"""Agent response parsers and input normalizers.

Pure module: no FastAPI imports, no HTTPException, and no module-level state.
Mirrors job/candidate/decorators.py — helpers that clean/shape data before or
after the graph nodes run.
"""

from __future__ import annotations

import uuid


def normalize_job_posts(job_posts) -> list[dict]:
    """Keep only dict items with an id field; stringify ids for the LLM."""
    if not job_posts:
        return []
    normalized: list[dict] = []
    for item in job_posts:
        if not isinstance(item, dict):
            continue
        job_id = item.get("id")
        if job_id is None:
            continue
        normalized.append(
            {
                "id": str(job_id),
                "title": item.get("title") or "",
                "description": item.get("description") or "",
                "post_text": item.get("post_text") or "",
                "requirements": item.get("requirements") or [],
                "optional_skills": item.get("optional_skills") or [],
                "location": item.get("location") or "",
                "employment_type": item.get("employment_type") or "",
            }
        )
    return normalized


def parse_match_response(data, allowed_ids) -> tuple[list[str], str, str]:
    """Filter model JSON ids to the allowed job-post set."""
    if not isinstance(data, dict):
        raise RuntimeError(f"model did not return a JSON object: {data!r}")

    allowed = set(allowed_ids or [])
    raw_ids = data.get("suggested_job_post_ids") or []
    if not isinstance(raw_ids, list):
        raw_ids = []

    suggested: list[str] = []
    seen: set[str] = set()
    for raw_id in raw_ids:
        job_id = str(raw_id).strip()
        if not job_id or job_id not in allowed or job_id in seen:
            continue
        try:
            uuid.UUID(job_id)
        except ValueError:
            continue
        seen.add(job_id)
        suggested.append(job_id)

    summary = data.get("summary")
    if not isinstance(summary, str):
        summary = ""

    reasoning = data.get("reasoning")
    if isinstance(reasoning, list):
        reasoning = "\n".join(str(item) for item in reasoning)
    if not isinstance(reasoning, str):
        reasoning = ""
    return suggested, summary.strip(), reasoning.strip()