| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566 | import osimport pytestfrom core.model_runtime.entities.text_embedding_entities import TextEmbeddingResultfrom core.model_runtime.errors.validate import CredentialsValidateFailedErrorfrom core.model_runtime.model_providers.ollama.text_embedding.text_embedding import OllamaEmbeddingModeldef test_validate_credentials():    model = OllamaEmbeddingModel()    with pytest.raises(CredentialsValidateFailedError):        model.validate_credentials(            model="mistral:text",            credentials={                "base_url": "http://localhost:21434",                "mode": "chat",                "context_size": 4096,            },        )    model.validate_credentials(        model="mistral:text",        credentials={            "base_url": os.environ.get("OLLAMA_BASE_URL"),            "mode": "chat",            "context_size": 4096,        },    )def test_invoke_model():    model = OllamaEmbeddingModel()    result = model.invoke(        model="mistral:text",        credentials={            "base_url": os.environ.get("OLLAMA_BASE_URL"),            "mode": "chat",            "context_size": 4096,        },        texts=["hello", "world"],        user="abc-123",    )    assert isinstance(result, TextEmbeddingResult)    assert len(result.embeddings) == 2    assert result.usage.total_tokens == 2def test_get_num_tokens():    model = OllamaEmbeddingModel()    num_tokens = model.get_num_tokens(        model="mistral:text",        credentials={            "base_url": os.environ.get("OLLAMA_BASE_URL"),            "mode": "chat",            "context_size": 4096,        },        texts=["hello", "world"],    )    assert num_tokens == 2
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