Worked on the jeejeelee/vllm repository, focusing on backend development and Python to address a critical issue in the GLM4 Tool Parser’s streaming mode. Delivered a targeted bug fix that improved the handling of tool calls and argument parsing during streaming, directly enhancing the reliability of streaming workflows in production environments. The solution involved careful unit testing to ensure robust behavior across edge cases, resulting in fewer runtime errors and reduced support overhead. This contribution maintained strong code quality and collaborative standards, as reflected in the signed-off and co-authored commit, and enabled safer, more stable streaming inference for end users.