Why your LLM tool calls silently break — and a ~10µs fix

Streaming responses from large language models (LLMs) can encounter unexpected breaks due to json decoding errors, usually under heavy load on longer outputs. This happens because the model's response gets cut off mid-transmission, despite the model generating the complete text. The article dives into why standard solutions don't solve this issue and suggests a minimal 10 microsecond fix to address the problem, emphasizing the importance of seamless data flow for maintaining user trust and model reliability. This insight is crucial for developers aiming to ensure robust, uninterrupted responses from LLMs in production environments.