IETM_FIXE\ietm6
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Mise en place de tests unitaires coté Python et Angular Mise en place de la couverture de test directement dans le workflow : le programme ne build pas si jamais un test échoue Passage en v0.16.2 en conséquence
61 lines
2.3 KiB
Python
61 lines
2.3 KiB
Python
"""Tests du reranking LLM des passages RAG (app.application.rerank)."""
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from __future__ import annotations
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from app.application.rerank import pool_size, rerank
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class FakeLLM:
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def __init__(self, response: str | None = None, exc: Exception | None = None) -> None:
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self.response = response
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self.exc = exc
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async def generate(self, prompt, *, temperature=None, output_format=None) -> str:
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if self.exc:
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raise self.exc
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return self.response
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def test_pool_size():
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assert pool_size(8) == 24 # min(max(24, 8), 24)
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assert pool_size(4) == 12 # 4 * 3
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assert pool_size(10) == 24 # plafonné à POOL_MAX
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assert pool_size(1) == 3
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async def test_rerank_skips_when_pool_not_larger_than_top_k():
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passages = [{"text": "a"}, {"text": "b"}]
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# len <= top_k → renvoyé tel quel, sans appel LLM.
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assert await rerank(FakeLLM(exc=AssertionError("ne doit pas être appelé")),
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"q", passages, top_k=3) == passages
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async def test_rerank_reorders_by_llm_scores():
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passages = [{"text": "a"}, {"text": "b"}, {"text": "c"}]
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out = await rerank(FakeLLM(response='{"scores":[1, 9, 5]}'), "q", passages, top_k=2)
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assert [p["text"] for p in out] == ["b", "c"]
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async def test_rerank_stable_on_score_ties():
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passages = [{"text": "a"}, {"text": "b"}, {"text": "c"}]
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# Notes égales → ordre cosinus d'origine préservé.
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out = await rerank(FakeLLM(response='{"scores":[5, 5, 5]}'), "q", passages, top_k=2)
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assert [p["text"] for p in out] == ["a", "b"]
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async def test_rerank_llm_failure_falls_back_to_cosine_order():
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passages = [{"text": "a"}, {"text": "b"}, {"text": "c"}]
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out = await rerank(FakeLLM(exc=RuntimeError("LLM HS")), "q", passages, top_k=2)
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assert [p["text"] for p in out] == ["a", "b"]
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async def test_rerank_wrong_score_count_falls_back():
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passages = [{"text": "a"}, {"text": "b"}, {"text": "c"}]
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out = await rerank(FakeLLM(response='{"scores":[1, 2]}'), "q", passages, top_k=2)
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assert [p["text"] for p in out] == ["a", "b"]
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async def test_rerank_non_numeric_scores_fall_back():
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passages = [{"text": "a"}, {"text": "b"}, {"text": "c"}]
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out = await rerank(FakeLLM(response='{"scores":["x","y","z"]}'), "q", passages, top_k=2)
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assert [p["text"] for p in out] == ["a", "b"]
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