mitai-jinkendo/backend/tests/test_placeholder_modifier_d.py

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"""Tests für {{key|d}}, {{key|x}}, ai_caption und Unbekannt-Erkennung."""
from placeholder_registry import (
PlaceholderMetadata,
PlaceholderType,
OutputType,
build_ai_placeholder_caption,
)
import placeholder_resolver as pr
from placeholder_resolver import format_value_with_d_modifier
from prompt_executor import resolve_placeholders
def test_build_ai_caption_is_explanation_only():
m = PlaceholderMetadata(
key="test_x",
category="Test",
description="Kurzbeschreibung",
resolver_module="m",
resolver_function="f",
semantic_contract="Lang Vertrag " * 50,
business_meaning="Kernbedeutung für die KI.",
unit="g/day",
placeholder_type=PlaceholderType.INTERPRETED,
output_type=OutputType.NUMERIC,
)
cap = build_ai_placeholder_caption(m)
assert "Kernbedeutung" in cap
assert "Kurzbeschreibung" not in cap
def test_build_ai_caption_protein_avg_no_description_prefix():
m = PlaceholderMetadata(
key="protein_avg",
category="Ernährung",
description="Durchschn. Protein in g (30d)",
resolver_module="m",
resolver_function="f",
business_meaning="Zentraler Placeholder für Muskelerhalt.",
unit="g/day",
placeholder_type=PlaceholderType.INTERPRETED,
output_type=OutputType.NUMERIC,
)
cap = build_ai_placeholder_caption(m)
assert cap.startswith("Zentraler Placeholder")
assert "Durchschn. Protein" not in cap
assert "Technischer Bezug" not in cap
def test_build_ai_caption_score_adds_scale():
m = PlaceholderMetadata(
key="test_score",
category="Test",
description="Score",
resolver_module="m",
resolver_function="f",
business_meaning="Gewichteter Gesamtscore.",
unit="Score (0-100)",
placeholder_type=PlaceholderType.SCORE,
output_type=OutputType.NUMERIC,
)
cap = build_ai_placeholder_caption(m)
assert "0–100" in cap or "0-100" in cap
assert "Gewichteter" in cap
def test_placeholder_token_regex_optional_modifier():
m0 = pr._PLACEHOLDER_TOKEN_RE.search("{{fat_avg}}")
assert m0 and m0.group(1) == "fat_avg" and m0.group(2) is None
m1 = pr._PLACEHOLDER_TOKEN_RE.search("{{fat_avg|d}}")
assert m1 and m1.group(1) == "fat_avg" and m1.group(2).strip() == "d"
m2 = pr._PLACEHOLDER_TOKEN_RE.search("{{ protein_avg | d }}")
assert m2 and m2.group(1) == "protein_avg" and m2.group(2).strip() == "d"
m3 = pr._PLACEHOLDER_TOKEN_RE.search("{{k|d,x}}")
assert m3 and m3.group(1) == "k" and m3.group(2).strip() == "d,x"
def test_get_unknown_placeholders_strips_modifier():
unk = pr.get_unknown_placeholders("{{not_a_real_key|d}}")
assert set(unk) == {"not_a_real_key"}
def test_format_value_with_d_modifier_uses_description_only():
row = {
"key": "protein_avg",
"description": "Durchschn. Protein in g (30d)",
"ai_caption": "Nur für |x",
}
out = format_value_with_d_modifier("119g/Tag", row)
assert out == "119g/Tag — Durchschn. Protein in g (30d)"
assert "Nur für |x" not in out
def test_format_value_with_d_modifier_falls_back_to_description():
row = {"description": "Nur Beschreibung", "key": "x"}
assert format_value_with_d_modifier("42", row) == "42 — Nur Beschreibung"
def test_prompt_executor_modifiers_d_x_combined():
catalog = {"E": [{"key": "p", "description": "Desc", "ai_caption": "Expl"}]}
v = {"p": "99"}
assert resolve_placeholders("{{p|d}}", v, None, catalog) == "99 — Desc"
assert resolve_placeholders("{{p|x}}", v, None, catalog) == "Expl"
assert resolve_placeholders("{{p|d,x}}", v, None, catalog) == "99 — Desc — Expl"
assert resolve_placeholders("{{p}}", v, None, catalog) == "99"