gwoe-antragspruefer/tests/test_llm_bewerter.py
Dotty Dotter 2902164eff test: 467 -> 574 Tests (+107) — DDD, abgeordnetenwatch, monitoring, v2, Bug-Regressions
Neue Tests in dieser Migration:
- test_database.py (Merkliste-CRUD, Subscriptions, abgeordnetenwatch-Joins)
- test_clustering.py (82% Coverage)
- test_drucksache_typen.py (100%)
- test_mail.py (86%)
- test_monitoring.py (23 Tests)
- test_abgeordnetenwatch.py (23 Tests, inkl. Drucksache-Extraction)
- test_redline_parser.py (20 Tests fuer §INS§/§DEL§-Marker)
- test_bug_regressions.py (PRAGMA, JWT-azp, CDU-PDF, PFLICHT-FRAKTIONEN, NRW-Titel)
- test_embeddings_v3_v4.py (WRITE/READ-Pattern)
- test_wahlprogramm_check.py (#128)
- test_wahlprogramm_fetch.py (#138)
- test_antrag/bewertung/abonnement_repository.py + test_llm_bewerter.py (DDD)
- test_domain_behavior.py (5 Domain-Methoden boundary tests)
- tests/e2e/test_ui.py (Playwright)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 20:55:57 +02:00

138 lines
5.1 KiB
Python

"""Tests für LlmBewerter-Port und QwenBewerter-Adapter (ADR 0008).
Der Adapter wird mit einem Fake-Client getestet — kein Netzwerk, kein
``openai``-Paket. Retry-Semantik (Temperatur steigt um 0.1 pro Versuch)
ist hier explizit getestet, damit die Migration die Semantik nicht
still verändert.
"""
from __future__ import annotations
import asyncio
import json
import types
import pytest
from app.adapters.qwen_bewerter import QwenBewerter, _strip_markdown_fences
from app.ports.llm_bewerter import LlmBewerter, LlmRequest
def _run(coro):
return asyncio.get_event_loop().run_until_complete(coro)
def _make_fake_client(responses: list[str]):
"""Produziert einen Fake-OpenAI-Client, der pro Call einen Response aus
der Liste liefert und Metadaten (Temperatur) aufzeichnet."""
calls: list[dict] = []
class FakeCompletions:
async def create(self, **kwargs):
calls.append(dict(kwargs))
idx = len(calls) - 1
content = responses[min(idx, len(responses) - 1)]
return types.SimpleNamespace(
choices=[types.SimpleNamespace(
message=types.SimpleNamespace(content=content)
)]
)
class FakeChat:
completions = FakeCompletions()
class FakeClient:
chat = FakeChat()
return FakeClient(), calls
# ─── Strip-Fences ──────────────────────────────────────────────────────────
class TestStripMarkdownFences:
def test_plain_json_unchanged(self):
assert _strip_markdown_fences('{"a": 1}') == '{"a": 1}'
def test_json_fence(self):
assert _strip_markdown_fences('```json\n{"a": 1}\n```') == '{"a": 1}'
def test_plain_fence(self):
assert _strip_markdown_fences('```\n{"a": 1}\n```') == '{"a": 1}'
# ─── Protocol-Konformität ──────────────────────────────────────────────────
class TestProtocol:
def test_qwen_implements_llm_bewerter(self):
# runtime_checkable Protocol — Method bewerte existiert
qb = QwenBewerter(api_key="x", base_url="y", client=object())
assert isinstance(qb, LlmBewerter)
# ─── QwenBewerter mit FakeClient ───────────────────────────────────────────
class TestQwenBewerterHappyPath:
def test_single_successful_call(self):
fake, calls = _make_fake_client(['{"gwoeScore": 7.0}'])
qb = QwenBewerter(api_key="x", base_url="y", client=fake)
request = LlmRequest(system_prompt="sys", user_prompt="usr")
result = _run(qb.bewerte(request))
assert result == {"gwoeScore": 7.0}
assert len(calls) == 1
assert calls[0]["temperature"] == pytest.approx(0.3)
def test_markdown_fence_is_stripped(self):
fake, _ = _make_fake_client(['```json\n{"gwoeScore": 8.0}\n```'])
qb = QwenBewerter(client=fake)
result = _run(qb.bewerte(LlmRequest("sys", "usr")))
assert result == {"gwoeScore": 8.0}
def test_passes_model_through(self):
fake, calls = _make_fake_client(['{"a": 1}'])
qb = QwenBewerter(client=fake)
_run(qb.bewerte(LlmRequest("sys", "usr", model="qwen-turbo")))
assert calls[0]["model"] == "qwen-turbo"
class TestQwenBewerterRetries:
def test_retry_raises_temperature(self):
"""Bei JSON-Parse-Fehler steigt die Temperatur um 0.1 pro Versuch."""
fake, calls = _make_fake_client([
"nicht valides JSON",
"immer noch kaputt",
'{"gwoeScore": 6.0}', # 3. Versuch klappt
])
qb = QwenBewerter(client=fake)
request = LlmRequest("sys", "usr", max_retries=3)
result = _run(qb.bewerte(request))
assert result == {"gwoeScore": 6.0}
assert len(calls) == 3
assert calls[0]["temperature"] == pytest.approx(0.3)
assert calls[1]["temperature"] == pytest.approx(0.4)
assert calls[2]["temperature"] == pytest.approx(0.5)
def test_exhausted_retries_raise(self):
fake, _ = _make_fake_client([
"kaputt", "kaputt", "kaputt",
])
qb = QwenBewerter(client=fake)
request = LlmRequest("sys", "usr", max_retries=3)
with pytest.raises(json.JSONDecodeError):
_run(qb.bewerte(request))
def test_single_retry_is_respected(self):
"""max_retries=1 heißt: genau ein Versuch, kein Retry."""
fake, calls = _make_fake_client(["kaputt"])
qb = QwenBewerter(client=fake)
with pytest.raises(json.JSONDecodeError):
_run(qb.bewerte(LlmRequest("sys", "usr", max_retries=1)))
assert len(calls) == 1
class TestLlmRequestDefaults:
def test_defaults_match_legacy_analyzer(self):
req = LlmRequest("s", "u")
assert req.model == "qwen-plus"
assert req.max_retries == 3
assert req.max_tokens == 4000
assert req.base_temperature == 0.3