modules/database.py

# database.py
import logging
import os
from azure.cosmos import CosmosClient
from azure.cosmos.exceptions import CosmosHttpResponseError
from pymongo import MongoClient
import certifi
from datetime import datetime
import io
import base64
import bcrypt
print(f"Bcrypt version: {bcrypt.__version__}")

logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)

# Variables globales para Cosmos DB SQL API
cosmos_client = None
user_database = None
user_container = None

# Variables globales para Cosmos DB MongoDB API
mongo_client = None
mongo_db = None
analysis_collection = None

#####################################################################################33
def initialize_cosmos_sql_connection():
    global cosmos_client, user_database, user_container
    try:
        cosmos_endpoint = os.environ.get("COSMOS_ENDPOINT")
        cosmos_key = os.environ.get("COSMOS_KEY")

        print(f"Cosmos Endpoint: {cosmos_endpoint}")
        print(f"Cosmos Key: {'*' * len(cosmos_key) if cosmos_key else 'Not set'}")

        if not cosmos_endpoint or not cosmos_key:
            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")
        
        print(f"user_container initialized: {user_container is not None}")
        logger.info("Conexión 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)}")
        return False

############################################################################################3        
def initialize_mongodb_connection():
    global mongo_client, mongo_db, analysis_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 está 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']
        analysis_collection = mongo_db['text_analysis']
        
        logger.info("Conexión 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

#######################################################################################################
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,
            'created_at': datetime.utcnow().isoformat()
        }
        user_container.create_item(body=user_data)
        print(f"Usuario {role} creado: {username}")  # Log para depuración
        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 añadido
        else:
            print(f"Usuario no encontrado: {username}")  # Log añadido
        return user
    except Exception as e:
        print(f"Error al obtener usuario {username}: {str(e)}")
        return None

################################################################################
# Funciones para Cosmos DB MongoDB API (análisis de texto)

def get_student_data(username):
    if analysis_collection is None:
        logger.error("La conexión a MongoDB no está inicializada")
        return None

    try:
        logger.info(f"Buscando datos para el usuario: {username}")
        cursor = analysis_collection.find({"username": username})
        
        formatted_data = {
            "username": username,
            "entries": [],
            "entries_count": 0,
            "word_count": {},
            "semantic_analyses": [],
            "discourse_analyses": [],
            "chat_history": []
        }
        
        for entry in cursor:
            formatted_entry = {
                "timestamp": entry["timestamp"],
                "text": entry["text"],
                "analysis_type": entry.get("analysis_type", "morphosyntax")
            }
            
            if formatted_entry["analysis_type"] == "morphosyntax":
                formatted_entry.update({
                    "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["network_diagram"] = entry.get("network_diagram", "")
                formatted_data["semantic_analyses"].append(formatted_entry)
            
            elif formatted_entry["analysis_type"] == "discourse":
                formatted_entry.update({
                    "graph1": entry.get("graph1", ""),
                    "graph2": entry.get("graph2", "")
                })
                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()
        
        # Obtener el historial del chat
        chat_cursor = chat_collection.find({"username": username})
        formatted_data["chat_history"] = list(chat_cursor)
        
        logger.info(f"Datos formateados para {username}: {formatted_data}")
        return formatted_data

    except Exception as e:
        logger.error(f"Error al obtener datos del estudiante {username}: {str(e)}")
        return None
        
#######################################################################################################

def store_morphosyntax_result(username, text, repeated_words, arc_diagrams):
    if analysis_collection is None:
        logger.error("La conexión a MongoDB no está inicializada")
        return False

    try:
        word_count = {}
        for word, color in repeated_words.items():
            category = color  # Asumiendo que 'color' es la categoría gramatical
            word_count[category] = word_count.get(category, 0) + 1

        analysis_document = {
            'username': username,
            'timestamp': datetime.utcnow(),
            'text': text,
            'word_count': word_count,
            'arc_diagrams': arc_diagrams,
        }

        result = analysis_collection.insert_one(analysis_document)

        logger.info(f"Análisis guardado con ID: {result.inserted_id} para el usuario: {username}")
        return True
    except Exception as e:
        logger.error(f"Error al guardar el análisis para el usuario {username}: {str(e)}")
        return False

################################################################################################################
def store_semantic_result(username, text, network_diagram):
    try:
        analysis_document = {
            'username': username,
            'timestamp': datetime.utcnow(),
            'text': text,
            'network_diagram': network_diagram,
            'analysis_type': 'semantic'
        }

        result = analysis_collection.insert_one(analysis_document)

        logger.info(f"Análisis semántico guardado con ID: {result.inserted_id} para el usuario: {username}")
        return True
    except Exception as e:
        logger.error(f"Error al guardar el análisis semántico para el usuario {username}: {str(e)}")
        return False

###############################################################################################################
def store_discourse_analysis_result(username, text, graph1, graph2):
    try:
        analysis_document = {
            'username': username,
            'timestamp': datetime.utcnow(),
            'text': text,
            'graph1': graph1,
            'graph2': graph2,
            'analysis_type': 'discourse'
        }
        result = analysis_collection.insert_one(analysis_document)
        logger.info(f"Análisis discursivo guardado con ID: {result.inserted_id} para el usuario: {username}")
        return True
    except Exception as e:
        logger.error(f"Error al guardar el análisis discursivo para el usuario {username}: {str(e)}")
        return False

###############################################################################################################
def store_chat_history(username, messages):
    try:
        chat_document = {
            'username': username,
            'timestamp': datetime.utcnow(),
            'messages': messages
        }
        result = chat_collection.insert_one(chat_document)
        logger.info(f"Chat history saved with ID: {result.inserted_id} for user: {username}")
        return True
    except Exception as e:
        logger.error(f"Error saving chat history for user {username}: {str(e)}")
        return False