Technical Thoughts

 from azure.core.credentials import AzureKeyCredential from azure.ai.documentintelligence import DocumentIntelligenceClient from azure.ai.documentintelligence.models import AnalyzeDocumentRequest from azure.storage.blob import BlobServiceClient, BlobClient, ContainerClient from warnings import filterwarnings import pyodbc import sqlalchemy from sqlalchemy import create_engine, text import json from azure.storage.blob import BlobServiceClient import pandas as pd import os from IPython.display import display from constants import STORED_PROCEDURES from connection import get_engine,get_connection_details,var_blob_connection_string,var_container_name,var_subfolder_path,var_endpoint,var_key,var_formUrl #from connection import get_engine,get_connection_details def fn_extract_document_data(Asset_Fund_Val_Doc_Map_Id,Asset_Valuation_Id):     filterwarnings("ignore", category=UserWarning, message='.*pandas only supports SQLAlchemy connectable.*')     engine = get_engine()...

 Connection.py import os import sqlalchemy import pyodbc def get_engine ():         connection_string = (     'DRIVER={ODBC Driver 17 for SQL Server};'     f 'SERVER= { os.environ[ "DB_SERVER" ] } ;'     f 'DATABASE= { os.environ[ "DB_SCHEMA" ] } ;'     f 'UID= { os.environ[ "DB_USER" ] } ;'     f 'PWD= { os.environ[ "DB_PWD" ] } ;'     'Trusted_Connection=no;'     )     connection_url = sqlalchemy.engine.URL.create(         "mssql+pyodbc" ,         query = dict ( odbc_connect = connection_string)     )     return sqlalchemy.create_engine(connection_url, fast_executemany = True ) def get_connection_details ():     conn = pyodbc.connect(         'DRIVER={ODBC Driver 17 for SQL Server}; \             SERVER= %s ; \             ...