"""employment_agent parse_employment_response — linkedin_url is an agent key.

parse_employment_response returns a DICT. These tests used to unpack it
positionally, which silently read dict KEYS instead of values and asserted
against whatever the last key happened to be.
"""

from __future__ import annotations

from employment_agent.decorators import parse_employment_response
from employment_agent.prompt import EDUCATION, NO_COMPANY, NO_LINKEDIN


def test_parses_linkedin_url_key_separately():
    # The resume must actually contain the slug: _clean_linkedin keeps a URL
    # only when the CV evidences it, so a resume that never mentions LinkedIn
    # correctly yields None however confident the model was.
    fields = parse_employment_response(
        {
            "current_employment": "Acme",
            "education": "BS CS",
            "current_title": "Engineer",
            "linkedin_url": "https://www.linkedin.com/in/jane-doe",
        },
        "Acme BS CS Engineer https://www.linkedin.com/in/jane-doe",
    )
    assert fields["current_employment"] == "Acme"
    assert fields["education"] == "BS CS"
    assert fields["current_title"] == "Engineer"
    assert fields["linkedin_url"] == "https://www.linkedin.com/in/jane-doe"


def test_url_absent_from_the_resume_is_not_trusted():
    fields = parse_employment_response(
        {
            "current_employment": "Acme",
            "education": "BS CS",
            "current_title": "Engineer",
            "linkedin_url": "https://www.linkedin.com/in/jane-doe",
        },
        "Acme BS CS Engineer",
    )
    assert fields["linkedin_url"] is None


def test_sentinel_and_non_linkedin_are_dropped():
    sentinel = parse_employment_response(
        {
            "current_employment": NO_COMPANY,
            "education": EDUCATION,
            "current_title": "x",
            "linkedin_url": NO_LINKEDIN,
        },
        "",
    )
    assert sentinel["linkedin_url"] is None

    github = parse_employment_response(
        {
            "current_employment": NO_COMPANY,
            "education": EDUCATION,
            "current_title": "x",
            "linkedin_url": "https://github.com/jane",
        },
        "",
    )
    assert github["linkedin_url"] is None


def test_adds_scheme_and_rejects_company_page():
    bare = parse_employment_response(
        {
            "current_employment": NO_COMPANY,
            "education": EDUCATION,
            "current_title": "x",
            "linkedin_url": "www.linkedin.com/in/jane-doe",
        },
        "",
    )
    assert bare["linkedin_url"] == "https://www.linkedin.com/in/jane-doe"

    company_page = parse_employment_response(
        {
            "current_employment": NO_COMPANY,
            "education": EDUCATION,
            "current_title": "x",
            "linkedin_url": "https://www.linkedin.com/company/acme",
        },
        "",
    )
    assert company_page["linkedin_url"] is None


def test_city_prompt_asks_openai_for_a_proper_city_name():
    from employment_agent.prompt import city_list_prompt, prompt
    text = prompt()
    assert "Karachi(Malir)" in text
    assert 'JSON city must be "Karachi"' in text
    assert "Return ONE proper city name only" in text
    listed = city_list_prompt()
    assert "Karachi(Malir)" in listed
    assert '"cities"' in listed


def test_parse_normalized_cities_keeps_agent_names():
    from employment_agent.execute_agent import parse_normalized_cities
    assert parse_normalized_cities(
        {"cities": ["Karachi", "Karachi", "Lahore", "no city mentioned"]},
        fallback=["Karachi(Malir)"],
    ) == ["Karachi", "Lahore"]


def test_parse_normalized_cities_falls_back_when_the_model_shape_is_wrong():
    from employment_agent.execute_agent import parse_normalized_cities
    assert parse_normalized_cities({"oops": True}, fallback=["Karachi(Malir)"]) == ["Karachi(Malir)"]