LLM Based Custom Email Sender with Real Time Analytics

Overview

This project is a custom email sender application that leverages Large Language Models (LLMs) to generate personalized email content. It also includes real-time analytics to track the status of sent emails.

Features

• Custom Email Generation: Generate personalized email content using LLMs.
• Real-Time Analytics: Track the status of sent emails in real-time.
• Scheduling: Schedule emails to be sent at a specific time.
• Throttling: Control the rate at which emails are sent to avoid spamming.
• Open Tracking: Check whether the email has been opened straight from the dashboard.

Usage

1. Clone the repository:

   git clone https://github.com/ShreyaSev/Custom-Email-Sender.git
   cd Custom-Email-Sender

2. Install dependencies:

    pip install -r requirements.txt

3.Setup MongoDB: Ensure you have MongoDB installed and running on port 27017. To connect to a different port, change the mongodb connection url in the EmailAnalyicsTab.py file.

4.Setup NGrok: Download NGrok using

    sudo snap install ngrok

Open a terminal and run

    ngrok http 5000

to start a session.

NGrok will generate a url endpoint, ending in ngrok-free.app. Note down this url. It will be used in the next step.

5.Setup SendGrid ESP:

• Visit the SendGrid website and follow the steps to create an account. Confirm that you have completed registration as a single sender. Go to Email API -> Integration Guide -> Web API and follow the steps to setup an API key for Python. You can either export the key as an environment variable or create a .env file to store the environment variables.
• Also set the sender address as FROM_EMAIL in the environment variables/.env file.
• Next, set up the webhook. On the left menu, scroll down and click on Settings -> Mail Settings. Click on event webhooks and create a new webhook. You might have to do this step from mobile. Check the following options: After creating a name for your webhook, paste the url you noted down in the previous step in the Post URL field, and add /webhook/sendgrid to the end. Sendgrid will send the tracking statuses to this endpoint which will be accessed by our application.

6. Setup your LLM: I used the Grok API, but you can use any OpenAI compatible LLM API. Setup your API key and add it to your environment variables/.env file.

7. Run the app:

    python3 main.py

Here's a short video demo:

Video Link

Overview.of.LLM-based.Custom.Email.Sender.Project.mp4