Customize Amazon Nova models to improve tool usage

Modern large language models (LLMs) excel in language processing but are limited by their static training data. However, as industries require more adaptive, decision-making AI, integrating tools and external APIs has become essential. This has led to the evolution and rapid rise of agentic workflows, where AI systems autonomously plan, execute, and refine tasks. Accurate tool use is foundational for enhancing the decision-making and operational efficiency of these autonomous agents and building successful and complex agentic workflows.

In this post, we dissect the technical mechanisms of tool calling using Amazon Nova models through Amazon Bedrock, alongside methods for model customization to refine tool calling precision.

Expanding LLM capabilities with tool use

LLMs excel at natural language tasks but become significantly more powerful with tool integration, such as APIs and computational frameworks. Tools enable LLMs to access real-time data, perform domain-specific computations, and retrieve precise information, enhancing their reliability and versatility ...