Lumotia/docs/architecture-map/02-tauri-runtime/commands/llm.md

name, type, slice, last_verified

name	type	slice	last_verified
Local LLM commands	architecture-map-page	02-tauri-runtime	2026/05/09

commands::llm

Where you are: Architecture map → Tauri runtime → Commands → LLM

Plain English summary. Owns the local LLM lifecycle (recommend tier, check, download with progress events, load with sequential-GPU coordination, unload, delete, status, test) plus two inference commands the frontend uses on demand: cleanup-transcript-text (the "fix this" pass that runs after a transcription) and extract-content-tags (Phase 9, surface topic / intent tags on the History page). Diagnostic test command classifies load failures into VRAM / corrupt / permission / other so Settings shows actionable hints rather than raw llama.cpp exceptions.

At a glance

• Path: src-tauri/src/commands/llm.rs.
• LOC: 423.
• Tauri commands exposed (10 total):
  • recommend_llm_tier() -> Result<String, String>. No window guard — pure hardware probe.
  • check_llm_model(state, model_id) -> Result<LlmModelStatusDto, String>.
  • download_llm_model(window, app, model_id) -> Result<(), String>. Main-window only. Emits magnotia:llm-download-progress.
  • load_llm_model(window, state, model_id, use_gpu, concurrent) -> Result<(), String>. Main-window only.
  • unload_llm_model(window, state) -> Result<(), String>. Main-window only.
  • delete_llm_model(window, state, model_id) -> Result<(), String>. Main-window only.
  • get_llm_status(state) -> Result<bool, String>.
  • test_llm_model(window, state, model_id) -> Result<LlmTestResult, String>. Main-window only.
  • cleanup_transcript_text_cmd(window, state, transcript, profile_id, preset) -> Result<String, String>. Main-window only.
  • extract_content_tags_cmd(state, transcript) -> Result<ContentTags, String>.
• Events emitted: magnotia:llm-download-progress ({ modelId, done, total, percent }) — src-tauri/src/commands/llm.rs:76.
• Depends on: magnotia_llm::{LlmEngine, LlmModelId, ContentTags, model_manager::{download_model, model_path, model_info, recommend_tier, is_downloaded, delete_model}}, magnotia_ai_formatting::{llm_cleanup_text, LlmPromptPreset}, magnotia_core::hardware, magnotia_storage::database::list_profile_terms. Plus commands::power::PowerAssertion, commands::security::ensure_main_window.
• Called from frontend at: Settings → AI page (download / load / unload / delete / test), dictation result panel (cleanup_transcript_text_cmd), History page (extract_content_tags_cmd).

What's in here

LlmModelStatusDto (src-tauri/src/commands/llm.rs:11)

Frontend-facing status DTO: id, displayName, downloaded, loaded, sizeBytes, description, minimumRamBytes, recommendedVramBytes.

parse_model_id (:24)

Wraps model_id.parse() (which goes through the LlmModelId parser).

recommend_llm_tier (:28)

Probes RAM via magnotia_core::hardware::probe_system, multiplies the MB to bytes, then defers to magnotia_llm::model_manager::recommend_tier(ram, vram). No window guard — Settings calls this at first paint to populate the default tier suggestion.

check_llm_model (:40)

Combines model_info(id) (static metadata), model_manager::is_downloaded(id), and state.llm_engine.loaded_model_id() into a LlmModelStatusDto. Used by Settings to render per-tier status chips.

download_llm_model (:61)

ensure_main_window. Calls model_manager::download_model(id, progress_cb) with a closure that emits magnotia:llm-download-progress on each chunk. The percent calculation rounds against total > 0 (avoids division by zero on a server that doesn't return a content-length).

load_llm_model (:90)

ensure_main_window, parse_model_id, check the file exists. Implements the inverse Phase A.1 sequential-GPU guard: when concurrent == Some(false), unloads BOTH state.whisper_engine and state.parakeet_engine before loading the LLM. Default use_gpu = true. Loads inside spawn_blocking.

unload_llm_model (:122), delete_llm_model (:131), get_llm_status (:145)

Thin wrappers. delete_llm_model unloads first if the model is currently loaded.

