scripts/validate_mirror_parity.py

#!/usr/bin/env python3
"""Validate parity between the repo and prepared Hugging Face mirrors.

This is a publisher-side check. It compares critical website data, figures, and
validator scripts across the local repo, prepared HF Space bundle, prepared HF
artifact dataset bundle, and prepared HF model bundle before upload.
"""

from __future__ import annotations

import argparse
import hashlib
import json
from datetime import datetime, timezone
from pathlib import Path


ROOT = Path(__file__).resolve().parents[1]
DEFAULT_HF_ROOT = ROOT.parent / "hf_publish"
DEFAULT_OUTPUT = ROOT / "docs/data/mirror_parity.json"
QWEN3_FUTURE_TASK_PROBE_RUN_ID = "xperience10m_qwen3_omni_v6_future_task_probes_a100_20260616T143608Z"
QWEN3_RETRIEVAL_TASK_PROBE_RUN_IDS = [
    "xperience10m_qwen3_omni_v6_retrieval_task_probes_a100_20260617T175919Z",
    "xperience10m_qwen3_omni_v6_cross_modal_retrieval_probe_a100_20260618T000000Z",
    "xperience10m_qwen3_omni_v6_camera_view_sync_mosaic_tile_a100_20260619T0305Z",
    "xperience10m_qwen3_omni_v6_sensor_target_probes_a100_20260619T000000Z",
    "xperience10m_qwen3_omni_v6_interaction_text_task15_a100_20260620T010305Z",
]
COSMOS3_SUPER_RETRIEVAL_TASK_PROBE_RUN_IDS = [
    "xperience10m_cosmos3_super_retrieval_task_probes_a100_textonly_prompatch_v2_20260620",
    "xperience10m_cosmos3_nano_retrieval_task_probes_a100_patched_textonly_20260621",
]
COSMOS3_SUPER_FUTURE_TASK_PROBE_RUN_IDS = [
    "xperience10m_cosmos3_super_future_task_probes_a100_textonly_v1_20260620",
    "xperience10m_cosmos3_nano_future_order_misalignment_patched_textonly_20260621",
    "xperience10m_cosmos3_nano_current_subtask_object_relevance_patched_textonly_20260621",
]
COSMOS3_SUPER_INTERACTION_TEXT_TASK_PROBE_RUN_IDS = [
    "xperience10m_cosmos3_super_interaction_text_task15_textonly_v1_20260620T1558Z",
    "xperience10m_cosmos3_nano_interaction_text_task15_patched_textonly_20260621",
]

DATA_FILES = [
    "additional_development_directions.json",
    "audio_ablation_summary.json",
    "artifact_index.json",
    "brand_assets.json",
    "evidence_contract.json",
    "evaluation_protocol.json",
    "figure_index.json",
    "foundation_model_plan.json",
    "live_publication_status.json",
    "language_versions.json",
    "modality_atlas.json",
    "omni_finetune_verified_result.json",
    "omni_model_comparison.json",
    "project_brief.json",
    "project_manifest.json",
    "project_packet.json",
    "public_reader_map.json",
    "project_status.json",
    "publication_audit.json",
    "public_surface_qa.json",
    "qwen3_full_parameter_gates.json",
    "qwen3_v5_v6_comparison.json",
    "quality_gates.json",
    "raw_sample_files.json",
    "rendered_site_check.json",
    "reproducibility_matrix.json",
    "research_roadmap.json",
    "research_roadmap_interactive.json",
    "research_takeaways.json",
    "research_direction_extensions.json",
    "research_directions.json",
    "scope_claims_audit.json",
    "single_episode_explorer.json",
    "source_alignment_audit.json",
    "summary_metrics.json",
    "single_episode_task_model_radar.json",
    "episode128_task_model_radar.json",
    "three_foundation_pipelines.json",
    "two_evidence_lines.json",
    "two_evidence_line_result_summary.json",
    "task_suite_20.json",
    "task_suite_enhancement_128.json",
    "task_surface_integrity.json",
    "task_walkthroughs.json",
    "task_method_20_result_matrix.json",
    "task_method_20_gap_audit.json",
    "task_method_20_source_audit.json",
    "tier2_task_suite.json",
    "unified_task_model_radar.json",
    "website_integrity.json",
    "xperience10m_128_episode_feature_index.json",
    "xperience10m_dataset_card_alignment.json",
]

