Merge pull request 'feat: LLM queue optimizer — resource-aware batch scheduler (closes #2)' (#13) from feature/llm-queue-optimizer into main

Reviewed-on: #13

.gitignore

@@ -44,3 +44,7 @@ config/label_tool.yaml
 config/server.yaml
 
 demo/data/*.db
+demo/seed_demo.py
+
+# Git worktrees
+.worktrees/

app/app.py

@@ -42,12 +42,12 @@ def _startup() -> None:
     2. Auto-queues re-runs for any research generated without SearXNG data,
        if SearXNG is now reachable.
     """
+    # Reset only in-flight tasks — queued tasks survive for the scheduler to resume.
+    # MUST run before any submit_task() call in this function.
+    from scripts.db import reset_running_tasks
+    reset_running_tasks(get_db_path())
+
     conn = sqlite3.connect(get_db_path())
-    conn.execute(
-        "UPDATE background_tasks SET status='failed', error='Interrupted by server restart',"
-        " finished_at=datetime('now') WHERE status IN ('queued','running')"
-    )
-    conn.commit()
 
     # Auto-recovery: re-run LLM-only research when SearXNG is available
     try:

config/llm.yaml.example

@@ -64,3 +64,14 @@ vision_fallback_order:
 # Note: 'ollama' (alex-cover-writer) intentionally excluded — research
 # must never use the fine-tuned writer model, and this also avoids evicting
 # the writer from GPU memory while a cover letter task is in flight.
+
+# ── Scheduler — LLM batch queue optimizer ─────────────────────────────────────
+# The scheduler batches LLM tasks by model type to avoid GPU model switching.
+# VRAM budgets are conservative peak estimates (GB) for each task type.
+# Increase if your models are larger; decrease if tasks share GPU memory well.
+scheduler:
+  vram_budgets:
+    cover_letter: 2.5       # alex-cover-writer:latest (~2GB GGUF + headroom)
+    company_research: 5.0   # llama3.1:8b or vllm model
+    wizard_generate: 2.5    # same model family as cover_letter
+  max_queue_depth: 500      # max pending tasks per type before drops (with logged warning)

scripts/db.py

@@ -366,6 +366,18 @@ def kill_stuck_tasks(db_path: Path = DEFAULT_DB) -> int:
     return count
 
 
+def reset_running_tasks(db_path: Path = DEFAULT_DB) -> int:
+    """On restart: mark in-flight tasks failed. Queued tasks survive for the scheduler."""
+    conn = sqlite3.connect(db_path)
+    count = conn.execute(
+        "UPDATE background_tasks SET status='failed', error='Interrupted by restart',"
+        " finished_at=datetime('now') WHERE status='running'"
+    ).rowcount
+    conn.commit()
+    conn.close()
+    return count
+
+
 def purge_email_data(db_path: Path = DEFAULT_DB) -> tuple[int, int]:
     """Delete all job_contacts rows and email-sourced pending jobs.
     Returns (contacts_deleted, jobs_deleted).

scripts/task_runner.py

@@ -26,19 +26,29 @@ from scripts.db import (
 def submit_task(db_path: Path = DEFAULT_DB, task_type: str = "",
                 job_id: int = None,
                 params: str | None = None) -> tuple[int, bool]:
-    """Submit a background LLM task.
+    """Submit a background task.
 
-    Returns (task_id, True) if a new task was queued and a thread spawned.
+    LLM task types (cover_letter, company_research, wizard_generate) are routed
+    through the TaskScheduler for VRAM-aware batch scheduling.
+    All other types spawn a free daemon thread as before.
+
+    Returns (task_id, True) if a new task was queued.
     Returns (existing_id, False) if an identical task is already in-flight.
     """
     task_id, is_new = insert_task(db_path, task_type, job_id or 0, params=params)
     if is_new:
-        t = threading.Thread(
+        from scripts.task_scheduler import get_scheduler, LLM_TASK_TYPES
-            target=_run_task,
+        if task_type in LLM_TASK_TYPES:
-            args=(db_path, task_id, task_type, job_id or 0, params),
+            get_scheduler(db_path, run_task_fn=_run_task).enqueue(
-            daemon=True,
+                task_id, task_type, job_id or 0, params
-        )
+            )
-        t.start()
+        else:
+            t = threading.Thread(
+                target=_run_task,
+                args=(db_path, task_id, task_type, job_id or 0, params),
+                daemon=True,
+            )
+            t.start()
     return task_id, is_new
 
