homelab/ansible/roles/llm-inference-multimodel/templates/llama-server-router-preset.ini.j2

; ------------------------------------------------------------------------------
; FILE: roles/llm-inference-multimodel/templates/llama-server-router-preset.ini.j2
; DESCRIPTION: llama.cpp --models-preset INI for llama-server-router.
;
; Purpose: define all router-served GGUFs as named model entries so that:
;   - Each model is explicitly named and configured (no auto-discovery surprises)
;   - Aliases can be added per model (impossible with --models-dir alone)
;   - The Phi-3.5-mini-instruct-Q8_0 entry carries the alias
;     "Phi-3.5-mini-instruct-8bit" — Ryan's Hermes auxiliary.title_generation
;     already references this friendlier name; both names resolve to the same
;     GGUF child process.
;
; INI format notes (llama.cpp preset.md):
;   - Section header (e.g. [Phi-3.5-mini-instruct-Q8_0]) is the primary model ID
;     that appears in /v1/models and that clients send in the "model" field.
;   - `alias` adds an ADDITIONAL name — both the section name and the alias work.
;   - The `model` key is the absolute path to the GGUF file.
;   - All other keys map directly to llama-server CLI flags (underscores or hyphens).
;
; Known upstream issues (Aug 2026):
;   - GH #22364: --models-preset creates an extra "default" model entry in
;     /v1/models. This is cosmetic — it has no functional effect on model
;     selection by name. Document and move on.
;   - GH #23460: can't pass per-model samplers via --models-preset in router
;     mode. Non-issue: Hermes always sends sampling params in the request body.
;
; Added 2026-08-12 (t_9adf0889): Phi alias — War Machine.
; All per-model settings carry over unchanged from the --models-dir baseline
; (ctx_size=65536, n_gpu_layers=99, cache=q4_0 for both K and V, models-max=4).
;
; UPDATED (t_ryan_per_model_ctx, per Ryan/JARVIS request): Llama-3.1-8B and
; Phi-3.5-mini now get PER-MODEL ctx-size/flash-attn matched to actual
; workload instead of the uniform 65536 used by every model previously:
;   - Llama-3.1-8B-Instruct-Q4_K_M: ctx-size 8192  (tool-routing/micro-tasks)
;   - Phi-3.5-mini-instruct-Q8_0:   ctx-size 32768 (long web scrapes/logs)
; Both now request explicit flash-attn=true (was "auto"). Qwen3.6-35B is
; INTENTIONALLY left untouched at ctx-size 65536 / flash-attn auto — not part
; of this change. Existing aliases (Meta-Llama-3.1-8B-Instruct-4bit,
; Phi-3.5-mini-instruct-8bit) are PRESERVED unchanged to avoid breaking live
; Hermes custom_providers routing — see role README / deployment report for
; the alias-naming ambiguity flag (Ryan's pasted TOML used different alias
; strings: "llama-3.1-8b" / "phi-3.5-mini").
;
; UPDATED (t_34b96e83, 2026-08-13, per Ryan approval): Added nomic-embed-text-v1.5
; embedding model. Embedding models fold cleanly into the router preset via
; embedding=true. No alias needed — clients call it by section name.
; VRAM estimate ~90MB (negligible). sleep-idle-seconds=-1 keeps it always loaded
; since embedding calls are latency-sensitive and it costs near-nothing to hold.
; load-on-startup=true ensures the embedding endpoint is warm at boot without
; waiting for the first request. — War Machine.
; ------------------------------------------------------------------------------