ASSET_FILES = [
    "charts/audio_ablation_delta.svg",
    "charts/single_episode_task_model_radar.svg",
    "charts/episode128_task_model_radar.svg",
    "charts/tier2_task_suite.svg",
    "charts/unified_task_model_radar.svg",
    "charts/research_direction_coverage.svg",
    "brand/xperience10m-logo-apple-touch.png",
    "brand/xperience10m-logo-favicon-32.png",
    "brand/xperience10m-logo-favicon-64.png",
    "brand/xperience10m-logo-mark.png",
    "brand/xperience10m-logo-mark-192.png",
    "brand/xperience10m-logo-mark-512.png",
    "brand/xperience10m-logo-social-card.png",
    "task_suite_infographic.png",
    "pipeline_diagram.png",
    "pipeline_diagram.svg",
    "task_architectures.png",
    "task_architectures.svg",
    "foundation-pipelines/spatial-intelligence-pipeline.png",
    "foundation-pipelines/human-video-world-model-pipeline.png",
    "foundation-pipelines/vision-language-action-pipeline.png",
    "foundation-pipelines/README.md",
    "foundation-pipelines/prompts.md",
    "foundation-pipelines/source-slides/spatial-intelligence-slide.png",
    "foundation-pipelines/source-slides/human-video-world-model-slide.png",
    "foundation-pipelines/source-slides/vision-language-action-slide.png",
    "foundation-pipelines/source-photos/spatial-intelligence-source.jpg",
    "foundation-pipelines/source-photos/human-video-world-model-source.jpg",
    "foundation-pipelines/source-photos/vision-language-action-source.jpg",
    "modalities/audio.png",
    "modalities/depth.jpg",
    "modalities/inertial.png",
    "modalities/language.png",
    "modalities/motion_capture.png",
    "modalities/pose_slam.png",
    "modalities/video.jpg",
    "raw-sample-preview/fisheye_cam0_preview.mp4",
    "raw-sample-preview/fisheye_cam1_preview.mp4",
    "raw-sample-preview/fisheye_cam2_preview.mp4",
    "raw-sample-preview/fisheye_cam3_preview.mp4",
    "raw-sample-preview/stereo_left_preview.mp4",
    "raw-sample-preview/stereo_right_preview.mp4",
]

SCRIPT_FILES = [
    "omni/analyze_qwen3_omni_errors.py",
    "omni/audit_cosmos3_super_training_contract.py",
    "omni/build_omni_model_comparison.py",
    "omni/build_qwen3_full_parameter_gate_summary.py",
    "omni/build_128_episode_feature_index.py",
    "omni/collect_qwen3_future_task_probe_results.sh",
    "omni/collect_qwen3_retrieval_task_probe_results.sh",
    "omni/collect_cosmos3_super_retrieval_task_probe_results.sh",
    "omni/collect_cosmos3_super_future_task_probe_results.sh",
    "omni/eval_cosmos3_super_interaction_text_task.py",
    "omni/collect_qwen3_v4_release_artifacts.py",
    "omni/defer_cosmos3_super_after_qwen_v4.sh",
    "omni/defer_qwen3_retrieval_after_order_sync.sh",
    "omni/defer_qwen3_fullparam_after_verified_qwen.sh",
    "omni/eval_qwen3_omni_future_task_probes.py",
    "omni/eval_qwen3_omni_retrieval_task_probes.py",
    "omni/eval_cosmos3_super_future_task_probes.py",
    "omni/eval_cosmos3_super_retrieval_task_probes.py",
    "omni/export_cosmos3_camera_pose_targets.py",
    "omni/launch_all_task_model_scoring_when_free.sh",
    "omni/merge_qwen3_omni_future_task_probe_shards.py",
    "omni/merge_qwen3_omni_retrieval_task_probe_shards.py",
    "omni/merge_cosmos3_super_future_task_probe_shards.py",
    "omni/merge_cosmos3_super_interaction_text_task_shards.py",
    "omni/pack_cosmos3_super_action_batch.py",
    "omni/prepare_cosmos3_super_lora_hf_package.py",
    "omni/prepare_qwen3_lora_hf_package.py",
    "omni/patch_qwen3_omni_video_features.py",
    "omni/probe_cosmos3_super_training_readiness.py",
    "omni/run_private_gpu_qwen3_v6_repro_smoke.sh",
    "omni/run_qwen3_omni_future_task_probes_sharded.sh",
    "omni/run_qwen3_omni_retrieval_task_probes_sharded.sh",
    "omni/run_cosmos3_super_future_task_probes_sharded.sh",
    "omni/run_cosmos3_super_retrieval_task_probes_sharded.sh",
    "omni/run_cosmos3_super_interaction_text_task_sharded.sh",
    "omni/score_existing_model_output_task_probes.py",
    "omni/score_model_output_probes.py",
    "omni/run_128_task_baselines.py",
    "omni/build_task_suite_enhancement_128.py",
    "omni/run_cosmos3_super_forward_dynamics_lora.sh",
    "omni/train_cosmos3_super_forward_dynamics_lora.py",
    "audio_ablation_and_raw_upgrade.py",
    "build_artifact_index.py",
    "build_brand_assets.py",
    "build_evaluation_protocol.py",
    "build_figure_index.py",
    "build_quality_gates.py",
    "build_public_surface_qa.py",
    "build_rendered_site_check.py",
    "build_interactive_research_roadmap.py",
    "build_multilingual_public_readmes.py",
    "render_foundation_pipeline_diagrams.py",
    "build_single_episode_explorer.py",
    "build_task_method_20_gap_audit.py",
    "build_research_takeaways.py",
    "export_modality_atlas_assets.py",
    "generate_visualizations.py",
    "render_overview_figures.py",
    "render_task_suite_infographic.py",
    "research_direction_taxonomy.py",
    "task_display.py",
    "task_walkthroughs.py",
    "build_unified_task_suite.py",
    "build_unified_task_model_radar.py",
    "single_episode_diagnostics.py",
    "verify_live_publication.py",
    "validate_mirror_parity.py",
    "validate_publication_package.py",
    "validate_task_method_matrix_sources.py",
    "validate_scope_claims.py",
    "validate_source_alignment.py",
    "validate_task_surface.py",
    "validate_website_integrity.py",
    "sync_hf_publish_mirrors.py",
    "tier2_task_suite.py",
    "publish_hf_bundles.py",
]

