}")
mongodb_success = False
try:
print("Iniciando conexi贸n a Cosmos DB SQL API")
sql_success = initialize_cosmos_sql_connection()
print(f"Conexi贸n a Cosmos DB SQL API: {'exitosa' if sql_success else 'fallida'}")
except Exception as e:
print(f"Error al conectar con Cosmos DB SQL API: {str(e)}")
sql_success = False
return {
"mongodb": mongodb_success,
"cosmos_sql": sql_success
}
#####################################################################################33
def initialize_cosmos_sql_connection():
global cosmos_client, user_database, user_container, application_requests_container, user_feedback_container
logger.info("Initializing Cosmos DB SQL API connection")
try:
cosmos_endpoint = os.environ.get("COSMOS_ENDPOINT")
cosmos_key = os.environ.get("COSMOS_KEY")
logger.info(f"Cosmos Endpoint: {cosmos_endpoint}")
logger.info(f"Cosmos Key: {'*' * len(cosmos_key) if cosmos_key else 'Not set'}")
if not cosmos_endpoint or not cosmos_key:
logger.error("COSMOS_ENDPOINT or COSMOS_KEY environment variables are not set")
raise ValueError("Las variables de entorno COSMOS_ENDPOINT y COSMOS_KEY deben estar configuradas")
cosmos_client = CosmosClient(cosmos_endpoint, cosmos_key)
user_database = cosmos_client.get_database_client("user_database")
user_container = user_database.get_container_client("users")
application_requests_container = user_database.get_container_client("application_requests")
user_feedback_container = user_database.get_container_client("user_feedback")
logger.info(f"user_container initialized: {user_container is not None}")
logger.info(f"application_requests_container initialized: {application_requests_container is not None}")
logger.info(f"user_feedback_container initialized: {user_feedback_container is not None}")
logger.info("Conexi贸n a Cosmos DB SQL API exitosa")
return True
except Exception as e:
logger.error(f"Error al conectar con Cosmos DB SQL API: {str(e)}", exc_info=True)
return False
############################################################################################3
def initialize_mongodb_connection():
global mongo_client, mongo_db, analysis_collection, chat_collection
try:
cosmos_mongodb_connection_string = os.getenv("MONGODB_CONNECTION_STRING")
if not cosmos_mongodb_connection_string:
logger.error("La variable de entorno MONGODB_CONNECTION_STRING no est谩 configurada")
return False
mongo_client = MongoClient(cosmos_mongodb_connection_string,
tls=True,
tlsCAFile=certifi.where(),
retryWrites=False,
serverSelectionTimeoutMS=5000,
connectTimeoutMS=10000,
socketTimeoutMS=10000)
mongo_client.admin.command('ping')
mongo_db = mongo_client['aideatext_db']
# export = mongo_db['export']
analysis_collection = mongo_db['text_analysis']
chat_collection = mongo_db['chat_history'] # Inicializar la nueva colecci贸n
# Verificar la conexi贸n
mongo_client.admin.command('ping')
logger.info("Conexi贸n a Cosmos DB MongoDB API exitosa")
return True
except Exception as e:
logger.error(f"Error al conectar con Cosmos DB MongoDB API: {str(e)}", exc_info=True)
return False
##############################################################################--- FIN DEL INICIO DE LAS BASES DE DATOS --- ################################################################################################################################
########################################################## -- INICIO DE GESTION DE USUARIOS ---##########################################################
def create_user(username, password, role):
global user_container
try:
print(f"Attempting to create user: {username} with role: {role}")
if user_container is None:
print("Error: user_container is None. Attempting to reinitialize connection.")
