"""
Gradio/Space entrypoint: predict backlink quality and risk. Returns formatted string.
"""
from config import MODEL_DIR, FEATURE_COLUMNS, TARGET_QUALITY, TARGET_RISK

def predict(domain_authority: float, dofollow: int, ref_domains: int, anchor_length: int, same_topic: int) -> str:
    try:
        import joblib
        import pandas as pd
    except ImportError as e:
        return f"Error: {e}"
    row = {
        "domain_authority": float(domain_authority or 0),
        "dofollow": int(dofollow if dofollow is not None else 1),
        "ref_domains": int(ref_domains or 0),
        "anchor_length": int(anchor_length or 0),
        "same_topic": int(same_topic if same_topic is not None else 0),
    }
    df = pd.DataFrame([row])
    features = joblib.load(MODEL_DIR / "feature_columns.joblib") if (MODEL_DIR / "feature_columns.joblib").exists() else [c for c in FEATURE_COLUMNS if c in df.columns]
    if not features:
        return "Model not found."
    X = df[features].fillna(0)
    out = []
    if (MODEL_DIR / "quality_model.joblib").exists():
        model = joblib.load(MODEL_DIR / "quality_model.joblib")
        out.append(f"**pred_{TARGET_QUALITY}:** {model.predict(X)[0]:.3f}")
    if (MODEL_DIR / "risk_model.joblib").exists():
        model = joblib.load(MODEL_DIR / "risk_model.joblib")
        out.append(f"**pred_risk_label:** {int(model.predict(X)[0])} (0=ok, 1=risk)")
    return "\n".join(out) if out else "Model not found. Run train.py and re-upload."