Gmail Unnecessary Email Filter

This project provides a modular Python application that connects to your Gmail account, analyzes your emails using a local Ollama LLM instance, and moves unnecessary emails to a separate label.

Features

• Gmail Integration: Securely connects to your Gmail account using OAuth2
• Smart Email Analysis: Uses local Ollama API to evaluate email content
• Customizable Filters: Define what makes an email necessary or unnecessary
• Label Management: Creates and manages labels in your Gmail account
• Detailed Logging: Comprehensive logging for monitoring and debugging
• Result Tracking: Saves processing results for future reference

Prerequisites

• Python 3.7+
• Gmail account
• Google Cloud project with Gmail API enabled
• Ollama installed locally (https://ollama.ai)

Installation

1. Clone the repository:

   git clone https://github.com/subhashdasyam/ai-gmail-filter.git
   cd ai-gmail-filter
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Create a .env file by copying the example:

   cp .env.example .env
   

4. Edit the .env file to configure the application.

Google API Setup

1. Create a Google Cloud Project:

   • Go to https://console.cloud.google.com/
   • Create a new project or select an existing one
   • Enable billing for the project (required for API usage)

2. Enable the Gmail API:

   • Go to https://console.cloud.google.com/apis/library
   • Search for "Gmail API" and select it
   • Click "Enable"

3. Create OAuth 2.0 credentials:

   • Go to https://console.cloud.google.com/apis/credentials
   • Click "Create Credentials" and select "OAuth client ID"
   • Select "Desktop app" as the application type
   • Name your credentials and click "Create"
   • Download the credentials JSON file
   • Rename it to "credentials.json" and place it in the project root directory

Ollama Setup

1. Install Ollama from https://ollama.ai
2. Start the Ollama service
3. Pull the model you want to use:

   ollama pull llama2
   

   or any other model you prefer, like:

   ollama pull mistral
   

4. Ensure Ollama is running before starting the application

Usage

Run the application:

python main.py

On first run, the script will open a browser window for you to authenticate with your Gmail account. After authentication, the script will:

1. Fetch emails from your inbox
2. Analyze each email using the local Ollama LLM
3. Move unnecessary emails to the "potential-unnecessary" label (or the label name you configured)
4. Save processing results to a file

Configuration Options

You can customize the behavior of the application by editing the .env file:

• MAX_EMAILS: Maximum number of emails to process at once
• OLLAMA_MODEL: The LLM model to use for email analysis (must be pulled into Ollama first)
• LABEL_NAME: Name of the label for unnecessary emails
• BODY_PREVIEW_LENGTH: Length of email body to include in analysis
• LOG_LEVEL: Logging verbosity (DEBUG, INFO, WARNING, ERROR)

License

MIT License

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.