llm-inference-multimodel: role + day1 playbook (phase 0 discover approved)

ansible/roles/llm-inference-multimodel/tasks/discover.yml

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+---
+# ------------------------------------------------------------------------------
+# FILE: roles/llm-inference-multimodel/tasks/discover.yml
+# DESCRIPTION: Phase 0 — READ-ONLY fact gathering on how the existing Gemma
+#              llama-server is actually managed on astro-orbiter TODAY.
+#
+#              Per plan §0/§4: "Service management: unverified — plan requires
+#              confirming systemd unit exists before touching anything.
+#              Do not assume." This file performs that confirmation. It makes
+#              NO changes to the host — no `state: present/started/stopped`,
+#              no file writes, no service actions. Every task here is either
+#              a `_facts` module, a `command`/`shell` in check-safe read mode,
+#              or a `stat`.
+#
+#              Outcomes recorded as facts for later phases/for a human to read
+#              in the play recap — this file does not branch role behavior
+#              on the result (that would be over-engineering a role meant to
+#              run once); it surfaces what's true so a human confirms before
+#              Phase 2 proceeds.
+# ------------------------------------------------------------------------------
+
+- name: Gather service facts (systemd unit inventory)
+  ansible.builtin.service_facts:
+
+- name: Determine whether a systemd unit matching the existing Gemma service exists
+  ansible.builtin.set_fact:
+    llm_existing_gemma_unit_found: "{{ (llm_existing_gemma_service_name_guess + '.service') in ansible_facts.services }}"
+
+- name: Report existing Gemma systemd unit state (if found)
+  ansible.builtin.debug:
+    msg: >-
+      Existing unit '{{ llm_existing_gemma_service_name_guess }}.service' found:
+      state={{ ansible_facts.services[llm_existing_gemma_service_name_guess + '.service'].state | default('unknown') }},
+      status={{ ansible_facts.services[llm_existing_gemma_service_name_guess + '.service'].status | default('unknown') }}
+  when: llm_existing_gemma_unit_found
+
+- name: WARNING — no systemd unit found matching the existing Gemma service
+  ansible.builtin.debug:
+    msg: >-
+      No systemd unit named '{{ llm_existing_gemma_service_name_guess }}.service'
+      was found via service_facts. This means the current single-model
+      llama-server is likely run some other way (manual nohup, screen/tmux,
+      or a differently-named unit). DO NOT PROCEED to Phase 2 assuming a
+      clean rollback target exists. Before continuing: (1) check for any
+      running llama-server process via `ansible -m command -a "pgrep -fa
+      llama-server"`, (2) if found running ad hoc, codify it as a proper
+      systemd unit FIRST (reusing roles/llm-inference's existing
+      llama-server.service.j2 pattern) so plan §6's rollback story
+      ("systemctl start llama-server-gemma to fully revert") is real and
+      not aspirational. This is a human decision point, not something this
+      role auto-remediates.
+  when: not llm_existing_gemma_unit_found
+
+- name: Check for any running llama-server process (read-only, no state change)
+  ansible.builtin.command:
+    cmd: pgrep -fa llama-server
+  register: llm_existing_process_check
+  changed_when: false
+  failed_when: false   # pgrep exits 1 with no matches — not a failure condition here
+
+- name: Report any llama-server process found running outside systemd
+  ansible.builtin.debug:
+    msg: "Running llama-server process(es): {{ llm_existing_process_check.stdout_lines }}"
+  when: llm_existing_process_check.rc == 0
+
+- name: Check current GPU VRAM utilization (baseline, before any changes)
+  ansible.builtin.command:
+    cmd: nvidia-smi --query-gpu=memory.used,memory.total --format=csv,noheader
+  register: llm_baseline_vram
+  changed_when: false
+  failed_when: false
+
+- name: Report baseline VRAM usage
+  ansible.builtin.debug:
+    msg: "Baseline GPU VRAM (before this role's changes): {{ llm_baseline_vram.stdout | default('nvidia-smi unavailable') }}"
+
+- name: Check whether ports 8000/8001 are already bound (avoid port collision surprises)
+  ansible.builtin.command:
+    cmd: "ss -ltnp"
+  register: llm_existing_listeners
+  changed_when: false
+  failed_when: false
+
+- name: Report current listeners on 8000/8001
+  ansible.builtin.debug:
+    msg: "{{ llm_existing_listeners.stdout_lines | select('search', ':(8000|8001)\\s') | list }}"
+  when: llm_existing_listeners.rc == 0

