astrololo/services/logic/tests/test_prompt.py

"""Generator promptów (LOG-29) i budżetowanie (LOG-30).

Testy nie wołają żadnego modelu — sprawdzają skład promptu i niezmienniki redukcji.
"""
import pytest

from app.prompt import (
    BUDGETS,
    build_natal_prompt,
    build_period_prompt,
    natal_indications,
    period_indications,
    reduce_indications,
)

CHART = {
    "zodiac": "tropical",
    "house_system": "whole_sign",
    "sect": "day",
    "positions": [
        {"name": "Sun", "sign": "Taurus", "in_sign": "Tau 10°12'37\"", "house": 11, "direction": "D"},
        {"name": "Moon", "sign": "Aries", "in_sign": "Ari 7°48'40\"", "house": 10, "direction": "D"},
    ],
    "angles": {"Asc": {"name": "Asc", "in_sign": "Can 16°00'54\""},
               "MC": {"name": "MC", "in_sign": "Pis 25°50'50\""}},
    "lots": [{"name": "Fortune", "in_sign": "Can 7°15'14\"", "house": 1,
              "formula": "Asc + Moon − Sun"}],
    "aspects": [{"obj1": "Sun", "obj2": "Moon", "aspect": "conjunction", "orb": 2.34, "as": "A"}],
}


def _report(n_samples=3, score=2.0):
    return {"objects": [{
        "object": "Sun", "sign": "Taurus", "house": 11,
        "facets": [{
            "type": "sign", "label": "w znaku Taurus", "score": score,
            "samples": [{"significator": f"[Su in [Tau {i}", "expanded": f"Sun in Taurus {i}",
                         "effect": f"efekt numer {i}"} for i in range(n_samples)],
        }],
    }]}


# ---------------------------------------------------------------- budżetowanie

def test_budget_limits_prompt_size():
    # opisy MUSZĄ być różne — identyczne zlałoby grupowanie w jedną pozycję
    big = {"objects": [{
        "object": "Sun", "sign": "Taurus", "house": 11,
        "facets": [{"type": "sign", "label": "w znaku Taurus", "score": 1.0,
                    "samples": [{"significator": f"[Su {i}", "expanded": f"Sun {i}",
                                 "effect": f"opis {i} " + "x" * 200} for i in range(500)]}],
    }]}
    out = build_natal_prompt(CHART, big, budget="concise")
    assert out["stats"]["chars"] <= BUDGETS["concise"] * 1.1     # z marginesem na sekcje stałe
    assert out["stats"]["omitted"] > 0


def test_bigger_budget_includes_more():
    big = _report(n_samples=300, score=1.0)
    small = build_natal_prompt(CHART, big, budget="concise")["stats"]
    large = build_natal_prompt(CHART, big, budget="extensive")["stats"]
    assert large["included"] > small["included"]
    assert large["omitted"] < small["omitted"]


def test_grouping_merges_identical_effects():
    items = [
        {"context": "Sun — w znaku", "sort_key": ("Sun", "a"), "score": 1.0,
         "significator": "Sun in Taurus", "effect": "ten sam opis"},
        {"context": "Sun — w znaku", "sort_key": ("Sun", "a"), "score": 1.0,
         "significator": "Sun in Taurus (inny zapis)", "effect": "Ten Sam Opis  "},
    ]
    chosen, stats = reduce_indications(items, 10_000)
    assert len(chosen) == 1                    # zlane w jedno
    assert chosen[0]["count"] == 2             # z licznikiem wystąpień
    assert stats["after_grouping"] == 1
    assert stats["deduplicated"] == 1


def test_sorted_by_score_desc():
    items = [
        {"context": f"c{i}", "sort_key": (f"c{i}", ""), "score": float(i),
         "significator": f"s{i}", "effect": f"e{i}"} for i in range(5)
    ]
    chosen, _ = reduce_indications(items, 10_000)
    scores = [c["score"] for c in chosen]
    assert scores == sorted(scores, reverse=True)


def test_weakest_are_dropped_first():
    items = [
        {"context": f"c{i}", "sort_key": (f"c{i}", ""), "score": float(i),
         "significator": f"s{i}", "effect": "opis " * 20} for i in range(20)
    ]
    chosen, stats = reduce_indications(items, 400)
    assert stats["omitted"] > 0
    # to, co weszło, ma wagę nie niższą niż to, co odpadło
    assert stats["min_score_included"] >= stats["max_score_omitted"]


def test_long_effects_are_shortened():
    items = [{"context": "c", "sort_key": ("c", ""), "score": 1.0,
              "significator": "s", "effect": "x" * 1000}]
    chosen, stats = reduce_indications(items, 10_000)
    assert stats["shortened"] == 1
    assert "skrócono" in chosen[0]["effect"]


def test_never_truncates_mid_indication():
    items = [{"context": "c", "sort_key": ("c", ""), "score": 1.0,
              "significator": "s", "effect": "opis " * 50} for _ in range(10)]
    chosen, _ = reduce_indications(items, 200)
    assert chosen                                  # zawsze co najmniej jedno całe
    for c in chosen:
        assert c["effect"].endswith(("opis", "[…skrócono]"))   # nie urwane w pół słowa


def test_unknown_budget_rejected():
    with pytest.raises(ValueError):
        build_natal_prompt(CHART, _report(), budget="gigantyczny")


