"""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_for_a_proper_city_name():
    from employment_agent.prompt import 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
    assert "city_list_prompt" not in text
    assert "Pakistan:" in text
    assert "United Kingdom:" in text
    assert "Karachi" in text
    assert "London" in text


def test_countries_dataset_is_global_and_includes_pakistan():
    from global_cities import CITY_BY_KEY, Countries, countries_prompt_block

    assert isinstance(Countries, dict)
    assert "Pakistan" in Countries
    assert "Karachi" in Countries["Pakistan"]
    assert "United Kingdom" in Countries
    assert "London" in Countries["United Kingdom"]
    assert "United States" in Countries
    assert "New York" in Countries["United States"]
    assert CITY_BY_KEY["karachi"] == "Karachi"
    assert CITY_BY_KEY["london"] == "London"
    block = countries_prompt_block()
    assert block.startswith("Afghanistan:")
    assert "Pakistan: " in block
    assert "Karachi" in block


def test_canonical_city_maps_messy_localities():
    from employment_agent.decorators import canonical_city
    from employment_agent.prompt import NO_CITY

    assert canonical_city("Karachi(Malir)") == "Karachi"
    assert canonical_city("Karachi (Malir)") == "Karachi"
    assert canonical_city("Karachi Malir") == "Karachi"
    assert canonical_city("DHA Karachi") == "Karachi"
    assert canonical_city("Karachi DHA") == "Karachi"
    assert canonical_city("Lahore Cantt") == "Lahore"
    assert canonical_city("Gulberg, Lahore") == "Lahore"
    assert canonical_city("F-10 Islamabad") == "Islamabad"
    assert canonical_city("Wah Cantt") == "Wah"
    assert canonical_city("Karachi") == "Karachi"
    assert canonical_city("Karachi Malir Wah Cantt") == "Karachi"
    assert canonical_city("London(Westminster)") == "London"
    assert canonical_city("New York") == "New York"
    assert canonical_city("Dubai Marina") == "Dubai"
    assert canonical_city("") is None
    assert canonical_city("   ") is None
    assert canonical_city(NO_CITY) is None
    assert canonical_city("none") is None
    assert canonical_city("n/a") is None


def test_list_cities_is_distinct_without_openai(monkeypatch):
    import asyncio
    import inspect

    from g_sheet.models import FormData
    from inbox.models import Inbox_Messages
    from inbox.views import Email

    source = inspect.getsource(Email.list_cities)
    assert "normalize_cities" not in source
    assert "llm_call" not in source

    async def inbox_cities(session):
        return ["Karachi", "Lahore", "Karachi"]

    async def form_cities(session):
        return ["Lahore", "Islamabad", "  ", None]

    monkeypatch.setattr(Inbox_Messages, "distinct_cities", inbox_cities)
    monkeypatch.setattr(FormData, "distinct_cities", form_cities)
    cities = asyncio.run(Email(session=object()).list_cities())
    assert cities == ["Islamabad", "Karachi", "Lahore"]