"""The agent's startup report of which runtime landed on the GPU (#1451).

Both runtimes fall back to the CPU without raising, so the report is the only
thing that says so. These pin the distinction it exists for: onnxruntime
listing the CUDA provider is not the same as the provider being able to load
its libraries.
"""

from __future__ import annotations

import types

from agent.fc_agent import accel


def _ort(providers, preload=None):
    mod = types.SimpleNamespace(
        __version__="1.30.0",
        __file__="/site/onnxruntime/__init__.py",
        get_available_providers=lambda: providers,
    )
    if preload is not None:
        mod.preload_dlls = preload
    return mod


def _imp(mod):
    return lambda name: mod


class _Cudart:
    """libcudart as ctypes sees it: cudaGetDeviceCount writes through a pointer."""

    def __init__(self, rc=0, count=1):
        self.rc = rc
        self.count = count
        self.cudaGetErrorString = lambda rc: b"unknown error"

    def cudaGetDeviceCount(self, ref):
        ref._obj.value = self.count
        return self.rc


def _loader(calls, cudart):
    def load(path, mode=0):
        calls.append(path)
        return cudart if path == "libcudart.so.13" else None
    return load


GPU_BUILD = ["CUDAExecutionProvider", "CPUExecutionProvider"]


def test_onnx_on_gpu_when_the_provider_loads_and_a_device_answers():
    calls = []
    s = accel.onnx_status(
        _imp(_ort(GPU_BUILD, lambda: calls.append("preload"))),
        load=_loader(calls, _Cudart()),
    )
    assert s["device"] == "cuda"
    assert calls[0] == "preload"
    assert any(c.endswith("capi/libonnxruntime_providers_cuda.so") for c in calls)


def test_onnx_libraries_loading_is_not_a_gpu_when_cuda_cannot_initialise():
    """The 2026-09-24 case: every library resolved, cuInit failed."""
    s = accel.onnx_status(_imp(_ort(GPU_BUILD)), load=_loader([], _Cudart(rc=999)))
    assert s["device"] == "cpu"
    assert "unknown error" in s["error"]


def test_onnx_listed_but_unloadable_reports_cpu_with_the_reason():
    def load(path, mode=0):
        if path.endswith("providers_cuda.so"):
            raise OSError("libcudart.so.13: cannot open shared object file")

    s = accel.onnx_status(_imp(_ort(GPU_BUILD)), load=load)
    assert s["device"] == "cpu"
    assert "libcudart.so.13" in s["error"]


def test_onnx_cpu_build_never_tries_the_cuda_library():
    def load(path, mode=0):
        raise AssertionError("a CPU build has no CUDA provider to load")

    s = accel.onnx_status(_imp(_ort(["CPUExecutionProvider"])), load=load)
    assert s["device"] == "cpu"


def test_torch_reports_cpu_when_cuda_is_unavailable():
    torch = types.SimpleNamespace(
        __version__="2.14.0+cu130",
        version=types.SimpleNamespace(cuda="13.0"),
        cuda=types.SimpleNamespace(is_available=lambda: False),
    )
    s = accel.torch_status(_imp(torch))
    assert s == {"version": "2.14.0+cu130", "cuda_build": "13.0", "device": "cpu"}


def test_a_missing_runtime_is_reported_not_raised():
    def imp(name):
        raise ImportError(f"No module named {name!r}")

    assert accel.torch_status(imp)["device"] == "unavailable"
    assert accel.onnx_status(imp)["device"] == "unavailable"


def test_summary_is_what_the_server_stores(monkeypatch):
    """Device plus a bounded reason, per runtime — sent on every lease."""
    monkeypatch.setattr(accel, "LAST", {
        "torch": {"version": "2.14.0", "device": "cuda", "gpu": "RTX"},
        "onnx": {"version": "1.30.0", "device": "cpu", "error": "e" * 500},
    })
    assert accel.summary() == {
        "torch": {"device": "cuda"},
        "onnx": {"device": "cpu", "error": "e" * 200},
    }


def test_summary_before_the_report_is_none(monkeypatch):
    monkeypatch.setattr(accel, "LAST", {})
    assert accel.summary() is None