; --- Production model: Qwen3.8-27B-Q4_K_M ------------------------------------
; Swapped from Qwen3.6-35B-A3B-UD-Q4_K_S by War Machine (t_f5f7e9ad, 2026-08-16).
; Ryan-directed swap. Qwen3.8-27B is a dense 27B VLM (Apache-2.0) from Alibaba,
; released Aug 2026. GGUF quantized by Unsloth Dynamic V3.0 (preview).
; Q4_K_M chosen: 17.1GB weights — fits RTX 3090 (24GB) with ~7GB headroom for
; KV cache at ctx=65536 (q4_0 KV). Smaller than prior Qwen3.6 at ~20GB.
; Native context: 262,144 tokens. Running at 65536 (Hermes floor) for now;
; can be raised later if needed.
; VRAM footprint (measured 2026-08-16): 17,068 MiB at ctx=32768 with q4_0 KV;
;   17,804 MiB at ctx=65536. Using 32768 (32K) to give more eviction headroom
;   on the 24GB RTX 3090 (nomic-embed 558MB always resident; total ~17.6GB).
;   Native context is 262,144 tokens; 32K is sufficient for Hermes usage.
; Architecture note: Qwen3.8 uses Gated DeltaNet; llama.cpp 6ea215d logs
; "fused Gated Delta Net (chunked) not supported, set to disabled" — falls
; back to non-fused implementation. Inference works correctly but may be
; slower on the GDN layers. An updated llama.cpp may improve throughput.
; load-on-startup NOT set (loads on first request, ~30-60s cold load).
; With models-max=2 in host_vars, nomic-embed occupies slot 1 (pinned),
; and the generative slot (slot 2) is Qwen3.8 on first request. Auxiliary
; models (Phi, Llama, Coder) evict Qwen3.8 when requested; Qwen3.8 evicts
; them in turn. One cold-load (~30-60s) per switch between Qwen3.8 and
; auxiliary models is expected and acceptable. In practice, once Hermes
; config.yaml references Qwen3.8 as primary, it stays resident.
; Primary model ID: Qwen3.8-27B-Q4_K_M
[Qwen3.8-27B-Q4_K_M]
model              = {{ llm_models_dir }}/Qwen3.8-27B-Q4_K_M.gguf
n-gpu-layers       = {{ llm_router_gpu_layers }}
ctx-size           = {{ llm_router_qwen38_ctx_size }}
cache-type-k       = {{ llm_router_cache_type_k }}
cache-type-v       = {{ llm_router_cache_type_v }}
batch-size         = {{ llm_router_batch_size }}
ubatch-size        = {{ llm_router_ubatch_size }}
parallel           = {{ llm_router_parallel }}

; --- Auxiliary model: Phi-3.5-mini-instruct-Q8_0 ----------------------------
; Primary model ID: Phi-3.5-mini-instruct-Q8_0 (unchanged from --models-dir)
; Alias:            Phi-3.5-mini-instruct-8bit (NEW — Ryan's config target)
; Both names resolve to this GGUF child process.
; ~3.8GB, auxiliary.title_generation consumer in Ryan's Hermes config.
; The alias is deployed — "model not found" errors are resolved.
;
; KNOWN ISSUE (2026-08-12, t_9adf0889):
;   json_schema response_format fails for Phi-3.5-mini in llama.cpp router
;   mode due to chat template grammar sampler incompatibility (GH #23460).
;   The grammar sampler generates root ::= "assistant|>\n" ... which fails
;   to initialize. This means Hermes auxiliary.title_generation still errors
;   with "HTTP 400: Failed to initialize samplers" when json_schema format
;   is requested. Without response_format (plain text), Phi works fine.
;
;   Resolution options:
;   a) Update auxiliary.title_generation.model in ~/.hermes/config.yaml to
;      Meta-Llama-3.1-8B-Instruct-Q4_K_M (which supports json_schema) — Ryan
;      needs to approve this config.yaml write (protected file).
;   b) Rebuild llama.cpp from a newer commit if this bug is fixed upstream.
;   c) Accept title generation degradation for Phi-specific structured output.
[Phi-3.5-mini-instruct-Q8_0]
model        = {{ llm_models_dir }}/Phi-3.5-mini-instruct-Q8_0.gguf
alias        = Phi-3.5-mini-instruct-8bit
n-gpu-layers = {{ llm_router_gpu_layers }}
ctx-size     = {{ llm_router_phi_ctx_size }}
flash-attn   = {{ llm_router_phi_flash_attn }}
cache-type-k = {{ llm_router_cache_type_k }}
cache-type-v = {{ llm_router_cache_type_v }}
batch-size   = {{ llm_router_batch_size }}
ubatch-size  = {{ llm_router_ubatch_size }}
parallel     = {{ llm_router_parallel }}

; --- Auxiliary model: Meta-Llama-3.1-8B-Instruct-Q4_K_M --------------------
; Primary model ID: Meta-Llama-3.1-8B-Instruct-Q4_K_M (unchanged from --models-dir)
; Alias:            Meta-Llama-3.1-8B-Instruct-4bit (NEW — friendlier name)
; Both names resolve to this GGUF child process.
; ~4.6GB, general-purpose small model. Works with json_schema structured output.
[Meta-Llama-3.1-8B-Instruct-Q4_K_M]
model        = {{ llm_models_dir }}/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf
alias        = Meta-Llama-3.1-8B-Instruct-4bit
n-gpu-layers = {{ llm_router_gpu_layers }}
ctx-size     = {{ llm_router_llama_ctx_size }}
flash-attn   = {{ llm_router_llama_flash_attn }}
cache-type-k = {{ llm_router_cache_type_k }}
cache-type-v = {{ llm_router_cache_type_v }}
batch-size   = {{ llm_router_batch_size }}
ubatch-size  = {{ llm_router_ubatch_size }}
parallel     = {{ llm_router_parallel }}

