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.entities.model_entities import AIModelEntity from core.model_runtime.errors.validate import CredentialsValidateFailedError from core.model_runtime.model_providers.stepfun.llm.llm import StepfunLargeLanguageModel def test_validate_credentials(): model = StepfunLargeLanguageModel() with pytest.raises(CredentialsValidateFailedError): model.validate_credentials(model="step-1-8k", credentials={"api_key": "invalid_key"}) model.validate_credentials(model="step-1-8k", credentials={"api_key": os.environ.get("STEPFUN_API_KEY")}) def test_invoke_model(): model = StepfunLargeLanguageModel() response = model.invoke( model="step-1-8k", credentials={"api_key": os.environ.get("STEPFUN_API_KEY")}, prompt_messages=[UserPromptMessage(content="Hello World!")], model_parameters={"temperature": 0.9, "top_p": 0.7}, stop=["Hi"], stream=False, user="abc-123", ) assert isinstance(response, LLMResult) assert len(response.message.content) > 0 def test_invoke_stream_model(): model = StepfunLargeLanguageModel() response = model.invoke( model="step-1-8k", credentials={"api_key": os.environ.get("STEPFUN_API_KEY")}, prompt_messages=[ SystemPromptMessage( content="You are a helpful AI assistant.", ), UserPromptMessage(content="Hello World!"), ], model_parameters={"temperature": 0.9, "top_p": 0.7}, 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_customizable_model_schema(): model = StepfunLargeLanguageModel() schema = model.get_customizable_model_schema( model="step-1-8k", credentials={"api_key": os.environ.get("STEPFUN_API_KEY")} ) assert isinstance(schema, AIModelEntity) def test_invoke_chat_model_with_tools(): model = StepfunLargeLanguageModel() result = model.invoke( model="step-1-8k", credentials={"api_key": os.environ.get("STEPFUN_API_KEY")}, prompt_messages=[ SystemPromptMessage( content="You are a helpful AI assistant.", ), UserPromptMessage( content="what's the weather today in Shanghai?", ), ], model_parameters={"temperature": 0.9, "max_tokens": 100}, tools=[ PromptMessageTool( name="get_weather", description="Determine weather in my 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"], }, ), PromptMessageTool( name="get_stock_price", description="Get the current stock price", parameters={ "type": "object", "properties": {"symbol": {"type": "string", "description": "The stock symbol"}}, "required": ["symbol"], }, ), ], stream=False, user="abc-123", ) assert isinstance(result, LLMResult) assert isinstance(result.message, AssistantPromptMessage) assert len(result.message.tool_calls) > 0