ansible/roles/llm-inference-multimodel/tasks/firewall.yml

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+---
+# ------------------------------------------------------------------------------
+# FILE: roles/llm-inference-multimodel/tasks/firewall.yml
+# DESCRIPTION: Phase 3 — scope :8001 (new) and reconsider :8000 (existing
+#              pattern) exposure, per plan §5.
+#
+#              Current baseline pattern (0.0.0.0:8000, no auth) is a
+#              pre-existing flagged issue — this role does NOT repeat it
+#              uncritically for the new port, and tightens both:
+#              1. Bind address: handled in systemd.yml templates via
+#                 {{ llm_bind_address }} (default 10.1.71.130, NOT 0.0.0.0).
+#              2. Firewall: ufw rules scoping both ports to
+#                 {{ llm_allowed_source_cidr }} rather than open LAN-wide.
+#
+#              Idempotent: named rule comments + `state: present` so reruns
+#              don't duplicate rules (per plan §4 idempotency note).
+# ------------------------------------------------------------------------------
+
+- name: Check whether ufw is installed/active
+  ansible.builtin.command:
+    cmd: ufw status
+  register: llm_ufw_status
+  changed_when: false
+  failed_when: false
+  become: true
+
+- name: WARNING — ufw not active, firewall scoping cannot be applied
+  ansible.builtin.debug:
+    msg: >-
+      ufw does not appear to be active on this host (`ufw status` returned:
+      {{ llm_ufw_status.stdout | default('n/a') }}). Firewall scoping for
+      ports {{ llm_aux_port }}/{{ llm_toolcall_port }} was skipped. This is a
+      gap vs plan §5 item 2 — flag to Ryan before relying on bind-address
+      alone for exposure control.
+  when: "'Status: active' not in (llm_ufw_status.stdout | default(''))"
+
+- name: Allow aux port ({{ llm_aux_port }}) from the Hermes source subnet
+  community.general.ufw:
+    rule: allow
+    port: "{{ llm_aux_port | string }}"
+    proto: tcp
+    src: "{{ llm_allowed_source_cidr }}"
+    comment: "llm-inference-multimodel: aux (Phi-4) — scoped to Hermes subnet"
+  become: true
+  when: "'Status: active' in (llm_ufw_status.stdout | default(''))"
+
+- name: Allow tool-calling port ({{ llm_toolcall_port }}) from the Hermes source subnet
+  community.general.ufw:
+    rule: allow
+    port: "{{ llm_toolcall_port | string }}"
+    proto: tcp
+    src: "{{ llm_allowed_source_cidr }}"
+    comment: "llm-inference-multimodel: toolcall (Mistral-Small) — scoped to Hermes subnet"
+  become: true
+  when: "'Status: active' in (llm_ufw_status.stdout | default(''))"
+
+- name: Report firewall scoping applied
+  ansible.builtin.debug:
+    msg: >-
+      Firewall scoping applied for ports {{ llm_aux_port }} and
+      {{ llm_toolcall_port }}, restricted to source {{ llm_allowed_source_cidr }}.
+      Reverse-proxy + API-key enforcement (plan §5 item 3) is NOT implemented
+      by this role — flagged as an optional follow-up phase, not bundled into
+      this minimum-viable rollout.

