2 Commits

Include renames

Author	SHA1	Message	Date
jpmschweitzerandClaude	bf13f9f0de	refactor(bench): share the GPU residency guard, and guard tool calling too ... Extracts the residency snapshot/restore into scripts/ollama_residency.py so the two benchmarks cannot drift, and applies it to benchmark_tool_calling.py, which had no protection at all. That script was the more dangerous of the two. It rewrites OLLAMA_DEFAULT_MODEL in .env and lets uvicorn reload onto it, restoring the original only after the loop — so any crash or interrupt left the *running server* pointed at the benchmark model. Its DEFAULT_MODELS begins with mistral-nemo-large, the 9.2G model implicated in the 2026-08-07 VRAM outage. Both the .env restore and the residency restore now run from `finally`. SIGTERM is handled explicitly in the shared module. Python runs `finally` for SIGINT, which arrives as KeyboardInterrupt, but the default SIGTERM action terminates outright, so `timeout` or a plain `kill` skipped the guard entirely. Co-Authored-By: Claude <noreply@anthropic.com>	2026-08-08 17:03:53 +02:00
jpmschweitzerandClaude Opus 4.6	427ad311dc	feat: switch default Ollama model to gemma4:e2b ... gemma4:e2b has native function calling with dedicated tool tokens, achieving 100% tool selection accuracy in benchmarks vs 67% for mistral-nemo-large, with 5-8x faster response times (2-4s vs 15-20s) and lower VRAM usage (8GB vs 9.2GB). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-04 22:44:27 +02:00