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Lumotia/src-tauri/src/commands/tasks.rs
Jake 089349d966
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agent: lumotia-rebrand — rust workspace crates magnotia-* -> lumotia-*
Phase 2 of the rebrand cascade. Renames all 9 workspace crates from
magnotia-* to lumotia-* plus the src-tauri binary crate name:

- magnotia-ai-formatting   -> lumotia-ai-formatting
- magnotia-audio           -> lumotia-audio
- magnotia-cloud-providers -> lumotia-cloud-providers
- magnotia-core            -> lumotia-core
- magnotia-hotkey          -> lumotia-hotkey
- magnotia-llm             -> lumotia-llm
- magnotia-mcp             -> lumotia-mcp
- magnotia-storage         -> lumotia-storage
- magnotia-transcription   -> lumotia-transcription
- magnotia                 -> lumotia (src-tauri binary)
- magnotia_lib             -> lumotia_lib (src-tauri lib target)

Crate directories (crates/audio/ etc.) stay as-is; only the Cargo.toml
[package] name field changes plus all consumer module imports
(magnotia_core -> lumotia_core, etc.).

Remaining magnotia_* references at this point are intentional and
scoped to later phases: tracing targets (Phase 4), DB setting keys
magnotia_preferences/magnotia_history (Phase 5).

cargo build --workspace passes. cargo test --workspace: 330 pass, 0 fail.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-13 08:48:09 +01:00