 

scripts/task_scheduler.py

@@ -0,0 +1,243 @@
+# scripts/task_scheduler.py
+"""Resource-aware batch scheduler for LLM background tasks.
+
+Routes LLM task types through per-type deques with VRAM-aware scheduling.
+Non-LLM tasks bypass this module — routing lives in scripts/task_runner.py.
+
+Public API:
+    LLM_TASK_TYPES  — set of task type strings routed through the scheduler
+    get_scheduler() — lazy singleton accessor
+    reset_scheduler() — test teardown only
+"""
+import logging
+import sqlite3
+import threading
+from collections import deque, namedtuple
+from pathlib import Path
+from typing import Callable, Optional
+
+# Module-level import so tests can monkeypatch scripts.task_scheduler._get_gpus
+try:
+    from scripts.preflight import get_gpus as _get_gpus
+except Exception:  # graceful degradation if preflight unavailable
+    _get_gpus = lambda: []
+
+logger = logging.getLogger(__name__)
+
+# Task types that go through the scheduler (all others spawn free threads)
+LLM_TASK_TYPES: frozenset[str] = frozenset({
+    "cover_letter",
+    "company_research",
+    "wizard_generate",
+})
+
+# Conservative peak VRAM estimates (GB) per task type.
+# Overridable per-install via scheduler.vram_budgets in config/llm.yaml.
+DEFAULT_VRAM_BUDGETS: dict[str, float] = {
+    "cover_letter":     2.5,   # alex-cover-writer:latest (~2GB GGUF + headroom)
+    "company_research": 5.0,   # llama3.1:8b or vllm model
+    "wizard_generate":  2.5,   # same model family as cover_letter
+}
+
+# Lightweight task descriptor stored in per-type deques
+TaskSpec = namedtuple("TaskSpec", ["id", "job_id", "params"])
+
+
+class TaskScheduler:
+    """Resource-aware LLM task batch scheduler. Use get_scheduler() — not direct construction."""
+
+    def __init__(self, db_path: Path, run_task_fn: Callable) -> None:
+        self._db_path = db_path
+        self._run_task = run_task_fn
+
+        self._lock = threading.Lock()
+        self._wake = threading.Event()
+        self._stop = threading.Event()
+        self._queues: dict[str, deque] = {}
+        self._active: dict[str, threading.Thread] = {}
+        self._reserved_vram: float = 0.0
+        self._thread: Optional[threading.Thread] = None
+
+        # Load VRAM budgets: defaults + optional config overrides
+        self._budgets: dict[str, float] = dict(DEFAULT_VRAM_BUDGETS)
+        config_path = db_path.parent.parent / "config" / "llm.yaml"
+        self._max_queue_depth: int = 500
+        if config_path.exists():
+            try:
+                import yaml
+                with open(config_path) as f:
+                    cfg = yaml.safe_load(f) or {}
+                sched_cfg = cfg.get("scheduler", {})
+                self._budgets.update(sched_cfg.get("vram_budgets", {}))
+                self._max_queue_depth = sched_cfg.get("max_queue_depth", 500)
+            except Exception as exc:
+                logger.warning("Failed to load scheduler config from %s: %s", config_path, exc)
+
+        # Warn on LLM types with no budget entry after merge
+        for t in LLM_TASK_TYPES:
+            if t not in self._budgets:
+                logger.warning(
+                    "No VRAM budget defined for LLM task type %r — "
+                    "defaulting to 0.0 GB (unlimited concurrency for this type)", t
+                )
+
+        # Detect total GPU VRAM; fall back to unlimited (999) on CPU-only systems.
+        # Uses module-level _get_gpus so tests can monkeypatch scripts.task_scheduler._get_gpus.
+        try:
+            gpus = _get_gpus()
+            self._available_vram: float = (
+                sum(g["vram_total_gb"] for g in gpus) if gpus else 999.0
+            )
+        except Exception:
+            self._available_vram = 999.0
+
+        # Durability: reload surviving 'queued' LLM tasks from prior run
+        self._load_queued_tasks()
+
+    def enqueue(self, task_id: int, task_type: str, job_id: int,
+                params: Optional[str]) -> None:
+        """Add an LLM task to the scheduler queue.
+
+        If the queue for this type is at max_queue_depth, the task is marked
+        failed in SQLite immediately (no ghost queued rows) and a warning is logged.
+        """
+        from scripts.db import update_task_status
+
+        with self._lock:
+            q = self._queues.setdefault(task_type, deque())
+            if len(q) >= self._max_queue_depth:
+                logger.warning(
+                    "Queue depth limit reached for %s (max=%d) — task %d dropped",
+                    task_type, self._max_queue_depth, task_id,
+                )
+                update_task_status(self._db_path, task_id, "failed",
+                                   error="Queue depth limit reached")
+                return
+            q.append(TaskSpec(task_id, job_id, params))
+
+        self._wake.set()
+
+    def start(self) -> None:
+        """Start the background scheduler loop thread. Call once after construction."""
+        self._thread = threading.Thread(
+            target=self._scheduler_loop, name="task-scheduler", daemon=True
+        )
+        self._thread.start()
+
+    def shutdown(self, timeout: float = 5.0) -> None:
+        """Signal the scheduler to stop and wait for it to exit."""
