Creating an Email Sorting and Prioritization Tool with Ollama

Why Email Management Matters

• Boost Productivity: By efficiently sorting important emails, individuals can focus on what truly matters.
• Reduce Stress: An organized inbox is easier to manage, leading to a more relaxed mindset.
• Enhance Communication: Quickly sorting & prioritizing emails ensures timely communication.

What is Ollama?

Key Features of Ollama:

• Local Model Execution: Run AI models without relying on cloud services.
• User-Friendly Interface: Simplified tools for managing complex tasks.
• Flexibility: Adapt the model according to user preferences & use cases.

Developing the Email Sorting Tool

Step 1: Setting Up Ollama

Step 2: Designing the Functionality

• Categorization of Emails: Automatically categorize emails into folders (e.g., work, personal, promotions).
• Prioritization: Sort emails based on urgency using specific keywords or senders.
• Spam Detection: Filter out unwanted or spam emails efficiently.

Step 3: Writing the Code

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import ollama  # Import Ollama's library

# Define a function to sort emails
def sort_emails(email_list):
    responses = []
    for email in email_list:
        # Categorize the emails with Ollama's API
        response = ollama.chat(model='mistral', messages=[
            {
                'role': 'user',
                'content': f'Categorize this email: {email}'
            }
        ])
        responses.append(response['message']['content'])
    return responses

# Example email list
emails = [
    'Work meeting agenda for Monday',
    'Congratulations! You have won a prize!',
    'Your subscription is about to expire',
]

# Sort the emails
sorted_emails = sort_emails(emails)
print(sorted_emails)

Step 4: Integrating with Gmail API

1. Go to the Google Developers Console and create a new project.
2. Enable the Gmail API for the project.
3. Create credentials & download the
   1 credentials.json
   file.
4. Use the following code to authorize your app & connect to Gmail:

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from google.oauth2 import service_account
from googleapiclient.discovery import build

# Load the credentials
credentials = service_account.Credentials.from_service_account_file(
    'path/to/credentials.json'
)

gmail_service = build('gmail', 'v1', credentials=credentials)

Step 5: Filtering Emails

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def fetch_unread_emails(gmail_service):
    results = gmail_service.users().messages().list(userId='me', labelIds=['INBOX'], q='is:unread').execute()
    messages = results.get('messages', [])
    return messages

# Fetch unread emails
unread_emails = fetch_unread_emails(gmail_service)

# Process each unread email
for email in unread_emails:
    # Use the previously defined sort_emails function to categorize
    email_content = get_email_content(email)
    categorization = sort_emails([email_content])  # Pass the email content

Step 6: Implementing Spam Filtering

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def is_spam(email_content):
    response = ollama.chat(model='mistral', messages=[
        {'role': 'user', 'content': f'Is this email spam: {email_content}'}
    ])
    return 'spam' in response['message']['content'].lower()

Step 7: User Interface Development

Promoting Your Tool

• START with Social Media: Share your creation on platforms like Twitter & LinkedIn.
• Create a Demo Video: Showcase the capabilities of your tool on platforms like YouTube.
• Leverage Influencers: Engage with productivity bloggers or YouTubers to review your tool.

Arsturn Integration: Take It to the Next Level

• Quick Setup: Arsturn’s no-code AI chatbot builder makes it easy to create and engage your audience.
• Customizable Responses: Tailor the chatbot to meet specific needs of your users, offering a unique experience.
• Valuable Insights: Gain analytics on user interaction, helping refine both your tool and chatbot for better engagement.

Conclusion