Dialogue Systems are crucial for human-machine interaction, particularly in social robotics where natural communication is essential. However, there is no standardized framework for developing Dialogue Systems, and the integration of Large Language Models (LLMs) faces challenges such as hallucinations, outdated information, and sycophancy, which can compromise trust and effectiveness in high-stakes applications. Also, LLMs often violate Gricean Maxims, affecting user interpretation and system efficacy. To address these issues, we present ROS2 Open-source Toolkit for Efficient Dialogue (ROOTED), a framework for developing adaptable dialogue systems for social robots. ROOTED combines rule-based dialogue generation, web search, and LLMs to better adhere to Gricean Maxims by grounding responses. It also includes components for non-verbal communication analysis and generation. The capabilities of ROOTED are demonstrated through its deployment in the Social Plantroid Robot, which uses ROOTED for managing interactions and emotional responses.