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"""
Copyright 2024 Infosys Ltd.”
Use of this source code is governed by MIT license that can be found in the LICENSE file or at
MIT license https://opensource.org/licenses/MIT
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
"""
from pymongo.errors import InvalidDocument
from fairness.config.logger import CustomLogger
from fairness.dao.WorkBench.databaseconnection import DataBase_WB
from dotenv import load_dotenv
load_dotenv()
load_dotenv()
log = CustomLogger()
# Create a MongoDB database instance
class Model:
def __init__(self,db=None) -> None:
if db is not None:
log.info("inside model loop")
self.ModelWorkBench= db
else:
ModelWorkBenchconnection = DataBase_WB()
self.ModelWorkBench=ModelWorkBenchconnection.db
# Access the "Model" collection in the Common Workbench MongoDB database
self.collection = self.ModelWorkBench["Model"]
def find(self,model_id: float):
# Check if model_id is not None and is a string
if model_id is None or not isinstance(model_id, float):
raise ValueError("Model ID must be a non-empty float")
# Try to find the model by model_id in the database
try:
result = self.collection.find_one({"ModelId": model_id}, {"_id": 0, "ModelName": 1, "ModelData": 1, 'ModelEndPoint': 1})
except Exception as e:
raise ValueError(f"Invalid model ID {model_id}: {str(e)}")
return result
class ModelAttributes:
# Access the "ModelAttributes" collection in the Common Workbench MongoDB database
def __init__(self,db=None) -> None:
if db is not None:
log.info("inside model attributesloop")
self.ModelWorkBench= db
else:
ModelWorkBenchconnection = DataBase_WB()
self.ModelWorkBench=ModelWorkBenchconnection.db
self.collection = self.ModelWorkBench["ModelAttributes"]
def find(self,model_attributes: list):
# Check if model_id is not None and is a string
if model_attributes is None or not isinstance(model_attributes, list):
raise ValueError("Model attributes must be a non-empty list")
# Check if model_attributes is an empty list
if not model_attributes:
raise ValueError("Model attributes must not be an empty list")
# Try to find the model by model_attributes in the database
try:
# Query the database for the model attributes
model_attribute_ids = list(self.collection.find({"ModelAttributeName": {"$in": model_attributes}}, {"_id": 0, "ModelAttributeId": 1, "ModelAttributeName": 1}))
# Sort dataset_attribute_ids based on the order of dataset_attributes
model_attribute_ids.sort(key=lambda x: model_attributes.index(x['ModelAttributeName']))
# Get all values of each dictionary in dataset_attribute_ids
# model_attribute_ids_values = [list(d.values())[0] for d in model_attribute_ids]
# Check if the query returned any results
if not model_attribute_ids:
raise ValueError(f"Unable to found attribute id(s) from the given list: {model_attributes}")
# Extract the ModelAttributeId values from the query results
model_attribute_ids_values = [item['ModelAttributeId'] for item in model_attribute_ids]
except Exception as e:
# Catch exceptions that might occur during the database query
raise ValueError(str(e))
return model_attribute_ids_values
class ModelAttributeValues:
# Access the "ModelAttributesValues" collection in the Common Workbench MongoDB database
def __init__(self,db=None) -> None:
if db is not None:
log.info("inside model loop")
self.ModelWorkBench= db
else:
ModelWorkBenchconnection = DataBase_WB()
self.ModelWorkBench=ModelWorkBenchconnection.db
self.collection = self.ModelWorkBench["ModelAttributesValues"]
def find(self,batch_id: float, model_id: float, model_attribute_ids: list):
# Check if model_id is not None and is a string
if model_id is None or not isinstance(model_id, float):
raise ValueError("Model ID must be a non-empty float")
# Try to find the model by model_id in the database
try:
if batch_id is not None:
# Query the database for the model attribute values
log.info("executing")
model_attributes = list(self.collection.find({"ModelId": model_id, "ModelAttributeId": {"$in": model_attribute_ids}, "BatchId": batch_id, 'IsActive':'Y'}, {"_id": 0, "ModelAttributeValues": 1, "ModelAttributeId": 1}))
log.info("execution completed")
else:
# Query the database for the model attribute values
model_attributes = list(self.collection.find({"ModelId": model_id, "ModelAttributeId": {"$in": model_attribute_ids}, 'IsActive':'Y'}, {"_id": 0, "ModelAttributeValues": 1, "ModelAttributeId": 1}))
if not model_attributes:
raise ValueError(f"No records found for model_id: {model_id}. Please check the model_id.")
# Sort dataset_attributes_result based on the order of dataset_attribute_ids
model_attributes.sort(key=lambda x: model_attribute_ids.index(x['ModelAttributeId']))
# Extract the ModelAttributeId values from the query results
model_attribute_values = [item['ModelAttributeValues'] for item in model_attributes]
except Exception as e:
raise
return model_attribute_values
def update(self,batch_id,model_id,model_attribute_id,value:dict):
try:
# Update the document in the collection
update_result= self.collection.update_one({'BatchId': batch_id, 'ModelId': model_id,'ModelAttributeId': model_attribute_id, 'IsActive':'Y'}, {'$set': value})
# Check if the update was acknowledged
if not update_result.acknowledged:
raise RuntimeError(f"Failed to update document with ModelId {model_id} and ModelAttributeId {model_attribute_id}")
return update_result.acknowledged
except InvalidDocument:
raise ValueError(f"Document is not a valid document with ModelId {model_id} and ModelAttributeId {model_attribute_id}") |