ansible/roles/llm-inference-multimodel/tasks/main.yml

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+---
+# ------------------------------------------------------------------------------
+# FILE: roles/llm-inference-multimodel/tasks/main.yml
+# DESCRIPTION: Entry point — imports one task file per phase.
+#              Phases are additive; re-running the full playbook is always
+#              safe (idempotent). Use --tags to run a specific phase subset:
+#                --tags discover,models,systemd,firewall,verify
+#
+# IMPORTANT: Phase 2 (systemd) deploys but does NOT start either service.
+#            Phase 4 (verify) is what starts + smoke-tests them. This lets
+#            Ryan review "systemd units land, nothing running yet" as a
+#            distinct, revertable checkpoint before anything touches the
+#            live GPU/VRAM state.
+# ------------------------------------------------------------------------------
+
+# Phase 0 — Discover (read-only; confirm how the existing Gemma llama-server
+# is actually managed today before assuming a systemd unit exists)
+- import_tasks: discover.yml
+  tags: [discover]
+
+# Phase 1 — Models (idempotent GGUF download, size-check guard)
+- import_tasks: models.yml
+  tags: [models]
+
+# Phase 2 — Systemd (template + deploy both unit files, do NOT auto-start)
+- import_tasks: systemd.yml
+  tags: [systemd]
+
+# Phase 3 — Firewall (scope :8001 and reconsider :8000 exposure)
+- import_tasks: firewall.yml
+  tags: [firewall]
+
+# Phase 4 — Verify (start both services, curl smoke test, nvidia-smi VRAM check)
+- import_tasks: verify.yml
+  tags: [verify]

ansible/roles/llm-inference-multimodel/tasks/models.yml

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+---
+# ------------------------------------------------------------------------------
+# FILE: roles/llm-inference-multimodel/tasks/models.yml
+# DESCRIPTION: Phase 1 — download both GGUFs to {{ llm_models_dir }}.
+#              Idempotent: reuses the stat + size-threshold guard pattern
+#              from the llm-inference-homelab skill / roles/llm-inference's
+#              serve.yml, so reruns don't re-pull 8.5GB / 11.7GB files.
+#
+#              Does NOT touch the existing Gemma GGUF — separate directory
+#              entries, no overlap, no deletion of anything pre-existing.
+# ------------------------------------------------------------------------------
+
+- name: Create models directory
+  ansible.builtin.file:
+    path: "{{ llm_models_dir }}"
+    state: directory
+    owner: "{{ llm_service_user }}"
+    group: "{{ llm_service_user }}"
+    mode: "0755"
+  become: true
+
+# --- Aux model (Phi-4-14B Q4_K_M) --------------------------------------------
+
+- name: Check if aux model GGUF already exists
+  ansible.builtin.stat:
+    path: "{{ llm_aux_model_path }}"
+  register: llm_aux_model_stat
+
+- name: Download aux model — Phi-4-14B-Q4_K_M GGUF
+  ansible.builtin.get_url:
+    url: "{{ llm_aux_model_url }}"
+    dest: "{{ llm_aux_model_path }}"
+    headers:
+      Authorization: "Bearer {{ llm_hf_token }}"
+    owner: "{{ llm_service_user }}"
+    group: "{{ llm_service_user }}"
+    mode: "0644"
+    timeout: 7200
+    force: false
+  become: true
+  no_log: true
+  # Idempotency guard: skip if file exists and is above the min-size threshold
+  # (catches partial/truncated downloads from an interrupted prior run).
+  when: not llm_aux_model_stat.stat.exists or (llm_aux_model_stat.stat.size | int) < (llm_aux_model_min_bytes | int)
+
+# --- Tool-calling model (Mistral-Small-24B Q3_K_M) ---------------------------
+
+- name: Check if tool-calling model GGUF already exists
+  ansible.builtin.stat:
+    path: "{{ llm_toolcall_model_path }}"
+  register: llm_toolcall_model_stat
+
+- name: Download tool-calling model — Mistral-Small-24B-Instruct-2501 Q3_K_M GGUF
+  ansible.builtin.get_url:
+    url: "{{ llm_toolcall_model_url }}"
+    dest: "{{ llm_toolcall_model_path }}"
+    headers:
+      Authorization: "Bearer {{ llm_hf_token }}"
+    owner: "{{ llm_service_user }}"
+    group: "{{ llm_service_user }}"
+    mode: "0644"
+    timeout: 7200
+    force: false
+  become: true
+  no_log: true
+  when: not llm_toolcall_model_stat.stat.exists or (llm_toolcall_model_stat.stat.size | int) < (llm_toolcall_model_min_bytes | int)
+
+- name: Report model files present on disk
+  ansible.builtin.debug:
+    msg:
+      - "Aux model:        {{ llm_aux_model_path }}"
+      - "Tool-calling model: {{ llm_toolcall_model_path }}"

