Home Applications dc-customer-support-agent

dc-customer-support-agent

InterSystems does not provide technical support for this project. Please contact its developer for the technical assistance.
5
1 reviews
0
Awards
114
Views
0
IPM installs
0
0
Details
Releases (1)
Reviews (1)
Issues
example about AI agents powered by LangGraph in InterSystems Ir

What's new in this version

Initial Release

dc-customer-support-agent

📖 Overview

Welcome to the dc-customer-support-agent project! This practical example accompanies an article about AI agents powered by LangGraph in InterSystems IRIS.

The project demonstrates an AI-based customer support agent capable of analyzing incoming email requests, determining their priority, and categorizing them appropriately.

🛠️ How It Works

The Customer Support AI Agent is designed to automate the initial handling of customer support emails. Its workflow is as follows:

  1. Read Incoming Support Emails:

    • The agent accesses emails requiring assistance.
  2. Classify Priority:

    • Emails are analyzed to determine their priority level: High, Medium, or Low.
  3. Identify Topic:

    • The agent detects the topic or category of the request, such as password reset, VPN issues, printer problems, etc.
  4. Decision Making:

    • The agent decides whether to auto-respond to the email or escalate it to human support for further attention.
  5. Auto-Responding:

    • If auto-responding is the chosen course of action, the agent retrieves past examples (RAG) and crafts a personalized reply.

📋 Prerequisites

Before you begin, ensure you have the following:

  • Docker and Docker Compose installed on your system.
  • An .env file set up with necessary environment variables. You can use the env_sample file available at the repository’s root directory as a template.

🛠️ Installation

Follow these steps to set up the project:

  1. Clone the repository:

    git clone https://github.com/henryhamon/dc-customer-support-agent
    
  2. Navigate to the project directory:

    cd dc-customer-support-agent
    
  3. Configure environment variables:

    • Copy the env_sample file to a new file named .env and fill in the required details.
  4. Build the Docker container:

    docker-compose build --no-cache --progress=plain
    

💡 How to Use

To start and manage the Customer Support AI Agent, use Docker Compose:

  1. Start the Application:

    • Run the following command to start the application in detached mode:
      docker-compose up -d
      
  2. Stop and Remove Containers:

    • To stop the application and remove containers along with their images, use:
      docker-compose down --rmi all
      
Made with
Version
1.0.002 Jun, 2025
Ideas portal
Category
Frameworks
Works with
InterSystems IRIS
First published
02 Jun, 2025
Last edited
02 Jun, 2025
Last checked by moderator
27 Sep, 2025Works