Merge origin/main: sync Qwen3-8B no_think variant to Ansible repo (t_36e8ba68)
Resolved conflicts between localbafd76a(t_c5cef2b2, Qwen3-8B single-variant) and origin/main5cf4468(t_664289a0, Qwen3-8B dual-thinking deployment). Conflict resolution strategy: took origin/main version throughout — it is the authoritative result from t_664289a0 which deployed the live no_think config to astro-orbiter and already reflects the correct production state. Changes incorporated from origin/main: - defaults/main.yml: Qwen3-8B-Q4_K_M-no_think model entry (port 8107, n_gpu_layers=99, chat_template_file), row6 matrix entry, dual-thinking comment block. - templates/llama-server-router-preset.ini.j2: [Qwen3-8B-Q4_K_M] with sleep-idle-seconds=60 plus new [Qwen3-8B-Q4_K_M-no_think] section with chat-template-file directive. - templates/qwen3-no-think.jinja.j2: new file — Qwen3 template with enable_thinking=false. - tasks/models.yml: template deploy task for qwen3-no-think.jinja (chat_templates tag). - tasks/swapmode.yml: GATE 2 assert updated to 7 models. - templates/llama-swap-config.yaml.j2: chat_template_file flag support. Also pulled in monitoring defaults (llm_monitoring_enabled, VRAM exporter settings, Grafana dashboard vars, Prometheus scrape config) from origin/main monitoring branch.
This commit is contained in:
Hermes Agent service account
@@ -190,38 +190,6 @@ llm_router_nomic_ctx_size: 8192
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llm_router_nomic_batch_size: 4096
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llm_router_nomic_ubatch_size: 4096
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# --- Monitoring: VRAM exporter + Prometheus scrape + Grafana dashboard -------
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# Phase 3: GPU/LLM monitoring deployment (Wong, 2026-08-18)
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# Provides: VRAM textfile exporter, Prometheus scrape config for llama-swap
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# /metrics endpoint, Grafana 6-panel dashboard, PrometheusRule alert rules.
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#
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# Ref: roles/llm-inference-multimodel/references/monitoring-llm-homelab-ciro-luciotta-2026.md
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llm_monitoring_enabled: true # gate for monitoring tasks
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llm_vram_exporter_script: /opt/llama-server-monitoring/nvidia-smi-vram-exporter.sh
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llm_vram_exporter_cron_minute: "*" # run every minute
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llm_vram_exporter_gpu_index: 0 # GPU 0 (RTX 3090 on astro-orbiter)
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llm_vram_textfile_dir: /var/lib/node_exporter/textfile_collector
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# Alert thresholds (per Ciro Luciotta pattern)
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llm_vram_critical_mib: 24000 # ~90% of 24GB RTX 3090
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llm_kv_cache_spill_ratio: 0.92 # KV-cache spill threshold
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llm_throughput_baseline_tokens_per_min: 50 # baseline for degradation alert
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# Grafana dashboard
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llm_grafana_dashboard_uid: llama-swap-monitor
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llm_grafana_dashboard_title: "llama-swap GPU/LLM Monitoring"
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llm_grafana_dashboard_tags:
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- llm
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- llama-swap
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- gpu-monitoring
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- ciro-luciotta
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llm_grafana_dashboard_refresh: "30s"
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llm_grafana_dashboard_time_from: "now-24h"
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# Prometheus scrape job
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llm_prometheus_scrape_interval: "30s"
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llm_prometheus_scrape_timeout: "10s"
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# --- llama-swap mode (port 8001) -----------------------------------------------
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# Deploy llama-swap — Go-based hot-swap proxy (v250+) for model orchestration.
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# Replaces router mode entirely: single binary + YAML config.json, no --models-preset INI.
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@@ -317,26 +285,36 @@ llm_swapmode_models:
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sleep_idle_seconds: -1 # never idle (always ready for embeddings)
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load_on_startup: true
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# Added t_c5cef2b2 (2026-08-19, War Machine): Qwen3-8B aux model.
