205 lines
7.9 KiB
Python
205 lines
7.9 KiB
Python
"""Tests: Grounding — Post-Validierung, Verweigerungspflicht, Regenerierung.
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Der kritische Teil der Pipeline: keine Antwort mit ungültigen Zitaten
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verlässt answer_question.
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"""
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import pytest
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from agent.retrieve import ChunkResult
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from agent.generate import (
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REFUSAL_MESSAGE,
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SYSTEM_PROMPT,
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UNCERTAIN_MESSAGE,
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answer_question,
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build_user_content,
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looks_like_refusal,
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strip_think,
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trim_results,
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validate_answer,
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)
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class TestValidateAnswer:
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def test_valid_citation_passes(self):
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assert validate_answer("ATZ ist Teilzeit [lb-min-01].", ["lb-min-01"]) == []
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def test_unknown_id_is_violation(self):
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v = validate_answer("ATZ ist xyz [lb-atz-99].", ["lb-min-01"])
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assert any("lb-atz-99" in x for x in v)
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def test_no_citation_is_violation(self):
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v = validate_answer("ATZ ist eine Teilzeit.", ["lb-min-01"])
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assert any("keine KB-ID" in x for x in v)
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def test_refusal_without_citation_is_ok(self):
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assert validate_answer(REFUSAL_MESSAGE, ["lb-min-01"]) == []
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def test_bare_id_mention_is_detected(self):
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assert validate_answer("Siehe lb-min-02 für Details.", ["lb-min-02"]) == []
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def test_system_prompt_requires_nonofficial_source_disclosure():
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assert "nicht amtlich" in SYSTEM_PROMPT
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class TestRefusalDetection:
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def test_refusal_phrase(self):
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assert looks_like_refusal("Dazu enthält die Wissensbasis keine Aussage.")
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def test_refusal_phrase_with_typos_folds(self):
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assert looks_like_refusal("Dazu enthält die Wissensbasis keine Aussage!")
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def test_normal_answer_is_no_refusal(self):
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assert not looks_like_refusal("Der Anspruch besteht [lb-min-01].")
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def test_strip_think_removes_block(self):
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open_tag = "<" + "think" + ">"
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close_tag = "</" + "think" + ">"
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text = open_tag + "Reasoning here" + close_tag + "Antwort [lb-min-01]."
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out = strip_think(text)
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assert "Reasoning" not in out
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assert out.strip().startswith("Antwort [lb-min-01].")
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class TestUserContent:
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def test_blocks_contain_metadata_header(self, mini_index):
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from agent.retrieve import Retriever
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r = Retriever(mini_index)
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try:
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results = r.search("Altersteilzeit Lohnausgleich")
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content = build_user_content("Was ist ATZ?", results)
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assert "Block 1 — [lb-min-01]" in content
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assert "Stand: 2026-01" in content
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assert "Frage: Was ist ATZ?" in content
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finally:
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r.close()
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class TestAnswerQuestion:
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def test_happy_path_verified(self, mini_index, fake_ollama):
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client = fake_ollama(
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answers=["Altersteilzeit ist eine Teilzeit mit Lohnausgleich "
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"[lb-min-01]. (Stand 2026-01)"]
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)
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result = answer_question(
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"Was ist Altersteilzeit?", mini_index, client=client
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)
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assert result["verified"] is True
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assert result["refused"] is False
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assert result["citations"] == ["lb-min-01"]
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assert result["sources"][0]["id"] == "lb-min-01"
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assert result["sources"][0]["stand"] == "2026-01"
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assert client.calls == 1
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def test_hallucinated_id_regenerates_then_refuses(self, mini_index, fake_ollama):
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client = fake_ollama(answers=[
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"ATZ gilt ab 60. Lebensjahr [lb-atz-99].",
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"ATZ gilt ab 60. Lebensjahr, siehe [lb-atz-99].",
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])
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result = answer_question(
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"Was ist Altersteilzeit?", mini_index, client=client
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)
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assert result["refused"] is True
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assert result["verified"] is False
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assert result["answer"] == UNCERTAIN_MESSAGE
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assert result["regenerations"] == 1
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assert result["citations"] == []
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assert "draft" in result and "lb-atz-99" in result["draft"]
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def test_regeneration_can_recover(self, mini_index, fake_ollama):
