#!/usr/bin/env python3
"""Cheap HF Jobs boot/log/runtime smoke for HYDRA/Feather images.

This command is intentionally non-training and non-secret-printing. It exists so
we can verify that an HF image starts, emits logs, sees the requested runtime
environment, and carries the checkpoint symbols needed by the real training
entrypoint before spending on data prep or training.
"""
from __future__ import annotations

import importlib
import json
import os
import sys
from pathlib import Path


SAFE_ENV_KEYS = [
    "FEATHER_GPU_PROFILE",
    "FEATHER_HF_FLAVOR",
    "FEATHER_RUNTIME_MODE",
    "FEATHER_HF_STRICT_RUNTIME_PREFLIGHT",
    "HYDRA_RUNTIME_PROFILE",
    "HYDRA_STRICT_OPTIMAL_COMPONENTS",
    "HYDRA_USE_NEMOTRON",
    "HYDRA_NEMOTRON_SINGLE_CONFIG",
    "HYDRA_LOCAL_SHARDS_ONLY",
    "HYDRA_TARGET_SHARDS",
    "HYDRA_TIME_BUDGET",
    "HYDRA_CKPT_INTERVAL",
    "HYDRA_EVAL_TOKENS",
    "HYDRA_HYENA_LAYERS",
    "HYDRA_FORCE_HTM_CPU",
    "HYDRA_HTM_FUSED",
    "HYDRA_HTM_BATCHED_FUSED",
    "HYDRA_DISABLE_FUSED_SDR_TRITON",
    "HYDRA_TOKEN_CACHE_GB",
    "HYDRA_DISABLE_TOKEN_CACHE",
    "HYDRA_HTM_STRICT_SCALE_FREE",
    "HYDRA_HTM_REGION_POOL_SIZE",
    "HYDRA_HTM_CHUNK_B",
    "HTM_CUDA_ARCH",
    "TORCH_CUDA_ARCH_LIST",
]


def _repo_candidates() -> list[Path]:
    here = Path(__file__).resolve()
    return [
        Path("/workspace/feather"),
        Path("/app"),
        here.parents[1] if len(here.parents) > 1 else here.parent,
    ]


def ensure_repo_on_path() -> None:
    for candidate in _repo_candidates():
        if (candidate / "hydra").exists() and str(candidate) not in sys.path:
            sys.path.insert(0, str(candidate))
            print(f"[boot_smoke] repo_path={candidate}", flush=True)
            return
    print("[boot_smoke] repo_path=<not-found>; using existing sys.path", flush=True)


def safe_env_summary() -> dict[str, str]:
    return {key: os.environ[key] for key in SAFE_ENV_KEYS if key in os.environ}


def _truthy_env(name: str) -> bool:
    return os.environ.get(name, "0").strip().lower() in {"1", "true", "yes", "on"}


def strict_optimal_preflight_requested() -> bool:
    return (
        _truthy_env("FEATHER_HF_STRICT_RUNTIME_PREFLIGHT")
        or os.environ.get("HYDRA_STRICT_OPTIMAL_COMPONENTS", "0") == "1"
        or os.environ.get("HYDRA_RUNTIME_PROFILE", "").strip().lower() == "optimal-strict"
    )


def _import_required_module(module_name: str):
    try:
        module = importlib.import_module(module_name)
    except Exception as exc:
        print(f"[strict_preflight] {module_name}=failed {type(exc).__name__}: {exc}", flush=True)
        return None
    print(f"[strict_preflight] {module_name}=ok", flush=True)
    return module


def run_strict_optimal_preflight() -> int:
    """Fail before training if the strict-optimal A10G fast path is unavailable.

    This is intentionally a runtime/image preflight, not a CPU fallback.  It
    verifies the same strict fast-path surfaces that otherwise fail only after a
    paid trainer has finished build/provenance setup.
    """
    print("[strict_preflight] phase=start", flush=True)
    failures: list[str] = []

    torch = _import_required_module("torch")
    if torch is None:
        failures.append("torch_import")
    else:
        try:
            cuda_available = bool(torch.cuda.is_available())
            device_count = int(torch.cuda.device_count()) if cuda_available else 0
            device_name = torch.cuda.get_device_name(0) if cuda_available and device_count else "<none>"
            if not cuda_available or device_count < 1:
                failures.append("torch_cuda")
                print(
                    f"[strict_preflight] torch_cuda=failed cuda_available={int(cuda_available)} device_count={device_count}",
                    flush=True,
                )
            else:
                print(
                    f"[strict_preflight] torch_cuda=ok device_count={device_count} device0={device_name}",
                    flush=True,
                )
        except Exception as exc:
            failures.append("torch_cuda")
            print(f"[strict_preflight] torch_cuda=failed {type(exc).__name__}: {exc}", flush=True)