+        self._stop.set()
+        self._wake.set()  # unblock any wait()
+        if self._thread and self._thread.is_alive():
+            self._thread.join(timeout=timeout)
+
+    def _scheduler_loop(self) -> None:
+        """Main scheduler daemon — wakes on enqueue or batch completion."""
+        while not self._stop.is_set():
+            self._wake.wait(timeout=30)
+            self._wake.clear()
+
+            with self._lock:
+                # Defense in depth: reap externally-killed batch threads.
+                # In normal operation _active.pop() runs in finally before _wake fires,
+                # so this reap finds nothing — no double-decrement risk.
+                for t, thread in list(self._active.items()):
+                    if not thread.is_alive():
+                        self._reserved_vram -= self._budgets.get(t, 0.0)
+                        del self._active[t]
+
+                # Start new type batches while VRAM allows
+                candidates = sorted(
+                    [t for t in self._queues if self._queues[t] and t not in self._active],
+                    key=lambda t: len(self._queues[t]),
+                    reverse=True,
+                )
+                for task_type in candidates:
+                    budget = self._budgets.get(task_type, 0.0)
+                    # Always allow at least one batch to run even if its budget
+                    # exceeds _available_vram (prevents permanent starvation when
+                    # a single type's budget is larger than the VRAM ceiling).
+                    if self._reserved_vram == 0.0 or self._reserved_vram + budget <= self._available_vram:
+                        thread = threading.Thread(
+                            target=self._batch_worker,
+                            args=(task_type,),
+                            name=f"batch-{task_type}",
+                            daemon=True,
+                        )
+                        self._active[task_type] = thread
+                        self._reserved_vram += budget
+                        thread.start()
+
+    def _batch_worker(self, task_type: str) -> None:
+        """Serial consumer for one task type. Runs until the type's deque is empty."""
+        try:
+            while True:
+                with self._lock:
+                    q = self._queues.get(task_type)
+                    if not q:
+                        break
+                    task = q.popleft()
+                # _run_task is scripts.task_runner._run_task (passed at construction)
+                self._run_task(
+                    self._db_path, task.id, task_type, task.job_id, task.params
+                )
+        finally:
+            # Always release — even if _run_task raises.
+            # _active.pop here prevents the scheduler loop reap from double-decrementing.
+            with self._lock:
+                self._active.pop(task_type, None)
+                self._reserved_vram -= self._budgets.get(task_type, 0.0)
+            self._wake.set()
+
+    def _load_queued_tasks(self) -> None:
+        """Load pre-existing queued LLM tasks from SQLite into deques (called once in __init__)."""
+        llm_types = sorted(LLM_TASK_TYPES)  # sorted for deterministic SQL params in logs
+        placeholders = ",".join("?" * len(llm_types))
+        conn = sqlite3.connect(self._db_path)
+        rows = conn.execute(
+            f"SELECT id, task_type, job_id, params FROM background_tasks"
+            f" WHERE status='queued' AND task_type IN ({placeholders})"
+            f" ORDER BY created_at ASC",
+            llm_types,
+        ).fetchall()
+        conn.close()
+
+        for row_id, task_type, job_id, params in rows:
+            q = self._queues.setdefault(task_type, deque())
+            q.append(TaskSpec(row_id, job_id, params))
+
+        if rows:
+            logger.info("Scheduler: resumed %d queued task(s) from prior run", len(rows))
+
+
+# ── Singleton ─────────────────────────────────────────────────────────────────
+
+_scheduler: Optional[TaskScheduler] = None
+_scheduler_lock = threading.Lock()
+
+
+def get_scheduler(db_path: Path, run_task_fn: Callable = None) -> TaskScheduler:
+    """Return the process-level TaskScheduler singleton, constructing it if needed.
+
+    run_task_fn is required on the first call; ignored on subsequent calls.
+    Safety: inner lock + double-check prevents double-construction under races.
+    The outer None check is a fast-path performance optimisation only.
+    """
+    global _scheduler
+    if _scheduler is None:                      # fast path — avoids lock on steady state
+        with _scheduler_lock:
+            if _scheduler is None:              # re-check under lock (double-checked locking)
+                if run_task_fn is None:
+                    raise ValueError("run_task_fn required on first get_scheduler() call")
+                _scheduler = TaskScheduler(db_path, run_task_fn)
+                _scheduler.start()
+    return _scheduler
+
+
+def reset_scheduler() -> None:
+    """Shut down and clear the singleton. TEST TEARDOWN ONLY."""
+    global _scheduler
+    with _scheduler_lock:
+        if _scheduler is not None:
+            _scheduler.shutdown()
+            _scheduler = None

