terra: add Hermes Agent, wired to local ollama
Points Nous Research's Hermes Agent at terra's own ROCm ollama server (gemma4:12b) as a custom OpenAI-compatible provider instead of a cloud key. Native systemd mode via the hermes-agent flake's own NixOS module — simpler than container mode, avoids the podman-rootful-sudo dance its docs call out. Also bumps OLLAMA_CONTEXT_LENGTH (and Hermes' mirrored model.context_length) from ollama's ~4k default to 131072, load-tested with real multi-ten- thousand-token prompts rather than just idle `ollama ps` checks — chosen as the practical ceiling where VRAM headroom and prefill throughput both start visibly degrading, not just the largest number that technically fit. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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@@ -18,6 +18,7 @@ in
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../../services/desktop/desktop-hyprland.nix
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../../services/desktop/desktop-apps.nix
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../../services/desktop/librechat.nix
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../../services/desktop/hermes-agent.nix
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];
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networking.hostName = "terra";
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@@ -95,6 +96,24 @@ in
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# Sparse activation makes that far less painful than it'd be for a dense
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# model this size, but still expect it to run slower than the two above.
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loadModels = [ "gemma4:12b" "qwen3.6:35b-a3b" ];
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# Ollama truncates context far below the model's real window unless
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# told otherwise (the OpenAI-compat /v1 route it's reached through has
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# no way to set this per-request — see services/desktop/hermes-agent.nix,
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# which points at this server and mirrors the same number in
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# model.context_length). 131072 chosen as the practical ceiling after
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# load-testing with real prompts, not just idle `ollama ps` checks:
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# 32768 (31.6k-token prompt) and 65536 (40.8k-token prompt) both stayed
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# 100% GPU with VRAM barely moving (~10.1G / ~10.67G of 16G) — KV cache
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# cost barely grows with context, likely sliding-window/local attention
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# on most of gemma4:12b's layers. At 131072 that stopped being true: a
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# ~108k-token prompt pushed VRAM to ~11.4G/16G (still 100% GPU, no CPU
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# spillover, negligible GTT) but with visibly shrinking headroom, and
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# prefill throughput measurably dropped (~490 -> ~460 tok/s) over just
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# the last 13k tokens — filling the full window would take minutes of
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# pure prompt processing. Stopped here rather than push further: next
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# doubling would risk CPU spillover under any concurrent GPU load
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# (desktop compositor, jellyfin transcode) for diminishing benefit.
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environmentVariables.OLLAMA_CONTEXT_LENGTH = "131072";
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};
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# ---- Dev-data disks — NOT in disko, mounted read-write, never wiped ----
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