    triton = _import_required_module("triton")
    if triton is None:
        failures.append("triton_import")
    else:
        try:
            active = triton.runtime.driver.active
            device = active.get_current_device()
            print(f"[strict_preflight] triton_driver=ok device={device}", flush=True)
        except Exception as exc:
            failures.append("triton_driver")
            print(f"[strict_preflight] triton_driver=failed {type(exc).__name__}: {exc}", flush=True)

    mamba = _import_required_module("mamba_ssm")
    if mamba is None or not hasattr(mamba, "Mamba3"):
        failures.append("mamba")
        print("[strict_preflight] mamba=missing Mamba3", flush=True)
    else:
        print("[strict_preflight] mamba=ok Mamba3=True", flush=True)

    fused_sdr = None
    for module_name in ("subsystems.fused_sdr_project",):
        try:
            module = importlib.import_module(module_name)
        except Exception as exc:
            print(f"[strict_preflight] fused_sdr_candidate={module_name} failed {type(exc).__name__}: {exc}", flush=True)
            continue
        if hasattr(module, "FusedSDRProject"):
            fused_sdr = (module_name, module)
            break
    if fused_sdr is None:
        failures.append("fused_sdr")
        print("[strict_preflight] fused_sdr=missing FusedSDRProject", flush=True)
    else:
        module_name, _module = fused_sdr
        print(f"[strict_preflight] fused_sdr=ok module={module_name}", flush=True)

    htm = _import_required_module("htm_rust")
    if htm is None:
        failures.append("htm_rust")
    else:
        has_region = hasattr(htm, "HTMRegion")
        has_gpu = hasattr(htm, "HTMRegionGpu")
        has_fused = hasattr(htm, "step_batch_fused_cuda")
        if not (has_region and has_gpu and has_fused):
            failures.append("htm_rust")
            print(
                "[strict_preflight] htm_rust=failed "
                f"HTMRegion={has_region} HTMRegionGpu={has_gpu} step_batch_fused_cuda={has_fused}",
                flush=True,
            )
        else:
            print(
                "[strict_preflight] htm_rust=ok "
                f"HTMRegion={has_region} HTMRegionGpu={has_gpu} step_batch_fused_cuda={has_fused}",
                flush=True,
            )

    if failures:
        print(f"[strict_preflight] phase=failed failures={','.join(failures)}", flush=True)
        return 5
    print("[strict_preflight] phase=done", flush=True)
    return 0


def main() -> int:
    print("[boot_smoke] phase=start", flush=True)
    ensure_repo_on_path()
    print(f"[boot_smoke] python={sys.version.split()[0]} executable={sys.executable}", flush=True)
    print(f"[boot_smoke] env={json.dumps(safe_env_summary(), sort_keys=True)}", flush=True)

    try:
        torch = importlib.import_module("torch")
        cuda_available = bool(torch.cuda.is_available())
        device_count = int(torch.cuda.device_count()) if cuda_available else 0
        device_name = torch.cuda.get_device_name(0) if cuda_available and device_count else "<none>"
        print(
            f"[boot_smoke] torch={torch.__version__} cuda_available={int(cuda_available)} "
            f"device_count={device_count} device0={device_name}",
            flush=True,
        )
    except Exception as exc:  # pragma: no cover - depends on image contents
        print(f"[boot_smoke] torch_import_failed={type(exc).__name__}: {exc}", flush=True)
        return 2

    if strict_optimal_preflight_requested():
        rc = run_strict_optimal_preflight()
        if rc != 0:
            return rc

    try:
        training = importlib.import_module("hydra.training")
        required = ["LATEST_CKPT", "PRETRAIN_FINAL_CKPT", "save_ckpt", "maybe_resume_ckpt"]
        missing = [name for name in required if not hasattr(training, name)]
        if missing:
            print(f"[boot_smoke] training_contract=missing {missing}", flush=True)
            return 3
        print(
            "[boot_smoke] training_contract=ok "
            f"LATEST_CKPT={getattr(training, 'LATEST_CKPT')} "
            f"PRETRAIN_FINAL_CKPT={getattr(training, 'PRETRAIN_FINAL_CKPT')}",
            flush=True,
        )
    except Exception as exc:  # pragma: no cover - depends on image contents
        print(f"[boot_smoke] training_import_failed={type(exc).__name__}: {exc}", flush=True)
        return 4

    print("[boot_smoke] phase=done", flush=True)
    return 0


if __name__ == "__main__":
    raise SystemExit(main())