Gmail Summarizer README

Overview

This project processes emails in your Gmail inbox, summarizes them using OpenAI's large language model, and converts the summary into an audio MP3 file using Google Cloud Text-to-Speech (TTS).

The program is terminal-based and requires setting up Google Cloud and Gmail API authentication, as well as providing an OpenAI API key.

At the end I have included a segment on how I would improve this project if I were to revisit it.

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Example Output

Text Output

Audio Output

GmailSummarizerDemo.mp4

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Prerequisites

1. Python Environment:

   • Ensure you have Python 3.7 or above installed.
   • Install the required libraries using the following command:

     pip install -r requirements.txt

2. Google Cloud Project Setup:

   • Set up a Google Cloud project for Gmail API access and Text-to-Speech API.

3. Gmail API and Authentication:

   • Create a credentials JSON file for Gmail API.

4. Google Cloud Text-to-Speech:

   • Create a service account and generate a key JSON file.

5. OpenAI API Key:

   • Obtain an API key from OpenAI.

6. Directory Structure:

   • Place credentials files in the appropriate directories:

     BASE_DIR/
     ├── GmailSummarizer.py
     ├── credentials.json
     ├── key/
     │   └── <service-account-key>.json
     

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Setup Guide

Step 1: Set the Base Directory

In the main Python script, set the BASE_DIR variable to your project's directory path. For example:

BASE_DIR = 'C:\\Users\\your-username\\Desktop\\GmailSummarizer\\'

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Step 2: Setting Up Gmail API

1. Enable Gmail API:

   • Go to the Google Cloud Console.
   • Create or select an existing project.
   • Search for and enable the Gmail API.

2. Create OAuth 2.0 Credentials:

   • In the Credentials tab, create an OAuth 2.0 Client ID.
   • Download the credentials.json file and place it in the project's main directory (BASE_DIR).

3. Authenticate Gmail:

   • Run the script once to initiate the authentication process:

     python GmailSummarizer.py

   • During this process:
     • A browser will open for you to log in and grant access to your Gmail account.
     • A token.json file will be generated and saved in the main directory.

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Step 3: Setting Up Google Cloud Text-to-Speech

1. Enable Text-to-Speech API:

   • Go to the Google Cloud Console.
   • Search for and enable the Cloud Text-to-Speech API.

2. Create a Service Account:

   • In the IAM & Admin section, create a new service account.
   • Assign the role Text-to-Speech Admin to the service account.

3. Generate and Save Key:

   • Generate a JSON key file for the service account.
   • Save the file in a subdirectory called key within the project directory. Example path:

     BASE_DIR/key/<service-account-key>.json
     

4. Update Service Account Path:

   • In the script, update the SERVICE_ACCOUNT_PATH variable:

     SERVICE_ACCOUNT_PATH = os.path.join(BASE_DIR, 'key\\<service-account-key>.json')

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Step 4: Add OpenAI API Key

1. Obtain OpenAI API Key:

   • Sign up for an account on OpenAI.
   • Retrieve your API key from the OpenAI dashboard.

2. Add API Key to the Script:

   • Replace <your-api-key> in the script with your actual OpenAI API key:

     client = OpenAI(api_key='<your-api-key>')

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Step 5: Run the Script

1. Launch the Script:

   • Open a terminal and navigate to the project directory.
   • Run the following command:

     python GmailSummarizer.py

2. Workflow Overview: The script provides a menu-driven interface with several options. Here's the recommended workflow:

   • Step 1: Update Emails:
     • Select the option to Update Emails.
     • This action retrieves emails from your Gmail inbox based on the configured timeframe (default: last 24 hours).
   • Step 2: Get Text Summary:
     • After updating emails, select the option to Get Text Summary.
     • This generates a summarized version of the gathered emails.
     • The text summary will be saved in the output directory.
   • Step 3: Get Audio Summary:
     • Once you have the text summary, choose Get Audio Summary.
     • This converts the text summary into a script and generates an MP3 file using Google Cloud Text-to-Speech.
     • The audio file will be saved in the output directory.

3. Additional Features:

   • Adjust Settings:
     • Use the Settings menu to change the email retrieval timeframe (e.g., include emails older than 24 hours).
   • Fix Gmail Authentication:
     • If you encounter issues with Gmail authentication, use the Fix Gmail Link option to refresh your credentials.

4. Output:

   • After completing the steps, check the output directory for:
     • The summarized text file.
     • The generated MP3 file.

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How I Would Improve the Project

This project was created a few months ago, and since then, my coding skills have improved significantly. If I were to revisit this project, these are the changes I would make to enhance its functionality, efficiency, and user experience:

1. Code Refactoring:

   • The current code structure could benefit from improved readability and efficiency.
   • I would apply modern coding practices, such as better modularization, error handling, and documentation, to make the codebase cleaner and easier to maintain.

2. Enhanced File Structure:

   • Instead of a monolithic script, I would reorganize the project into multiple smaller files with specific functionality, such as:
     • email_handler.py: For Gmail API interactions.
     • summarizer.py: For processing and summarizing emails.
     • text_to_speech.py: For converting summaries to audio.
     • main.py: To act as the entry point and coordinate other modules.

3. Improved Frontend:

   • Currently, the project is terminal-based, which can be intimidating for non-technical users.
   • I would develop a simple graphical user interface (GUI) to make the tool more accessible. For example:
     • A desktop application using frameworks like Tkinter or PyQt.
     • A web-based interface for easier interaction.

4. Streamlined Pipeline:

   • I would redesign the workflow to be more user-friendly:
     • Combine the steps into a single process triggered by a single click or command.
     • Automate intermediate steps like email updates and text summarization.
     • Provide clear real-time feedback on progress (e.g., “Fetching emails...”, “Generating summary...”).

5. Improved Audio Output:

   • I would enhance the quality of the audio output by utilizing a Text-to-Speech model that supports SSML (Speech Synthesis Markup Language).
   • Fully implementing SSML formatting in the code would allow for advanced control over speech patterns, such as:
     • Adding appropriate pause breaks between sections.
     • Emphasizing key phrases.
     • Adjusting the tone and rhythm for a more natural and engaging audio experience.

6. Cost-Effective API Usage:

   • To optimize the cost of OpenAI API usage, I would:
     • Scale the token usage for email summaries based on the character count of the email body and other variables (e.g., importance, length, or user-selected criteria).

7. Additional Features:

   • Add support for filtering emails by specific labels or keywords, enabling more tailored summaries.
   • Include more customization options for the summary and audio output, such as selecting voice types, languages, or tones.

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