feat: add gte rerank for tongyi (#9153)

api/tests/integration_tests/model_runtime/tongyi/test_rerank.py

@@ -0,0 +1,40 @@
+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