A conversation agent built for customer support workflows. It maintains context across turns, answers from a knowledge base, and escalates to humans when needed.
What's included
- Conversation agent — multi-turn chat with managed history
- Context awareness — remembers prior messages and user intent
- Escalation logic — hands off to human agents when appropriate
- FAQ integration — answers from a structured knowledge base
When to use this
Pick the Customer Support Agent example when you want to:
- Build a support chatbot that handles multi-turn conversations
- Implement context-aware responses and escalation flows
- See how conversation type and knowledge sections work together
Project structure
├── agents/
│ └── support.py # Support conversation agent
├── knowledge/
│ └── faq.py # FAQ content and structure
├── main.py # Entry point — serve(agents)
├── pyproject.toml
└── reminix.config.toml
Quick start
Deploy the project and start a conversation with the support agent. It will use the FAQ knowledge to answer questions and escalate when needed.