WEBSITE_FILES = [
    "404.html",
    "apple-touch-icon.png",
    "favicon.png",
    "index.html",
    "research_roadmap.html",
    "single_episode_explorer.html",
    "site.webmanifest",
]

RESULT_FILES = [
    "audio_ablation/AUDIO_ABLATION_SUMMARY.md",
    "audio_ablation/audio_ablation_metrics.csv",
    "audio_ablation/audio_ablation_summary.json",
    "audio_ablation/audio_delta_summary.csv",
    "audio_ablation/raw_logmel_fisheye_cam0_sr16000_mels64_fft512_hop160.npz",
    "single_episode_diagnostics/provenance.json",
    "single_episode_diagnostics/README.md",
    "single_episode_diagnostics/modality_ablation/ablation_metrics.csv",
    "single_episode_diagnostics/modality_ablation/ablation_summary.json",
    "single_episode_diagnostics/object_labels/object_vocab.json",
    "single_episode_diagnostics/object_labels/window_object_labels.csv",
    "single_episode_diagnostics/timeline_overlay/timeline_overlay.csv",
    "single_episode_diagnostics/alignment_stress/alignment_shift_metrics.csv",
    "single_episode_diagnostics/alignment_stress/alignment_stress_summary.json",
    "omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_eval/analysis/ERROR_ANALYSIS.md",
    "omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_eval/analysis/error_analysis_summary.json",
    "omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_eval/analysis/episode_error_analysis.csv",
    "omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_eval/analysis/action_family_error_analysis.csv",
    "omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_eval/analysis/train_seen_error_analysis.csv",
    "omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_eval/analysis/missing_modality_error_analysis.csv",
    "omni_finetune/verified_public/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_eval/analysis/object_category_error_analysis.csv",
    "omni_finetune/multi_episode_128_task_baselines/BASELINE_ALIGNMENT_REPORT.md",
    "omni_finetune/multi_episode_128_task_baselines/summary_report.json",
    "omni_finetune/multi_episode_128_task_baselines/task_metrics.csv",
    "omni_finetune/task_suite_enhancement_128_v1_20260608/ENHANCEMENT_REPORT.md",
    "omni_finetune/task_suite_enhancement_128_v1_20260608/dense_window_scenarios.csv",
    "omni_finetune/task_suite_enhancement_128_v1_20260608/enhancement_plan.json",
    "omni_finetune/task_suite_enhancement_128_v1_20260608/experiment_backlog.json",
    "omni_finetune/task_suite_enhancement_128_v1_20260608/hierarchical_target_contract.json",
    "omni_finetune/task_suite_enhancement_128_v1_20260608/qwen_action_family_error_summary.csv",
    "omni_finetune/task_suite_enhancement_128_v1_20260608/task_bottlenecks.csv",
    "omni_finetune/OMNI_MODEL_COMPARISON.md",
    "omni_finetune/QWEN3_FULL_PARAMETER_GATES_20260609.md",
    "omni_finetune/QWEN3_V5_V6_COMPARISON_20260614.md",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_smoke_preemptible_8gpu_20260609/fullparam_feasibility_summary.json",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_smoke_preemptible_8gpu_20260609/progress.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_smoke_preemptible_8gpu_20260609/training_metadata.json",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_smoke_preemptible_8gpu_20260609/RUN_REPORT.md",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_shorttrain8_preemptible_8gpu_20260609/fullparam_shorttrain8_summary.json",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_shorttrain8_preemptible_8gpu_20260609/progress.