if not initialize_cosmos_sql_connection():
raise Exception("Failed to initialize SQL connection")
hashed_password = bcrypt.hashpw(password.encode('utf-8'), bcrypt.gensalt()).decode('utf-8')
print(f"Password hashed successfully for user: {username}")
user_data = {
'id': username,
'password': hashed_password,
'role': role,
'timestamp':datetime.now(timezone.utc).isoformat(),
}
user_container.create_item(body=user_data)
print(f"Usuario {role} creado: {username}") # Log para depuraci贸n
return True
except Exception as e:
print(f"Detailed error in create_user: {str(e)}")
return False
#######################################################################################################
def create_admin_user(username, password):
return create_user(username, password, 'Administrador')
#######################################################################################################
def create_student_user(username, password):
return create_user(username, password, 'Estudiante')
#######################################################################################################
# Funciones para Cosmos DB SQL API (manejo de usuarios)
def get_user(username):
try:
query = f"SELECT * FROM c WHERE c.id = '{username}'"
items = list(user_container.query_items(query=query, enable_cross_partition_query=True))
user = items[0] if items else None
if user:
print(f"Usuario encontrado: {username}, Rol: {user.get('role')}") # Log a帽adido
else:
print(f"Usuario no encontrado: {username}") # Log a帽adido
return user
except Exception as e:
print(f"Error al obtener usuario {username}: {str(e)}")
return None
########################################################## -- FIN DE GESTION DE USUARIOS ---##########################################################
########################################################## -- INICIO GESTION DE ARCHIVOS ---##########################################################
def manage_file_contents(username, file_name, analysis_type, file_contents=None):
if user_container is None:
logger.error("La conexi贸n a Cosmos DB SQL API no est谩 inicializada")
return None
item_id = f"{analysis_type}_{file_name}"
try:
if file_contents is not None:
# Storing or updating file
document = {
'id': item_id,
'username': username,
'file_name': file_name,
'analysis_type': analysis_type,
'file_contents': file_contents,
'timestamp': datetime.now(timezone.utc).isoformat()
}
user_container.upsert_item(body=document, partition_key=username)
logger.info(f"Contenido del archivo guardado/actualizado para el usuario: {username}, tipo de an谩lisis: {analysis_type}")
return True
else:
# Retrieving file
item = user_container.read_item(item=item_id, partition_key=username)
return item['file_contents']
except CosmosHttpResponseError as e:
if e.status_code == 404:
logger.info(f"No se encontr贸 el archivo para el usuario: {username}, tipo de an谩lisis: {analysis_type}")
return None
else:
logger.error(f"Error de Cosmos DB al manejar el archivo para el usuario {username}: {str(e)}")
return None
except Exception as e:
logger.error(f"Error al manejar el archivo para el usuario {username}: {str(e)}")
return None
def get_user_files(username, analysis_type=None):
if user_container is None:
logger.error("La conexi贸n a Cosmos DB SQL API no est谩 inicializada")
return []
try:
if analysis_type:
query = f"SELECT c.file_name, c.analysis_type, c.timestamp FROM c WHERE c.username = '{username}' AND c.analysis_type = '{analysis_type}'"
else:
query = f"SELECT c.file_name, c.analysis_type, c.timestamp FROM c WHERE c.username = '{username}'"
items = list(user_container.query_items(query=query, enable_cross_partition_query=True))
return items
except Exception as e:
logger.error(f"Error al obtener la lista de archivos del usuario {username}: {str(e)}")
return []
def delete_file(username, file_name, analysis_type):
if user_container is None:
logger.error("La conexi贸n a Cosmos DB SQL API no est谩 inicializada")
return False
try:
item_id = f"{analysis_type}_{file_name}"
user_container.delete_item(item=item_id, partition_key=username)
logger.info(f"Archivo eliminado para el usuario: {username}, tipo de an谩lisis: {analysis_type}, nombre: {file_name}")
return True
if success:
# Invalidar cach茅
cache_key = f"student_data_{username}"
if cache_key in st.session_state:
del st.session_state[cache_key]
except CosmosHttpResponseError as e:
logger.error(f"Cosmos DB error al eliminar el archivo para el usuario {username}: {str(e)}")
return False
except Exception as e:
logger.error(f"Error al eliminar el archivo para el usuario {username}: {str(e)}")
return False
########################################################## -- FIN GESTION DE ARCHIVOS ---##########################################################
########################################################## -- INICIO GESTION DE FORMULARIOS ---##########################################################
def store_application_request(name, email, institution, role, reason):
global application_requests_container
logger.info("Entering store_application_request function")
try:
logger.info("Checking application_requests_container")
if application_requests_container is None:
logger.error("application_requests_container is not initialized")
return False
logger.info("Creating application request document")
application_request = {
"id": str(uuid.uuid4()),
"name": name,
"email": email,
"institution": institution,
"role": role,
"reason": reason,
"requestDate": datetime.utcnow().isoformat()
}
logger.info(f"Attempting to store document: {application_request}")
application_requests_container.create_item(body=application_request)
logger.info(f"Application request stored for email: {email}")
return True
except Exception as e:
logger.error(f"Error storing application request: {str(e)}")
return False
#######################################################################################################
def store_user_feedback(username, name, email, feedback):
global user_feedback_container
logger.info(f"Attempting to store user feedback for user: {username}")
try:
if user_feedback_container is None:
logger.error("user_feedback_container is not initialized")