410 lines
13 KiB
Rust

// Tauri commands wrapping lumotia_storage task CRUD.
// Pattern mirrors transcripts.rs — TaskDto is the camelCase frontend shape,
// storage functions are aliased with db_ prefix to avoid name collisions.
use serde::{Deserialize, Serialize};
use uuid::Uuid;
use lumotia_llm::prompts::FeedbackExample as LlmFeedbackExample;
use lumotia_storage::{
complete_subtask_and_check_parent as db_complete_subtask, complete_task as db_complete_task,
delete_task as db_delete_task, get_task_by_id as db_get_task,
insert_subtask as db_insert_subtask, insert_task as db_insert_task,
list_feedback_examples as db_list_feedback_examples,
list_recent_completions as db_list_recent_completions, list_subtasks as db_list_subtasks,
list_tasks as db_list_tasks, set_task_energy as db_set_task_energy,
uncomplete_task as db_uncomplete_task, update_task as db_update_task, DailyCompletionCount,
FeedbackRow, FeedbackTargetType, TaskRow,
};
use crate::commands::power::PowerAssertion;
use crate::AppState;
/// Frontend-facing task shape. Matches the in-memory object in page.svelte.js.
#[derive(Debug, Clone, Serialize)]
#[serde(rename_all = "camelCase")]
pub struct TaskDto {
pub id: String,
pub text: String,
pub bucket: String,
pub list_id: Option<String>,
pub effort: Option<String>,
pub notes: String,
pub done: bool,
pub done_at: Option<String>,
pub created_at: String,
pub source_transcript_id: Option<String>,
pub parent_task_id: Option<String>,
pub energy: Option<String>,
}
impl From<TaskRow> for TaskDto {
fn from(r: TaskRow) -> Self {
Self {
id: r.id,
text: r.text,
bucket: r.bucket,
list_id: r.list_id,
effort: r.effort,
notes: r.notes,
done: r.done,
done_at: r.done_at,
created_at: r.created_at,
source_transcript_id: r.source_transcript_id,
parent_task_id: r.parent_task_id,
energy: r.energy,
}
}
}
/// Accepted energy tag values. Kept as a const so frontend and storage
/// validate against the same list. Migration v11 enforces the same
/// set via a CHECK constraint.
const ENERGY_LEVELS: &[&str] = &["high", "medium", "brain_dead"];
fn validate_energy(raw: Option<&str>) -> Result<Option<&str>, String> {
match raw {
None => Ok(None),
Some(s) if ENERGY_LEVELS.contains(&s) => Ok(Some(s)),
Some(other) => Err(format!(
"energy must be one of {:?} or null, got {:?}",
ENERGY_LEVELS, other
)),
}
}
#[derive(Debug, Deserialize)]
#[serde(rename_all = "camelCase")]
pub struct CreateTaskRequest {
pub id: String,
pub text: String,
pub bucket: String,
#[serde(default)]
pub source_transcript_id: Option<String>,
#[serde(default)]
pub list_id: Option<String>,
#[serde(default)]
pub effort: Option<String>,
#[serde(default)]
pub energy: Option<String>,
}
#[tauri::command]
pub async fn create_task_cmd(
state: tauri::State<'_, AppState>,
request: CreateTaskRequest,
) -> Result<TaskDto, String> {
let energy = validate_energy(request.energy.as_deref())?;
db_insert_task(
&state.db,
&request.id,
&request.text,
&request.bucket,
request.source_transcript_id.as_deref(),
request.list_id.as_deref(),
request.effort.as_deref(),
energy,
)
.await
.map_err(|e| e.to_string())?;
// Fetch the freshly-inserted row so the frontend can stop doing
// client-side object construction. Mirrors list_tasks_cmd's shape.
db_get_task(&state.db, &request.id)
.await
.map_err(|e| e.to_string())?
.map(TaskDto::from)
.ok_or_else(|| format!("Task {} not found after insert", request.id))
}
/// Patch-shaped update. Any field omitted (or explicit `null`) leaves the
/// column untouched via `COALESCE` in the storage layer. Matches
/// `update_transcript`'s partial-update philosophy. `done` / `doneAt` are
/// intentionally absent — those flow through `complete_task_cmd` /
/// `uncomplete_task_cmd` to stamp the server-side timestamp.
#[derive(Debug, Deserialize)]
#[serde(rename_all = "camelCase")]
pub struct UpdateTaskRequest {
#[serde(default)]
pub text: Option<String>,
#[serde(default)]
pub bucket: Option<String>,
#[serde(default)]
pub list_id: Option<String>,
#[serde(default)]
pub effort: Option<String>,
#[serde(default)]
pub notes: Option<String>,
}
#[tauri::command]
pub async fn update_task_cmd(
state: tauri::State<'_, AppState>,
id: String,
patch: UpdateTaskRequest,
) -> Result<TaskDto, String> {
let row = db_update_task(
&state.db,
&id,
patch.text.as_deref(),
patch.bucket.as_deref(),
patch.list_id.as_deref(),
patch.effort.as_deref(),
patch.notes.as_deref(),
)
.await
.map_err(|e| e.to_string())?;
Ok(TaskDto::from(row))
}
#[tauri::command]
pub async fn list_tasks_cmd(state: tauri::State<'_, AppState>) -> Result<Vec<TaskDto>, String> {
db_list_tasks(&state.db)
.await
.map(|rows| rows.into_iter().map(TaskDto::from).collect())
.map_err(|e| e.to_string())
}
#[tauri::command]
pub async fn complete_task_cmd(
state: tauri::State<'_, AppState>,
id: String,
) -> Result<(), String> {
db_complete_task(&state.db, &id)
.await
.map_err(|e| e.to_string())
}
#[tauri::command]
pub async fn delete_task_cmd(state: tauri::State<'_, AppState>, id: String) -> Result<(), String> {
db_delete_task(&state.db, &id)
.await
.map_err(|e| e.to_string())
}
#[tauri::command]
pub async fn uncomplete_task_cmd(
state: tauri::State<'_, AppState>,
id: String,
) -> Result<(), String> {
db_uncomplete_task(&state.db, &id)
.await
.map_err(|e| e.to_string())
}
/// Phase 3: set or clear the `energy` tag on a task. Dedicated command
/// rather than a field on `update_task_cmd` because the existing update
/// path uses `COALESCE` semantics where `None` means "preserve" — which
/// makes clearing the tag impossible. This command always writes exactly
/// what you send, including `None` to explicitly clear.
#[tauri::command]
pub async fn set_task_energy_cmd(
state: tauri::State<'_, AppState>,
id: String,
energy: Option<String>,