tests/test_task_runner.py

@@ -6,6 +6,14 @@ from unittest.mock import patch
 import sqlite3
 
 
+@pytest.fixture(autouse=True)
+def clean_scheduler():
+    """Reset the TaskScheduler singleton between tests to prevent cross-test contamination."""
+    yield
+    from scripts.task_scheduler import reset_scheduler
+    reset_scheduler()
+
+
 def _make_db(tmp_path):
     from scripts.db import init_db, insert_job
     db = tmp_path / "test.db"
@@ -143,14 +151,20 @@ def test_run_task_email_sync_file_not_found(tmp_path):
 
 
 def test_submit_task_actually_completes(tmp_path):
-    """Integration: submit_task spawns a thread that completes asynchronously."""
+    """Integration: submit_task routes LLM tasks through the scheduler and they complete."""
     db, job_id = _make_db(tmp_path)
     from scripts.db import get_task_for_job
+    from scripts.task_scheduler import get_scheduler
+    from scripts.task_runner import _run_task
+
+    # Prime the singleton with the correct db_path before submit_task runs.
+    # get_scheduler() already calls start() internally.
+    get_scheduler(db, run_task_fn=_run_task)
 
     with patch("scripts.generate_cover_letter.generate", return_value="Cover letter text"):
         from scripts.task_runner import submit_task
         task_id, _ = submit_task(db, "cover_letter", job_id)
-        # Wait for thread to complete (max 5s)
+        # Wait for scheduler to complete the task (max 5s)
         for _ in range(50):
             task = get_task_for_job(db, "cover_letter", job_id)
             if task and task["status"] in ("completed", "failed"):