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_shorttrain8_preemptible_8gpu_20260609/launch_status.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot32_preemptible_8gpu_20260609/fullparam_pilot32_summary.json",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot32_preemptible_8gpu_20260609/progress.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot32_preemptible_8gpu_20260609/launch_status.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot64_preemptible_8gpu_20260609/fullparam_pilot64_summary.json",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot64_preemptible_8gpu_20260609/progress.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot64_preemptible_8gpu_20260609/training_metadata.json",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot64_preemptible_8gpu_20260609/RUN_REPORT.md",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot64_preemptible_8gpu_20260609/config.yaml",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot64_preemptible_8gpu_20260609/launch_status.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_preemptible_8gpu_20260609/fullparam_pilot128_summary.json",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_preemptible_8gpu_20260609/progress.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_preemptible_8gpu_20260609/launch_status.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_after_qwen_v5_preemptible_8gpu_20260609/progress.jsonl",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_after_qwen_v5_preemptible_8gpu_20260609/config.yaml",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_after_qwen_v5_preemptible_8gpu_20260609/training_metadata.json",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_after_qwen_v5_preemptible_8gpu_20260609/RUN_REPORT.md",
    "omni_finetune/xperience10m_qwen3_omni_128ep_fullparam_pilot128_after_qwen_v5_preemptible_8gpu_20260609/launch_status.jsonl",
    "omni_finetune/HF_UPLOAD.md",
    "omni_finetune/model_output_probe_readiness/model_output_probe_readiness.json",
    "omni_finetune/model_output_probe_readiness/RUN_REPORT.md",
    "omni_finetune/xperience10m_cosmos3_super_training_readiness_20260607/training_readiness.json",
    "omni_finetune/xperience10m_cosmos3_super_training_readiness_20260607/RUN_REPORT.md",
    "omni_finetune/xperience10m_cosmos3_super_training_readiness_metadata_a100_20260609/training_readiness.json",
    "omni_finetune/xperience10m_cosmos3_super_training_readiness_metadata_a100_20260609/RUN_REPORT.md",
    "omni_finetune/xperience10m_cosmos3_super_training_contract_audit_camera_pose_20260608/training_contract_audit.json",
    "omni_finetune/xperience10m_cosmos3_super_training_contract_audit_camera_pose_20260608/RUN_REPORT.md",
    "omni_finetune/xperience10m_cosmos3_super_action_packer_schema_smoke_20260608/packer_summary.json",
    "omni_finetune/xperience10m_cosmos3_super_action_packer_schema_smoke_20260608/RUN_REPORT.md",
    "omni_finetune/verified_public/xperience10m_cosmos3_nano_128ep_future_window_h5_compat_adapter_eval_test_full/verified_result_summary.json",
    "omni_finetune/verified_public/xperience10m_cosmos3_nano_128ep_future_window_h5_compat_adapter_eval_test_full/PUBLIC_RESULT_SUMMARY.md",
    "omni_finetune/verified_public/xperience10m_cosmos3_nano_128ep_future_window_h5_compat_adapter_eval_test_full/eval/metrics.json",
    "omni_finetune/verified_public/xperience10m_cosmos3_nano_128ep_future_window_h5_compat_adapter_eval_test_full/eval/RUN_REPORT.md",
]

