from workflow_graph import STEP_COPY

EXAMPLES = {
    "Paper 1": "https://arxiv.org/abs/2208.00329",
    # AveriTeC demo hidden from the picker for now.
    # "Paper 2 (AveriTeC)": "https://arxiv.org/abs/2505.17978",
    "Paper 2": "https://arxiv.org/abs/2211.08788",
}

# System Run setting picker labels (match SciPaths Dev case-study report).
SYSTEM_RUN_METHODS = {
    "Parametric - LLM Only": "codeagent_parametric",
    "Websearch Deep - LLM + Web Search + Crawl": "codeagent_websearch_deep",
}

TAB_NAMES = [
    "Run",
    "Clusters",
    "Decomposition",
]

APP_VIEWS = [
    "Annotation Process",
    "System Run",
]

# Left-nav items (mina-style icon + label rows). Icons use Streamlit Material symbols.
APP_NAV = [
    {
        "view": "Annotation Process",
        "icon": ":material/account_tree:",
    },
    {
        "view": "System Run",
        "icon": ":material/play_circle:",
    },
]

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 = [1, 2, 3, 4, 5, 6, 7, 8]


def pipeline_steps_markdown() -> str:
    return "\n".join(f"{idx}. {STEP_COPY[idx]}" for idx in DISPLAY_STEPS)