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# Dense 8B (not MoE). ~4.68GB weights at Q4_K_M. GPU-resident (~5.2GB total
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# including KV at 32K ctx). Thinking mode on by default — callers MUST send
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# /no_think prefix for latency-sensitive aux tasks. See INI template comments.
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# VRAM budget: Qwen3.8-27B (~17,804 MiB @ 65536 ctx) + Qwen3-8B (~5,300 MiB
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# @ 32K ctx) = ~23,104 MiB — fits in 24GB (24,576 MiB) with ~1.4GB headroom.
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# llama-swap evicts Qwen3.8 when Qwen3-8B is requested (cannot co-reside).
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# LRU eviction is the operative strategy; cold load ~5s for 5GB GGUF.
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# t_c5cef2b2 / t_664289a0 (2026-08-19): Qwen3-8B dual-thinking deployment.
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# Both variants point to the same GGUF. GPU-resident (~5.2GB each).
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# Cannot co-reside with Qwen3.8-27B-Q4_K_M; LRU eviction applies.
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# chat_template_file for no_think variant: {{ llm_models_dir }}/templates/qwen3-no-think.jinja
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- id: Qwen3-8B-Q4_K_M
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gguf_path: "{{ llm_models_dir }}/Qwen3-8B-Q4_K_M.gguf"
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port: 8106
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n_gpu_layers: -1 # -1 = auto-detect / all layers to GPU (~5GB, fits easily)
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n_gpu_layers: 99 # GPU-resident (thinking variant)
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ctx_size: 32768
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batch_size: 4096
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ubatch_size: 4096
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parallel: 1
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cache_type: q4_0
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flash_attn: true
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flash_attn: "true"
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sleep_idle_seconds: 60 # idle after 60s no requests
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- id: Qwen3-8B-Q4_K_M-no_think
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gguf_path: "{{ llm_models_dir }}/Qwen3-8B-Q4_K_M.gguf"
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port: 8107
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n_gpu_layers: 99 # GPU-resident (no-think variant)
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ctx_size: 32768
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batch_size: 4096
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ubatch_size: 4096
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parallel: 1
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cache_type: q4_0
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flash_attn: "true"
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sleep_idle_seconds: 60
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chat_template_file: "{{ llm_models_dir }}/templates/qwen3-no-think.jinja"
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# llama-swap matrix routing configuration
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# Each row defines a set of models that can be co-resident and hot-swappable
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# Syntax: "model1 & model2" = both models in same row (via v250 expression DSL)
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@@ -356,5 +334,13 @@ llm_swapmode_matrix_rows:
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- row: row4
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expr: "Phi-3.5-mini-instruct-Q8_0 & nomic-embed-text-v1.5" # Mini + embed
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# t_c5cef2b2 / t_664289a0 (2026-08-19): Qwen3-8B dual-thinking rows.
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# Both Qwen3-8B variants co-reside with nomic-embed but NOT with
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# Qwen3.8-27B-Q4_K_M (17.8GB). LRU eviction swaps between primary and
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# Qwen3-8B when needed. They CAN co-reside with each other (~10.4GB total)
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# but NOT simultaneously with Qwen3.8-27B.
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- row: row5
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expr: "Qwen3-8B-Q4_K_M & nomic-embed-text-v1.5" # Aux 8B + embed
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expr: "Qwen3-8B-Q4_K_M & nomic-embed-text-v1.5" # Thinking variant + embed
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- row: row6
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expr: "Qwen3-8B-Q4_K_M-no_think & nomic-embed-text-v1.5" # No-think variant + embed
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@@ -74,3 +74,30 @@
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loop_control:
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loop_var: staged_model
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tags: [models]
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# --- Chat template overrides ---------------------------------------------------
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# Deploy per-model chat template files used by llama-server via chat-template-file.