DOC_FILES = [
    "README.zh.md",
    "README.es.md",
    "README.fr.md",
    "README.de.md",
    "README.ja.md",
    "README.ko.md",
    "README.pt.md",
    "ARTIFACT_GUIDE.md",
    "OMNI_MODEL_EXTENSION_CONTRACT.md",
    "QUALITY_GATES.md",
    "EVALUATION_PROTOCOL.md",
    "FIGURE_INDEX.md",
    "FOUNDATION_MODEL_PLAN.md",
    "ADDITIONAL_DEVELOPMENT_DIRECTIONS.md",
    "THREE_FOUNDATION_PIPELINES.md",
    "TWO_EVIDENCE_LINES.md",
    "TWO_EVIDENCE_LINE_RESULT_SUMMARY.md",
    "PROJECT_BRIEF.md",
    "PUBLIC_READER_MAP.md",
    "RENDERED_SITE_CHECK.md",
    "RESEARCH_ROADMAP.md",
    "PROJECT_STATUS.md",
    "REPRODUCIBILITY.md",
    "TASK_SUITE_ENHANCEMENT_128.md",
    "XPERIENCE10M_128_EPISODE_FEATURE_INDEX.md",
    "TASK_METHOD_20_GAP_AUDIT.md",
    "TASK_METHOD_20_RESULT_MATRIX.md",
    "TASK_SUITE_20.md",
    "PUBLIC_SURFACE_QA.md",
    "EVIDENCE_CONTRACT.md",
    "RESEARCH_TAKEAWAYS.md",
    "SOURCE_ALIGNMENT_AUDIT.md",
    "XPERIENCE_EMBODIED_FOUNDATION_MODEL_PRETRAINING.md",
    "XPERIENCE10M_DATASET_CARD_ALIGNMENT.md",
]


def sha256(path: Path) -> str:
    digest = hashlib.sha256()
    with path.open("rb") as handle:
        for chunk in iter(lambda: handle.read(1024 * 1024), b""):
            digest.update(chunk)
    return digest.hexdigest()


def display_path(path: Path, hf_root: Path) -> str:
    resolved = path.resolve()
    bases = [
        ("hf_space", hf_root / "space"),
        ("hf_artifacts", hf_root / "artifacts"),
        ("hf_model", hf_root / "model"),
        ("repo", ROOT),
        ("hf_publish", hf_root),
    ]
    for label, base in bases:
        try:
            return f"{label}:{resolved.relative_to(base.resolve()).as_posix()}"
        except ValueError:
            continue
    return path.name


def file_record(path: Path, hf_root: Path) -> dict:
    record = {
        "path": display_path(path, hf_root),
        "exists": path.exists(),
    }
    if path.exists() and path.is_file():
        record["bytes"] = path.stat().st_size
        record["sha256"] = sha256(path)
    else:
        record["bytes"] = 0
        record["sha256"] = None
    return record


def verified_public_result_files() -> list[str]:
    """Return every public-safe file from verified model packages.

    Verified packages are already sanitized by the package audit; mirroring the
    whole package prevents final model results from being silently omitted when a
    new run lands under results/omni_finetune/verified_public.
    """

    verified_root = ROOT / "results/omni_finetune/verified_public"
    if not verified_root.exists():
        return []
    files: list[str] = []
    for path in verified_root.rglob("*"):
        if not path.is_file():
            continue
        files.append(path.relative_to(ROOT / "results").as_posix())
    return sorted(files)


def tier2_result_files() -> list[str]:
    """Return every generated public-safe artifact for tasks 13-20.

    The directory name is historical and kept for stable public links.
    """

    tier2_root = ROOT / "results/episode_task_suite/tier2_task_suite"
    if not tier2_root.exists():
        return []
    files: list[str] = []
    for path in tier2_root.rglob("*"):
        if path.is_file():
            files.append(path.relative_to(ROOT / "results").as_posix())
    return sorted(files)


def a100_128_metadata_result_files() -> list[str]:
    """Return the public-safe 128-episode metadata baseline rerun artifacts."""

    result_root = ROOT / "results/omni_finetune/a100_128_metadata_task_baselines_20260616_v2"
    if not result_root.exists():
        return []
    files: list[str] = []
    for path in result_root.rglob("*"):
        if path.is_file():
            files.append(path.relative_to(ROOT / "results").as_posix())
    return sorted(files)


def a100_128_raw20_result_files() -> list[str]:
    """Return public-safe 128-episode raw-feature 20-task baseline artifacts."""

    result_root = ROOT / "results/omni_finetune/a100_128_raw20_task_baselines_complete20_proxy_20260616T091500Z"
    if not result_root.exists():
        return []
    files: list[str] = []
    for path in result_root.rglob("*"):
        if path.is_file():
            files.append(path.relative_to(ROOT / "results").as_posix())
    return sorted(files)


def xperience10m_128_data_feature_files() -> list[str]:
    """Return selected 128-episode source and processed-feature artifacts."""

