An integrated framework for ethical healthcare chatbots using LangChain and NeMo guardrails

This paper presents an ethical guardrail framework for developing a healthcare chatbot using large language models (LLMs) fine-tuned for conversational tasks, integrated with LangChain and NeMo Guardrails. The system ensures safe and polite interactions by defining custom conversational flows, enforcing ethical guidelines, and preventing responses to harmful or sensitive topics. We have demonstrated this guardrail system with a fine-tuned Mistral-7B-v0.1 model on healthcare data. LangChain offers a modular interface for seamless integration, while NeMo Guardrails enforces ethical constraints, ensuring responsible responses. This approach demonstrates how LLMs can be effectively utilized in sensitive fields like healthcare while ensuring safety and integrity.