| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104 | import osfrom collections.abc import Generatorimport pytestfrom core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDeltafrom core.model_runtime.entities.message_entities import (    AssistantPromptMessage,    SystemPromptMessage,    UserPromptMessage,)from core.model_runtime.errors.validate import CredentialsValidateFailedErrorfrom core.model_runtime.model_providers.openrouter.llm.llm import OpenRouterLargeLanguageModeldef test_validate_credentials():    model = OpenRouterLargeLanguageModel()    with pytest.raises(CredentialsValidateFailedError):        model.validate_credentials(            model="mistralai/mixtral-8x7b-instruct", credentials={"api_key": "invalid_key", "mode": "chat"}        )    model.validate_credentials(        model="mistralai/mixtral-8x7b-instruct",        credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "chat"},    )def test_invoke_model():    model = OpenRouterLargeLanguageModel()    response = model.invoke(        model="mistralai/mixtral-8x7b-instruct",        credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "completion"},        prompt_messages=[            SystemPromptMessage(                content="You are a helpful AI assistant.",            ),            UserPromptMessage(content="Who are you?"),        ],        model_parameters={            "temperature": 1.0,            "top_k": 2,            "top_p": 0.5,        },        stop=["How"],        stream=False,        user="abc-123",    )    assert isinstance(response, LLMResult)    assert len(response.message.content) > 0def test_invoke_stream_model():    model = OpenRouterLargeLanguageModel()    response = model.invoke(        model="mistralai/mixtral-8x7b-instruct",        credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "chat"},        prompt_messages=[            SystemPromptMessage(                content="You are a helpful AI assistant.",            ),            UserPromptMessage(content="Who are you?"),        ],        model_parameters={            "temperature": 1.0,            "top_k": 2,            "top_p": 0.5,        },        stop=["How"],        stream=True,        user="abc-123",    )    assert isinstance(response, Generator)    for chunk in response:        assert isinstance(chunk, LLMResultChunk)        assert isinstance(chunk.delta, LLMResultChunkDelta)        assert isinstance(chunk.delta.message, AssistantPromptMessage)def test_get_num_tokens():    model = OpenRouterLargeLanguageModel()    num_tokens = model.get_num_tokens(        model="mistralai/mixtral-8x7b-instruct",        credentials={            "api_key": os.environ.get("TOGETHER_API_KEY"),        },        prompt_messages=[            SystemPromptMessage(                content="You are a helpful AI assistant.",            ),            UserPromptMessage(content="Hello World!"),        ],    )    assert isinstance(num_tokens, int)    assert num_tokens == 21
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