751180fdc1
Switch `make serve` default to Qwen3.6 UD Q6_K_XL (32 GB, hybrid DeltaNet, near-lossless) and register it in the model catalog. Add --jinja to the llama-server launcher so tool/function calling works — without it clients silently ignore tool definitions advertised by the server.
104 lines
3.6 KiB
Makefile
104 lines
3.6 KiB
Makefile
.PHONY: help audit audit-full monitor monitor-simple benchmark benchmark-baseline benchmark-compare optimize verify test agentic-setup agentic-quick agentic-full
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help: ## Show available commands
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@echo "Strix Halo Optimization Toolkit"
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@echo ""
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@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf " \033[36m%-22s\033[0m %s\n", $$1, $$2}'
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# --- Audit ---
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audit: ## Quick system status (single screen)
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@bash bin/audit --quick
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audit-full: ## Full system report (saved to data/audits/)
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@bash bin/audit --full
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# --- Monitor ---
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monitor: ## Launch tmux monitoring dashboard
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@bash bin/monitor --dashboard
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monitor-simple: ## Launch amdgpu_top only
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@bash bin/monitor --simple
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monitor-install: ## Install monitoring tools (amdgpu_top, btop)
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@bash scripts/monitor/install-tools.sh
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monitor-log: ## Start background metric logger
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@bash bin/monitor --log
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# --- Benchmark ---
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benchmark-setup: ## Ensure toolboxes and test models are ready
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@bash scripts/benchmark/setup.sh
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benchmark-baseline: ## Capture pre-optimization baseline (supports ARGS="--max-size 20 --skip-longctx")
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@bash bin/benchmark baseline $(ARGS)
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benchmark: ## Run full benchmark suite (supports ARGS="--tag NAME --max-size 20")
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@bash bin/benchmark run $(ARGS)
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benchmark-compare: ## Compare two benchmark runs (usage: make benchmark-compare BEFORE=dir AFTER=dir)
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@bash bin/benchmark compare $(BEFORE) $(AFTER)
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# --- Serve ---
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serve: ## Launch Qwen3.6-35B-A3B UD-Q6_K_XL daily driver (2 slots, 256K ctx)
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@bash bin/serve -m Qwen3.6-35B-A3B-UD-Q6_K_XL.gguf --parallel 2 --ctx 262144 $(ARGS)
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serve-custom: ## Launch llama-server with custom model (ARGS="-m MODEL.gguf")
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@bash bin/serve $(ARGS)
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serve-ngram: ## Launch with n-gram speculative decoding (ARGS="-m MODEL.gguf")
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@bash bin/serve --ngram $(ARGS)
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flush-gpu: ## Kill llama-server/bench processes and drop kernel caches to free unified VRAM
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-@pkill -x llama-server 2>/dev/null || true
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-@pkill -x llama-bench 2>/dev/null || true
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-@pkill -x llama-cli 2>/dev/null || true
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-@podman ps --filter name=llama --format '{{.Names}}' | xargs -r podman stop
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@sync && sudo sysctl vm.drop_caches=3
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@echo "VRAM usage:" && cat /sys/class/drm/card*/device/mem_info_vram_used 2>/dev/null | awk '{printf " %.2f MiB\n", $$1/1048576}'
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# --- Hardware Info ---
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hw-bandwidth: ## Measure GPU memory bandwidth and compute (clpeak)
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@clpeak 2>&1
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# --- Optimize ---
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optimize: ## Interactive optimization walkthrough
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@bash bin/optimize --all
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optimize-kernel: ## Configure kernel boot parameters
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@bash scripts/optimize/kernel-params.sh
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optimize-tuned: ## Switch to accelerator-performance profile
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@bash scripts/optimize/tuned-profile.sh
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optimize-power: ## Apply Phase 2 tuning (ryzenadj, sysctl, THP, RADV)
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@bash scripts/optimize/power-profile.sh
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optimize-vram: ## BIOS VRAM guidance + GTT verification
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@bash scripts/optimize/vram-gtt.sh
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verify: ## Post-optimization verification checklist
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@bash scripts/optimize/verify.sh
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rollback: ## Rollback optimizations
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@bash scripts/optimize/rollback.sh
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# --- Agentic Evaluation ---
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agentic-setup: ## Install agentic evaluation frameworks (inspect-ai, evalplus)
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@bash bin/agentic setup
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agentic-quick: ## EvalPlus + IFEval quick eval (needs --model, ~1h)
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@bash bin/agentic quick $(ARGS)
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agentic-code: ## Code generation eval: EvalPlus + BigCodeBench (~2-3h)
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@bash bin/agentic code $(ARGS)
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agentic-tooluse: ## Tool/function calling eval: BFCL (~1-2h)
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@bash bin/agentic tooluse $(ARGS)
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agentic-full: ## All agentic evaluations (~5-6h)
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@bash bin/agentic full $(ARGS)
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# --- Tests ---
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test: ## Run BATS test suite
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@bats tests/
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