(20241129) Day-end push.
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@@ -100,7 +100,6 @@ class MailOAuthModel(BaseModel):
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db_conn: AsyncMySQL,
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mongo_conn: AsyncMongo,
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user_info: dict,
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service_type: Literal["email", "chat"],
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service_client: Literal["gmail"],
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auth_type: Literal["oauth"],
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session_token: str = None
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@@ -112,7 +111,6 @@ class MailOAuthModel(BaseModel):
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:param db_conn: The database connection (MariaDB) to use to perform the action.
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:param mongo_conn: The database connection (MongoDB) to use to perform the action.
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:param user_info: The dictionary that has the user's session information.
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:param service_type: The type of service being provided.
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:param service_client: The name of the company or brand that is providing this service that is being integrated.
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:param auth_type: To identify the type of authentication being done here. This could indicate simple password
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authentication, more advance OAuth2.0 authentication, etc.
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@@ -127,7 +125,7 @@ class MailOAuthModel(BaseModel):
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mongo_json = await mongo_conn.find_one_and_update(
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collection = MailOAuthModel.AUTH_COLLECTION,
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filter = {
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"serviceType": service_type,
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"serviceType": "email",
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"client": service_client,
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"authType": auth_type,
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"user": user_info,
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@@ -138,7 +136,7 @@ class MailOAuthModel(BaseModel):
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},
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"$setOnInsert": {
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"version": "1.0.0",
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"serviceType": service_type,
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"serviceType": "email",
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"client": service_client,
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"authType": auth_type,
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"user": user_info,
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@@ -189,10 +187,10 @@ class MailOAuthModel(BaseModel):
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"""
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This method is to be called when the end user authorizes your service to connect to his third-party account. For
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example, when the end user allows you to access his GMail account.
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example, when the end user allows you to access his GMail account. USE THIS FOR UPDATING (REFRESHING) TOKENS
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ALSO.
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:param db_conn: The database connection (MariaDB) to use to perform the action.
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:param mongo_conn: The database connection (MongoDB) to use to perform the action.
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:param user_info: The dictionary that has the user's session information.
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:param user_identifier: The identifier granted by the 'get_user_identifier' method.
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:param token: The token granted by the third-party service.
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:param session_token: The session token of the user who requested this service.
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@@ -243,6 +241,44 @@ class MailOAuthModel(BaseModel):
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# Done here:
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return token_saved
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async def get_token(
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self,
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mongo_conn: AsyncMongo,
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user_identifier: ObjectId | str = None,
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**kwargs
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) -> dict | None:
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"""
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To retrieve stored tokens from the database.
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:param mongo_conn: The database connection (MongoDB) to use to perform the action.
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:param user_identifier: The identifier granted by the 'get_user_identifier' method.
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:param kwargs: Any set of key-value pairs to build custom search criteria. This could be things like the user
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info, the client, the type of authentication used, or even the kind of service.
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:return: The retrieved record that has the token, and information about the service and client if found, else
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None when there is no matching record.
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"""
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# Build the filter:
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filter_json = {k: v for k, v in kwargs.items()}
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if user_identifier: filter_json["_id"] = ObjectId(user_identifier)
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# If there is no search criteria, we exit with failure:
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if not filter_json: return None
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# If there is some filtering possible,
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# we fetch and return the token:
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return await mongo_conn.find_one(
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collection = self.AUTH_COLLECTION,
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filter = filter_json,
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projection = {
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"_id": True,
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"serviceType": True,
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"authType": True,
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"client": True,
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"token": True
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}
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)
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# *****************************************************************************************************************
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# ***** ****
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@@ -32,6 +32,9 @@
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# To make sibling directories accessible for imports:
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import sys
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from langchain.chains.summarize.stuff_prompt import prompt_template
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sys.path.append(".")
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sys.path.append("..")