) -> Result<TaskDto, String> {
let validated = validate_energy(energy.as_deref())?;
let row = db_set_task_energy(&state.db, &id, validated)
.await
.map_err(|e| e.to_string())?;
Ok(TaskDto::from(row))
}
/// Convert HITL feedback rows fetched from storage into the few-shot
/// exemplar shape the LLM crate consumes. We reconstruct the `input`
/// (parent task text, transcript chunk) from `context_json` where the
/// recorder has stored it. Rows without usable input are dropped —
/// the prompt builder filters them too, but doing it here keeps the
/// exemplar list tight and the prompt budget predictable.
///
/// Malformed `context_json` is logged rather than silently dropped so
/// data-integrity regressions surface instead of disappearing.
fn to_llm_examples(rows: Vec<FeedbackRow>) -> Vec<LlmFeedbackExample> {
rows.into_iter()
.filter_map(|r| {
let raw = r.context_json.as_deref().unwrap_or("{}");
let ctx: serde_json::Value = match serde_json::from_str(raw) {
Ok(v) => v,
Err(e) => {
tracing::warn!(
target: "lumotia_lib::feedback",
row_id = r.id,
error = %e,
"skipping feedback row with malformed context_json"
);
return None;
}
};
let input = ctx
.get("input")
.and_then(|v| v.as_str())
.map(str::to_string)
.unwrap_or_default();
if input.trim().is_empty() {
return None;
}
Some(LlmFeedbackExample {
input,
original_output: r.original_text,
corrected_output: r.corrected_text,
})
})
.collect()
}
/// Rough character budget for the few-shot block. Qwen's tokenizer
/// averages ~3.5 chars per token in English, so 2000 chars is ~570
/// tokens — well inside the 64-token reserve + response-token gap
/// against the 8192-token context cap (see `LlmEngine::generate`).
///
/// Exceed this and we drop the oldest examples first. Rationale: the
/// retrieval already orders most-recent-first, and the most recent
/// correction is usually the one carrying the user's live preference.
const FEW_SHOT_CHAR_BUDGET: usize = 2000;
fn example_char_cost(ex: &LlmFeedbackExample) -> usize {
// Matches the render path in `prompts::render_feedback_exemplar`:
// "Input: {input}\nGood output: {good}". Prefix strings + newlines
// + the two bodies. Slight overestimate to leave headroom.
let good_len = ex
.corrected_output
.as_deref()
.or(ex.original_output.as_deref())
.map(str::len)
.unwrap_or(0);
ex.input.len() + good_len + 24
}
fn trim_to_budget(mut examples: Vec<LlmFeedbackExample>) -> Vec<LlmFeedbackExample> {
let mut running = 0usize;
let mut kept = Vec::with_capacity(examples.len());
for ex in examples.drain(..) {
let cost = example_char_cost(&ex);
if running + cost > FEW_SHOT_CHAR_BUDGET {
break;
}
running += cost;
kept.push(ex);
}
kept
}
#[tauri::command]
pub async fn decompose_and_store(
state: tauri::State<'_, AppState>,
parent_task_id: String,
profile_id: Option<String>,
) -> Result<Vec<TaskDto>, String> {
let parent = db_get_task(&state.db, &parent_task_id)
.await
.map_err(|e| e.to_string())?
.ok_or_else(|| format!("Task {parent_task_id} not found"))?;
// Pull recent micro-step feedback so the system prompt gets
// conditioned on the user's preferred decomposition style. We
// cap at 5 examples AND at a char budget to keep the prompt
// under token budget regardless of how much feedback has been
// captured, and scope by profile so per-profile styles do not
// leak into each other.
let examples = db_list_feedback_examples(
&state.db,
FeedbackTargetType::MicroStep,
5,
0,
profile_id.as_deref(),
)
.await
.map(to_llm_examples)
.map(trim_to_budget)
.unwrap_or_default();
let engine = state.llm_engine.clone();
let parent_text = parent.text.clone();
let steps = tokio::task::spawn_blocking(move || {
let _power_guard = PowerAssertion::begin("magnotia LLM micro-step decomposition");
engine.decompose_task_with_feedback(&parent_text, &examples)
})
.await
.map_err(|e| e.to_string())?
.map_err(|e| e.to_string())?;
let mut created = Vec::new();
for text in steps {
let id = Uuid::new_v4().to_string();
db_insert_subtask(&state.db, &id, &text, &parent_task_id)
.await
.map_err(|e| e.to_string())?;
if let Some(row) = db_get_task(&state.db, &id)
.await
.map_err(|e| e.to_string())?
{
created.push(TaskDto::from(row));
}
}
Ok(created)
}
#[tauri::command]
pub async fn extract_tasks_from_transcript_cmd(
state: tauri::State<'_, AppState>,
transcript: String,
profile_id: Option<String>,
) -> Result<Vec<String>, String> {
let examples = db_list_feedback_examples(
&state.db,
FeedbackTargetType::TaskExtraction,
5,
0,
profile_id.as_deref(),
)
.await
.map(to_llm_examples)
.map(trim_to_budget)
.unwrap_or_default();
let engine = state.llm_engine.clone();
tokio::task::spawn_blocking(move || {
let _power_guard = PowerAssertion::begin("magnotia LLM task extraction");
engine.extract_tasks_with_feedback(&transcript, &examples)
})
.await
.map_err(|e| e.to_string())?
.map_err(|e| e.to_string())
}
#[tauri::command]
pub async fn list_subtasks_cmd(
state: tauri::State<'_, AppState>,
parent_task_id: String,
) -> Result<Vec<TaskDto>, String> {
db_list_subtasks(&state.db, &parent_task_id)
.await
.map(|rows| rows.into_iter().map(TaskDto::from).collect())
.map_err(|e| e.to_string())
}
#[tauri::command]
pub async fn complete_subtask_cmd(
state: tauri::State<'_, AppState>,
subtask_id: String,
) -> Result<(), String> {
db_complete_subtask(&state.db, &subtask_id)
.await
.map_err(|e| e.to_string())
}
/// Phase 8: daily completion counts for the Tasks-page badge and the
/// 7-day momentum sparkline. Returns a fixed-length oldest-first
/// series. Empty days are explicit zeros.
#[tauri::command]
pub async fn list_recent_completions_cmd(
state: tauri::State<'_, AppState>,
days: u32,
) -> Result<Vec<DailyCompletionCount>, String> {
db_list_recent_completions(&state.db, days)
.await
.map_err(|e| e.to_string())
}