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# Description Please include a summary of the changes and the related issue. Please also include relevant motivation and context. ## Checklist before requesting a review Please delete options that are not relevant. - [ ] My code follows the style guidelines of this project - [ ] I have performed a self-review of my code - [ ] I have commented hard-to-understand areas - [ ] I have ideally added tests that prove my fix is effective or that my feature works - [ ] New and existing unit tests pass locally with my changes - [ ] Any dependent changes have been merged ## Screenshots (if appropriate):
49 lines
1.4 KiB
Python
49 lines
1.4 KiB
Python
import os
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import pytest
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from langchain_core.language_models import FakeListChatModel
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from pydantic.v1.error_wrappers import ValidationError
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from quivr_core.config import LLMEndpointConfig
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from quivr_core.llm import LLMEndpoint
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@pytest.mark.base
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def test_llm_endpoint_from_config_default():
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from langchain_openai import ChatOpenAI
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del os.environ["OPENAI_API_KEY"]
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with pytest.raises(ValidationError):
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llm = LLMEndpoint.from_config(LLMEndpointConfig())
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# Working default
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config = LLMEndpointConfig(llm_api_key="test")
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llm = LLMEndpoint.from_config(config=config)
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assert llm.supports_func_calling()
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assert isinstance(llm._llm, ChatOpenAI)
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assert llm._llm.model_name in llm.get_config().model
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@pytest.mark.base
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def test_llm_endpoint_from_config():
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from langchain_openai import ChatOpenAI
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config = LLMEndpointConfig(
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model="llama2", llm_api_key="test", llm_base_url="http://localhost:8441"
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)
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llm = LLMEndpoint.from_config(config)
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assert not llm.supports_func_calling()
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assert isinstance(llm._llm, ChatOpenAI)
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assert llm._llm.model_name in llm.get_config().model
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def test_llm_endpoint_constructor():
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llm_endpoint = FakeListChatModel(responses=[])
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llm_endpoint = LLMEndpoint(
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llm=llm_endpoint, llm_config=LLMEndpointConfig(model="test")
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)
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assert not llm_endpoint.supports_func_calling()
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