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dc-customer-support-agent

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example about AI agents powered by LangGraph in InterSystems Ir

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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
Category
Frameworks
Works with
InterSystems IRIS
First published
02 Jun, 2025
Last edited
02 Jun, 2025