"""Freeze v2 executor with all curriculum references before opening model outputs."""

import hashlib
import json
from pathlib import Path
import numpy as np
from huggingface_hub import HfApi, hf_hub_download
import quantum_sandbox_v2 as sandbox

REPO = "itsalissonsilva/QuantumCoder-9B"
DATA_REV = "97bf11cde2ef2aeb43345a0da7eab3d8ea27993a"


def main():
    api = HfApi()
    assert api.model_info(REPO).private
    def get(name):
        return Path(hf_hub_download(REPO, "curriculum_v2/"+name, revision=DATA_REV))
    source = get("rows.json")
    manifest = json.loads(get("manifest.json").read_text())
    assert hashlib.sha256(source.read_bytes()).hexdigest() == manifest["rows_sha256"]
    rows = json.loads(source.read_text())
    versions = sandbox.initialize()
    isolation = sandbox.run("", 1, mode="isolation_check")
    assert isolation == dict(file_opens_blocked=True, network_blocked=True, uid=65534, environment_empty=True)
    for code in ["open('/etc/passwd')", "import os", "import numpy as np\nstate=np.load('/etc/passwd')", "x=().__class__", "eval('1+1')"]:
        try:
            sandbox.screen(code)
        except (ValueError, SyntaxError):
            continue
        raise AssertionError("Forbidden fixture passed")
    records = []
    for row in rows:
        result = sandbox.run(row["program"], row["qubits"])
        fidelity = None
        passed = False
        if result.get("status") == "executed":
            state = np.array(result["real"])+1j*np.array(result["imag"])
            target = np.array(row["state_real"])+1j*np.array(row["state_imag"])
            fidelity = float(abs(np.vdot(target, state))**2)
            passed = abs(result["norm"]-1)<1e-6 and fidelity>1-1e-6
        records.append(dict(id=row["id"], split=row["split"], framework=row["framework"], passed=passed, fidelity=fidelity,
                            execution={k:v for k,v in result.items() if k not in ["real","imag"]}))
        if len(records)%100==0:
            print(json.dumps(dict(stage="reference_checks", n=len(records), passed=sum(r["passed"] for r in records))), flush=True)
    report = dict(data_revision=DATA_REV, manifest=manifest, versions=versions, isolation=isolation,
                  reference_checks=records, all_passed=all(r["passed"] for r in records),
                  executor_sha256=hashlib.sha256(Path(sandbox.__file__).read_bytes()).hexdigest(),
                  scope="V2 independently frozen supported-Python executor. V1 remains unchanged. Adds RZ warmup and documented Cirq CX/Rx/Ry/Rz aliases; same nobody/seccomp isolation. No model outputs read by this preflight.")
    folder=Path("v2_executor_preflight")
    folder.mkdir(exist_ok=True)
    (folder/"preflight.json").write_text(json.dumps(report,indent=2))
    (folder/"quantum_sandbox_v2.py").write_bytes(Path(sandbox.__file__).read_bytes())
    (folder/"train_quantum_v2_preflight_pilot.py").write_bytes(Path(__file__).read_bytes())
    commit=api.upload_folder(repo_id=REPO,folder_path=str(folder),path_in_repo="v2_executor_preflight",
                             commit_message="Freeze isolated v2 executor against every fresh reference before reading model programs")
    print(json.dumps(dict(revision=commit.oid, all_passed=report["all_passed"], n=len(records))),flush=True)
    assert report["all_passed"], "Reference gate failed; do not score model programs"


if __name__ == "__main__":
    main()