feat: nightly agentic pre-generation of memory reels
Implement end-to-end nightly pre-generation of memory reels with agentic
scripting that grounds narration in calendar, location, messages, and RAG.
Sections A-E from the plan:
A. Extract produce_reel pipeline core from run_reel_job with
ScripterMode::Fast/Agentic and progress callbacks.
B. Agentic scripter: factor run_readonly_tool_loop from the insight
generator, build read-only tool gate, prompt builder with GPS, and
generate_script_agentic with fallback to fast path.
C. Precomputed reels ledger (SQLite table + DAO), GET /reels/precomputed
handler with validity gate, GET /reels/by-key/{key}/video streaming,
and normalize_library_key helper.
D. Nightly scheduler: spawn_pregen_scheduler with configurable hour,
run_pregen_batch (day/week/month spans), pregen_one with dedup and
disk-check, secs_until_next_run_hour time math.
E. user_ai_prefs passive mirror table + DAO for param capture in
create_reel_handler and replay in the scheduler.
Also fixes resolve_library_param signature to take &[Library] and adds
resolve_library_param_state wrapper for AppState callers.
New files: migrations/2026-06-13-000000_add_precomputed_reels/,
migrations/2026-06-13-000010_add_user_ai_prefs/,
src/database/precomputed_reel_dao.rs,
src/database/user_ai_prefs_dao.rs
This commit is contained in:
@@ -0,0 +1,212 @@
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use diesel::prelude::*;
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use diesel::sqlite::SqliteConnection;
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use std::ops::DerefMut;
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use std::sync::{Arc, Mutex};
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use crate::database::models::{UpsertUserAiPrefs, UserAiPrefs};
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use crate::database::schema;
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use crate::database::{DbError, DbErrorKind, connect};
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use crate::otel::trace_db_call;
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/// Generic single-row table that passively mirrors the latest client AI
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/// request parameters (voice, timezone, library). Read by the nightly
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/// pre-generation scheduler (Section D) to pick up user preferences.
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pub trait UserAiPrefsDao: Sync + Send {
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/// Read the single row; `None` when it hasn't been populated yet.
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fn get_prefs(
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&mut self,
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context: &opentelemetry::Context,
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) -> Result<Option<UserAiPrefs>, DbError>;
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/// Upsert the single row (id is always 1).
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#[allow(dead_code)]
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fn upsert_prefs(
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&mut self,
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context: &opentelemetry::Context,
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prefs: &UpsertUserAiPrefs,
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) -> Result<(), DbError>;
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}
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pub struct SqliteUserAiPrefsDao {
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connection: Arc<Mutex<SqliteConnection>>,
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}
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impl Default for SqliteUserAiPrefsDao {
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fn default() -> Self {
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Self::new()
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}
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}
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impl SqliteUserAiPrefsDao {
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pub fn new() -> Self {
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Self {
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connection: Arc::new(Mutex::new(connect())),
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}
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}
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#[cfg(test)]
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pub fn from_connection(conn: Arc<Mutex<SqliteConnection>>) -> Self {
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Self { connection: conn }
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}
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}
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impl UserAiPrefsDao for SqliteUserAiPrefsDao {
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fn get_prefs(
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&mut self,
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context: &opentelemetry::Context,
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) -> Result<Option<UserAiPrefs>, DbError> {
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trace_db_call(context, "query", "get_prefs", |_span| {
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use schema::user_ai_prefs::dsl;
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let mut connection = self
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.connection
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.lock()
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.expect("Unable to lock UserAiPrefsDao");
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dsl::user_ai_prefs
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.first::<UserAiPrefs>(connection.deref_mut())
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.optional()
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.map_err(|e| anyhow::anyhow!("Failed to get prefs: {}", e))
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})
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.map_err(|e| DbError::log(DbErrorKind::QueryError, e))
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}
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fn upsert_prefs(
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&mut self,
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context: &opentelemetry::Context,
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prefs: &UpsertUserAiPrefs,
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) -> Result<(), DbError> {
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trace_db_call(context, "upsert", "upsert_prefs", |_span| {
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use schema::user_ai_prefs::dsl;
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let mut connection = self
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.connection
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.lock()
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.expect("Unable to lock UserAiPrefsDao");
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// SQLite: INSERT on first call, UPDATE on subsequent calls.