    explicit = [
        ROOT / "results/omni_finetune/xperience10m_128_episode_selection.json",
        ROOT / "results/omni_finetune/xperience10m_128_episode_selection.csv",
        ROOT / "results/omni_finetune/xperience10m_128_episode_download_files.txt",
        ROOT / "results/omni_finetune/episode_manifest.json",
        ROOT / "results/omni_finetune/dataset_manifest.json",
        ROOT / "results/omni_finetune/multi_episode_128_task_baselines/metadata_feature_matrix.npz",
        ROOT / "results/omni_finetune/a100_128_metadata_task_baselines_20260616_v2/metadata_feature_matrix.npz",
    ]
    dense_root = ROOT / "results/omni_finetune/xperience10m_128ep_dense_multiscale_hierarchical_v1_20260608"
    files: list[str] = []
    for path in explicit:
        if path.is_file():
            files.append(path.relative_to(ROOT / "results").as_posix())
    if dense_root.exists():
        for path in dense_root.rglob("*"):
            if path.is_file():
                files.append(path.relative_to(ROOT / "results").as_posix())
    return sorted(set(files))


def model_output_task_probe_result_files() -> list[str]:
    """Return task-specific scores derived from existing verified model outputs."""

    result_root = ROOT / "results/omni_finetune/model_output_task_probes_20260616"
    if not result_root.exists():
        return []
    files: list[str] = []
    for path in result_root.rglob("*"):
        if path.is_file():
            files.append(path.relative_to(ROOT / "results").as_posix())
    return sorted(files)


def qwen3_future_task_probe_result_files() -> list[str]:
    """Return public-safe Qwen3 future-task probe outputs from the shard run."""

    result_root = ROOT / "results/omni_finetune" / QWEN3_FUTURE_TASK_PROBE_RUN_ID
    files: list[str] = []
    if result_root.exists():
        for path in result_root.rglob("*"):
            if path.is_file():
                files.append(path.relative_to(ROOT / "results").as_posix())

    launcher_log = (
        ROOT
        / "results/omni_finetune/deferred_launchers"
        / f"{QWEN3_FUTURE_TASK_PROBE_RUN_ID}.launcher.log"
    )
    if launcher_log.is_file():
        files.append(launcher_log.relative_to(ROOT / "results").as_posix())
    return sorted(files)


def qwen3_retrieval_task_probe_result_files() -> list[str]:
    """Return public-safe Qwen3 retrieval probe outputs from task 08/09 runs."""

    files: list[str] = []
    for run_id in QWEN3_RETRIEVAL_TASK_PROBE_RUN_IDS:
        result_root = ROOT / "results/omni_finetune" / run_id
        if result_root.exists():
            for path in result_root.rglob("*"):
                if path.is_file():
                    files.append(path.relative_to(ROOT / "results").as_posix())

        launch_log = ROOT / "results/omni_finetune/deferred_launchers" / f"{run_id}.launch.log"
        if launch_log.is_file():
            files.append(launch_log.relative_to(ROOT / "results").as_posix())
        direct_launch_log = ROOT / "results/omni_finetune/deferred_launchers" / f"{run_id}.launcher.log"
        if direct_launch_log.is_file():
            files.append(direct_launch_log.relative_to(ROOT / "results").as_posix())
    return sorted(set(files))


def cosmos3_super_retrieval_task_probe_result_files() -> list[str]:
    """Return public-safe Cosmos3-Super retrieval probe outputs."""

    files: list[str] = []
    compact_names = {"RUN_REPORT.md", "collection_validation.json", "metrics.json", "server_info.json", "summary.json"}
    for run_id in COSMOS3_SUPER_RETRIEVAL_TASK_PROBE_RUN_IDS:
        result_root = ROOT / "results/omni_finetune" / run_id
        if result_root.exists():
            for path in result_root.rglob("*"):
                if path.is_file() and (path.name in compact_names or path.name.endswith(".progress.jsonl")):
                    files.append(path.relative_to(ROOT / "results").as_posix())

        for suffix in ("launch", "launcher", "retrieval", "runner"):
            launch_log = ROOT / "results/omni_finetune/deferred_launchers" / f"{run_id}.{suffix}.log"
            if launch_log.is_file():
                files.append(launch_log.relative_to(ROOT / "results").as_posix())
    return sorted(set(files))


def cosmos3_super_future_task_probe_result_files() -> list[str]:
    """Return public-safe Cosmos3-Super future-task probe outputs."""

