Office365 toolkit integration

Integrate with the Office365 toolkit using LangChain Python.

Microsoft 365 is a product family of productivity software, collaboration and cloud-based services owned by Microsoft.

Note: Office 365 was rebranded as Microsoft 365.

This notebook walks through connecting LangChain to Office365 email and calendar.

To use this toolkit, you need to set up your credentials explained in the Microsoft Graph authentication and authorization overview. Once you’ve received a CLIENT_ID and CLIENT_SECRET, you can input them as environmental variables below.

You can also use the authentication instructions from here.

pip install -qU  O365
pip install -qU  beautifulsoup4  # This is optional but is useful for parsing HTML messages
pip install -qU langchain-community

Assign environmental variables

The toolkit will read the CLIENT_ID and CLIENT_SECRET environmental variables to authenticate the user so you need to set them here. You will also need to set your OPENAI_API_KEY to use the agent later.

# Set environmental variables here

Create the toolkit and get tools

To start, you need to create the toolkit, so you can access its tools later.

from langchain_community.agent_toolkits import O365Toolkit

toolkit = O365Toolkit()
tools = toolkit.get_tools()
tools

[O365SearchEvents(name='events_search', description=" Use this tool to search for the user's calendar events. The input must be the start and end datetimes for the search query. The output is a JSON list of all the events in the user's calendar between the start and end times. You can assume that the user can  not schedule any meeting over existing meetings, and that the user is busy during meetings. Any times without events are free for the user. ", args_schema=<class 'langchain_community.tools.office365.events_search.SearchEventsInput'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, account=Account Client Id: f32a022c-3c4c-4d10-a9d8-f6a9a9055302),
 O365CreateDraftMessage(name='create_email_draft', description='Use this tool to create a draft email with the provided message fields.', args_schema=<class 'langchain_community.tools.office365.create_draft_message.CreateDraftMessageSchema'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, account=Account Client Id: f32a022c-3c4c-4d10-a9d8-f6a9a9055302),
 O365SearchEmails(name='messages_search', description='Use this tool to search for email messages. The input must be a valid Microsoft Graph v1.0 $search query. The output is a JSON list of the requested resource.', args_schema=<class 'langchain_community.tools.office365.messages_search.SearchEmailsInput'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, account=Account Client Id: f32a022c-3c4c-4d10-a9d8-f6a9a9055302),
 O365SendEvent(name='send_event', description='Use this tool to create and send an event with the provided event fields.', args_schema=<class 'langchain_community.tools.office365.send_event.SendEventSchema'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, account=Account Client Id: f32a022c-3c4c-4d10-a9d8-f6a9a9055302),
 O365SendMessage(name='send_email', description='Use this tool to send an email with the provided message fields.', args_schema=<class 'langchain_community.tools.office365.send_message.SendMessageSchema'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, handle_tool_error=False, account=Account Client Id: f32a022c-3c4c-4d10-a9d8-f6a9a9055302)]

Use within an Agent

from langchain.agents import create_agent
from langchain_openai import OpenAI

llm = OpenAI(temperature=0)
agent = create_agent(
    model=llm,
    tools=toolkit.get_tools(),
)

agent.invoke(
    {"input": "Create an email draft for me to edit of a letter from the perspective of a sentient parrot who is looking to collaborate on some research with her estranged friend, a cat. Under no circumstances may you send the message, however."}
)

'The draft email was created correctly.'

agent.invoke(
    {"input": "Could you search in my drafts folder and let me know if any of them are about collaboration?"}
)

"I found one draft in your drafts folder about collaboration. It was sent on 2023-06-16T18:22:17+0000 and the subject was 'Collaboration Request'."

agent.invoke(
    {"input": "Can you schedule a 30 minute meeting with a sentient parrot to discuss research collaborations on October 3, 2023 at 2 pm Eastern Time?"}
)

/home/vscode/langchain-py-env/lib/python3.11/site-packages/O365/utils/windows_tz.py:639: PytzUsageWarning: The zone attribute is specific to pytz's interface; please migrate to a new time zone provider. For more details on how to do so, see https://pytz-deprecation-shim.readthedocs.io/en/latest/migration.html
  iana_tz.zone if isinstance(iana_tz, tzinfo) else iana_tz)
/home/vscode/langchain-py-env/lib/python3.11/site-packages/O365/utils/utils.py:463: PytzUsageWarning: The zone attribute is specific to pytz's interface; please migrate to a new time zone provider. For more details on how to do so, see https://pytz-deprecation-shim.readthedocs.io/en/latest/migration.html
  timezone = date_time.tzinfo.zone if date_time.tzinfo is not None else None

'I have scheduled a meeting with a sentient parrot to discuss research collaborations on October 3, 2023 at 2 pm Easter Time. Please let me know if you need to make any changes.'

agent.invoke(
    {"input": "Can you tell me if I have any events on October 3, 2023 in Eastern Time, and if so, tell me if any of them are with a sentient parrot?"}
)

"Yes, you have an event on October 3, 2023 with a sentient parrot. The event is titled 'Meeting with sentient parrot' and is scheduled from 6:00 PM to 6:30 PM."

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