"""Deterministic prompt compaction that preserves candidate evidence."""

import json


def estimate_tokens(payload) -> int:
    return max(1, len(json.dumps(payload, ensure_ascii=False, sort_keys=True)) // 4)


def compact_payload(payload):
    """Remove repeated metadata only; candidate codes/descriptions are untouched."""
    compact = dict(payload)
    compact.pop("debug", None)
    compact.pop("duplicate_examples", None)
    candidates = compact.get("official_candidates")
    if isinstance(candidates, list):
        seen = set()
        compact["official_candidates"] = [
            row for row in candidates
            if not (row.get("ncm") in seen or seen.add(row.get("ncm")))
        ]
    return compact


def measure_payloads(payloads):
    before = sum(estimate_tokens(payload) for payload in payloads)
    after = sum(estimate_tokens(compact_payload(payload)) for payload in payloads)
    return {"items": len(payloads), "tokens_before": before, "tokens_after": after, "reduction_percent": round((1 - after / before) * 100, 2) if before else 0.0}