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@@ -41,12 +44,20 @@ from utils_v2.date_time import date_time
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from utils_v2.database.async_mysql_v2 import AsyncMySQL
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from utils_v2.database.async_mongo_v2 import AsyncMongo
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# Mail Clients:
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from utils_v2.goog.gmail.gmail_client import AsyncGMailClient
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from utils_v2.goog.models.data.auth_tokens import GoogleAuthTokens
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# Base model:
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from models.behaviour.base import BaseModel
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# To work with MongoDB:
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from bson import ObjectId
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# To work with LLMs:
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from langchain_openai import ChatOpenAI
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from langchain_core.prompts import ChatPromptTemplate
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# To work with datatypes:
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from typing import Literal
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@@ -91,22 +102,98 @@ import copy
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# *****************************************************************************************************************
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class MailReadModel(BaseModel):
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class MailSyncModel(BaseModel):
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# For MongoDB:
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AUTH_COLLECTION = "_authTokens"
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MAIL_COLLECTION = "_messages"
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async def read_one(
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# For AI Magic through LLMs:
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prompt_template = ChatPromptTemplate.from_messages([
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(
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"system",
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"You're a mail summary expert that summarizes mails in 150 chars or less. HIDE SENSITIVE INFO (LIKE OTPS) FROM THE SUMMARY."
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),
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(
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"user",
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"Please summarize this mail: \"\"\"{mail}\"\"\""
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)
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])
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async def sync_one(
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self,
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db_conn: AsyncMySQL,
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mongo_conn: AsyncMongo,
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user_info: dict,
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service_type: Literal["email", "chat"],
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service_client: Literal["gmail"],
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auth_type: Literal["oauth"],
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session_token: str = None
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user_identifier: str | ObjectId,
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mail_client: AsyncGMailClient,
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tokens: GoogleAuthTokens,
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message_id: str,
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llm: ChatOpenAI = None,
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session_token: str = None,
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force_sync: bool = False
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) -> ObjectId:
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pass
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# ┏┓┓ ┓ ┏┓ • • ┳┓ ┓
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# ┃ ┣┓┏┓┏┃┏ ┣ ┓┏┓┏╋┓┏┓┏┓ ┣┫┏┓┏┏┓┏┓┏┫┏
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# ┗┛┛┗┗ ┗┛┗ ┗┛┛┗┗┛┗┗┛┗┗┫ ┛┗┗ ┗┗┛┛ ┗┻┛
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# ┛
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# Check if you already have that mail in your database:
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existing_record = await mongo_conn.find_one(
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collection = self.MAIL_COLLECTION,
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filter = {
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"messageType": "email",
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"$or": [
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{"payload.messageId": message_id}
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]
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},
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projection = {"_id": True}
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)
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# If there already exists such a record, and we haven't been forced to re-sync it:
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if existing_record and not force_sync: return existing_record["_id"]
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# ┏┓ ┓┏ • ┓ ┓
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# ┃┃┏┓┏┓┏┓┏┓┏┓┏┓ ┃┃┏┓┏┓┓┏┓┣┓┃┏┓┏
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# ┣┛┛ ┗ ┣┛┗┻┛ ┗ ┗┛┗┻┛ ┗┗┻┗┛┗┗ ┛
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# ┛
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mail_payload = None
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mail_id = existing_record["_id"] if existing_record else None
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# ┏┓┳┳┓ •┓
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# ┃┓┃┃┃┏┓┓┃
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# ┗┛┛ ┗┗┻┗┗
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if isinstance(mail_client, AsyncGMailClient):
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# Refresh the tokens:
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tokens_refreshed
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# Fetch the mail formatted message:
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client_response = await mail_client.get_message(
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tokens = tokens,
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message_id = message_id,
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return_raw = False
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)
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# If the fetch was successful:
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if client_response.success:
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# Summarize the content:
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prompt = self.prompt_template.invoke({"mail": client_response.data.pop["unformattedText"]})
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llm_response = await llm.ainvoke(prompt)
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client_response.data["aiSnippet"] = llm_response.content
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# Note down the response:
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mail_payload = client_response.data
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# ┏┓ ┏┳┓┓ ┳┳┓ •┓
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# ┗┓┓┏┏┓┏ ┃ ┣┓┏┓ ┃┃┃┏┓┓┃
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# ┗┛┗┫┛┗┗ ┻ ┛┗┗ ┛ ┗┗┻┗┗
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# ┛
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if mail_payload:
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pass
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# *****************************************************************************************************************
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