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# These are static files dropped into {{ llm_models_dir }}/templates/.
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# t_664289a0: qwen3-no-think.jinja — Qwen3 template with enable_thinking=false
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# hardcoded. Used by [Qwen3-8B-Q4_K_M-no_think] in the router preset INI and
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# the llama-swap config. The companion [Qwen3-8B-Q4_K_M] section uses the GGUF's
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# baked-in template (thinking ON by default).
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- name: Ensure chat template directory exists at {{ llm_models_dir }}/templates
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ansible.builtin.file:
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path: "{{ llm_models_dir }}/templates"
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state: directory
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owner: "{{ llm_service_user }}"
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group: "{{ llm_service_user }}"
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mode: "0755"
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become: true
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tags: [models, chat_templates]
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- name: Deploy qwen3-no-think.jinja (thinking=false hard-switch for Qwen3-8B no_think variant)
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ansible.builtin.template:
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src: qwen3-no-think.jinja.j2
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dest: "{{ llm_models_dir }}/templates/qwen3-no-think.jinja"
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owner: "{{ llm_service_user }}"
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group: "{{ llm_service_user }}"
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mode: "0644"
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become: true
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tags: [models, chat_templates]
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@@ -241,12 +241,12 @@
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when: llm_swapmode_enabled | default(false)
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tags: [swapmode_verify]
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- name: "[swapmode_verify] Assert all 5 models are discoverable"
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- name: "[swapmode_verify] Assert all 7 models are discoverable"
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ansible.builtin.assert:
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that:
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- llm_swapmode_models_list.json.data | map(attribute='id') | list | length == 5
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- llm_swapmode_models_list.json.data | map(attribute='id') | list | length == 7
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fail_msg: >-
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Expected 5 models in /v1/models response, got {{ llm_swapmode_models_list.json.data | length }}.
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Expected 7 models in /v1/models response, got {{ llm_swapmode_models_list.json.data | length }}.
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Models: {{ llm_swapmode_models_list.json.data | map(attribute='id') | list }}
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when: llm_swapmode_enabled | default(false)
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tags: [swapmode_verify]
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@@ -300,5 +300,6 @@
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✓ GATE 4: VRAM guard ({{ llm_swapmode_vram_used.stdout }} MiB < {{ llm_swapmode_vram_max_mib }} MiB) PASS
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llama-swap service is ready at http://{{ llm_swapmode_bind_address }}:{{ llm_swapmode_port }}/
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NOTE: 7 models registered (5 original + Qwen3-8B-Q4_K_M + Qwen3-8B-Q4_K_M-no_think).
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when: llm_swapmode_enabled | default(false)
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tags: [swapmode_verify]
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@@ -208,37 +208,19 @@ rope-freq-scale = 0.75
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load-on-startup = true
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sleep-idle-seconds = -1
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; --- Aux model: Qwen3-8B-Q4_K_M -----------------------------------------------
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; Added t_c5cef2b2 (2026-08-19, War Machine).
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; Qwen3-8B is a dense 8B model (Qwen3 family, Alibaba) for aux tasks:
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; intent classification, query rewriting, structured extraction, tool-call
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; construction, and draft generation. Chosen over Llama-3.1-8B for superior
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; json_schema grammar support and stronger instruction-following.
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;
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; Architecture: 36 layers, 32 Q heads, 8 KV heads (GQA), 32K native context,
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; 131K via YaRN. Q4_K_M GGUF from bartowski/Qwen_Qwen3-8B-GGUF. ~4.68GB weights.
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;
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; ctx-size=32768: native training context (safe, no YaRN extension needed).
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; VRAM at 32K ctx with q4_0 KV: ~4.68GB weights + ~0.5GB KV ≈ 5.2GB total.
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; Fits comfortably on RTX 3090 24GB. Co-resident with nomic-embed (~84MB):
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; ~5.3GB total — well within 24GB budget even as a warm auxiliary model.
