66 lines
2.4 KiB
Python
66 lines
2.4 KiB
Python
from unittest.mock import MagicMock, patch
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import pytest
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from langchain.schema import HumanMessage, SystemMessage
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from embedchain.config import BaseLlmConfig
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from embedchain.llm.anthropic import AnthropicLlm
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@pytest.fixture
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def anthropic_llm():
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config = BaseLlmConfig(temperature=0.5, model="gpt2")
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return AnthropicLlm(config)
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def test_get_llm_model_answer(anthropic_llm):
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with patch.object(AnthropicLlm, "_get_answer", return_value="Test Response") as mock_method:
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prompt = "Test Prompt"
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response = anthropic_llm.get_llm_model_answer(prompt)
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assert response == "Test Response"
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mock_method.assert_called_once_with(prompt=prompt, config=anthropic_llm.config)
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def test_get_answer(anthropic_llm):
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with patch("langchain.chat_models.ChatAnthropic") as mock_chat:
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mock_chat_instance = mock_chat.return_value
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mock_chat_instance.return_value = MagicMock(content="Test Response")
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prompt = "Test Prompt"
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response = anthropic_llm._get_answer(prompt, anthropic_llm.config)
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assert response == "Test Response"
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mock_chat.assert_called_once_with(
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temperature=anthropic_llm.config.temperature, model=anthropic_llm.config.model
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)
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mock_chat_instance.assert_called_once_with(
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anthropic_llm._get_messages(prompt, system_prompt=anthropic_llm.config.system_prompt)
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)
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def test_get_messages(anthropic_llm):
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prompt = "Test Prompt"
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system_prompt = "Test System Prompt"
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messages = anthropic_llm._get_messages(prompt, system_prompt)
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assert messages == [
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SystemMessage(content="Test System Prompt", additional_kwargs={}),
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HumanMessage(content="Test Prompt", additional_kwargs={}, example=False),
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]
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def test_get_answer_max_tokens_is_provided(anthropic_llm, caplog):
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with patch("langchain.chat_models.ChatAnthropic") as mock_chat:
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mock_chat_instance = mock_chat.return_value
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mock_chat_instance.return_value = MagicMock(content="Test Response")
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prompt = "Test Prompt"
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config = anthropic_llm.config
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config.max_tokens = 500
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response = anthropic_llm._get_answer(prompt, config)
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assert response == "Test Response"
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mock_chat.assert_called_once_with(temperature=config.temperature, model=config.model)
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assert "Config option `max_tokens` is not supported by this model." in caplog.text
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