Large Language Models (LLM) & AI Market: Making Local AI Tool Calls More Reliable

A developer describes a simple, programmatic recovery pattern to make local AI agent tool calls more reliable. The author observed that allowing models to auto-select tools sometimes caused them to skip required tool calls. The fix: attempt automatic selection first, and if a local-data request returns no tool call, retry once with tool_choice="required" (only before any tool runs) and then fall back to auto. The flow was tested with automated regression tests and a running local Gemma model; streaming output is buffered to avoid showing incorrect answers during recovery. The post was published on DEV Community on 2026-08-21.