inarrator

INarrator

Install the Package

pip install inarrator

Use the Package

Gmail

• In the Google Cloud console, enable the Gmail API.

• Register your App

  • In the Google Cloud console, go to OAuth Consent screen
  • Once on OAuth Consent Screen, select User Type External and then click create:
  • Now complete the registration of your app which is fairly simple. Just remember two things:
    • Since this is a Testing App, you will have to add some test users (ideally make it the same email through which you are registering the app)
    • Add .../auth/gmail.readonly scope

• Create "gmail_credentials.json" file:

  • Go to Credentials
  • Click + CREATE CREDENTIALS > OAuth client ID
  • SELECT Desktop app as application type
  • After this a pop up will appear which will have a option to DOWNLOAD OAuth Client JSON file.
  • Save the JSON and rename it to gmail_credentials.json

• Use the inarrator

• Chat-GPT Example

  from inarrator.email import Gmail
  from inarrator.summarizer.gpt import GPTModel
  
  gmail = Gmail()
  gmail.authenticate(
      credentials_path="gmail_credentials.json",
      gmail_scope=["https://www.googleapis.com/auth/gmail.readonly"],
  )
  # https://support.google.com/mail/answer/7190 (You can read more about Gmail Filters)
  emails = gmail.get_latest_emails(
          gmail_filters="from:(-noreply -no-reply) is:unread -category:social -category:promotions -unsubscribe", # 
          gmail_max_emails="30",
      )
  model = GPTModel(model_name = 'gpt-3.5-turbo-16k',api_token = "") # OPENAI_API_KEY
  documents = []
  for email in emails:
      documents.append(email)
  print(model.summarize(documents))
  
  

• Hugging Face Hub Example

  
  from inarrator.email import Gmail
  from inarrator.summarizer import HuggingFaceModel
  
  
  gmail = Gmail()
  gmail.authenticate(
      credentials_path="gmail_credentials.json",
      gmail_scope=["https://www.googleapis.com/auth/gmail.readonly"],
  )
  emails = gmail.get_latest_emails(
          gmail_filters="from:(-noreply -no-reply) is:unread -category:social -category:promotions -unsubscribe",
          gmail_max_emails="30",
      )
  model =  HuggingFaceModel(model_name="tuner007/pegasus_summarizer", api_token="") # HF_HUB_TOKEN
  print(model.summarize(emails[0])) # Hugging Face Hub Models currently can summarize one email at a time.
  

Outlook

• Create a New App Registration

• Request API permissions (Only Mail.Read)

• Configure the Platform

  • Add a Mobile and Desktop Application
  • Choose the Following Configuration

• Create a new client secret

  • Click on + New client secret.
  • Now create the following JSON and name it outlook_credentials.json. You can get Application (client) ID & Directory (tenant) ID from overview of your App.

  {"application_id":"Application (client) ID",
  "authority_url":"https://login.microsoftonline.com/{Directory (tenant) ID}",
  "outlook_scope":["Mail.Read"]}
  

• Since OAuth only work https but our redirect URI is localhost, we would have to make the following environment variable

export OAUTHLIB_INSECURE_TRANSPORT=1

• Use the inarrator

• Chat-GPT Example

  from inarrator.email import OutLook
  from inarrator.summarizer.gpt import GPTModel
  
  outlook = OutLook()
  outlook.authenticate(
      credentials_path="outlook_credentials.json",
      outlook_scope=["Mail.Read"],
  )
  emails = outlook.get_latest_emails(
              outlook_max_emails=5,
          )
  model = GPTModel(model_name = 'gpt-3.5-turbo-16k',api_token = "") # OPENAI_API_KEY
  documents = []
  for email in emails:
      documents.append(email)
  print(model.summarize(documents))
  
  

• Hugging Face Hub Example

  
  from inarrator.email import OutLook
  from inarrator.summarizer.huggingface import HuggingFaceModel
  
  
  outlook = OutLook()
  outlook.authenticate(
      credentials_path="outlook_credentials.json",
      outlook_scope=["Mail.Read"],
  )
  emails = outlook.get_latest_emails(
              outlook_max_emails=5,
          )
  model =  HuggingFaceModel(model_name="tuner007/pegasus_summarizer", api_token="") # HF_HUB_TOKEN
  print(model.summarize(emails[0])) # Hugging Face Hub Models currently can summarize one email at a time.