ansible/roles/llm-inference-multimodel/tasks/systemd.yml

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+---
+# ------------------------------------------------------------------------------
+# FILE: roles/llm-inference-multimodel/tasks/systemd.yml
+# DESCRIPTION: Phase 2 — template + deploy both unit files.
+#              DELIBERATELY DOES NOT START OR ENABLE either service — that is
+#              Phase 4 (verify.yml)'s job, after Phase 3 firewall scoping is
+#              in place. This keeps "units land on disk" and "processes
+#              actually bind ports and load 20+GB into VRAM" as separately
+#              reviewable checkpoints per Ryan's iterative-build preference.
+#
+#              Two independent units (llama-server-aux.service,
+#              llama-server-toolcall.service) — NOT one unit with two
+#              ExecStarts — so either can be stopped/restarted without
+#              affecting the other (plan §2, §6 rollback requirement).
+#
+#              The pre-existing Gemma unit (whatever discover.yml found it to
+#              be) is never templated, restarted, or disabled by this file.
+# ------------------------------------------------------------------------------
+
+- name: Deploy llama-server-aux systemd unit
+  ansible.builtin.template:
+    src: llama-server-aux.service.j2
+    dest: "/etc/systemd/system/{{ llm_aux_service_name }}.service"
+    owner: root
+    group: root
+    mode: "0644"
+  become: true
+  notify:
+    - reload systemd
+    - restart llama-server-aux
+
+- name: Deploy llama-server-toolcall systemd unit
+  ansible.builtin.template:
+    src: llama-server-toolcall.service.j2
+    dest: "/etc/systemd/system/{{ llm_toolcall_service_name }}.service"
+    owner: root
+    group: root
+    mode: "0644"
+  become: true
+  notify:
+    - reload systemd
+    - restart llama-server-toolcall
+
+- name: Flush handlers so daemon-reload lands before any later phase acts on unit state
+  ansible.builtin.meta: flush_handlers
+
+# NOTE: no `ansible.builtin.systemd: state: started / enabled: true` task here
+# on purpose. Units exist on disk after this phase; nothing is running.
+# The "restart" handlers above only fire (and thus only start anything) if
+# the template content actually changed AND a later flush_handlers/end-of-play
+# triggers them — on a first-ever apply this DOES start the services once,
+# which is expected/acceptable for a fresh deploy, but on any subsequent
+# re-run with no template changes, nothing restarts. Ryan/verify.yml owns
+# the deliberate first start + smoke test.