return False
feedback_item = {
"id": str(uuid.uuid4()),
"username": username,
"name": name,
"email": email,
"feedback": feedback,
'timestamp':datetime.now(timezone.utc).isoformat(),
}
result = user_feedback_container.create_item(body=feedback_item)
logger.info(f"User feedback stored with ID: {result['id']} for user: {username}")
return True
except Exception as e:
logger.error(f"Error storing user feedback for user {username}: {str(e)}")
return False
########################################################## -- FIN GESTION DE FORMULARIOS ---##########################################################
########################################################## -- INICIO ALMACENAMIENTO AN脕LISIS MORFOSINT脕CTICO ---##########################################################
def store_morphosyntax_result(username, text, repeated_words, arc_diagrams, pos_analysis, morphological_analysis, sentence_structure):
if analysis_collection is None:
logger.error("La conexi贸n a MongoDB no est谩 inicializada")
return False
try:
word_count = {}
for word, color in repeated_words.items():
category = color # Asumiendo que 'color' es la categor铆a gramatical
word_count[category] = word_count.get(category, 0) + 1
analysis_document = {
'username': username,
'timestamp':datetime.now(timezone.utc).isoformat(),
'text': text,
'repeated_words': repeated_words,
'word_count': word_count,
'arc_diagrams': arc_diagrams,
'pos_analysis': pos_analysis,
'morphological_analysis': morphological_analysis,
'sentence_structure': sentence_structure,
'analysis_type': 'morphosyntax'
}
result = analysis_collection.insert_one(analysis_document)
logger.info(f"An谩lisis guardado con ID: {result.inserted_id} para el usuario: {username}")
return True
except Exception as e:
logger.error(f"Error al guardar el an谩lisis para el usuario {username}: {str(e)}")
return False
################################################-- INICIO DE LA SECCI脫N DEL CHATBOT --- ###############################################################
def store_chat_history(username, messages):
try:
logger.info(f"Attempting to save chat history for user: {username}")
logger.debug(f"Messages to save: {messages}")
chat_document = {
'username': username,
'timestamp':datetime.now(timezone.utc).isoformat(),
'messages': messages
}
result = chat_collection.insert_one(chat_document)
logger.info(f"Chat history saved with ID: {result.inserted_id} for user: {username}")
logger.debug(f"Chat content: {messages}")
return True
except Exception as e:
logger.error(f"Error saving chat history for user {username}: {str(e)}")
return False
#######################################################################################################
def export_analysis_and_chat(username, analysis_data, chat_data):
try:
export_data = {
"username": username,
'timestamp':datetime.now(timezone.utc).isoformat(),
"analysis": analysis_data,
"chat": chat_data
}
# Aqu铆 puedes decidir c贸mo quieres exportar los datos
# Por ejemplo, podr铆as guardarlos en una nueva colecci贸n en MongoDB
export_collection = mongo_db['exports']
result = export_collection.insert_one(export_data)
# Tambi茅n podr铆as generar un archivo JSON o CSV y guardarlo en Azure Blob Storage
return True
except Exception as e:
logger.error(f"Error al exportar an谩lisis y chat para {username}: {str(e)}")
return False
################################################-- FIN DE LA SECCI脫N DEL CHATBOT --- ###############################################################
########--- STUDENT DATA -------
def get_student_data(username):
if analysis_collection is None or chat_collection is None:
logger.error("La conexi贸n a MongoDB no est谩 inicializada")
return None
formatted_data = {
"username": username,
"entries": [],
"entries_count": 0,
"word_count": {},
"semantic_analyses": [],
"discourse_analyses": [],
"chat_history": []
}
try:
logger.info(f"Buscando datos de an谩lisis para el usuario: {username}")
cursor = analysis_collection.find({"username": username})
for entry in cursor:
formatted_entry = {
'timestamp':datetime.now(timezone.utc).isoformat(),
"analysis_type": entry.get("analysis_type", "morphosyntax")
}
if formatted_entry["analysis_type"] == "morphosyntax":
formatted_entry.update({
"text": entry.get("text", ""),
"word_count": entry.get("word_count", {}),
"arc_diagrams": entry.get("arc_diagrams", [])
})
for category, count in formatted_entry["word_count"].items():
formatted_data["word_count"][category] = formatted_data["word_count"].get(category, 0) + count
elif formatted_entry["analysis_type"] == "semantic":
formatted_entry.update({
"key_concepts": entry.get("key_concepts", []),
"graph": entry.get("graph", "")
})
formatted_data["semantic_analyses"].append(formatted_entry)
elif formatted_entry["analysis_type"] == "discourse":
formatted_entry.update({
"text1": entry.get("text1", ""),
"text2": entry.get("text2", ""),
"key_concepts1": entry.get("key_concepts1", []),
"key_concepts2": entry.get("key_concepts2", []),
"graph1": entry.get("graph1", ""),
"graph2": entry.get("graph2", ""),
"combined_graph": entry.get("combined_graph", "")
})
formatted_data["discourse_analyses"].append(formatted_entry)
formatted_data["entries"].append(formatted_entry)
formatted_data["entries_count"] = len(formatted_data["entries"])
formatted_data["entries"].sort(key=lambda x: x["timestamp"], reverse=True)
for entry in formatted_data["entries"]:
entry["timestamp"] = entry["timestamp"].isoformat()
except Exception as e:
logger.error(f"Error al obtener datos de an谩lisis del estudiante {username}: {str(e)}")
try:
logger.info(f"Buscando historial de chat para el usuario: {username}")
chat_cursor = chat_collection.find({"username": username})
for chat in chat_cursor:
formatted_chat = {
"timestamp": chat["timestamp"].isoformat(),
"messages": chat["messages"]
}
formatted_data["chat_history"].append(formatted_chat)
formatted_data["chat_history"].sort(key=lambda x: x["timestamp"], reverse=True)
except Exception as e:
logger.error(f"Error al obtener historial de chat del estudiante {username}: {str(e)}")
logger.info(f"Datos formateados para {username}: {formatted_data}")
return formatted_data