def rerank_candidates(candidates, w_cos=0.60, w_path=0.20, w_fresh=0.15, w_deg=0.05):
    """
    Rerank chunks with a hybrid scoring formula.
    Weights are configurable from the ui.
    """
    reranked = []
    logs = []

    for idx, c in enumerate(candidates, 1):
        score = (
            w_cos * c.get("cosine", 0) +
            w_path * c.get("path_proximity", 0) +
            w_fresh * c.get("freshness_decay", 0) +
            w_deg * c.get("degree_norm", 0)
        )
        c["final_score"] = score
        reranked.append(c)

        logs.append(
            f"Candidate {idx}: "
            f"cosine={c.get('cosine',0):.3f}, "
            f"path={c.get('path_proximity',0):.3f}, "
            f"freshness={c.get('freshness_decay',0):.3f}, "
            f"degree={c.get('degree_norm',0):.3f} "
            f"→ final={score:.3f}"
        )

    reranked.sort(key=lambda x: x["final_score"], reverse=True)
    return reranked, logs