import os from collections.abc import Generator import pytest from core.model_runtime.entities.llm_entities import ( LLMResult, LLMResultChunk, LLMResultChunkDelta, ) from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, PromptMessageTool, SystemPromptMessage, UserPromptMessage, ) from core.model_runtime.errors.validate import CredentialsValidateFailedError from core.model_runtime.model_providers.gpustack.llm.llm import GPUStackLanguageModel def test_validate_credentials_for_chat_model(): model = GPUStackLanguageModel() with pytest.raises(CredentialsValidateFailedError): model.validate_credentials( model="llama-3.2-1b-instruct", credentials={ "endpoint_url": "invalid_url", "api_key": "invalid_api_key", "mode": "chat", }, ) model.validate_credentials( model="llama-3.2-1b-instruct", credentials={ "endpoint_url": os.environ.get("GPUSTACK_SERVER_URL"), "api_key": os.environ.get("GPUSTACK_API_KEY"), "mode": "chat", }, ) def test_invoke_completion_model(): model = GPUStackLanguageModel() response = model.invoke( model="llama-3.2-1b-instruct", credentials={ "endpoint_url": os.environ.get("GPUSTACK_SERVER_URL"), "api_key": os.environ.get("GPUSTACK_API_KEY"), "mode": "completion", }, prompt_messages=[UserPromptMessage(content="ping")], model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10}, stop=[], user="abc-123", stream=False, ) assert isinstance(response, LLMResult) assert len(response.message.content) > 0 assert response.usage.total_tokens > 0 def test_invoke_chat_model(): model = GPUStackLanguageModel() response = model.invoke( model="llama-3.2-1b-instruct", credentials={ "endpoint_url": os.environ.get("GPUSTACK_SERVER_URL"), "api_key": os.environ.get("GPUSTACK_API_KEY"), "mode": "chat", }, prompt_messages=[UserPromptMessage(content="ping")], model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10}, stop=[], user="abc-123", stream=False, ) assert isinstance(response, LLMResult) assert len(response.message.content) > 0 assert response.usage.total_tokens > 0 def test_invoke_stream_chat_model(): model = GPUStackLanguageModel() response = model.invoke( model="llama-3.2-1b-instruct", credentials={ "endpoint_url": os.environ.get("GPUSTACK_SERVER_URL"), "api_key": os.environ.get("GPUSTACK_API_KEY"), "mode": "chat", }, prompt_messages=[UserPromptMessage(content="Hello World!")], model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10}, stop=["you"], 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) assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True def test_get_num_tokens(): model = GPUStackLanguageModel() num_tokens = model.get_num_tokens( model="????", credentials={ "endpoint_url": os.environ.get("GPUSTACK_SERVER_URL"), "api_key": os.environ.get("GPUSTACK_API_KEY"), "mode": "chat", }, prompt_messages=[ SystemPromptMessage( content="You are a helpful AI assistant.", ), UserPromptMessage(content="Hello World!"), ], tools=[ PromptMessageTool( name="get_current_weather", description="Get the current weather in a given location", parameters={ "type": "object", "properties": { "location": { "type": "string", "description": "The city and state e.g. San Francisco, CA", }, "unit": {"type": "string", "enum": ["c", "f"]}, }, "required": ["location"], }, ) ], ) assert isinstance(num_tokens, int) assert num_tokens == 80 num_tokens = model.get_num_tokens( model="????", credentials={ "endpoint_url": os.environ.get("GPUSTACK_SERVER_URL"), "api_key": os.environ.get("GPUSTACK_API_KEY"), "mode": "chat", }, prompt_messages=[UserPromptMessage(content="Hello World!")], ) assert isinstance(num_tokens, int) assert num_tokens == 10