Gmail Openings Parser with Notion Integration

This project allows you to parse Gmail messages, vectorize their content, and store them in a Notion database with similarity search capabilities.

Features

• Gmail API integration for fetching emails
• Email content vectorization using sentence-transformers
• Notion database integration for storing emails
• Similarity search between emails
• Configurable search criteria

Setup

1. Install dependencies:

pip install -r requirements.txt

2. Set up environment variables: Create a .env file with the following variables:

NOTION_API_KEY=your_notion_api_key
NOTION_DATABASE_ID=your_notion_database_id

3. Set up Gmail API:

• Follow the Gmail API Quickstart to set up OAuth 2.0 credentials
• Place your credentials file as resi.json in the project root

4. Set up Notion:

• Create a new database in Notion
• Get the database ID from the URL (the part after the workspace name and before the question mark)
• Create an integration in Notion and get the API key
• Share your database with the integration

Usage

1. Run the main script:

python Gmail_Messages_by_Label.py

2. The script will:

• Authenticate with Gmail
• Search for emails matching the criteria
• Vectorize the email content
• Find similar emails in the Notion database
• Store the email in Notion

Customization

• Modify the search query in Gmail_Messages_by_Label.py to change the email filtering criteria
• Adjust the similarity threshold in email_vectorizer.py to change how similar emails are identified
• Customize the Notion database schema in notion_integration.py to match your database structure

Notes

• The vectorization uses the all-MiniLM-L6-v2 model by default, which provides a good balance between performance and accuracy

• Similarity search is performed using cosine similarity

• Emails are stored in Notion with their vector embeddings for future similarity searches