Altafalam3-Email-Assistant-Agents

This project utilizes Large Language Models (LLMs) powered by the Autogen multi-agent architecture to automate and streamline email management. By intelligently analyzing, prioritizing, and generating responses for incoming emails, the system enhances productivity and reduces manual effort. Seamless integration with Gmail enables real-time email processing, while WhatsApp notifications ensure timely alerts for high-priority messages, creating an efficient and responsive communication ecosystem.

---

🚀 Key Features

• 📩 Real-time Email Monitoring
  Continuously monitors your Gmail inbox for new emails.

• 🔍 Intelligent Email Analysis
  Analyzes email content to extract intent, tone, and keywords using LLMs.

• ⚙️ Prioritization System
  Categorizes emails as SPAM, HIGH, or LOW priority based on user preferences and content.

• ✉️ Automated Draft Responses
  Generates professional or casual draft responses for high-priority emails.

• 📱 WhatsApp Integration
  Sends notifications for high-priority emails directly to your WhatsApp.

---

🏷️ Email Labels

• Spam Emails → Moved to Spam Folder.
• High-Priority Emails → Labeled High Priority and saved as drafts.
• Low-Priority Emails → Labeled Low Priority for later review.

---

📂 Directory Structure

Email-Assistant-Agents/
│
├── app/
│   ├── .env.example               # Template for environment variables
│   ├── config.py                  # LLM and API configuration
│   ├── app.py                     # Main Streamlit app for email processing
│   ├── lib/
│   │   ├── info.py                # Email extraction (body, subject, sender)
│   │   └── attachments.py         # Extracts text from attachments (PDFs, etc.)
│   ├── test.py                    # Test script for spam detection
│   ├── agent_prompts.py           # Prompts for email analysis & response generation
│   ├── utils.py                   # Utility functions (spam detection, email parsing)
│   ├── agents.py                  # LLM agents handling email workflows
│   ├── models/                    # Directory for storing ML models (e.g., spam detection)
│   │   └── spam_detection_model.joblib   # spam detection model file
│   ├── requirements.txt           # Python dependencies
│
└── wpbot/                         
    ├── app.js                     # WhatsApp bot server (Node.js)
    ├── package.json               # Node.js dependencies
    ├── package-lock.json          # Locks npm dependencies
    └── README.md                  # WhatsApp bot README.md

---

⚙️ Installation and Setup

1. Clone the Repository

git clone https://github.com/Altafalam3/Email-Assistant-Agents.git
cd Email-Assistant-Agents

---

2. Setup the WhatsApp Bot

Navigate to the WhatsApp Bot directory:

cd wpbot

Install dependencies:

npm install

Run the bot:

npm start

---

3. Setup the Streamlit App (Email Assistant)

Navigate to the app folder:

cd ../app

Install required Python packages:

pip install -r requirements.txt

---

4. Configure Environment Variables

• Copy .env.example to .env and update it with your credentials:

cp .env.example .env

• Required Environment Variables:
  • GROQ_API_KEY – GROQ API KEY.
  • GMAIL_IMAP_SERVER – Gmail IMAP server (imap.gmail.com).
  • GMAIL_IMAP_PORT – IMAP port (993).

---

5. Run the Email Assistant

streamlit run app.py

---

🛠️ How to Use

1. Start Monitoring Emails

   • Enter your Gmail credentials (email ID, app password).
   • Input your WhatsApp number for notifications (optional).
   • Define email priorities (e.g., deployment errors, critical emails).

2. Automated Analysis

   • The app scans incoming emails.
   • Spam emails are archived.
   • High-priority emails trigger WhatsApp notifications and draft responses.

3. Drafts and Labels

   • Draft responses for important emails are auto-generated and saved to Gmail.
   • Emails are labeled as High Priority or Low Priority based on analysis.

---

🧩 Example Usage

• Deployment Alerts – Get WhatsApp notifications for production issues.
• Client Communication – Generate drafts for high-priority client emails.
• Spam Detection – Archive phishing or scam emails automatically.

---

🔑 Environment Variables (Example .env File)

GROQ_API_KEY=your_groq_api_key_here
GMAIL_IMAP_SERVER=imap.gmail.com
GMAIL_IMAP_PORT=993

👉 Obtain a GROQ API Key here: GROQ Console

---

🤝 Contributing

We welcome contributions to enhance Altafalam3-Email-Assistant-Agents!

To contribute:

1. Fork the repository.

2. Create a new branch:

   git checkout -b feature-name

3. Commit your changes:

   git commit -m "Add new feature"

4. Push to your branch:

   git push origin feature-name

5. Open a Pull Request.

---

🛡️ License

This project is licensed under the GNU GENERAL PUBLIC LICENSE.