"""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]:
    if not job_posts:
        return []
    normalized=[]
    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,str]:
    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=[]
    seen=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=""

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

    return suggested,summary.strip(),reasoning.strip(),experience.strip()