from runner import STEP_LABELS

EXAMPLES = {
    "Confidence-based MBR Decoding": "https://arxiv.org/abs/2311.14919",
    "AVerImaTeC": "https://arxiv.org/abs/2505.17978",
    "CSCD-NS (2022)": "https://arxiv.org/abs/2211.08788",
}

TAB_NAMES = [
    "Pipeline Run",
    "Citation Clusters",
    "Target Contribution Decomposition",
]

METHOD_NOTES = {
    "Pipeline scope": "Runs steps 0, 1, 2, 3, 4, 5, 6, and 8, then launches cluster-first two-pass annotation.",
    "Input": "Accepts a single arXiv URL or arXiv ID.",
    "Cluster-first annotation": "Uses all refined downstream USES/EXTENDS clusters to derive target contributions, then decomposes each target contribution separately.",
    "Stopping rule": "If no valid downstream usage clusters remain after refinement and filtering, annotation is skipped.",
}

DISPLAY_STEPS = [0, 1, 2, 3, 4, 5, 6, 8]


def pipeline_steps_markdown() -> str:
    lines = []
    for idx in DISPLAY_STEPS:
        lines.append(f"{idx}. {STEP_LABELS[idx]}")
    lines.append("9. Cluster-first target contribution annotation and enabling contribution decomposition")
    return "\n".join(lines)