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;
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; THINKING MODE NOTE (JARVIS clarification, t_c5cef2b2):
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; Qwen3-8B has thinking (chain-of-thought) mode ENABLED BY DEFAULT.
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; For latency-sensitive aux tasks (routing, rewriting, structured extraction),
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; disable at call time — NOT in this deployment config:
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; - Prompt prefix: begin the user message with "/no_think"
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; - Chat template override: pass enable_thinking=False in the template vars
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; (llama.cpp Jinja2 template: {% if enable_thinking is false %} ... )
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; Do NOT hardcode thinking=false here — this is a call-site concern.
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; Thinking mode IS appropriate for complex multi-step tool plans and long-context
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; summarization; leave that decision to the caller.
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;
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; Source: bartowski/Qwen_Qwen3-8B-GGUF (public, no auth). Stored locally as
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; Qwen3-8B-Q4_K_M.gguf (canonical name, trimmed from HF's Qwen_Qwen3-8B prefix).
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; n-gpu-layers=99: GPU (all layers). At ~5GB, fully GPU-resident with headroom.
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; flash-attn=true: Qwen3-8B uses standard attention; flash-attn is safe.
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; sleep-idle-seconds=60: evict after 60s idle to free GPU VRAM for Qwen3.8-27B.
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; --- Auxiliary model: Qwen3-8B-Q4_K_M (thinking variant) ----------------------
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; GGUF: bartowski/Qwen_Qwen3-8B-GGUF (5,027,784,224 bytes)
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; Thinking mode: ON BY DEFAULT (Qwen3 baked-in template, no override).
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; - Use for complex aux tasks: long-context summarization, multi-step tool
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; planning, structured extraction requiring CoT.
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; - To suppress thinking at request time, send /no_think prefix in the prompt
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; OR route to [Qwen3-8B-Q4_K_M-no_think] section below.
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; n-gpu-layers=99: GPU-resident (~5.2GB VRAM). Cannot co-reside with
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; Qwen3.8-27B-Q4_K_M (17.8GB). LRU eviction handles swapping.
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; ctx-size=32768: 32K context, q4_0 KV cache.
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; flash-attn=true: required for Qwen3 architecture at this context size.
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; sleep-idle-seconds=60: evict after 60s idle (free VRAM for primary model).
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; Added: t_c5cef2b2 (2026-08-19, War Machine) — initial Qwen3-8B deployment.
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[Qwen3-8B-Q4_K_M]
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model = {{ llm_models_dir }}/Qwen3-8B-Q4_K_M.gguf
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n-gpu-layers = 99
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@@ -249,4 +231,32 @@ cache-type-v = {{ llm_router_cache_type_v }}
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batch-size = {{ llm_router_batch_size }}
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ubatch-size = {{ llm_router_ubatch_size }}
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parallel = {{ llm_router_parallel }}
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sleep-idle-seconds = 60
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; --- Auxiliary model: Qwen3-8B-Q4_K_M (no-think variant) ----------------------
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; Secondary section serving the SAME GGUF with enable_thinking=False via an
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; overridden Jinja2 template. This gives low-latency, non-reasoning inference
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; for latency-sensitive aux tasks (intent classification, query rewriting,
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; structured extraction, tool-call construction, draft generation).
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;
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; Both sections point to the same .gguf file — llama-server spawns independent
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; child processes. VRAM cost: ~5.2GB per instance (~10.4GB total). Fits on
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; RTX 3090 24GB alongside nomic-embed (84MB).
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;
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; Thinking variant (Qwen3-8B-Q4_K_M) remains available for complex tasks that
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; benefit from CoT (long-context summarization, multi-step tool planning).
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;
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; Cannot co-reside with Qwen3.8-27B-Q4_K_M (17.8GB); LRU eviction applies.
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; Added: t_664289a0 (2026-08-19, War Machine) — dual thinking deployment.