; --- Coder model: Qwen2.5-Coder-14B-Instruct-Q4_K_M -------------------------
; Primary model ID: Qwen2.5-Coder-14B-Instruct-Q4_K_M (filename-derived)
; Alias:            Qwen2.5-Coder-14B-Instruct-4bit (friendlier name)
; Both names resolve to this GGUF child process.
; ~8.4GB weights + ~0.6GB KV @ 16K ctx = ~9.0GB VRAM.
; ctx-size=16384, flash-attn=true per task t_55c164f5 / Ryan's request.
; Source: bartowski/Qwen2.5-Coder-14B-Instruct-GGUF (public, no auth)
; Added 2026-08-13 (t_55c164f5) — War Machine.
[Qwen2.5-Coder-14B-Instruct-Q4_K_M]
model        = {{ llm_models_dir }}/Qwen2.5-Coder-14B-Instruct-Q4_K_M.gguf
alias        = Qwen2.5-Coder-14B-Instruct-4bit
n-gpu-layers = {{ llm_router_gpu_layers }}
ctx-size     = {{ llm_router_coder_ctx_size }}
flash-attn   = {{ llm_router_coder_flash_attn }}
cache-type-k = {{ llm_router_cache_type_k }}
cache-type-v = {{ llm_router_cache_type_v }}
batch-size   = {{ llm_router_batch_size }}
ubatch-size  = {{ llm_router_ubatch_size }}
parallel     = {{ llm_router_parallel }}

; --- Embedding model: nomic-embed-text-v1.5 ----------------------------------
; Primary model ID: nomic-embed-text-v1.5 (section name / client-visible ID)
; ~84MB GGUF — negligible VRAM, always-loaded. Embedding endpoint: /v1/embeddings.
; embedding=true: required to expose /v1/embeddings and embed the model (not chat).
; n-gpu-layers=99: GPU offload all layers (tiny model, no reason to leave on CPU).
; ctx-size=8192: per task spec (OpenViking Phase 1b, t_34b96e83).
; load-on-startup=true: warm at boot — embedding callers (peter-parker) are
;   latency-sensitive; no cold-load wait on first request.
; sleep-idle-seconds=-1: never evict — ~84MB is negligible, always keep hot.
; NO flash-attn, NO KV cache params: embedding models use a different forward
;   pass (bidirectional, no autoregressive KV cache). These keys are irrelevant
;   for embedding inference and may be silently ignored or cause warnings; omit.
; Source: nomic-ai/nomic-embed-text-v1.5-GGUF (public, no auth needed)
; Added 2026-08-13 (t_34b96e83) — War Machine.
;
; FIXED (2026-08-14, t_openviking_embed_batch): the original section omitted
; batch-size/ubatch-size, so llama-server defaulted the PHYSICAL batch
; (ubatch-size) to 512 tokens. For embedding requests llama.cpp cannot split
; a single input across ubatches, so any OpenViking chunk over ~512 tokens
; large chunk over ~512 tokens (observed 2000-3400 tokens/chunk) failed hard with "input (N tokens) is too
; large to process. increase the physical batch size (current batch size:
; 512)". This tripped OpenViking's circuit breaker into an infinite
; fail/re-enqueue loop. Fix: set batch-size/ubatch-size to 4096 (comfortably
; over the observed max chunk size and under ctx-size=8192).
;
; FOLLOW-UP FINDING (2026-08-14, same task): after the batch-size fix landed,
; logs showed a SECOND, separate problem: llama.cpp capped the effective
; context to 2048 regardless of ctx-size=8192 ("n_ctx_seq (8192) > n_ctx_train
; (2048)" / "capping"). This is expected per the nomic-embed-text-v1.5-GGUF
; model card: the base GGUF's native RoPE training context is 2048; the
; original HF model reaches its benchmarked 8192-token context via Dynamic
; NTK-Aware RoPE scaling, which llama.cpp does not implement — so llama.cpp
; defaults to 2048 unless YaRN scaling is explicitly requested. Model card
; prescribes: --rope-scaling yarn --rope-freq-scale 0.75 alongside -c 8192.
; Added rope-scaling/rope-freq-scale below to actually reach 8192.
[nomic-embed-text-v1.5]
model              = {{ llm_models_dir }}/nomic-embed-text-v1.5-Q4_K_M.gguf
embedding          = true
n-gpu-layers       = {{ llm_router_gpu_layers }}
ctx-size           = {{ llm_router_nomic_ctx_size }}
batch-size         = {{ llm_router_nomic_batch_size }}
ubatch-size        = {{ llm_router_nomic_ubatch_size }}
rope-scaling       = yarn
rope-freq-scale    = 0.75
load-on-startup    = true
sleep-idle-seconds = -1