"""swe_bench_verified_agentic: same data as swe_bench_verified, agentic bench.

Separate bench name so both variants coexist (single-turn oracle vs
multi-turn agent); source/split/fields identical — the difference lives
in the recipe (env loop + official harness scoring) and config."""

from ..registry import register_dataset
from ..spec import DatasetSpec


@register_dataset(
    DatasetSpec(
        name='swe_bench_verified_agentic',
        source='princeton-nlp/SWE-bench_Verified',
        split='test',
        task_type='agent',
        tags=['code', 'agent', 'swe'],
        requires=['docker'],
        description='SWE-bench Verified (agentic): multi-turn bash agent in '
                    'the per-instance /testbed container.',
    )
)
def swe_bench_verified_agentic():
    def to_sample(record: dict):
        from .swe_bench_verified import _record_to_sample

        s = _record_to_sample(record)
        # official make_test_spec requires these raw fields
        md = s.metadata or {}
        md.setdefault('version', record.get('version') or '')
        md.setdefault('patch', record.get('patch') or '')
        md.setdefault('hints_text', record.get('hints_text') or '')
        md.setdefault('created_at', record.get('created_at') or '')
        md['problem_statement'] = record.get('problem_statement') or s.input_text
        s.metadata = md
        return s

    return to_sample