LlmTestResult (:155) and test_llm_model (:186)

Settings → AI's "Test LLM" button. Brief item B.1 #27. Decision tree:

1. File missing → not-downloaded with a "Click Download" hint.
2. File present but ≤ 90% of expected size → incomplete (truncated download) with a re-download hint. 10% tolerance because info.size_bytes is rounded.
3. Same model already loaded → ready without disturbing the engine.
4. Otherwise attempt engine.load_model(id, &path, use_gpu=true) inside spawn_blocking and pass any error string to classify_llm_load_error.

classify_llm_load_error (:272)

Pure string classifier. Tested independently. Buckets: load-failed-vram (looks for out of memory, oom, allocation failed, vram, cudamalloc), load-failed-corrupt (looks for magic, invalid gguf, unsupported file format, tensor shape), load-failed-permission (looks for permission denied, access is denied), and load-failed-other for everything else. Each bucket pairs with a user-facing hint string.

cleanup_transcript_text_cmd (:362)

ensure_main_window. Resolves profile_id. Fetches profile_terms from storage. Resolves the preset (Brief item B.1 #15: Default, Email, Notes, Code). spawn_blocking runs llm_cleanup_text(&engine, &transcript, &profile_terms, resolved_preset) inside a PowerAssertion::begin("magnotia LLM cleanup") so macOS App Nap doesn't throttle mid-token.

extract_content_tags_cmd (:407)

Phase 9 LLM tagging. NO window guard (the History page lives in main but the command would be safe even without it; if you ever expose the History page in a secondary window, add the guard). Errors out cleanly if no LLM is loaded. spawn_blocking runs engine.extract_content_tags(&transcript) under the same App Nap power-assertion pattern.

Tests (:306)

Eight classify_llm_load_error cases cover the four classification buckets and edge cases (cudaMalloc, OOM, generic allocation failure, GGUF magic mismatch, unsupported file format, permission denied, Windows access denied, unknown error).

Data flow

Settings -> recommend_llm_tier() -> hardware probe -> tier string
Settings -> download_llm_model(model_id) -> model_manager::download_model
                                          -> per-chunk progress events
                                          -> file lands in ~/.magnotia/models/llm/
Settings -> load_llm_model(model_id, use_gpu, concurrent)
              -> if concurrent=false: unload whisper + parakeet
              -> spawn_blocking(engine.load_model)
Settings -> test_llm_model(model_id) -> tiered checks -> LlmTestResult
History page -> extract_content_tags_cmd(transcript) -> ContentTags { topics, intents }
Dictation result -> cleanup_transcript_text_cmd(transcript, profile_id, preset) -> cleaned text

Watch-outs

• Sequential-GPU guard is the inverse here. load_llm_model unloads transcription engines when concurrent=false. commands::models::ensure_model_loaded unloads the LLM. Settings owns the toggle; live transcription explicitly bypasses it (passes None). Confirm both halves stay in sync if you ever change the toggle's semantics.
• extract_content_tags_cmd lacks ensure_main_window. Intentional today, but if you change the ACL to expose this to a non-main window, add the guard.
• PowerAssertion is a no-op outside macOS. Long LLM cleanup on Linux can be idled by the compositor. See Power assertions and security.
• Partial-download detection uses 10% tolerance. A model that ships exactly 90% of expected size will be incorrectly flagged as incomplete. The expected size is rounded by model_manager, so empirically this is fine; if you tighten the rounding, also tighten the threshold.
• download_llm_model emits a percent rounded to u8. A frontend that wants smoother progress bars needs to use the raw done / total fields.
• The cleanup command silently passes an unrecognised preset as Default (LlmPromptPreset::parse returns Default for unknown strings). Consider erroring out instead so frontend bugs surface faster.

See also

• Models — the inverse sequential-GPU guard.
• Tasks — also calls engine.decompose_task_with_feedback / extract_tasks_with_feedback under the same App Nap pattern.
• Power assertions and security — PowerAssertion::begin is shared.
• Diagnostics — the test_llm_model failure messages cite "see Settings → About → Diagnostics bundle".
• Profiles — cleanup_transcript_text_cmd reads profile_terms from storage.