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import os
import dashscope
import pytest
from core.model_runtime.entities.rerank_entities import RerankResult
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.tongyi.rerank.rerank import GTERerankModel
def test_validate_credentials():
model = GTERerankModel()
with pytest.raises(CredentialsValidateFailedError):
model.validate_credentials(model="get-rank", credentials={"dashscope_api_key": "invalid_key"})
model.validate_credentials(
model="get-rank", credentials={"dashscope_api_key": os.environ.get("TONGYI_DASHSCOPE_API_KEY")}
)
def test_invoke_model():
model = GTERerankModel()
result = model.invoke(
model=dashscope.TextReRank.Models.gte_rerank,
credentials={"dashscope_api_key": os.environ.get("TONGYI_DASHSCOPE_API_KEY")},
query="什么是文本排序模型",
docs=[
"文本排序模型广泛用于搜索引擎和推荐系统中，它们根据文本相关性对候选文本进行排序",
"量子计算是计算科学的一个前沿领域",
"预训练语言模型的发展给文本排序模型带来了新的进展",
],
score_threshold=0.7,
)
assert isinstance(result, RerankResult)
assert len(result.docs) == 1
assert result.docs[0].index == 0
assert result.docs[0].score >= 0.7
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