"""Tiny Computer Agent - an agentic harness that drives a real computer with a
tiny, fully local model.

The harness is deliberately boring: it owns the loop, the closed action vocabulary,
perception and the safety gates, so the model only ever answers one question -
"which item from this short menu, and which verb?"  Nothing here needs a network
call at run time, and the core imports nothing outside the standard library.

    from tiny_computer_agent import AgentLoop, GrabScreen, IndexedScreen, OcrDetector
    from tiny_computer_agent.models import TextPlannerBrain

    screen = IndexedScreen(GrabScreen(), OcrDetector())      # pixels -> labels
    brain = TextPlannerBrain()                               # 0.5B, CPU-friendly
    loop = AgentLoop(screen=screen, brain=brain)             # dry run by default
    episode = loop.run("save the document")
    print(episode.render())

An episode can be saved as a portable *trace*, replayed offline, and scored, so
"the model looked plausible on that screenshot" becomes a number:

    from tiny_computer_agent import Trace, benchmark, run_scenario

    trace = run_scenario(Scenario("click 'Save'", frames=[...], expected="Save"), brain)
    trace.save("traces/save.json")                           # diffable, no pixels
    print(benchmark(scenarios, {"planner": lambda s: PlannerBrain()}).render())
"""

from tiny_computer_agent.accessibility import (
    INTERACTIVE_ROLES,
    TEXT_ROLES,
    AccessibleNode,
    AtspiDetector,
    AtspiReader,
    TreeReader,
    UiaDetector,
    UiaReader,
    accessibility_available,
)
from tiny_computer_agent.act import (
    ActionResult,
    DryRunExecutor,
    Executor,
    InputUnavailable,
    PyAutoGuiExecutor,
    resolve_point,
)
from tiny_computer_agent.actions import (
    ACTION_KINDS,
    ACTION_MENU,
    Action,
    ActionError,
    parse_action,
)
from tiny_computer_agent.brain import (
    Brain,
    BrainError,
    DecisionMenu,
    GoalUnreachable,
    MenuItem,
    MockBrain,
    ModelBrain,
    PlannerBrain,
    extract_json_object,
    extract_json_objects,
    parse_decision,
)
from tiny_computer_agent.loop import AgentLoop, Episode, Step
from tiny_computer_agent.models import (
    DEFAULT_TEXT_MODEL,
    DEFAULT_VISION_MODEL,
    MODEL_BRAINS,
    TextPlannerBrain,
    VLMBrain,
    make_model_brain,
    model_cached,
    model_dependencies,
    pick_dtype,
    resolve_device,
)
from tiny_computer_agent.demo import fake_desktop, write_fake_desktop
from tiny_computer_agent.observe import (
    Element,
    FakeScreen,
    GrabScreen,
    ImageScreen,
    Observation,
    ScreenSource,
    ScreenUnavailable,
    normalise_label,
)
from tiny_computer_agent.desktop import (
    BRAIN_NAMES,
    DEFAULT_KILL_SWITCH,
    Check,
    build_agent,
    display_available,
    doctor,
    run_checks,
)
from tiny_computer_agent.perception import (
    AutoDetector,
    Detector,
    DetectorUnavailable,
    GridDetector,
    IndexedScreen,
    OcrDetector,
    detector_available,
    make_detector,
)
from tiny_computer_agent.safety import Policy, PolicyViolation
from tiny_computer_agent.trace import (
    Scenario,
    Scoreboard,
    Trace,
    TraceStep,
    Verdict,
    benchmark,
    benchmark_traces,
    load_traces,
    run_scenario,
    score,
    score_replay,
    score_trace,
)

__version__ = "0.3.0"

__all__ = [
    "ACTION_KINDS", "ACTION_MENU", "AccessibleNode", "Action",
    "ActionError", "ActionResult", "AgentLoop", "AtspiDetector",
    "AtspiReader", "AutoDetector", "BRAIN_NAMES", "Brain",
    "BrainError", "Check", "DEFAULT_KILL_SWITCH", "DEFAULT_TEXT_MODEL",
    "DEFAULT_VISION_MODEL", "DecisionMenu", "Detector", "DetectorUnavailable",
    "DryRunExecutor", "Element", "Episode", "Executor",
    "FakeScreen", "GoalUnreachable", "GrabScreen", "GridDetector",
    "INTERACTIVE_ROLES", "ImageScreen", "IndexedScreen", "InputUnavailable",
    "MODEL_BRAINS", "MenuItem", "MockBrain", "ModelBrain",
    "Observation", "OcrDetector", "PlannerBrain", "Policy",
    "PolicyViolation", "PyAutoGuiExecutor", "Scenario", "Scoreboard",
    "ScreenSource", "ScreenUnavailable", "Step", "TEXT_ROLES",
    "TextPlannerBrain", "Trace", "TraceStep", "TreeReader",
    "UiaDetector", "UiaReader", "VLMBrain", "Verdict",
    "__version__", "accessibility_available", "benchmark", "benchmark_traces",
    "build_agent", "detector_available", "display_available", "doctor",
    "extract_json_object", "extract_json_objects", "fake_desktop", "load_traces",
    "make_detector", "make_model_brain", "model_cached", "model_dependencies",
    "normalise_label", "parse_action", "parse_decision", "pick_dtype",
    "resolve_device", "resolve_point", "run_checks", "run_scenario",
    "score", "score_replay", "score_trace", "write_fake_desktop",
]