Reliable Function Calling in Deeply Recursive Union Types: Fixing Qwen Models' Double-Stringify Bug

Introduction & Problem Statement Function calling in AI models is a cornerstone of their utility in engineering domains, enabling them to generate structured, executable code rather than mere text. However, when confronted with deeply recursive union types , even state-of-the-art models like Qwen falter. These types, characterized by nested structures and multiple possible data representations, introduce ambiguity that AI models struggle to resolve. The result? Low success rates and systematic bugs that undermine reliability. During my presentation at the Qwen Meetup Korea, I dissected the specific challenges with Qwen models. The qwen3-coder-next model exhibited a 6.75% first-try success rate on deeply recursive union types, while the entire Qwen 3.5 family consistently failed due to a double-stringify bug . This bug, a mechanical artifact of how the model processes JSON-like structures, causes nested objects to be incorrectly serialized twice, breaking type integrity. The causal chai