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๐ AI Customer Support Agent with Memory
๐ FREE Step-by-Step Tutorial
๐ 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?
- 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
- Install the required dependencies:
pip install -r requirements.txt
- 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
- 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)
- Refresh schedule
- Daily ยท 03:00 UTC
- Dedupe status
- Unique ยท deduped by (source, url)