tests/test_task_scheduler.py

@@ -0,0 +1,472 @@
+# tests/test_task_scheduler.py
+"""Tests for scripts/task_scheduler.py and related db helpers."""
+import sqlite3
+import threading
+from collections import deque
+from pathlib import Path
+
+import pytest
+
+from scripts.db import init_db, reset_running_tasks
+
+
+@pytest.fixture
+def tmp_db(tmp_path):
+    db = tmp_path / "test.db"
+    init_db(db)
+    return db
+
+
+def test_reset_running_tasks_resets_only_running(tmp_db):
+    """reset_running_tasks() marks running→failed but leaves queued untouched."""
+    conn = sqlite3.connect(tmp_db)
+    conn.execute(
+        "INSERT INTO background_tasks (task_type, job_id, status) VALUES (?,?,?)",
+        ("cover_letter", 1, "running"),
+    )
+    conn.execute(
+        "INSERT INTO background_tasks (task_type, job_id, status) VALUES (?,?,?)",
+        ("company_research", 2, "queued"),
+    )
+    conn.commit()
+    conn.close()
+
+    count = reset_running_tasks(tmp_db)
+
+    conn = sqlite3.connect(tmp_db)
+    rows = {r[0]: r[1] for r in conn.execute(
+        "SELECT task_type, status FROM background_tasks"
+    ).fetchall()}
+    conn.close()
+
+    assert count == 1
+    assert rows["cover_letter"] == "failed"
+    assert rows["company_research"] == "queued"
+
+
+def test_reset_running_tasks_returns_zero_when_nothing_running(tmp_db):
+    """Returns 0 when no running tasks exist."""
+    conn = sqlite3.connect(tmp_db)
+    conn.execute(
+        "INSERT INTO background_tasks (task_type, job_id, status) VALUES (?,?,?)",
+        ("cover_letter", 1, "queued"),
+    )
+    conn.commit()
+    conn.close()
+
+    assert reset_running_tasks(tmp_db) == 0
+
+
+from scripts.task_scheduler import (
+    TaskScheduler, LLM_TASK_TYPES, DEFAULT_VRAM_BUDGETS,
+    get_scheduler, reset_scheduler,
+)
+
+
+def _noop_run_task(*args, **kwargs):
+    """Stand-in for _run_task that does nothing."""
+    pass
+
+
+@pytest.fixture(autouse=True)
+def clean_scheduler():
+    """Reset singleton between every test."""
+    yield
+    reset_scheduler()
+
+
+def test_default_budgets_used_when_no_config(tmp_db):
+    """Scheduler falls back to DEFAULT_VRAM_BUDGETS when config key absent."""
+    s = TaskScheduler(tmp_db, _noop_run_task)
+    assert s._budgets == DEFAULT_VRAM_BUDGETS
+
+
+def test_config_budgets_override_defaults(tmp_db, tmp_path):
+    """Values in llm.yaml scheduler.vram_budgets override defaults."""
+    config_dir = tmp_db.parent.parent / "config"
+    config_dir.mkdir(parents=True, exist_ok=True)
+    (config_dir / "llm.yaml").write_text(
+        "scheduler:\n  vram_budgets:\n    cover_letter: 9.9\n"
+    )
+    s = TaskScheduler(tmp_db, _noop_run_task)
+    assert s._budgets["cover_letter"] == 9.9
+    # Non-overridden keys still use defaults
+    assert s._budgets["company_research"] == DEFAULT_VRAM_BUDGETS["company_research"]
+
+
+def test_missing_budget_logs_warning(tmp_db, caplog):
+    """A type in LLM_TASK_TYPES with no budget entry logs a warning."""
+    import logging
+    # Temporarily add a type with no budget
+    original = LLM_TASK_TYPES.copy() if hasattr(LLM_TASK_TYPES, 'copy') else set(LLM_TASK_TYPES)
+    from scripts import task_scheduler as ts
+    ts.LLM_TASK_TYPES = frozenset(LLM_TASK_TYPES | {"orphan_type"})
+    try:
+        with caplog.at_level(logging.WARNING, logger="scripts.task_scheduler"):
+            s = TaskScheduler(tmp_db, _noop_run_task)
+        assert any("orphan_type" in r.message for r in caplog.records)
+    finally:
+        ts.LLM_TASK_TYPES = frozenset(original)
+
+
+def test_cpu_only_system_gets_unlimited_vram(tmp_db, monkeypatch):
+    """_available_vram is 999.0 when _get_gpus() returns empty list."""
+    # Patch the module-level _get_gpus in task_scheduler (not preflight)
+    # so __init__'s _ts_mod._get_gpus() call picks up the mock.
+    monkeypatch.setattr("scripts.task_scheduler._get_gpus", lambda: [])
+    s = TaskScheduler(tmp_db, _noop_run_task)
+    assert s._available_vram == 999.0
+
+
+def test_gpu_vram_summed_across_all_gpus(tmp_db, monkeypatch):
+    """_available_vram sums vram_total_gb across all detected GPUs."""
+    fake_gpus = [
+        {"name": "RTX 3090", "vram_total_gb": 24.0, "vram_free_gb": 20.0},
