Implementing programmatic tool calling on Amazon Bedrock | Amazon Web Services
Programmatic tool calling (PTC) is a paradigm shift in how large language models (LLMs) interact with external tools. In a traditional tool-calling workflow, each tool invocation requires a full round trip back to the model. The model calls a tool, receives the result, reasons about it, calls the next tool, and so on. For workflows that involve multiple tool calls, this creates compounding latency and token consumption because every intermediate result must pass through the model’s context window.
PTC takes a different approach. Instead of orchestrating tool calls one at a time, the model writes code, typically Python, that invokes multiple tools programmatically within a sandboxed execution environment. The code can include loops, conditionals, filtering, and aggregation logic. The model is only sampled once to produce the code. The execution environment then handles tool invocations, and only the final processed result is returned to the model’s context. This dramatically reduces...
Copyright of this story solely belongs to amazon.com. To see the full text click HERE
