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README

awesome-llm-appsai_customer_support_agent

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๐Ÿ›’ AI Customer Support Agent with Memory

๐ŸŽ“ FREE Step-by-Step Tutorial

๐Ÿ‘‰ Click here to follow our complete step-by-step tutorial and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.

This Streamlit app implements an AI-powered customer support agent for synthetic data generated using GPT-4o. The agent uses OpenAI's GPT-4o model and maintains a memory of past interactions using the Mem0 library with Qdrant as the vector store.

Features

  • Chat interface for interacting with the AI customer support agent
  • Persistent memory of customer interactions and profiles
  • Synthetic data generation for testing and demonstration
  • Utilizes OpenAI's GPT-4o model for intelligent responses

How to get Started?

  1. Clone the GitHub repository
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd advanced_ai_agents/single_agent_apps/ai_customer_support_agent
  1. Install the required dependencies:
pip install -r requirements.txt
  1. Ensure Qdrant is running: The app expects Qdrant to be running on localhost:6333. Adjust the configuration in the code if your setup is different.
docker pull qdrant/qdrant

docker run -p 6333:6333 -p 6334:6334 \
    -v "$(pwd)/qdrant_storage:/qdrant/storage:z" \
    qdrant/qdrant
  1. Run the Streamlit App
streamlit run customer_support_agent.py

Ingestion metadata

Source catalog
awesome-llm-apps
Repository
Shubhamsaboo/awesome-llm-apps ยท main
File path
advanced_ai_agents/single_agent_apps/ai_customer_support_agent/README.md
Last refreshed
7/23/2026, 8:42:17 PM (3mo ago)
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