Fixing Tool-Call Accuracy in vLLM
Developers of the open‑source vLLM inference engine have released an update aimed at improving the precision of tool‑call handling. The patch addresses mismatches between model outputs and expected function signatures, adds stricter validation, and refines token‑level parsing. Early tests show reduced false positives and more reliable execution of external APIs when using vLLM for LLM serving.