This intermediate path covers the design of safe, agentic conversational systems using NVIDIA NeMo Guardrails and Colang 2.0. You will create configuration files, define guardrail policies, and test conversational behavior with Python. You will develop context-aware flows that manage response timing, follow-ups, corrections, and escalations. You will also use multi-layered configurations, modular design patterns, and standard library features to create flexible chatbot behavior. The path is intended for developers with foundational knowledge of Python, large language models, or conversational AI who want to build more reliable and secure AI assistants.
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Syllabus
- Configure guardrail policies for large language model applications
- Define conversational flows with Colang 2.0
- Manage context, response timing, follow-ups, corrections, and escalations
- Organize multi-layered and modular guardrail configurations
- Integrate custom Python actions for complex logic and API access
- Test and refine conversational behavior for safety and reliability