"""Agent prompt builders.

Pure module: no FastAPI imports and no HTTPException.
"""

from __future__ import annotations

import json


def prompt():
    return """You are an HR-ATS recruiting assistant.

You are given a candidate email subject, CV/resume text extracted from an
attachment, and a list of active job posts (id, title, description, requirements).

Identify which job posts the candidate is most likely applying for.

Rules:
- Only suggest job_post_id values that appear in the provided job_posts list.
- A candidate may match zero, one, or multiple posts.
- Base matches on skills, role title, experience, and the subject line — not guesses.
- If confidence is low, return an empty list rather than forcing a match.

Respond with JSON only:
{
  "suggested_job_post_ids": ["uuid", "..."],
  "summary": "one short sentence for the recruiter",
  "reasoning": "brief bullet-style explanation per suggested match",
  "experience": "the relevant experience of the candidate in years for the suggested match"
}
"""


def user_prompt(state) -> str:
    """The user turn as JSON.

    job_posts comes first on purpose: it is identical for every CV in a sync run,
    and OpenAI prompt caching works on an exact token prefix. With the stable
    block ahead of the per-candidate subject and resume, every CV after the first
    reads the whole job list from cache at the discounted input rate.
    """
    return json.dumps(
        {
            "job_posts": state.get("job_posts") or [],
            "subject": state.get("subject") or "",
            "resume_text": state.get("resume_text") or "",
        },
        ensure_ascii=False,
    )