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// The first INSERT creates the row with id=1 (auto-increment).
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// Subsequent calls UPDATE the existing row.
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let result = diesel::insert_into(dsl::user_ai_prefs)
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.values(prefs)
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.execute(connection.deref_mut());
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match result {
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Ok(_) => {
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// First insert succeeded.
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Ok(())
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}
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Err(_e) => {
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// Insert failed (likely due to duplicate key). Update instead.
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diesel::update(dsl::user_ai_prefs.filter(dsl::id.eq(1)))
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.set((
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dsl::voice.eq(&prefs.voice),
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dsl::tz_offset_minutes.eq(&prefs.tz_offset_minutes),
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dsl::library.eq(&prefs.library),
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dsl::updated_at.eq(&prefs.updated_at),
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))
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.execute(connection.deref_mut())
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.map_err(|e| anyhow::anyhow!("Failed to upsert prefs: {}", e))?;
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Ok(())
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}
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}
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})
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.map_err(|e| DbError::log(DbErrorKind::InsertError, e))
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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use diesel::Connection;
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use diesel_migrations::{EmbeddedMigrations, MigrationHarness, embed_migrations};
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const DB_MIGRATIONS: EmbeddedMigrations = embed_migrations!();
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fn setup_dao() -> SqliteUserAiPrefsDao {
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let mut conn = SqliteConnection::establish(":memory:")
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.expect("Unable to create in-memory db connection");
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conn.run_pending_migrations(DB_MIGRATIONS)
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.expect("Failure running DB migrations");
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SqliteUserAiPrefsDao::from_connection(Arc::new(Mutex::new(conn)))
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}
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fn ctx() -> opentelemetry::Context {
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opentelemetry::Context::new()
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}
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#[test]
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fn get_prefs_returns_none_when_empty() {
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let mut dao = setup_dao();
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let result = dao.get_prefs(&ctx()).unwrap();
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assert!(result.is_none());
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}
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#[test]
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fn upsert_prefs_inserts_row() {
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let mut dao = setup_dao();
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let now = 1_700_000_000i64;
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let prefs = UpsertUserAiPrefs {
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voice: Some("grandma".to_string()),
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tz_offset_minutes: Some(-480),
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library: Some("1".to_string()),
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updated_at: now,
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};
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dao.upsert_prefs(&ctx(), &prefs).unwrap();
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let row = dao.get_prefs(&ctx()).unwrap().unwrap();
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assert_eq!(row.id, 1);
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assert_eq!(row.voice, Some("grandma".to_string()));
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assert_eq!(row.tz_offset_minutes, Some(-480));
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assert_eq!(row.library, Some("1".to_string()));
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assert_eq!(row.updated_at, now);
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}
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#[test]
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fn upsert_prefs_replaces_existing() {
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let mut dao = setup_dao();
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let now1 = 1_700_000_000i64;
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let now2 = 1_800_000_000i64;
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let prefs1 = UpsertUserAiPrefs {
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voice: Some("grandma".to_string()),
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tz_offset_minutes: Some(-480),
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library: Some("1".to_string()),
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updated_at: now1,
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};
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dao.upsert_prefs(&ctx(), &prefs1).unwrap();
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let prefs2 = UpsertUserAiPrefs {
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voice: Some("dad".to_string()),
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tz_offset_minutes: Some(-300),
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library: None,
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updated_at: now2,
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};
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dao.upsert_prefs(&ctx(), &prefs2).unwrap();
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let row = dao.get_prefs(&ctx()).unwrap().unwrap();
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assert_eq!(row.voice, Some("dad".to_string()));
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assert_eq!(row.tz_offset_minutes, Some(-300));
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assert!(row.library.is_none());
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assert_eq!(row.updated_at, now2);
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}
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#[test]
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fn upsert_partial_fields() {
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let mut dao = setup_dao();
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let now = 1_700_000_000i64;
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let prefs = UpsertUserAiPrefs {
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voice: None,
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tz_offset_minutes: Some(-480),
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library: None,
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updated_at: now,
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};
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dao.upsert_prefs(&ctx(), &prefs).unwrap();
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let row = dao.get_prefs(&ctx()).unwrap().unwrap();
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assert_eq!(row.tz_offset_minutes, Some(-480));
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assert!(row.voice.is_none());
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assert!(row.library.is_none());
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}
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}
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