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.gitee_ai.llm.llm import GiteeAILargeLanguageModel def test_predefined_models(): model = GiteeAILargeLanguageModel() model_schemas = model.predefined_models() assert len(model_schemas) >= 1 assert isinstance(model_schemas[0], AIModelEntity) def test_validate_credentials_for_chat_model(): model = GiteeAILargeLanguageModel() with pytest.raises(CredentialsValidateFailedError): # model name to gpt-3.5-turbo because of mocking model.validate_credentials(model="gpt-3.5-turbo", credentials={"api_key": "invalid_key"}) model.validate_credentials( model="Qwen2-7B-Instruct", credentials={"api_key": os.environ.get("GITEE_AI_API_KEY")}, ) def test_invoke_chat_model(): model = GiteeAILargeLanguageModel() result = model.invoke( model="Qwen2-7B-Instruct", credentials={"api_key": os.environ.get("GITEE_AI_API_KEY")}, prompt_messages=[ SystemPromptMessage( content="You are a helpful AI assistant.", ), UserPromptMessage(content="Hello World!"), ], model_parameters={ "temperature": 0.0, "top_p": 1.0, "presence_penalty": 0.0, "frequency_penalty": 0.0, "max_tokens": 10, "stream": False, }, stop=["How"], stream=False, user="foo", ) assert isinstance(result, LLMResult) assert len(result.message.content) > 0 def test_invoke_stream_chat_model(): model = GiteeAILargeLanguageModel() result = model.invoke( model="Qwen2-7B-Instruct", credentials={"api_key": os.environ.get("GITEE_AI_API_KEY")}, prompt_messages=[ SystemPromptMessage( content="You are a helpful AI assistant.", ), UserPromptMessage(content="Hello World!"), ], model_parameters={"temperature": 0.0, "max_tokens": 100, "stream": False}, stream=True, user="foo", ) assert isinstance(result, Generator) for chunk in result: 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 if chunk.delta.finish_reason is not None: assert chunk.delta.usage is not None def test_get_num_tokens(): model = GiteeAILargeLanguageModel() num_tokens = model.get_num_tokens( model="Qwen2-7B-Instruct", credentials={"api_key": os.environ.get("GITEE_AI_API_KEY")}, prompt_messages=[UserPromptMessage(content="Hello World!")], ) assert num_tokens == 10 num_tokens = model.get_num_tokens( model="Qwen2-7B-Instruct", credentials={"api_key": os.environ.get("GITEE_AI_API_KEY")}, prompt_messages=[ SystemPromptMessage( content="You are a helpful AI assistant.", ), UserPromptMessage(content="Hello World!"), ], 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"], }, ), ], ) assert num_tokens == 77