71 lines
2.5 KiB
Python
71 lines
2.5 KiB
Python
from unittest.mock import Mock, patch
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import os
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import pytest
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from mem0.configs.llms.base import BaseLlmConfig
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from mem0.llms.openai import OpenAILLM
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@pytest.fixture
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def mock_openai_client():
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with patch("mem0.llms.openai.OpenAI") as mock_openai:
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mock_client = Mock()
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mock_openai.return_value = mock_client
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yield mock_client
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def test_openai_llm_base_url():
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# case1: default config: with openai official base url
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config = BaseLlmConfig(
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model="gpt-4o", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
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)
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llm = OpenAILLM(config)
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# Note: openai client will parse the raw base_url into a URL object, which will have a trailing slash
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assert str(llm.client.base_url) == "https://api.openai.com/v1/"
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# case2: with env variable OPENAI_API_BASE
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provider_base_url = "https://api.provider.com/v1"
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os.environ["OPENAI_API_BASE"] = provider_base_url
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config = BaseLlmConfig(
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model="gpt-4o", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
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)
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llm = OpenAILLM(config)
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# Note: openai client will parse the raw base_url into a URL object, which will have a trailing slash
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assert str(llm.client.base_url) == provider_base_url + "/"
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# case3: with config.openai_base_url
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config_base_url = "https://api.config.com/v1"
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config = BaseLlmConfig(
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model="gpt-4o",
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temperature=0.7,
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max_tokens=100,
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top_p=1.0,
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api_key="api_key",
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openai_base_url=config_base_url,
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)
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llm = OpenAILLM(config)
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# Note: openai client will parse the raw base_url into a URL object, which will have a trailing slash
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assert str(llm.client.base_url) == config_base_url + "/"
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def test_generate_response(mock_openai_client):
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config = BaseLlmConfig(model="gpt-4o", temperature=0.7, max_tokens=100, top_p=1.0)
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llm = OpenAILLM(config)
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Hello, how are you?"},
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]
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mock_response = Mock()
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mock_response.choices = [
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Mock(message=Mock(content="I'm doing well, thank you for asking!"))
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]
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mock_openai_client.chat.completions.create.return_value = mock_response
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response = llm.generate_response(messages)
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mock_openai_client.chat.completions.create.assert_called_once_with(
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model="gpt-4o", messages=messages, temperature=0.7, max_tokens=100, top_p=1.0
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)
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assert response == "I'm doing well, thank you for asking!"
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