wehub-resource-sync
134 lines
4.1 KiB
Python
134 lines
4.1 KiB
Python
from types import SimpleNamespace
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import pytest
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from yuxi.knowledge.eval import service as eval_service_module
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from yuxi.knowledge.eval.service import EvaluationService, build_evaluation_run_name
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class FakeEvaluationRepository:
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def __init__(self):
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self.created_dataset = None
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self.updated_dataset = None
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self.dataset = None
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self.created_run = None
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async def create_dataset(self, payload):
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self.created_dataset = payload
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async def update_dataset(self, dataset_id, payload):
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self.updated_dataset = (dataset_id, payload)
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async def get_dataset(self, dataset_id):
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return self.dataset
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async def create_run(self, payload):
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self.created_run = payload
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class FakeChunkRepository:
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def __init__(self, indexed_count):
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self.indexed_count = indexed_count
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async def count_graph_indexed_by_kb_id(self, kb_id):
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return self.indexed_count
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class FakeKnowledgeBaseRepository:
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async def get_by_kb_id(self, kb_id):
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return SimpleNamespace(query_params={"options": {"top_k": 3}})
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@pytest.mark.asyncio
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async def test_generate_dataset_saves_generation_params(monkeypatch):
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async def fake_enqueue(**kwargs):
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return SimpleNamespace(id="task_1")
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monkeypatch.setattr(eval_service_module.tasker, "enqueue", fake_enqueue)
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service = EvaluationService()
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service.eval_repo = FakeEvaluationRepository()
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service.chunk_repo = FakeChunkRepository(indexed_count=1)
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result = await service.generate_dataset(
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kb_id="db_1",
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name="dataset",
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description="desc",
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count=2,
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neighbors_count=3,
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concurrency_count=4,
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llm_model_spec="test:model",
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generation_mode="graph_enhanced",
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graph_expand_top_k=2,
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created_by="user_1",
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)
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assert result["task_id"] == "task_1"
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params = service.eval_repo.created_dataset["build_metadata"]["params"]
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assert params["generation_mode"] == "graph_enhanced"
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assert params["graph_expand_top_k"] == 2
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updated_metadata = service.eval_repo.updated_dataset[1]["build_metadata"]
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assert updated_metadata["params"] == params
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@pytest.mark.asyncio
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async def test_generate_dataset_rejects_graph_mode_without_indexed_chunks():
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service = EvaluationService()
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service.eval_repo = FakeEvaluationRepository()
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service.chunk_repo = FakeChunkRepository(indexed_count=0)
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with pytest.raises(ValueError, match="尚未完成图索引"):
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await service.generate_dataset(
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kb_id="db_1",
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name="dataset",
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description="desc",
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count=2,
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neighbors_count=3,
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concurrency_count=4,
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llm_model_spec="test:model",
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generation_mode="graph_enhanced",
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graph_expand_top_k=1,
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created_by="user_1",
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)
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assert service.eval_repo.created_dataset is None
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def test_build_evaluation_run_name_uses_eval_date_hash_format():
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name = build_evaluation_run_name(hash_value="abcdef12")
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assert name.startswith("eval-")
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assert name.endswith("-abcdef")
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assert len(name.split("-")[1]) == 8
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@pytest.mark.asyncio
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async def test_run_evaluation_saves_custom_name(monkeypatch):
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async def fake_enqueue(**kwargs):
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return SimpleNamespace(id="task_1")
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monkeypatch.setattr(eval_service_module.tasker, "enqueue", fake_enqueue)
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repo = FakeEvaluationRepository()
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repo.dataset = SimpleNamespace(
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dataset_id="dataset_1",
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kb_id="db_1",
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name="dataset",
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item_count=2,
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build_metadata={"status": "completed"},
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)
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service = EvaluationService()
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service.eval_repo = repo
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service.kb_repo = FakeKnowledgeBaseRepository()
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run_id = await service.run_evaluation(
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kb_id="db_1",
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dataset_id="dataset_1",
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name=" 回归评估 ",
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model_config={"answer_llm": "test:model"},
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created_by="user_1",
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)
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assert run_id.startswith("run_")
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assert repo.created_run["name"] == "回归评估"
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assert repo.created_run["retrieval_config"]["top_k"] == 3
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assert repo.created_run["retrieval_config"]["answer_llm"] == "test:model"
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