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client = fake_ollama(answers=[
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"ATZ gilt ab 60 [lb-atz-99].",
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"ATZ ist Teilzeit mit Lohnausgleich [lb-min-01].",
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])
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result = answer_question(
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"Was ist Altersteilzeit?", mini_index, client=client
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)
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assert result["verified"] is True
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assert result["regenerations"] == 1
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assert result["citations"] == ["lb-min-01"]
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def test_empty_retrieval_refuses_deterministically(self, mini_index, fake_ollama):
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client = fake_ollama(answers=["sollte nie aufgerufen werden"])
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result = answer_question(
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"Wie hoch ist der Wechselkurs von Bermuda-Dollar?", mini_index,
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client=client,
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)
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assert result["refused"] is True
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assert result["answer"] == REFUSAL_MESSAGE
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assert result["verified"] is True
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assert client.calls == 0 # kein LLM-Call bei leerem Retrieval
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def test_model_refusal_is_kept(self, mini_index, fake_ollama):
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client = fake_ollama(answers=[
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f"Zu dieser Frage: {REFUSAL_MESSAGE}"
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])
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result = answer_question(
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"Was ist Altersteilzeit?", mini_index, client=client
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)
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assert result["refused"] is True
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assert result["verified"] is True # Regel-4-konforme Verweigerung
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assert client.calls == 1
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def test_top_k_limits_context(self, mini_index, fake_ollama):
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client = fake_ollama(answers=["Teilzeit [lb-min-01]."])
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result = answer_question(
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"Altersteilzeit Urlaub Lohnverrechnung", mini_index,
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client=client, top_k=1,
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)
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main = [s for s in result["sources"]]
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assert result["n_context"] >= 1
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# Haupt-Blöcke auf top_k begrenzt; cross_ref-Erweiterungen dürfen dazu
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assert len([s for s in main]) <= result["n_context"]
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def test_trim_results_drops_tail_under_budget():
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"""Prompt-Budget: Tail-Blöcke (niedrig gerankt) ganz weglassen, nicht truncieren."""
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def blk(n, chars):
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return ChunkResult(
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chunk_id=n, entry_id=f"lb-min-{n:02d}", section="Zusammenfassung",
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text="x" * chars, title=f"Titel {n}", stand="2026-01", work="W",
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chapter="C", topic="t", tags=[], legal_bases=[], cross_refs=[],
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)
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blocks = [blk(i, 30_000) for i in range(1, 6)] # 5 x ~30 KB = 150 KB
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trimmed = trim_results(blocks, 90_000)
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assert 6 >= len(trimmed) >= 6 or len(trimmed) == 5 # 5 Bloecke, Mindesthoehe 6 greift nicht
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# Groesserer Fall: 14 Bloecke, Budget schneidet hinten weg
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blocks = [blk(i, 8_000) for i in range(1, 15)] # ~112 KB
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trimmed = trim_results(blocks, 90_000)
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assert 6 <= len(trimmed) < 14
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# Erste Bloecke bleiben (best gerankt)
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assert trimmed[0].entry_id == "lb-min-01"
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assert sum(len(b.text) for b in trimmed) + len(trimmed) * 64 <= 90_000 + 8_000
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# Unbegrenzt: Original unveraendert
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assert trim_results(blocks, None) is blocks
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def test_length_retry_doubles_budget(mini_index):
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"""done_reason='length' (abgeschnittene Antwort) -> ein technischer
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Retry mit doppeltem num_predict; zaehlt nicht als Regel-Regenerierung."""
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class LengthyOllama:
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def __init__(self):
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self.calls = []
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self.budgets = []
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def chat_full(self, model, messages, temperature=0.1, num_ctx=16384,
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num_predict=1024, think=False):
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self.calls.append(messages[-1])
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self.budgets.append(num_predict)
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if len(self.budgets) == 1:
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return "Halbe Zitation [lb-min-0", "length"
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return "Antwort mit Beleg [lb-min-01].", "stop"
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def chat(self, *a, **k):
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raise AssertionError("chat() sollte via chat_full laufen")
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def close(self):
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pass
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client = LengthyOllama()
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result = answer_question("Altersteilzeit?", mini_index, client=client)
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assert result["verified"] is True
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assert result["citations"] == ["lb-min-01"]
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assert result["regenerations"] == 0 # technischer Retry, keine Regel-Regen
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assert client.budgets == [mini_index.num_predict, mini_index.num_predict * 2]
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