    files: list[str] = []
    compact_names = {
        "RUN_REPORT.md",
        "collection_validation.json",
        "metrics.json",
        "per_class_metrics.csv",
        "server_info.json",
        "summary.json",
    }
    for run_id in COSMOS3_SUPER_FUTURE_TASK_PROBE_RUN_IDS:
        result_root = ROOT / "results/omni_finetune" / run_id
        if result_root.exists():
            for path in result_root.rglob("*"):
                if path.is_file() and (path.name in compact_names or path.name.endswith(".progress.jsonl")):
                    files.append(path.relative_to(ROOT / "results").as_posix())

        for suffix in ("launch", "launcher", "runner"):
            launch_log = ROOT / "results/omni_finetune/deferred_launchers" / f"{run_id}.{suffix}.log"
            if launch_log.is_file():
                files.append(launch_log.relative_to(ROOT / "results").as_posix())
    return sorted(set(files))


def cosmos3_super_interaction_text_task_probe_result_files() -> list[str]:
    """Return public-safe Cosmos3-Super task-15 interaction-text probe outputs."""

    files: list[str] = []
    compact_names = {
        "RUN_REPORT.md",
        "collection_validation.json",
        "confusion_matrix.csv",
        "launch_env.txt",
        "metrics.json",
        "per_class_metrics.csv",
        "server_info.json",
        "summary.json",
    }
    for run_id in COSMOS3_SUPER_INTERACTION_TEXT_TASK_PROBE_RUN_IDS:
        result_root = ROOT / "results/omni_finetune" / run_id
        if result_root.exists():
            for path in result_root.rglob("*"):
                if path.is_file() and (path.name in compact_names or path.name.endswith(".progress.jsonl")):
                    files.append(path.relative_to(ROOT / "results").as_posix())

        for suffix in ("launch", "launcher", "runner"):
            launch_log = ROOT / "results/omni_finetune/deferred_launchers" / f"{run_id}.{suffix}.log"
            if launch_log.is_file():
                files.append(launch_log.relative_to(ROOT / "results").as_posix())
    return sorted(set(files))


def parity_group(name: str, local_path: Path, mirrors: dict[str, Path], hf_root: Path) -> dict:
    local = file_record(local_path, hf_root)
    mirror_records = {surface: file_record(path, hf_root) for surface, path in mirrors.items()}
    failures = []
    if not local["exists"]:
        failures.append({"surface": "repo", "kind": "missing", "path": local["path"]})
    for surface, record in mirror_records.items():
        if not record["exists"]:
            failures.append({"surface": surface, "kind": "missing", "path": record["path"]})
            continue
        if local["exists"] and record["sha256"] != local["sha256"]:
            failures.append(
                {
                    "surface": surface,
                    "kind": "hash_mismatch",
                    "path": record["path"],
                    "expected_sha256": local["sha256"],
                    "actual_sha256": record["sha256"],
                }
            )
    return {
        "name": name,
        "status": "pass" if not failures else "fail",
        "local": local,
        "mirrors": mirror_records,
        "failures": failures,
    }


def build_report(hf_root: Path) -> dict:
    groups = []

    for filename in DATA_FILES:
        groups.append(
            parity_group(
                f"data/{filename}",
                ROOT / "docs/data" / filename,
                {
                    "hf_space": hf_root / "space/data" / filename,
                    "hf_artifacts_data": hf_root / "artifacts/data" / filename,
                    "hf_artifacts": hf_root / "artifacts/docs/data" / filename,
                    "hf_model_data": hf_root / "model/data" / filename,
                    "hf_model_docs_data": hf_root / "model/docs/data" / filename,
                    "hf_model": hf_root / "model/metrics" / filename,
                },
                hf_root,
            )
        )

    for filename in ASSET_FILES:
        groups.append(
            parity_group(
                f"assets/{filename}",
                ROOT / "docs/assets" / filename,
                {
                    "hf_space": hf_root / "space/assets" / filename,
                    "hf_artifacts_docs": hf_root / "artifacts/docs/assets" / filename,
                    "hf_artifacts_card": hf_root / "artifacts/assets" / filename,
                    "hf_model": hf_root / "model/assets" / filename,
                },
                hf_root,
            )
        )

    for filename in SCRIPT_FILES:
        groups.append(
            parity_group(
                f"scripts/{filename}",
                ROOT / "scripts" / filename,
                {
                    "hf_artifacts": hf_root / "artifacts/scripts" / filename,
                    "hf_model": hf_root / "model/scripts" / filename,
                },
                hf_root,
            )
        )

    for filename in WEBSITE_FILES:
        groups.append(
            parity_group(
                f"website/{filename}",
                ROOT / "docs" / filename,
                {
                    "hf_space": hf_root / "space" / filename,
                    "hf_artifacts_root": hf_root / "artifacts" / filename,
                    "hf_artifacts_docs": hf_root / "artifacts/docs" / filename,
                    "hf_model": hf_root / "model" / filename,
                    "hf_model_docs": hf_root / "model/docs" / filename,
                },
                hf_root,
            )
        )