# ----------------------------------------------------------------- skład promptu

def test_natal_prompt_contains_required_sections():
    p = build_natal_prompt(CHART, _report(), moment_label="1984-04-30 09:20 UTC")["prompt"]
    for section in ["# ZADANIE", "# DANE HOROSKOPU", "# WSKAZANIA Z BAZ",
                    "# JAK MA WYGLĄDAĆ ODPOWIEDŹ", "# ZASTRZEŻENIE"]:
        assert section in p
    assert "HOROSKOPU\nURODZENIOWEGO" in p or "URODZENIOWEGO" in p


def test_natal_prompt_carries_chart_data():
    p = build_natal_prompt(CHART, _report(), moment_label="1984-04-30 09:20 UTC")["prompt"]
    assert "Tau 10°12'37\"" in p and "dom 11" in p      # pozycja + dom
    assert "Can 16°00'54\"" in p                          # Asc
    assert "Fortune" in p                                 # Lots
    assert "Sun conjunction Moon" in p or "conjunction" in p
    assert "sekta: dzienna" in p
    assert "1984-04-30 09:20 UTC" in p


def test_prompt_demands_citing_significators():
    p = build_natal_prompt(CHART, _report())["prompt"]
    assert "Teza bez wskazania jest niedopuszczalna" in p
    assert "Nie zmyślaj" in p


def test_prompt_has_disclaimer():
    p = build_natal_prompt(CHART, _report())["prompt"]
    assert "nie stanowi porady" in p


def test_prompt_is_deterministic():
    a = build_natal_prompt(CHART, _report(n_samples=50), budget="medium")["prompt"]
    b = build_natal_prompt(CHART, _report(n_samples=50), budget="medium")["prompt"]
    assert a == b


def test_omission_is_reported_in_prompt():
    out = build_natal_prompt(CHART, _report(n_samples=400, score=1.0), budget="concise")
    assert out["stats"]["omitted"] > 0
    assert "pominięto" in out["prompt"]      # użytkownik/model wie, że coś odpadło


def test_empty_report_still_builds_prompt():
    out = build_natal_prompt(CHART, {"objects": []})
    assert out["stats"]["included"] == 0
    assert "brak trafień" in out["prompt"]
    assert "# DANE HOROSKOPU" in out["prompt"]


# ------------------------------------------------------------------- okresowy

EVENTS = [
    {"technique": "profection", "significator": "Lord of Year: Mars", "start": "2026-04-30",
     "exact": "2026-04-30", "end": "2027-04-30", "interpretations_count": 2,
     "interpretations": [{"significator": "[Ma", "expanded": "Mars", "effect": "opis marsowy"}]},
    {"technique": "solar_arc", "significator": "Sun conj Saturn", "start": "2026-01-01",
     "exact": "2026-06-15", "end": "2026-12-31", "interpretations_count": 1,
     "interpretations": [{"significator": "[Su [conj [Sa", "expanded": "Sun conjunction Saturn",
                          "effect": "opis saturniczny"}]},
]


def test_period_prompt_has_dates_and_timeline():
    out = build_period_prompt(CHART, EVENTS, "2026-01-01", "2027-01-01")
    p = out["prompt"]
    assert "2026-01-01 — 2027-01-01" in p
    assert "# OŚ CZASU" in p
    assert "profection" in p and "solar_arc" in p
    assert "2026-06-15" in p                      # data dokładna zdarzenia
    assert "CHRONOLOGICZNIE" in p
    assert out["stats"]["events"] == 2
    assert out["profile"] == "period"


def test_period_prompt_keeps_timeline_without_interpretations():
    """Padnięta warstwa danych zabiera wskazania, ale NIE oś czasu — ta jest czysto
    obliczeniowa i bez niej prognoza okresowa jest bezużyteczna."""
    bare = [{k: v for k, v in ev.items()
             if k not in ("interpretations", "interpretations_count")} for ev in EVENTS]
    out = build_period_prompt(CHART, bare, "2026-01-01", "2027-01-01")
    assert out["stats"]["events"] == 2
    assert "profection" in out["prompt"] and "2026-06-15" in out["prompt"]
    assert out["stats"]["included"] == 0          # brak wskazań, ale oś czasu jest


def test_period_indications_weight_by_hit_count():
    items = period_indications(EVENTS)
    assert [i["score"] for i in items] == [2.0, 1.0]


def test_natal_indications_flatten_facets():
    items = natal_indications(_report(n_samples=4))
    assert len(items) == 4
    assert all(i["context"].startswith("Sun —") for i in items)
    assert all(i["score"] == 2.0 for i in items)