vh
91bda3c480
The box is physically at Fountain Valley, renamed, renumbered onto 10.251/16, and serving inference again. This lands the repo half of that. Host: hostname ana-ml2 -> fv-ml1, pinned to 10.251.50.54 by a dnsmasq reservation so the address the runbook, DNS and LiteLLM all assume is the address it actually has. Its headscale node is renamed too. The sweep ran from scripts/fv-ml1-rename-sweep.sh, whose allowlist is the reason this diff touches current-state files and not the record. Dated persistent-memory entries, archival-memory and incident notes still say ana-ml2 in 31 and 62 places respectively, because that is what the box was when those things happened. Rewriting them would make the history lie. LiteLLM was the load-bearing piece and needed more than the api_base sed the runbook describes. Twenty api_base entries repointed, but a grep-and-verify pass also caught a LIVE pass_through_endpoints target for the scalar-judge reward route still on the old address -- an api_base-only substitution would have left it dead. Four prose references describing current state were repointed as well; one historical note recording where a hand-test was run is deliberately left pointing at 10.250.50.54. Two facts in the server tables were wrong and are corrected here. The site is Fountain Valley, not Anaheim. And the box has FOUR RTX PRO 6000 Blackwell Max-Q, not two -- verified by nvidia-smi -L and independently by PCI enumeration of four GB202GL devices. That is 391 GB of VRAM rather than 196, which changes what fits on it. DNS: fv-ml1, fv-ml1-bmc and fv-gw added under the fv site via the piggyback approach, scriberr re-homed, and the ana-ml2 records removed. Applied to all three resolvers. The BMC record carries a warning that its 802.1q VLAN tag must stay disabled -- it shipped tagging VLAN 250 into an untagged port, which made it invisible to every network-side diagnostic and is the reason it appeared dead through several cable changes. Verified end to end: summarizer and sec both answer through the Anaheim gateway across the mesh to FV seats on different ports.
57 lines
2.0 KiB
YAML
57 lines
2.0 KiB
YAML
# llama-swap — GGUF model server with on-demand model swapping.
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#
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# Proxies OpenAI-compatible API requests to llama.cpp server instances
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# and swaps which model is loaded into VRAM per request. Runs on
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# fv-ml1 using both GPUs dynamically (no explicit device pinning —
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# llama-swap picks per-model-definition).
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#
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# Model definitions live in /opt/docker/conf/llama-swap/config.yaml on
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# the server. Canonical copy of that config is config.yaml in this
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# workspace; deploy with scp + `docker compose restart` or the script
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# at the bottom of README.md.
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#
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# All tunables live in .env — edit that, not this file.
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services:
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llama-swap:
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image: ghcr.io/mostlygeek/llama-swap:${LLAMA_SWAP_VERSION}
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container_name: llama-swap
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restart: unless-stopped
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stdin_open: true
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tty: true
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runtime: nvidia
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ports:
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- "${LLAMA_SWAP_PORT}:8080"
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volumes:
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- /opt/docker/conf/llama-swap/config.yaml:/app/config.yaml
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- ${MODELS_DIR}:/models
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- ${HF_CACHE_DIR}:/hfcache
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environment:
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- HF_HOME=/hfcache
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- HF_HUB_CACHE=/hfcache/hub
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# Pin to GPU 0 — the reserved card for on-demand large-model hot-loads.
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# The always-on vLLM services (granite + embed/rerank/reward) own GPU 1;
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# keeping llama-swap off GPU 1 stops a hot-loaded model from contending
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# with them. llama.cpp then sees only GPU 0 (cuda:0), so --n-gpu-layers
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# 999 loads there with no per-model device targeting needed.
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- NVIDIA_VISIBLE_DEVICES=${LLAMA_SWAP_GPU:-0}
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healthcheck:
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test: ["CMD-SHELL", "curl -fsS http://localhost:8080/ >/dev/null || exit 1"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 30s
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networks:
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- tnet
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labels:
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- homepage.group=AI Systems
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- homepage.name=llama-swap
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- homepage.icon=mdi-swap-horizontal
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- homepage.description=GGUF model swapper (llama.cpp; fv-ml1)
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- homepage.href=http://10.251.50.54:${LLAMA_SWAP_PORT}
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networks:
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tnet:
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name: traefik-net
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external: true
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