run_phase1_prereq_audit_live.py 3.93 KB
#!/usr/bin/env /usr/local/miniconda3/bin/python
from __future__ import annotations

import argparse
import importlib
import json
from pathlib import Path
import sys
from typing import Any

import psycopg

ROOT = Path(__file__).resolve().parents[1]
if str(ROOT) not in sys.path:
    sys.path.insert(0, str(ROOT))

from workers._job_common import validate_schema
DEFAULT_OUTPUT = ROOT / 'data' / 'pgvector_eval' / 'music20' / 'phase1_prereq_audit_report.json'
MODEL_REQUIREMENTS = {
    'mert': ['numpy', 'torch', 'torchaudio', 'transformers'],
    'muq': ['numpy', 'torch', 'torchaudio', 'transformers'],
    'ecapa': ['numpy', 'torch', 'torchaudio', 'speechbrain'],
    'chromaprint': ['numpy'],
}


def check_import(name: str) -> dict[str, Any]:
    try:
        importlib.import_module(name)
        return {'package': name, 'available': True}
    except Exception as exc:  # noqa: BLE001
        return {'package': name, 'available': False, 'error_type': type(exc).__name__, 'error': str(exc).splitlines()[0]}


def load_jobs(conn: psycopg.Connection) -> list[dict[str, Any]]:
    rows = conn.execute(
        """
        SELECT fej.extraction_job_id, mr.model_name, mr.model_version, fs.embedding_dim, fej.target_scope
        FROM feature_extraction_job fej
        JOIN feature_set_registry fs ON fs.feature_set_id = fej.feature_set_id
        JOIN model_registry mr ON mr.model_id = fs.model_id
        ORDER BY fej.extraction_job_id;
        """
    ).fetchall()
    return [
        {
            'extraction_job_id': int(row[0]),
            'model_name': row[1],
            'model_version': row[2],
            'embedding_dim': int(row[3]) if row[3] is not None else None,
            'target_scope': row[4],
        }
        for row in rows
    ]


def main() -> None:
    ap = argparse.ArgumentParser()
    ap.add_argument('--dsn', required=True)
    ap.add_argument('--schema', default='acr_test')
    ap.add_argument('--downloads-root', default='/workspace/downloads')
    ap.add_argument('--output', default=str(DEFAULT_OUTPUT))
    args = ap.parse_args()

    schema = validate_schema(args.schema)
    downloads_root = Path(args.downloads_root)
    downloads_exists = downloads_root.exists()

    with psycopg.connect(args.dsn, autocommit=True) as conn:
        conn.execute(f'SET search_path TO {schema}, public;')
        jobs = load_jobs(conn)

    package_names = sorted({pkg for job in jobs for pkg in MODEL_REQUIREMENTS.get(job['model_name'], ['numpy'])})
    package_checks = {item['package']: item for item in (check_import(name) for name in package_names)}

    job_reports = []
    for job in jobs:
        required = MODEL_REQUIREMENTS.get(job['model_name'], ['numpy'])
        missing = [name for name in required if not package_checks[name]['available']]
        job_reports.append(
            {
                **job,
                'required_packages': required,
                'missing_packages': missing,
                'downloads_root_exists': downloads_exists,
                'ready_for_live_worker': downloads_exists and not missing,
            }
        )

    payload = {
        'schema': schema,
        'dsn_redacted': 'postgres://d2:***@127.0.0.1:5432/d2',
        'downloads_root': str(downloads_root),
        'downloads_root_exists': downloads_exists,
        'package_checks': package_checks,
        'jobs': job_reports,
        'summary': {
            'total_jobs': len(job_reports),
            'ready_jobs': sum(1 for job in job_reports if job['ready_for_live_worker']),
            'blocked_jobs': sum(1 for job in job_reports if not job['ready_for_live_worker']),
            'missing_packages_union': sorted({pkg for job in job_reports for pkg in job['missing_packages']}),
        },
    }
    out = Path(args.output)
    out.parent.mkdir(parents=True, exist_ok=True)
    out.write_text(json.dumps(payload, ensure_ascii=False, indent=2), encoding='utf-8')
    print(json.dumps(payload, ensure_ascii=False, indent=2))


if __name__ == '__main__':
    main()