kami
76a6a007ef
The most load-bearing decision in the project was stated four incompatible ways: the docs said Qwen3-1.7B, deploy/mavend.json said Qwen3.5-2B, the repo's models/llm/ held an LFM2.5-1.2B gguf, and five code comments still said LFM. Answering "which model is deployed" meant re-deriving it from scratch every time. Two facts the review missed, found while resolving it: - /mnt/hdd1/llms is bind-mounted over /opt/maven/models/llm, which shadows the repo's models/llm/. The LFM2.5 gguf sitting there was never loaded by anything, so it was not evidence of the deployed model at all. - That library holds Qwen3.5-0.8B, -2B and -4B, and no Qwen3-1.7B. The config pointed at a file that does exist; the docs' Qwen3-1.7B was the stale claim, the reverse of the assumed direction. Qwen3-1.7B is the CPT target, and that training is still in flight (Vikunja #122), so no such gguf exists yet. phraser.model_path moves to Qwen3.5-0.8B (Q4_K_M) — the smallest checkpoint on disk, chosen for latency, and relevant to whether the LLM router is affordable on this box. Docs and comments now say the same thing in one voice: 0.8B resident now, CPT'd Qwen3-1.7B as the target, and the bind-mount shadowing written down so the next reader does not mistake models/llm/ for ground truth. Comments name the model, never a filename, so a swap stays a one-line config change. n_gpu_layers: 99 is correct and stays — compose passes /dev/dri and the render gid for Vulkan offload to the Vega iGPU. CLAUDE.md's "CPU-only" was the stale half of that contradiction and is corrected. phraser.go also dropped a wrong "sub-1b, prompted not trained" size claim: the target is trained end-to-end (RU CPT + joint persona/router SFT). Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01X5JApcrCRVGmqrxnhynSik