    result_files = sorted(
        set(RESULT_FILES)
        | set(verified_public_result_files())
        | set(tier2_result_files())
        | set(a100_128_metadata_result_files())
        | set(a100_128_raw20_result_files())
        | set(xperience10m_128_data_feature_files())
        | set(model_output_task_probe_result_files())
        | set(qwen3_future_task_probe_result_files())
        | set(qwen3_retrieval_task_probe_result_files())
        | set(cosmos3_super_retrieval_task_probe_result_files())
        | set(cosmos3_super_future_task_probe_result_files())
        | set(cosmos3_super_interaction_text_task_probe_result_files())
    )
    for filename in result_files:
        groups.append(
            parity_group(
                f"results/{filename}",
                ROOT / "results" / filename,
                {
                    "hf_artifacts": hf_root / "artifacts/results" / filename,
                    "hf_model": hf_root / "model/results" / filename,
                },
                hf_root,
            )
        )

    space_result_files = sorted(
        set(RESULT_FILES)
        | set(tier2_result_files())
        | set(model_output_task_probe_result_files())
        | set(qwen3_future_task_probe_result_files())
        | set(qwen3_retrieval_task_probe_result_files())
        | set(cosmos3_super_retrieval_task_probe_result_files())
        | set(cosmos3_super_future_task_probe_result_files())
        | set(cosmos3_super_interaction_text_task_probe_result_files())
    )
    for filename in space_result_files:
        groups.append(
            parity_group(
                f"space_results/{filename}",
                ROOT / "results" / filename,
                {
                    "hf_space": hf_root / "space/results" / filename,
                },
                hf_root,
            )
        )

    for filename in DOC_FILES:
        groups.append(
            parity_group(
                f"docs/{filename}",
                ROOT / filename,
                {
                    "hf_space": hf_root / "space" / filename,
                    "hf_artifacts": hf_root / "artifacts" / filename,
                    "hf_model": hf_root / "model" / filename,
                },
                hf_root,
            )
        )

    failures = [
        {"group": group["name"], **failure}
        for group in groups
        for failure in group["failures"]
    ]
    by_surface: dict[str, int] = {}
    for failure in failures:
        by_surface[failure["surface"]] = by_surface.get(failure["surface"], 0) + 1

    return {
        "status": "pass" if not failures else "fail",
        "generated_at_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"),
        "hf_root": "hf_publish",
        "summary": {
            "group_count": len(groups),
            "failure_count": len(failures),
            "failures_by_surface": by_surface,
        },
        "checks": [
            {
                "name": "repo_hf_space_artifact_model_data_parity",
                "status": "pass"
                if not any(failure["group"].startswith("data/") for failure in failures)
                else "fail",
            },
            {
                "name": "repo_hf_visual_asset_parity",
                "status": "pass"
                if not any(failure["group"].startswith("assets/") for failure in failures)
                else "fail",
            },
            {
                "name": "repo_hf_validator_script_parity",
                "status": "pass"
                if not any(failure["group"].startswith("scripts/") for failure in failures)
                else "fail",
            },
            {
                "name": "repo_hf_website_html_parity",
                "status": "pass"
                if not any(failure["group"].startswith("website/") for failure in failures)
                else "fail",
            },
            {
                "name": "repo_hf_diagnostic_result_parity",
                "status": "pass"
                if not any(failure["group"].startswith("results/") for failure in failures)
                else "fail",
            },
            {
                "name": "repo_hf_quality_doc_parity",
                "status": "pass"
                if not any(failure["group"].startswith("docs/") for failure in failures)
                else "fail",
            },
        ],
        "groups": groups,
        "failures": failures,
    }


def main() -> int:
    parser = argparse.ArgumentParser()
    parser.add_argument("--hf-root", type=Path, default=DEFAULT_HF_ROOT)
    parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT)
    args = parser.parse_args()

    report = build_report(args.hf_root.resolve())
    args.output.parent.mkdir(parents=True, exist_ok=True)
    args.output.write_text(json.dumps(report, indent=2) + "\n", encoding="utf-8")
    print(f"{report['status'].upper()}: wrote {args.output}")
    if report["status"] != "pass":
        for failure in report["failures"][:40]:
            print(f"- {failure['group']}: {failure['surface']} {failure['kind']} {failure['path']}")
        if len(report["failures"]) > 40:
            print(f"- ... {len(report['failures']) - 40} more failures")
        return 1
    return 0


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