+        {"name": "RTX 3090", "vram_total_gb": 24.0, "vram_free_gb": 18.0},
+    ]
+    monkeypatch.setattr("scripts.task_scheduler._get_gpus", lambda: fake_gpus)
+    s = TaskScheduler(tmp_db, _noop_run_task)
+    assert s._available_vram == 48.0
+
+
+def test_enqueue_adds_taskspec_to_deque(tmp_db):
+    """enqueue() appends a TaskSpec to the correct per-type deque."""
+    s = TaskScheduler(tmp_db, _noop_run_task)
+    s.enqueue(1, "cover_letter", 10, None)
+    s.enqueue(2, "cover_letter", 11, '{"key": "val"}')
+
+    assert len(s._queues["cover_letter"]) == 2
+    assert s._queues["cover_letter"][0].id == 1
+    assert s._queues["cover_letter"][1].id == 2
+
+
+def test_enqueue_wakes_scheduler(tmp_db):
+    """enqueue() sets the _wake event so the scheduler loop re-evaluates."""
+    s = TaskScheduler(tmp_db, _noop_run_task)
+    assert not s._wake.is_set()
+    s.enqueue(1, "cover_letter", 10, None)
+    assert s._wake.is_set()
+
+
+def test_max_queue_depth_marks_task_failed(tmp_db):
+    """When queue is at max_queue_depth, dropped task is marked failed in DB."""
+    from scripts.db import insert_task
+
+    s = TaskScheduler(tmp_db, _noop_run_task)
+    s._max_queue_depth = 2
+
+    # Fill the queue to the limit via direct deque manipulation (no DB rows needed)
+    from scripts.task_scheduler import TaskSpec
+    s._queues.setdefault("cover_letter", deque())
+    s._queues["cover_letter"].append(TaskSpec(99, 1, None))
+    s._queues["cover_letter"].append(TaskSpec(100, 2, None))
+
+    # Insert a real DB row for the task we're about to drop
+    task_id, _ = insert_task(tmp_db, "cover_letter", 3)
+
+    # This enqueue should be rejected and the DB row marked failed
+    s.enqueue(task_id, "cover_letter", 3, None)
+
+    conn = sqlite3.connect(tmp_db)
+    row = conn.execute(
+        "SELECT status, error FROM background_tasks WHERE id=?", (task_id,)
+    ).fetchone()
+    conn.close()
+
+    assert row[0] == "failed"
+    assert "depth" in row[1].lower()
+    # Queue length unchanged
+    assert len(s._queues["cover_letter"]) == 2
+
+
+def test_max_queue_depth_logs_warning(tmp_db, caplog):
+    """Queue depth overflow logs a WARNING."""
+    import logging
+    from scripts.db import insert_task
+    from scripts.task_scheduler import TaskSpec
+
+    s = TaskScheduler(tmp_db, _noop_run_task)
+    s._max_queue_depth = 0  # immediately at limit
+
+    task_id, _ = insert_task(tmp_db, "cover_letter", 1)
+    with caplog.at_level(logging.WARNING, logger="scripts.task_scheduler"):
+        s.enqueue(task_id, "cover_letter", 1, None)
+
+    assert any("depth" in r.message.lower() for r in caplog.records)
+
+
+# ── Threading helpers ─────────────────────────────────────────────────────────
+
+def _make_recording_run_task(log: list, done_event: threading.Event, expected: int):
+    """Returns a mock _run_task that records (task_id, task_type) and sets done when expected count reached."""
+    def _run(db_path, task_id, task_type, job_id, params):
+        log.append((task_id, task_type))
+        if len(log) >= expected:
+            done_event.set()
+    return _run
+
+
+def _start_scheduler(tmp_db, run_task_fn, available_vram=999.0):
+    s = TaskScheduler(tmp_db, run_task_fn)
+    s._available_vram = available_vram
+    s.start()
+    return s
+
+
+# ── Tests ─────────────────────────────────────────────────────────────────────
+
+def test_deepest_queue_wins_first_slot(tmp_db):
+    """Type with more queued tasks starts first when VRAM only fits one type."""
+    log, done = [], threading.Event()
+
+    # Build scheduler but DO NOT start it yet — enqueue all tasks first
+    # so the scheduler sees the full picture on its very first wake.
+    run_task_fn = _make_recording_run_task(log, done, 4)
+    s = TaskScheduler(tmp_db, run_task_fn)
+    s._available_vram = 3.0  # fits cover_letter (2.5) but not +company_research (5.0)
+
+    # Enqueue cover_letter (3 tasks) and company_research (1 task) before start.
+    # cover_letter has the deeper queue and must win the first batch slot.
+    for i in range(3):
+        s.enqueue(i + 1, "cover_letter", i + 1, None)
+    s.enqueue(4, "company_research", 4, None)
+
+    s.start()  # scheduler now sees all tasks atomically on its first iteration