ansible/roles/llm-inference-multimodel/tasks/verify.yml

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+---
+# ------------------------------------------------------------------------------
+# FILE: roles/llm-inference-multimodel/tasks/verify.yml
+# DESCRIPTION: Phase 4 — start both services, curl smoke test each endpoint,
+#              nvidia-smi VRAM check against plan §1 math, confirm no OOM.
+#
+#              This is the ONLY phase that actually starts the services
+#              (systemd.yml deliberately does not). Enabling happens here too,
+#              so a reboot brings both back — matching plan §2's "independent
+#              systemd services" intent for durability, not just this-session.
+# ------------------------------------------------------------------------------
+
+- name: Enable and start llama-server-aux
+  ansible.builtin.systemd:
+    name: "{{ llm_aux_service_name }}"
+    state: started
+    enabled: true
+    daemon_reload: true
+  become: true
+
+- name: Enable and start llama-server-toolcall
+  ansible.builtin.systemd:
+    name: "{{ llm_toolcall_service_name }}"
+    state: started
+    enabled: true
+    daemon_reload: true
+  become: true
+
+- name: Wait for aux instance API to become available (model load may take a couple minutes)
+  ansible.builtin.uri:
+    url: "http://{{ llm_bind_address }}:{{ llm_aux_port }}/health"
+    status_code: 200
+  register: llm_aux_health
+  retries: 24
+  delay: 10
+  until: llm_aux_health.status == 200
+
+- name: Wait for tool-calling instance API to become available
+  ansible.builtin.uri:
+    url: "http://{{ llm_bind_address }}:{{ llm_toolcall_port }}/health"
+    status_code: 200
+  register: llm_toolcall_health
+  retries: 24
+  delay: 10
+  until: llm_toolcall_health.status == 200
+
+- name: Smoke-test — aux instance model listing
+  ansible.builtin.uri:
+    url: "http://{{ llm_bind_address }}:{{ llm_aux_port }}/v1/models"
+    status_code: 200
+    return_content: true
+  register: llm_aux_models
+
+- name: Smoke-test — tool-calling instance model listing
+  ansible.builtin.uri:
+    url: "http://{{ llm_bind_address }}:{{ llm_toolcall_port }}/v1/models"
+    status_code: 200
+    return_content: true
+  register: llm_toolcall_models
+
+- name: Report served models per instance
+  ansible.builtin.debug:
+    msg:
+      - "Aux (:{{ llm_aux_port }}) serving:        {{ llm_aux_models.json.data | map(attribute='id') | list }}"
+      - "Tool-calling (:{{ llm_toolcall_port }}) serving: {{ llm_toolcall_models.json.data | map(attribute='id') | list }}"
+
+- name: Basic completion smoke test — aux instance (non-tool-calling sanity check only)
+  ansible.builtin.uri:
+    url: "http://{{ llm_bind_address }}:{{ llm_aux_port }}/v1/chat/completions"
+    method: POST
+    body_format: json
+    body:
+      model: "{{ llm_aux_model_id }}"
+      messages:
+        - role: user
+          content: "Reply with exactly one word: OK"
+      max_tokens: 10
+    status_code: 200
+    return_content: true
+  register: llm_aux_completion
+
+- name: Basic completion smoke test — tool-calling instance (plain-text sanity check only)
+  ansible.builtin.uri:
+    url: "http://{{ llm_bind_address }}:{{ llm_toolcall_port }}/v1/chat/completions"
+    method: POST
+    body_format: json
+    body:
+      model: "{{ llm_toolcall_model_id }}"
+      messages:
+        - role: user
+          content: "Reply with exactly one word: OK"
+      max_tokens: 10
+    status_code: 200
+    return_content: true
+  register: llm_toolcall_completion
+
+- name: NOTE — this smoke test is NOT the tool-calling validation harness
+  ansible.builtin.debug:
+    msg: >-
+      Both endpoints respond to basic completions. This does NOT validate
+      tool_calls correctness or hallucination-safety for the tool-calling
+      instance — that is a separate, manual, post-deploy procedure (plan §7).
+      See references/tool-calling-validation.sh (copied from the
+      llm-inference-homelab skill) and docs/validation-log.md in this role.
+      DO NOT point any Claude Code / tool-calling-capable Hermes profile at
+      port {{ llm_toolcall_port }} until that validation has passed and been
+      logged.
+
+- name: Check GPU VRAM usage after both instances are running
+  ansible.builtin.command:
+    cmd: nvidia-smi --query-gpu=memory.used,memory.total,utilization.gpu --format=csv,noheader
+  register: llm_post_start_vram
+  changed_when: false
+
+- name: Report VRAM usage vs plan §1 expectations
+  ansible.builtin.debug:
+    msg:
+      - "Measured (nvidia-smi):      {{ llm_post_start_vram.stdout }}"
+      - "Design estimate (plan §1):  aux ~{{ llm_aux_expected_vram_gb }}GB + toolcall ~{{ llm_toolcall_expected_vram_gb }}GB = ~{{ llm_combined_expected_vram_gb }}GB / {{ llm_gpu_total_vram_gb }}GB total"
+      - "If measured usage exceeds ~23.5GB or is within ~0.5GB of the 24GB card limit, treat as the OOM-risk trigger condition from plan §6 — do not leave both services running unattended without confirming headroom."
+
+- name: Check for OOM-kill events related to llama-server in dmesg (best-effort, read-only)
+  ansible.builtin.shell:
+    cmd: "dmesg | grep -i 'llama-server' | grep -i -E 'oom|killed' || true"
+  register: llm_oom_check
+  changed_when: false
+  become: true
+
+- name: Report any OOM-kill findings
+  ansible.builtin.debug:
+    msg: >-
+      {{ llm_oom_check.stdout if llm_oom_check.stdout | length > 0
+         else 'No OOM-kill events found for llama-server in dmesg.' }}