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from pymongo import MongoClient
from dotenv import load_dotenv
import gridfs
import pickle
import os
# Load environment variables from .env file
load_dotenv()
def load_model_and_encoders(model_path, transformer_path, target_encoder_path):
with open(model_path, 'rb') as f:
model = pickle.load(f)
with open(transformer_path, 'rb') as f:
pipeline_encoder = pickle.load(f)
with open(target_encoder_path, 'rb') as f:
label_encoder = pickle.load(f)
return model, pipeline_encoder, label_encoder
def retrieve_image_by_name_from_mongodb(file_name, database_name, collection_name):
# Establish a connection to MongoDB
client = MongoClient(os.getenv("MONGO_URL"))
# Access the specified database
db = client[database_name]
# Create a new GridFS object (a specification for storing and retrieving large binary objects)
fs = gridfs.GridFS(db, collection=collection_name)
# Find the image data using the filename in the metadata
image_data = fs.find_one({"filename": file_name})
try:
if image_data is None:
raise ValueError("image_data is None")
return image_data.read()
except Exception as e:
print(f"An error occurred: {e}")
raise # Re-raise the caught exception
def retrieve_data(database_name, collection_name, search_query):
# Connect to MongoDB
client = MongoClient(os.getenv("MONGO_URL"))
database = client[database_name]
collection = database[collection_name]
# Search for the document based on the provided query
result = collection.find_one(search_query)
client.close()
return result['data_info']
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