+    assert done.wait(timeout=5.0), "timed out — not all 4 tasks completed"
+    s.shutdown()
+
+    assert len(log) == 4
+    cl = [i for i, (_, t) in enumerate(log) if t == "cover_letter"]
+    cr = [i for i, (_, t) in enumerate(log) if t == "company_research"]
+    assert len(cl) == 3 and len(cr) == 1
+    assert max(cl) < min(cr), "All cover_letter tasks must finish before company_research starts"
+
+
+def test_fifo_within_type(tmp_db):
+    """Tasks of the same type execute in arrival (FIFO) order."""
+    log, done = [], threading.Event()
+    s = _start_scheduler(tmp_db, _make_recording_run_task(log, done, 3))
+
+    for task_id in [10, 20, 30]:
+        s.enqueue(task_id, "cover_letter", task_id, None)
+
+    assert done.wait(timeout=5.0), "timed out — not all 3 tasks completed"
+    s.shutdown()
+
+    assert [task_id for task_id, _ in log] == [10, 20, 30]
+
+
+def test_concurrent_batches_when_vram_allows(tmp_db):
+    """Two type batches start simultaneously when VRAM fits both."""
+    started = {"cover_letter": threading.Event(), "company_research": threading.Event()}
+    all_done = threading.Event()
+    log = []
+
+    def run_task(db_path, task_id, task_type, job_id, params):
+        started[task_type].set()
+        log.append(task_type)
+        if len(log) >= 2:
+            all_done.set()
+
+    # VRAM=10.0 fits both cover_letter (2.5) and company_research (5.0) simultaneously
+    s = _start_scheduler(tmp_db, run_task, available_vram=10.0)
+    s.enqueue(1, "cover_letter", 1, None)
+    s.enqueue(2, "company_research", 2, None)
+
+    all_done.wait(timeout=5.0)
+    s.shutdown()
+
+    # Both types should have started (possibly overlapping)
+    assert started["cover_letter"].is_set()
+    assert started["company_research"].is_set()
+
+
+def test_new_tasks_picked_up_mid_batch(tmp_db):
+    """A task enqueued while a batch is running is consumed in the same batch."""
+    log, done = [], threading.Event()
+    task1_started = threading.Event()   # fires when task 1 begins executing
+    task2_ready = threading.Event()     # fires when task 2 has been enqueued
+
+    def run_task(db_path, task_id, task_type, job_id, params):
+        if task_id == 1:
+            task1_started.set()         # signal: task 1 is now running
+            task2_ready.wait(timeout=2.0)  # wait for task 2 to be in the deque
+        log.append(task_id)
+        if len(log) >= 2:
+            done.set()
+
+    s = _start_scheduler(tmp_db, run_task)
+    s.enqueue(1, "cover_letter", 1, None)
+    task1_started.wait(timeout=2.0)    # wait until task 1 is actually executing
+    s.enqueue(2, "cover_letter", 2, None)
+    task2_ready.set()                  # unblock task 1 so it finishes
+
+    assert done.wait(timeout=5.0), "timed out — task 2 never picked up mid-batch"
+    s.shutdown()
+
+    assert log == [1, 2]
+
+
+def test_worker_crash_releases_vram(tmp_db):
+    """If _run_task raises, _reserved_vram returns to 0 and scheduler continues."""
+    log, done = [], threading.Event()
+
+    def run_task(db_path, task_id, task_type, job_id, params):
+        if task_id == 1:
+            raise RuntimeError("simulated failure")
+        log.append(task_id)
+        done.set()
+
+    s = _start_scheduler(tmp_db, run_task, available_vram=3.0)
+    s.enqueue(1, "cover_letter", 1, None)
+    s.enqueue(2, "cover_letter", 2, None)
+
+    assert done.wait(timeout=5.0), "timed out — task 2 never completed after task 1 crash"
+    s.shutdown()
+
+    # Second task still ran, VRAM was released
+    assert 2 in log
+    assert s._reserved_vram == 0.0
+
+
+def test_get_scheduler_returns_singleton(tmp_db):
+    """Multiple calls to get_scheduler() return the same instance."""
+    s1 = get_scheduler(tmp_db, _noop_run_task)
+    s2 = get_scheduler(tmp_db, _noop_run_task)
+    assert s1 is s2
+
+
+def test_singleton_thread_safe(tmp_db):
+    """Concurrent get_scheduler() calls produce exactly one instance."""
+    instances = []
+    errors = []
+
+    def _get():
+        try:
+            instances.append(get_scheduler(tmp_db, _noop_run_task))
+        except Exception as e:
+            errors.append(e)
+
+    threads = [threading.Thread(target=_get) for _ in range(20)]
+    for t in threads:
+        t.start()
+    for t in threads:
+        t.join()
+
+    assert not errors
+    assert len(set(id(s) for s in instances)) == 1  # all the same object
+
+
+def test_reset_scheduler_cleans_up(tmp_db):
+    """reset_scheduler() shuts down the scheduler; no threads linger."""
+    s = get_scheduler(tmp_db, _noop_run_task)
+    thread = s._thread
+    assert thread.is_alive()
+
+    reset_scheduler()
+
+    thread.join(timeout=2.0)
+    assert not thread.is_alive()
+
+    # After reset, get_scheduler creates a fresh instance
+    s2 = get_scheduler(tmp_db, _noop_run_task)
+    assert s2 is not s
+
+
+def test_durability_loads_queued_llm_tasks_on_startup(tmp_db):
+    """Scheduler loads pre-existing queued LLM tasks into deques at construction."""
+    from scripts.db import insert_task
+
+    # Pre-insert queued rows simulating a prior run
+    id1, _ = insert_task(tmp_db, "cover_letter", 1)
+    id2, _ = insert_task(tmp_db, "company_research", 2)
+
+    s = TaskScheduler(tmp_db, _noop_run_task)
+
+    assert len(s._queues.get("cover_letter", [])) == 1
+    assert s._queues["cover_letter"][0].id == id1
+    assert len(s._queues.get("company_research", [])) == 1
+    assert s._queues["company_research"][0].id == id2
+
+
+def test_durability_excludes_non_llm_queued_tasks(tmp_db):
+    """Non-LLM queued tasks are not loaded into the scheduler deques."""
+    from scripts.db import insert_task
+
+    insert_task(tmp_db, "discovery", 0)
+    insert_task(tmp_db, "email_sync", 0)
+
+    s = TaskScheduler(tmp_db, _noop_run_task)
+
+    assert "discovery" not in s._queues or len(s._queues["discovery"]) == 0
+    assert "email_sync" not in s._queues or len(s._queues["email_sync"]) == 0
+
+
+def test_durability_preserves_fifo_order(tmp_db):
+    """Queued tasks are loaded in created_at (FIFO) order."""
+    conn = sqlite3.connect(tmp_db)
+    # Insert with explicit timestamps to control order
+    conn.execute(
+        "INSERT INTO background_tasks (task_type, job_id, params, status, created_at)"
+        " VALUES (?,?,?,?,?)", ("cover_letter", 1, None, "queued", "2026-01-01 10:00:00")
+    )
+    conn.execute(
+        "INSERT INTO background_tasks (task_type, job_id, params, status, created_at)"
+        " VALUES (?,?,?,?,?)", ("cover_letter", 2, None, "queued", "2026-01-01 09:00:00")
+    )
+    conn.commit()
+    ids = [r[0] for r in conn.execute(
+        "SELECT id FROM background_tasks ORDER BY created_at ASC"
+    ).fetchall()]
+    conn.close()
+
+    s = TaskScheduler(tmp_db, _noop_run_task)
+
+    loaded_ids = [t.id for t in s._queues["cover_letter"]]
+    assert loaded_ids == ids
+
+
+def test_non_llm_tasks_bypass_scheduler(tmp_db):
+    """submit_task() for non-LLM types invoke _run_task directly, not enqueue()."""
+    from scripts import task_runner
+
+    # Initialize the singleton properly so submit_task routes correctly
+    s = get_scheduler(tmp_db, _noop_run_task)
+
+    run_task_calls = []
+    enqueue_calls = []
+
+    original_run_task = task_runner._run_task
+    original_enqueue = s.enqueue
+
+    def recording_run_task(*args, **kwargs):
+        run_task_calls.append(args[2])  # task_type is 3rd arg
+
+    def recording_enqueue(task_id, task_type, job_id, params):
+        enqueue_calls.append(task_type)
+
+    import unittest.mock as mock
+    with mock.patch.object(task_runner, "_run_task", recording_run_task), \
+         mock.patch.object(s, "enqueue", recording_enqueue):
+        task_runner.submit_task(tmp_db, "discovery", 0)
+
+    # discovery goes directly to _run_task; enqueue is never called
+    assert "discovery" not in enqueue_calls
+    # The scheduler deque is untouched
+    assert "discovery" not in s._queues or len(s._queues["discovery"]) == 0
+
+
+def test_llm_tasks_routed_to_scheduler(tmp_db):
+    """submit_task() for LLM types calls enqueue(), not _run_task directly."""
+    from scripts import task_runner
+
+    s = get_scheduler(tmp_db, _noop_run_task)
+
+    enqueue_calls = []
+    original_enqueue = s.enqueue
+
+    import unittest.mock as mock
+    with mock.patch.object(s, "enqueue", side_effect=lambda *a, **kw: enqueue_calls.append(a[1]) or original_enqueue(*a, **kw)):
+        task_runner.submit_task(tmp_db, "cover_letter", 1)
+
+    assert "cover_letter" in enqueue_calls