"""Tests for the business-card vision wrapper (pure logic, no network — chat_fn is stubbed)."""
import os
import sys

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

import spark  # noqa: E402


def test_transcribe_card_returns_faithful_text():
    captured = {}

    def fake_chat(prompt, image_b64, mime="image/jpeg", system=None, max_tokens=600):
        captured["image_b64"] = image_b64
        captured["mime"] = mime
        captured["system"] = system
        return "Jane Doe\nGeneral Partner\nAcme Capital LLC\njane@acme.com\n+1 555 123 4567"

    out = spark.transcribe_card("Zm9vYmFy", mime="image/png", chat_fn=fake_chat)
    # The transcription is passed through verbatim — email survives for the integrity check.
    assert "jane@acme.com" in out
    assert "Acme Capital LLC" in out
    # The image + mime reached the vision call; the card system prompt was used.
    assert captured["image_b64"] == "Zm9vYmFy"
    assert captured["mime"] == "image/png"
    assert "business card" in (captured["system"] or "").lower()


def test_transcribe_card_none_sentinel_becomes_empty():
    # The model replies NONE for an unreadable / non-card image → we return "" so the bot can
    # ask for a clearer photo instead of feeding garbage into the intake parser.
    assert spark.transcribe_card("x", chat_fn=lambda *a, **k: "NONE") == ""
    assert spark.transcribe_card("x", chat_fn=lambda *a, **k: " none ") == ""


def test_transcribe_card_strips_whitespace():
    assert spark.transcribe_card("x", chat_fn=lambda *a, **k: "  Acme\n  ") == "Acme"


if __name__ == "__main__":
    fns = [v for k, v in sorted(globals().items()) if k.startswith("test_") and callable(v)]
    for fn in fns:
        fn()
        print(f"ok  {fn.__name__}")
    print(f"\n{len(fns)} passed")