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[Qwen3-8B-Q4_K_M-no_think]
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model = {{ llm_models_dir }}/Qwen3-8B-Q4_K_M.gguf
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n-gpu-layers = 99
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ctx-size = 32768
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flash-attn = true
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cache-type-k = {{ llm_router_cache_type_k }}
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cache-type-v = {{ llm_router_cache_type_v }}
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batch-size = {{ llm_router_batch_size }}
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ubatch-size = {{ llm_router_ubatch_size }}
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parallel = {{ llm_router_parallel }}
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chat-template-file = {{ llm_models_dir }}/templates/qwen3-no-think.jinja
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sleep-idle-seconds = 60
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@@ -39,6 +39,7 @@ models:
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--parallel {{ model.parallel }}
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{% if model.cache_type is defined %}--cache-type-k {{ model.cache_type }} --cache-type-v {{ model.cache_type }}{% endif %}
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{% if model.flash_attn is defined %}--flash-attn {{ model.flash_attn }}{% endif %}
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{% if model.chat_template_file is defined %}--chat-template-file {{ model.chat_template_file }}{% endif %}
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{% if model.sleep_idle_seconds is defined %}--sleep-idle-seconds {{ model.sleep_idle_seconds }}{% endif %}
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{% if model.load_on_startup is defined and model.load_on_startup %}--load-on-startup{% endif %}
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--host 127.0.0.1
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@@ -0,0 +1,103 @@
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{#
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FILE: roles/llm-inference-multimodel/templates/qwen3-no-think.jinja.j2
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DESCRIPTION: Qwen3 chat template with enable_thinking unconditionally false.
|
||||
|
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This is a chat-template FILE deployed to {{ llm_models_dir }}/templates/qwen3-no-think.jinja
|
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on astro-orbiter and referenced via chat-template-file in the INI preset for
|
||||
[Qwen3-8B-Q4_K_M-no_think]. The [Qwen3-8B-Q4_K_M] section uses the model's
|
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baked-in default template (thinking ON by default).
|
||||
|
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Mechanism: at the add_generation_prompt step, instead of checking
|
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"enable_thinking is defined and enable_thinking is false"
|
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we UNCONDITIONALLY emit the empty <think></think> prefix that suppresses CoT.
|
||||
This is the hard-switch documented in the Qwen3 template spec and confirmed in
|
||||
https://huggingface.co/blog/qwen-3-chat-template-deep-dive (section 1).
|
||||
|
||||
All other logic is identical to /opt/llama.cpp/models/templates/Qwen-Qwen3-0.6B.jinja
|
||||
(the shipped template for Qwen3). Only the final add_generation_prompt block differs.
|
||||
|
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Added: t_664289a0 (2026-08-19, War Machine) — dual thinking deployment.
|
||||
#}
|
||||
{%- if tools %}
|
||||
{{- '<|im_start|>system\n' }}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- messages[0].content + '\n\n' }}
|
||||
{%- endif %}
|
||||
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||
{%- for tool in tools %}
|
||||
{{- "\n" }}
|
||||
{{- tool | tojson }}
|
||||
{%- endfor %}
|
||||
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||
{%- else %}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
||||
{%- for message in messages[::-1] %}
|
||||
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||
{%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
|
||||
{%- set ns.multi_step_tool = false %}
|
||||
{%- set ns.last_query_index = index %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- for message in messages %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{%- set content = message.content %}
|
||||
{%- set reasoning_content = '' %}
|
||||
{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
|
||||
{%- set reasoning_content = message.reasoning_content %}
|
||||
{%- else %}
|
||||
{%- if '</think>' in message.content %}
|
||||
{%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
|
||||
{%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- if loop.index0 > ns.last_query_index %}
|
||||
{%- if loop.last or (not loop.last and reasoning_content) %}
|
||||
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- if message.tool_calls %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- message.content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{{- '<think>\n\n</think>\n\n' }}
|
||||
{%- endif %}
|
||||
Reference in New Issue
Block a user